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Speaker 1: You're listening to a podcast from News Talk sed B.

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Speaker 1: Follow this and our wide range of podcasts now on iHeartRadio.

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Speaker 2: Hello gret you' saiders, and welcome to Matt and Tyler

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Speaker 2: Full Show Podcast number three two, four March the six,

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Speaker 2: twenty twenty six. I just got stars. Haven't had it

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Speaker 2: for longest time. I just stood it really quickly. We've

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Speaker 2: got stars. What do you what do you get? Stars?

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Speaker 3: What is that? That's different vertigo? Isn't it? Stars? A

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Speaker 3: very different vertigo?

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Speaker 4: Yeah?

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Speaker 2: So they were intense stars I got from standing up.

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Speaker 3: Yeah, yeah, some good coffee.

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Speaker 2: It's been a hell of a Week's been quite a show.

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Speaker 2: I think you'll enjoy it. We go live track side

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Speaker 2: to the f one in Melbourne. So bloody good. Great

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Speaker 2: weekend of sport coming up. But yeah, you won't believe

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Speaker 2: some of the stories that come through on e one

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Speaker 2: hundred and eighty ten eighty round Counterfeiting in New Zealand.

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Speaker 2: I thought it wasn't a thing, but it's all over

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Speaker 2: the freaking shop.

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Speaker 3: We broke that right open. So download, subscribe and give

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Speaker 3: us a great review? Would you and give us?

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Speaker 4: Give lo you thiks.

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Speaker 1: The big issues, the big trends and everything in between.

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Speaker 1: It's Matt Heath and Tyler Adams Afternoon squid Shoda News

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Speaker 1: Talk said.

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Speaker 3: Be very good afternoon to welcome into the show seven

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Speaker 3: past one on a Friday. I hope you feeling pretty

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Speaker 3: good and thank you as always for listening. Hey you

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Speaker 3: do it, Matt very.

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Speaker 2: Well, Tyler, thanks for tuning everyone looking thanks for tuning in.

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Speaker 2: Everyone really looking forward to the next three hours of

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Speaker 2: chats on o Waite undred eighty ten eighty.

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Speaker 3: Got a great show for you lined up just before

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Speaker 3: we get into it. Now, what I did recently is

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Speaker 3: knowing I've long enjoyed being a gamer, but I don't

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Speaker 3: have any of the new consoles. But I just thought

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Speaker 3: last night it popped up that it was an old

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Speaker 3: game on a Nintendo sixty four that was for sale online.

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Speaker 3: So went to get myself a weak controller and purchased

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Speaker 3: GoldenEye Double O seven that was on the Nintendo sixty four.

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Speaker 2: Oh, the old classic, the nostalgia.

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Speaker 3: I'm absolutely loving it. I had no idea I could

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Speaker 3: actually play it on my computer, so downloaded a couple

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Speaker 3: of Nintendo sixty four games and can I just say

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Speaker 3: what a joy it is to just jump back on

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Speaker 3: and play some of those games that he used to

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Speaker 3: play as a kid, absolutely loving it.

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Speaker 2: Well, there's speaking of games you used to play a

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Speaker 2: new kid. The Reson an Evil. There's been a Reson

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Speaker 2: an Evil release. I think it's a remake of a

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Speaker 2: really old game. Someone might be able to tell me

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Speaker 2: what that is. But my son has been so incredibly

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Speaker 2: excited about it. It came out last week, but he's

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Speaker 2: been at his mum's house. So he's arriving home too,

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Speaker 2: has PS five at my house where it's all downloaded,

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Speaker 2: ready to go, and I think we won't see him

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Speaker 2: for a while.

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Speaker 3: There's a lot of excitement when a new game comes out.

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Speaker 3: But originally I looked at buying one of the Nintendo

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Speaker 3: sixty four consoles. That big money. You pay about a

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Speaker 3: thousand bucks for those. Now, if you can find them, you.

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Speaker 2: Can an emulate it though, right, yeah.

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Speaker 3: Yep you can. So happy days. So if you've got

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Speaker 3: any tips on old Nintendo sixty four games on all ears,

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Speaker 3: smears through gold tonight, all right, all right, ready to go.

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Speaker 2: You know you've got time. All I've got time for

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Speaker 2: is well, I get the steering well out and I

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Speaker 2: play the upcoming tracks for the F one.

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Speaker 3: Yeah, that is your life for the next eight months.

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Speaker 2: Yeah, yeah, you're needing completely okay with all the corners

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Speaker 2: before I watched the race.

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Speaker 3: Yeah, how good. Now, speaking of the F one is

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Speaker 3: about to cack off in Melbourne and after three point

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Speaker 3: thirty we are going to be crossing live to Herald

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Speaker 3: Sports reporter Alex Powell. He was live trackside. He's been

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Speaker 3: given all axis passes, he's been speaking to all the

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Speaker 3: big players, so that's going to be exciting to have

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Speaker 3: a chat with him just after three point thirty.

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Speaker 2: I mean, these you know, drivers are some of the

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Speaker 2: most recognizable and famous people in the world. And Alex Powell,

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Speaker 2: who we talk to every day, just down the office,

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Speaker 2: he's just he's just mingling with them walking around. It's

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Speaker 2: bloody Max for stepping this, Bloody Lando Norris, that Pire

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Speaker 2: Ghasly this.

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Speaker 3: He's living the dream.

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Speaker 2: Charlotte Cleare that.

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Speaker 3: Yeah, he's a lucky, lucky boy.

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Speaker 2: They're all over the place.

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Speaker 3: Yeah, so looking forward to having to catch up with

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Speaker 3: him after three thirty or so after three o'clock the

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Speaker 3: moment you all wait for. It is a Friday, which

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Speaker 3: means New Zealander of the week. Yeah, who will it

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Speaker 3: be a lot of big choices this week after two o'clock.

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Speaker 3: Want to have a chat about AI. There's a recent

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Speaker 3: visualization that's doing the rounds online and it really puts

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Speaker 3: things into perspective. So, out of the world's eight point

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Speaker 3: one billion people, about six point eight billion have never

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Speaker 3: never used AI at all, and around fifteen to twenty

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Speaker 3: five million people that's out of the whole world's population

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Speaker 3: actually pay for AI tools. Even more striking eighty two

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Speaker 3: percent of American businesses, and you'd go argue it'd be

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Speaker 3: about the same here say that they haven't used AI

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Speaker 3: at all in any shape or form in their business.

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Speaker 3: So it makes the point that if you think you're

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Speaker 3: behind AI, or if you've never used AI in your life,

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Speaker 3: you're actually in line with most of the world's population.

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Speaker 2: Yeah, So all we hear about is AI, this AI, that,

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Speaker 2: AI everywhere. But so this year in twenty twenty six,

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Speaker 2: it's it expected that two point five trillion dollars will

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Speaker 2: be pumped into AI. So two point five trillion dollars,

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Speaker 2: that's an insane amount of money globally being pumped into

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Speaker 2: AI development and running AI because it's incredibly expensive to

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Speaker 2: run the whole setup, the data centers, the cloud infrastructure,

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Speaker 2: the GPUs. There's just so much in training the models.

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Speaker 2: So that's two point five trillion dollars. It's expected to

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Speaker 2: bring in three hundred billion.

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Speaker 3: Right, that's a big shortfall. Yeah, that is a massive shortfall.

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Speaker 2: So I guess that's why people are talking about the bubble.

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Speaker 2: But is there a whole lot of talk about AI

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Speaker 2: and a whole lot of people just not using it?

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Speaker 3: Are you one of the six point eight billion in

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Speaker 3: the world that have never used AI? And if so,

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Speaker 3: why love to hear from you after two o'clock.

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Speaker 2: Were you one of the fifteen million people on the

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Speaker 2: planet who are paying for it?

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Speaker 3: Yeah, it's a shorter, much shorter population there that's.

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Speaker 2: Looking dollars, fifteen million using it.

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Speaker 3: Yeah, looking forward to that after talk clob But right

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Speaker 3: now we want to have a chat about counterfeit. Counterfeit cash.

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Speaker 3: So police have issued recent warnings of this counterfeit fifty

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Speaker 3: dollars and one hundred dollar notes circulating around in New Zealand.

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Speaker 3: Of course, there is no way to tell how many

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Speaker 3: of these notes are doing the round, but the Reserve

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Speaker 3: Bank in New Zealand. They are of course in charge

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Speaker 3: of banknotes and they recommend what it calls the look

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Speaker 3: tilt test to identify the official security features of a

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Speaker 3: legitimate cash note. But the question we've got for you

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Speaker 3: for you is do you think you could tell the

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Speaker 3: difference between a counterfeit note and a real note? And

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Speaker 3: if you work in retail, have you been presented with

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Speaker 3: some of this fake cash?

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Speaker 2: It sounds like a ye oldie crime, doesn't it be counterfeiting?

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Speaker 5: You know?

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Speaker 2: All the fraud that you hear about now is digital frauds,

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Speaker 2: scams here and they're getting money out of you account.

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Speaker 2: You don't even notice it's happening. All those kind of things. Yeah,

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Speaker 2: scam centers ringing people up. But isn't it interesting that

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Speaker 2: there's just good old fashioned, dirty old counterfeiting going on

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Speaker 2: in New Zealand ye fifties and so the police are

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Speaker 2: saying that they're in circulation right now.

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Speaker 3: Still doing the rounds.

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Speaker 2: So I mean this text is you know, typical of

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Speaker 2: a few that are coming through what a beat up?

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Speaker 2: There is no counterfeit money in New Zealand. Well the

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Speaker 2: police says there is. I mean I should have warned it. Yeah, yeah,

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Speaker 2: but this text on nine to two, there's no counterfeit

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Speaker 2: money in New Zealand. Well, who are you going to believe.

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Speaker 3: The police or an anonymous texter.

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Speaker 2: I'm going to believe the anonymous text as if it's

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Speaker 2: not Cowboy Times. Answer me this, Why would they counterfeit

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Speaker 2: New Zealand money when it isn't worth anything? You would

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Speaker 2: make pounds or the US dollar? This is scare mungery.

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Speaker 2: You really think people are going to check all the

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Speaker 2: fifties they get? What a waste of time. No one

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Speaker 2: is making them and no one is spending them, and

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Speaker 2: no one is being fooled by them.

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Speaker 3: Okay, right, It sounds someone deep in the counterfeit game.

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Speaker 3: To be honest, it sounds like a bit of a

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Speaker 3: red hearing to throw people off.

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Speaker 2: Yeah, because I mean it'd be silly to make us

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Speaker 2: dollars and then try and spend them on cut harang

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Speaker 2: a happy road.

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Speaker 3: That's a telltale sign that's going to get picked up

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Speaker 3: real fast.

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Speaker 2: That's another layer. I mean, you're going to have to

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Speaker 2: get that exchanged into New Zealand money and by people

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Speaker 2: that are much more likely to check it. So I'd

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Speaker 2: just be interested if anyone has come across any counterfeit

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Speaker 2: money in their time. You know how quickly you spotted it?

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Speaker 2: Did you find it in the till after it being

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Speaker 2: the person had already walked out with this stuff?

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Speaker 6: Yep?

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Speaker 2: Because I mean that's the thing. Now, if you try

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Speaker 2: and spend counterfeit money, right, there's there's a I guess yeah,

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Speaker 2: that's that's the interesting thing, isn't it. If you try

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Speaker 2: and spend counterfeit money, you're going to be on the CCTV, right,

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Speaker 2: Someone's going to see you at the counter spending it.

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Speaker 3: Yeah, correct, yep, so you'll get picked up.

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Speaker 2: So you wouldn't be able to do it a lot. No,

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Speaker 2: So how do you how do they how do they

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Speaker 2: how do they how does it work for them? How

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Speaker 2: do they get it into the system?

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Speaker 3: How do you spot it? If you work in retail

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Speaker 3: and you operate a with with cash, how do you

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Speaker 3: spot it if it's a counterfeit note? Because I imagine

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Speaker 3: there's a lot of cafes, dairy owners, gas stations and

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Speaker 3: they've unfortunately taken one of these counterfeit bills. By the

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Speaker 3: time they figure out it's not real and handed to

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Speaker 3: the police, that down fifty hundred bucks. So if that's

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Speaker 3: happened to you? Oh eight one hundred ay ten eighty

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Speaker 3: nine two ninety two is the text. It is fourteen

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Speaker 3: past one. We'll be back very shortly.

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Speaker 1: The big stories, the big issues, the big trends and

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Speaker 1: everything in between.

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Speaker 7: Matt Heath and Tyler Adams afternoons used talks.

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Speaker 3: That'd be seventeen past one. So we're talking about counterfeit

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Speaker 3: fake money circulating in New Zealand. Police have put out

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Speaker 3: multiple warnings that fifty dollars and one hundred dollars fake

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Speaker 3: bills are being used at various places. If you've come

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Speaker 3: across one of these fake bills, oh eight hundred and

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Speaker 3: eighty ten eighty and do you think you could tell

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Speaker 3: the difference? Nineteen nine two is the text as well, Dino,

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Speaker 3: You've come across it quite a bit.

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Speaker 8: Yeah, Hi, long time listeners, first time caller, big band.

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Speaker 9: Of your show.

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Speaker 2: Oh thanks danaet.

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Speaker 8: McDonald's and have done so for several years, and it

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Speaker 8: happens quite frequently. Majority of them are fifties. And what

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Speaker 8: we've had to do is get the you be lights

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Speaker 8: to check the notes. You can just rip them as well,

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Speaker 8: but the customers get very you rip up their counterfeit

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Speaker 8: notes in front of them.

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Speaker 3: I bet they do.

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Speaker 2: So if you once you hold it, does it feel

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Speaker 2: different because you know, the paper for a fifty and

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Speaker 2: money is very different. It's kind of that plastic situation.

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Speaker 2: So so is that when you the first idea you

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Speaker 2: have that it might be counterfeit din?

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Speaker 8: Yeah, is that you feel it and then you kind

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Speaker 8: of look at the see through area and that that

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Speaker 8: sort of highlighter sort of bit that goes through the note.

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Speaker 8: You can see things like that, and the people the

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Speaker 8: easiest way is to just rip it.

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Speaker 2: Yeah, right, and then and if it rips straight away,

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Speaker 2: then it's not a note, right, you know. Yeah, So,

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Speaker 2: and when people get rumbled with, I guess you know,

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Speaker 2: they could do a big act. But you get the

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Speaker 2: feeling that a lot of people that are handing over

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Speaker 2: these fifty dollars counterfeit notes don't know that they're running

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Speaker 2: a fifty dollar counterfeit note, that they are down the

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Speaker 2: track of it.

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Speaker 8: I think they do know. And then they target places

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Speaker 8: like McDonald's where you're trying to push through as many

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Speaker 8: customers as you can, yeah right, and then you can

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Speaker 8: see that the people are young as well, but handling

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Speaker 8: the money and so may not have as much experience

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Speaker 8: with it, and because of the speed that they're trying

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Speaker 8: to get through the customers, they're hoping that they can

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Speaker 8: get their money through before anyone notices. I think that

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Speaker 8: would be the most likely scenario that's happening.

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Speaker 2: Running a counterfeit operation is a serious crime. So when

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Speaker 2: that happens, when a counterfeit bill comes through, do the

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Speaker 2: police get notified? Do you share I don't know, CCTV

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Speaker 2: of the person that's trying to hand it over?

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Speaker 6: Yeah? Yeah, it all gets boarded through.

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Speaker 3: Yeah. And do you do the same with all money

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Speaker 3: that comes in, you know, a ten dollar note, twenty

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Speaker 3: dollar note, you're all cast the same eye over it,

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Speaker 3: just in case.

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Speaker 8: Normally it's predominantly the fifties that come through every now

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Speaker 8: and again. That's one hundred, but it seems like the

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Speaker 8: fifties are the ones that we get the most often.

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Speaker 3: How many slip through do you reckon? Is there there

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Speaker 3: are a few that gets that slip through and get

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Speaker 3: picked up later.

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Speaker 8: On potentially, But you'd be looking at I think throughout

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Speaker 8: the stores that you know, sort of a couple.

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Speaker 2: Of weeks, oh, really, a couple of weeks so.

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Speaker 8: Enough to certainly to certainly monitor. Yeah, and then that's

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Speaker 8: why we had to get those UV tortures because it

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Speaker 8: happens every now and again.

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Speaker 2: They don't show up anything else here. They're not one

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Speaker 2: of those DNA torches, are they.

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Speaker 8: Well, that could happen as well.

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Speaker 5: But mostly.

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Speaker 2: Thank you so much for your call.

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Speaker 5: Dno.

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Speaker 2: So I was just you know, looking at what the

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Speaker 2: creating banknotes or coins or counterfeiting. That's a seven year

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Speaker 2: prison sentence.

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Speaker 3: Hmm.

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Speaker 2: So that's pretty serious under the Crimes Act of nineteen

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Speaker 2: sixty one.

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Speaker 3: Yeah, but I wonder what the police would do in

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Speaker 3: Dino's example, that they've discovered it's a fake note, then

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Speaker 3: they take it to the police that well, what do

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Speaker 3: they do with that person? Because you can argue, oh,

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Speaker 3: I picked this up somewhere else, you know what I'm saying.

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Speaker 2: If you having fake banknotes, well knowing they are forged,

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Speaker 2: there is also a crime maximum penalty up to seven years.

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Speaker 2: So if you have a fake banknote and you know

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Speaker 2: it's a fake bank note and you try and use it,

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Speaker 2: that's a really serious crime.

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Speaker 3: Yeah, all for fifty bucks high risk? Oh, one hundred

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Speaker 3: and eighty ten eighty is that number to call. If

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Speaker 3: you work in a cash business, retail, cafe, a pub,

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Speaker 3: have you come across these fake notes? And if you

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Speaker 3: have any knowledge about how this is made, what's the operation?

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Speaker 3: Like keen to hear your story? Ninet toen nine two

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Speaker 3: is the text.

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Speaker 2: Far from what that first text was saying that it

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Speaker 2: doesn't exist and this isn't cowboy days and it's just

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Speaker 2: a beat up. This text here says lady in front

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Speaker 2: of me at the warehouse the other day handed over

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Speaker 2: four times fifty dollar notes and the cashier scan them

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Speaker 2: with a pen like device and rejected air.

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Speaker 3: There you go, right twenty two past one. We will

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Speaker 3: be back very shortly.

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Speaker 1: The headlines and the hard questions. It's the Mic Hosking Breakfast.

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Speaker 10: So the committee looking into whether we should bran social

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Speaker 10: media for under sixteens has produced its.

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Speaker 2: One a report.

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Speaker 10: Col Bates is one of the national members on that committee.

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Speaker 10: Some of the recommendations you make are from outer space.

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Speaker 10: They're not real, they're just theoretical whiteboarding.

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Speaker 11: So there's a.

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Speaker 2: Range of recommendations.

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Speaker 12: A number of what you reflect what's happening internationally, and

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Speaker 12: some of what are about immediate actions that can be taken.

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Speaker 10: Now regulate algorithmic recommendation systems. Do you honestly think New

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Speaker 10: Zealand Incs capable of doing that where no one else

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Speaker 10: in the world is.

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Speaker 12: From a committee perspective, we said the government should explore this,

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Speaker 12: not saying let's just go and say this should happen

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Speaker 12: right now.

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Speaker 10: Back Monday from six am, the mic asking Breakfast with

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Speaker 10: a Vida News Talk ZB.

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Speaker 3: Twenty five past one. We're talking about counterfeit notes circulating

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Speaker 3: in a community. If you've across them, one hundred and

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Speaker 3: eighteen eighty is that number to call get a Andy.

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Speaker 6: Oh Kuttle team. How you going?

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Speaker 3: Very good mate? What's what's your story? Have you come

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Speaker 3: across these?

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Speaker 6: Yeah? Yeah, we had up here in the far North.

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Speaker 6: The one of the local businesses, he got a fifty

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Speaker 6: dollars fake note unawares for the young person on the counter,

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Speaker 6: and then both when he did the cash up at

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Speaker 6: the end of the day when man and then so

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Speaker 6: he put that up, hanging that up on the wall.

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Speaker 6: And then another another couple of people came in and

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Speaker 6: to his store and added bought, brought products up to

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Speaker 6: one hundred dollars with a fake hundred dollar note and

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Speaker 6: they came out, tried to chase as fellows down, so

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Speaker 6: they managed to get away, kept the good put the

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Speaker 6: goods back on the shelf, and then kept one hundred

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Speaker 6: dollar note.

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Speaker 4: He let me know.

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Speaker 6: So I just came down and had a look and went, ay, yeah,

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Speaker 6: it says they look pretty. It looks pretty, looks pretty realistic.

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Speaker 6: And to the untrained eye, you'd be an easy pass

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Speaker 6: if you were busy, if you're doing a lot of transactions,

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Speaker 6: and for younger people, like the guy said before, he

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Speaker 6: can you may be able to miss it. But if

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Speaker 6: you just as long as you're aware of it. Then

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Speaker 6: we took them up. So them to my staff, everyone

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00:16:14,973 --> 00:16:16,613
Speaker 6: sort of going, oh, yeah, it looks all right until

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Speaker 6: you touch. As soon as you've touched it, all of

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00:16:18,933 --> 00:16:21,053
Speaker 6: a sudden you go, no, there's something dodgy going on here.

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Speaker 3: So even with the wee holographic they try and emulate

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Speaker 3: that today that we placed a holographic part.

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Speaker 6: It was there was it was if you if you

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Speaker 6: looked at it without touching it, you're just about couldn't

364
00:16:32,613 --> 00:16:36,373
Speaker 6: find anything wrong. In the holograph. It actually says sample

365
00:16:36,453 --> 00:16:38,173
Speaker 6: over the top of it, and you can see with

366
00:16:38,293 --> 00:16:40,213
Speaker 6: the notes that we've had a look at the been

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00:16:40,293 --> 00:16:43,412
Speaker 6: scratched off. It just looks like it looks a bit

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Speaker 6: dodgy over there. And then so he did a bit

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00:16:45,693 --> 00:16:47,933
Speaker 6: of investigation and found out that you can you can

370
00:16:47,933 --> 00:16:49,253
Speaker 6: buy them online these.

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00:16:49,173 --> 00:16:54,053
Speaker 2: Years and they're sold as are they sold as currency

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00:16:54,133 --> 00:16:55,412
Speaker 2: or are they sold as play.

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00:16:55,453 --> 00:16:58,812
Speaker 6: No, No, they're on a they're on a very popular website.

374
00:16:59,053 --> 00:17:01,773
Speaker 6: And they just called New Zealand play Money, the Zealand

375
00:17:01,813 --> 00:17:02,653
Speaker 6: play money.

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Speaker 2: Right, and so this New Zealand play money is almost

377
00:17:07,213 --> 00:17:11,132
Speaker 2: good in our hundreds, almost good enough to you know,

378
00:17:11,893 --> 00:17:13,053
Speaker 2: I would pick up might.

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00:17:12,933 --> 00:17:16,773
Speaker 6: Pick up a grandma at a at a market, you know,

380
00:17:16,813 --> 00:17:19,173
Speaker 6: with a fifty maybe you know the one hundreds, everyone

381
00:17:19,253 --> 00:17:21,373
Speaker 6: sort of like going what they're doing there. But you know,

382
00:17:21,413 --> 00:17:23,613
Speaker 6: if you just if you just haven't got the wherewithal,

383
00:17:23,773 --> 00:17:26,693
Speaker 6: just to think twice and slow down because you think, oh, well,

384
00:17:26,893 --> 00:17:27,773
Speaker 6: making some money here.

385
00:17:28,053 --> 00:17:30,853
Speaker 2: I wonder these people that I wonder if these people

386
00:17:30,893 --> 00:17:34,853
Speaker 2: that are trying to fall you know, stores worth this

387
00:17:35,573 --> 00:17:38,733
Speaker 2: fake TIMU play money, know how serious a crime they're

388
00:17:38,733 --> 00:17:41,693
Speaker 2: committing is in court of you know, because governments really

389
00:17:41,693 --> 00:17:44,653
Speaker 2: care about things like money, yes, because they love taxing people,

390
00:17:45,013 --> 00:17:46,013
Speaker 2: so they really care.

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Speaker 6: About it right, Yeah, they do. But you know we

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00:17:48,613 --> 00:17:51,653
Speaker 6: he got hold of the police and the police didn't

393
00:17:51,653 --> 00:17:53,613
Speaker 6: say anything, didn't want to take the money away. They

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00:17:53,653 --> 00:17:56,413
Speaker 6: know that it's around. It was I think it had

395
00:17:56,453 --> 00:17:58,933
Speaker 6: to be a lot of money before they were actually interested,

396
00:17:59,133 --> 00:18:02,053
Speaker 6: which sort of kind of pee us off a little bit.

397
00:18:01,933 --> 00:18:04,933
Speaker 6: But you know, this thing is serious because as much

398
00:18:04,933 --> 00:18:06,133
Speaker 6: as we thought, oh, I wonder if we could go

399
00:18:06,213 --> 00:18:07,653
Speaker 6: try this, take this down, because you know, one of

400
00:18:07,693 --> 00:18:10,613
Speaker 6: how we get onto we don't want our winnings received

401
00:18:10,613 --> 00:18:11,453
Speaker 6: and play money either.

402
00:18:14,373 --> 00:18:16,133
Speaker 3: I'm just having to look at some of that online

403
00:18:16,133 --> 00:18:19,293
Speaker 3: Andy that play money, and yeah, I mean on first glance,

404
00:18:19,693 --> 00:18:22,893
Speaker 3: it's pretty close, pretty close to the real deal. I

405
00:18:22,893 --> 00:18:24,573
Speaker 3: mean I wonder how they get away with it. I mean,

406
00:18:24,653 --> 00:18:27,133
Speaker 3: I can't understand how they get away with its Chinese

407
00:18:27,213 --> 00:18:28,533
Speaker 3: company and they don't care.

408
00:18:28,453 --> 00:18:31,093
Speaker 2: Because yeah, they don't give them crap. What's new Zealand

409
00:18:31,093 --> 00:18:31,373
Speaker 2: going to do?

410
00:18:31,413 --> 00:18:32,293
Speaker 3: They can do what they will, like.

411
00:18:32,293 --> 00:18:34,973
Speaker 2: Please won't even help Andy out when he gets one.

412
00:18:35,093 --> 00:18:37,253
Speaker 2: The police are to plane and going to smash up

413
00:18:37,493 --> 00:18:39,373
Speaker 2: some factory in China.

414
00:18:39,453 --> 00:18:42,893
Speaker 3: Yeah, yeah, it's two great points. Yeah, yeah, Andy, thanks

415
00:18:42,973 --> 00:18:45,333
Speaker 3: very much for joining the conversation. Oh eight one hundred

416
00:18:45,333 --> 00:18:46,453
Speaker 3: and eighty ten eighty.

417
00:18:46,773 --> 00:18:49,413
Speaker 2: So this is the exact wording of the Crimes Act

418
00:18:49,493 --> 00:18:55,133
Speaker 2: nineteen sixty one, Article two sixty three. Possessing forged banknotes.

419
00:18:55,533 --> 00:18:58,133
Speaker 2: Everyone is liable to imprisonment for a term not exceeding

420
00:18:58,173 --> 00:19:01,493
Speaker 2: seven years, who, without lawful authority or excuse the proof

421
00:19:01,533 --> 00:19:04,493
Speaker 2: of the lawful authority or excuse lying on him or her,

422
00:19:05,093 --> 00:19:09,093
Speaker 2: purchases or receives, purchases or receives from a person, or

423
00:19:09,173 --> 00:19:12,733
Speaker 2: has in his or her possession, or under his or

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00:19:12,733 --> 00:19:15,653
Speaker 2: her control, any forged banknote, whether it complete or not

425
00:19:16,173 --> 00:19:17,213
Speaker 2: knowing it to be forged.

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00:19:17,293 --> 00:19:19,693
Speaker 3: It's not mucking around now. It is severe.

427
00:19:20,093 --> 00:19:22,453
Speaker 2: Yeah. So you've got some kids that and you know,

428
00:19:22,493 --> 00:19:25,213
Speaker 2: in Andy's case the police wereen interested. But you've got

429
00:19:25,293 --> 00:19:28,533
Speaker 2: kids ordering in play money, trying to spend it and

430
00:19:29,093 --> 00:19:31,013
Speaker 2: committing a pretty serious crime.

431
00:19:31,093 --> 00:19:33,413
Speaker 3: Yeah. Oh, one hundred and eighty ten eighty is that

432
00:19:33,533 --> 00:19:37,013
Speaker 3: number to call if you've come across counter counterfeit cash,

433
00:19:37,013 --> 00:19:39,613
Speaker 3: whether at your business or just in the community. Keen

434
00:19:39,693 --> 00:19:41,853
Speaker 3: to hear your story, and if you've got any insight

435
00:19:41,933 --> 00:19:44,733
Speaker 3: knowledge into how they operate. Clearly you can buy it

436
00:19:44,773 --> 00:19:47,933
Speaker 3: off some of these Chinese Chinese sites, but if you

437
00:19:47,973 --> 00:19:49,573
Speaker 3: know how they make it if they do make it.

438
00:19:49,613 --> 00:19:51,613
Speaker 3: In New Zealand, keen to hear from You nineteen nine.

439
00:19:51,533 --> 00:19:53,493
Speaker 2: Two is a text does Texas says? Get yourself a

440
00:19:53,493 --> 00:19:54,573
Speaker 2: three D print to ya, muppet?

441
00:19:54,653 --> 00:19:56,213
Speaker 3: Okay, all right, there's someone in the know.

442
00:19:56,413 --> 00:19:56,773
Speaker 2: All right.

443
00:19:56,853 --> 00:19:59,133
Speaker 3: It has banging on past one headline's coming.

444
00:19:59,093 --> 00:20:04,533
Speaker 13: Up, news talks headlines with your Ride New Zealand's number

445
00:20:04,573 --> 00:20:08,533
Speaker 13: one taxi app, Download your ride today and explodin those

446
00:20:08,693 --> 00:20:12,613
Speaker 13: Pole shows National has reached its lowest result since forming

447
00:20:12,653 --> 00:20:16,733
Speaker 13: a government as Labour climbs ahead the Taxpayer's Union Courier

448
00:20:16,773 --> 00:20:20,173
Speaker 13: Pole has Labour on thirty four point four percent. National

449
00:20:20,253 --> 00:20:25,373
Speaker 13: drops six points behind to twenty eight point four gps

450
00:20:25,453 --> 00:20:28,573
Speaker 13: want better standards and to oversight for their digital systems

451
00:20:28,613 --> 00:20:33,333
Speaker 13: to avoid cyber attacks. Patient portals, shared records and electronic

452
00:20:33,373 --> 00:20:37,133
Speaker 13: referrals in are commonplace and primary care, but general practice.

453
00:20:37,133 --> 00:20:40,453
Speaker 13: New Zealand says the governance and standards haven't kept pace.

454
00:20:41,533 --> 00:20:44,573
Speaker 13: A section of State Highway one remains closed north of

455
00:20:44,653 --> 00:20:48,173
Speaker 13: Levinn after a crash between an ambulance and a gas

456
00:20:48,173 --> 00:20:52,133
Speaker 13: truck near pudou Tafao. Police say two people are being

457
00:20:52,173 --> 00:20:56,493
Speaker 13: treated for serious injuries. Detours are in place. A health

458
00:20:56,533 --> 00:21:00,013
Speaker 13: warning's been issued for North Canterbury's Ashley River due to

459
00:21:00,093 --> 00:21:03,733
Speaker 13: high levels of fecal bacteria. Medical Officer of Health doctor

460
00:21:03,773 --> 00:21:08,493
Speaker 13: Sheryl Brunton says the water isn't suitable for recreation, including swimming.

461
00:21:09,453 --> 00:21:11,293
Speaker 2: Demolish, convert all.

462
00:21:11,133 --> 00:21:16,052
Speaker 13: Finish the high stakes choices facing seascapes receivers. You can

463
00:21:16,093 --> 00:21:18,773
Speaker 13: read more at NZ and Herald Premium. Back to Matt

464
00:21:18,813 --> 00:21:20,293
Speaker 13: Eathan Tyler Adams.

465
00:21:19,933 --> 00:21:22,293
Speaker 3: Thank you very much, Raylean. So we're talking about counterfeit

466
00:21:22,333 --> 00:21:26,093
Speaker 3: money circulating in the community. Police have put out recent warnings.

467
00:21:26,213 --> 00:21:28,453
Speaker 3: It's impossible to tell how many of these notes are

468
00:21:28,453 --> 00:21:31,413
Speaker 3: doing the rounds. But if you've come across some fake cash,

469
00:21:31,693 --> 00:21:33,253
Speaker 3: can you hear your story? Oh one hundred and eighty

470
00:21:33,253 --> 00:21:33,893
Speaker 3: ten eighty.

471
00:21:33,733 --> 00:21:36,453
Speaker 2: Imagine counterfeitings are we weighed down the track and what

472
00:21:36,493 --> 00:21:38,493
Speaker 2: the police want to spend their time doing now? Right

473
00:21:38,573 --> 00:21:42,213
Speaker 2: with the much less cash being used out in the community.

474
00:21:42,213 --> 00:21:45,453
Speaker 2: I wonder if they've even got like an anti counterfeiting unit.

475
00:21:46,253 --> 00:21:48,933
Speaker 3: Great question. I've never heard of an anti county fitting unit.

476
00:21:49,133 --> 00:21:51,853
Speaker 2: He used to be, well, there used to be, you know, famously,

477
00:21:51,853 --> 00:21:54,293
Speaker 2: I'm probably talking about movies here, but kicking indoors and

478
00:21:54,333 --> 00:21:58,133
Speaker 2: smashing up printing presses yep. And because it used to

479
00:21:58,173 --> 00:21:59,413
Speaker 2: be a very very serious.

480
00:21:59,173 --> 00:22:00,373
Speaker 3: Thing, al Capone style.

481
00:22:00,493 --> 00:22:03,333
Speaker 2: But won't this just force more people if there's more

482
00:22:03,373 --> 00:22:06,933
Speaker 2: of this TMU cash in the market, won't it just

483
00:22:06,973 --> 00:22:10,053
Speaker 2: force more people of running stores to just not take cash.

484
00:22:10,173 --> 00:22:12,853
Speaker 3: That's the risk, right, And we talked about cash recently

485
00:22:12,893 --> 00:22:15,532
Speaker 3: and people were pushing back on the digitization of it.

486
00:22:16,133 --> 00:22:18,333
Speaker 3: But that is a real risk. Nine two ninety two

487
00:22:18,413 --> 00:22:19,373
Speaker 3: is the text number.

488
00:22:19,533 --> 00:22:22,613
Speaker 2: You can buy New Zealand forge notes for enz dollars

489
00:22:22,653 --> 00:22:24,933
Speaker 2: on the dark web for aquorder of the currency, and

490
00:22:24,973 --> 00:22:28,213
Speaker 2: they almost they are almost identical. Twenty five dollars for

491
00:22:28,213 --> 00:22:30,893
Speaker 2: one hundred dollars. See, I mean that's a big risk.

492
00:22:30,893 --> 00:22:32,773
Speaker 2: So you're paying twenty five dollars for one hundred dollars,

493
00:22:33,213 --> 00:22:35,693
Speaker 2: risking a possible seven year jail term which you probably

494
00:22:35,693 --> 00:22:37,333
Speaker 2: wouldn't get. You probably get a slap on the back

495
00:22:37,373 --> 00:22:39,933
Speaker 2: of the risk with a web five dollars hode seen

496
00:22:40,013 --> 00:22:44,013
Speaker 2: on your way by judges in New Zealand. But I

497
00:22:44,013 --> 00:22:44,413
Speaker 2: don't know.

498
00:22:44,853 --> 00:22:46,292
Speaker 3: Sure you can. But you can buy a lot of

499
00:22:46,533 --> 00:22:48,053
Speaker 3: dodgy stuff done on.

500
00:22:48,133 --> 00:22:50,973
Speaker 2: The dark dark web, and you spend one thousand. You

501
00:22:51,013 --> 00:22:52,853
Speaker 2: spent TI onred and fifty dollars to get one thousand dollars.

502
00:22:52,973 --> 00:22:56,493
Speaker 2: Is that enough of are returned for all the risk

503
00:22:56,573 --> 00:22:57,213
Speaker 2: that has evolved?

504
00:22:57,333 --> 00:22:59,853
Speaker 3: Yeah, high risk and low reward. You'd have to say,

505
00:22:59,893 --> 00:23:01,853
Speaker 3: but Stephanie, how are you today?

506
00:23:02,933 --> 00:23:03,093
Speaker 14: Oh?

507
00:23:03,133 --> 00:23:03,333
Speaker 15: Good?

508
00:23:03,413 --> 00:23:03,813
Speaker 10: Thank you?

509
00:23:03,853 --> 00:23:04,973
Speaker 2: How are you el good?

510
00:23:05,333 --> 00:23:08,333
Speaker 3: So you've had an issue with potential counterfeit cash heavy?

511
00:23:10,453 --> 00:23:11,413
Speaker 16: No, not an issue.

512
00:23:11,413 --> 00:23:14,333
Speaker 15: But we had a strange experience. I was driving through

513
00:23:14,453 --> 00:23:17,693
Speaker 15: Tempts and we stopped at the packing save there and

514
00:23:17,813 --> 00:23:22,853
Speaker 15: we paid with cash, and the cashier stopped and called

515
00:23:22,893 --> 00:23:25,413
Speaker 15: someone else over to check our money because we're paying

516
00:23:25,453 --> 00:23:28,373
Speaker 15: with a couple of fifties. And it seemed like this

517
00:23:28,493 --> 00:23:31,773
Speaker 15: staff member who came over this this is all she

518
00:23:31,893 --> 00:23:35,253
Speaker 15: did was go from till to till, checking people's cash,

519
00:23:35,373 --> 00:23:37,933
Speaker 15: checking people's FI. Yeller notes this was about a year

520
00:23:37,973 --> 00:23:40,733
Speaker 15: and a half ago, so it wasn't even reason. And

521
00:23:40,973 --> 00:23:43,133
Speaker 15: I said, oh, you know, I don't. I don't come

522
00:23:43,173 --> 00:23:47,053
Speaker 15: from a place where you know, we have counterfeit money

523
00:23:47,093 --> 00:23:50,133
Speaker 15: or use counterfeit money, and so this was kind of

524
00:23:50,133 --> 00:23:53,853
Speaker 15: a new experience for me. But I said, so, how

525
00:23:53,893 --> 00:23:56,253
Speaker 15: often would this happen? That you would come across the

526
00:23:56,293 --> 00:23:58,573
Speaker 15: counterfeit notes. And she just looked at me dead in

527
00:23:58,573 --> 00:24:01,933
Speaker 15: the eye. She said, every day.

528
00:24:01,493 --> 00:24:02,453
Speaker 3: The day, every day.

529
00:24:02,533 --> 00:24:05,733
Speaker 4: Yeah, wow, Yeah, so it's it's.

530
00:24:05,533 --> 00:24:09,093
Speaker 2: A big thing. Yeah, this we're getting We're just getting

531
00:24:09,133 --> 00:24:11,933
Speaker 2: so many texts through, calls, through saying that counterfeit money

532
00:24:12,013 --> 00:24:15,133
Speaker 2: is a really big problem in New Zealand. I would

533
00:24:15,173 --> 00:24:17,693
Speaker 2: never have guessed it seems like such an old fashioned crime.

534
00:24:18,533 --> 00:24:21,973
Speaker 3: So creepy if I'm wrong, hopefully I'm right here, Stephanie.

535
00:24:22,013 --> 00:24:23,933
Speaker 3: But you're originally from America.

536
00:24:23,533 --> 00:24:23,933
Speaker 5: Is that right?

537
00:24:25,573 --> 00:24:26,253
Speaker 15: I'm Canadian?

538
00:24:26,573 --> 00:24:27,093
Speaker 17: Canadian?

539
00:24:27,533 --> 00:24:29,853
Speaker 3: Right, and that's see I knew it was a gamble.

540
00:24:29,933 --> 00:24:31,453
Speaker 3: I knew it was a gamble and I rung a

541
00:24:31,533 --> 00:24:32,693
Speaker 3: risk and it didn't pay off.

542
00:24:33,373 --> 00:24:34,333
Speaker 2: Always go Canadian.

543
00:24:34,413 --> 00:24:37,933
Speaker 3: Yeah first, Okay, well this may different that the question then,

544
00:24:37,973 --> 00:24:40,693
Speaker 3: But in Canada, would you say that that country uses

545
00:24:40,733 --> 00:24:42,013
Speaker 3: kesh a bit more than we use it here?

546
00:24:43,893 --> 00:24:48,053
Speaker 15: Oh I've been here over twenty five years, so I'm

547
00:24:48,093 --> 00:24:53,813
Speaker 15: really not down with people's spending habits and what they

548
00:24:53,933 --> 00:24:57,653
Speaker 15: used to buy things with, but I would say that, yes,

549
00:24:57,813 --> 00:25:00,693
Speaker 15: in North America it's much more common use cash.

550
00:25:00,853 --> 00:25:03,533
Speaker 3: Yeah, Stephanie, thank you very much for giving us a call.

551
00:25:03,573 --> 00:25:05,973
Speaker 3: I mean fascinating to hear that pretty much every day

552
00:25:06,093 --> 00:25:09,053
Speaker 3: Peck and save and teamsters getting some fake So you would.

553
00:25:08,893 --> 00:25:11,293
Speaker 2: Have thought this is a huge risk for charities who

554
00:25:11,413 --> 00:25:15,133
Speaker 2: get given donations and cash when doing fundraising campaigns, says

555
00:25:15,173 --> 00:25:15,813
Speaker 2: this texture.

556
00:25:15,853 --> 00:25:17,613
Speaker 3: Oh that is a shame. That sucks.

557
00:25:17,973 --> 00:25:24,533
Speaker 2: What about this scenario though? You know illegal activities. Let's

558
00:25:24,533 --> 00:25:29,853
Speaker 2: say drug dealers you give them counterfeit cash, or you

559
00:25:29,853 --> 00:25:33,573
Speaker 2: give let's say you're buying your illegal stuff off a gang.

560
00:25:34,133 --> 00:25:37,133
Speaker 2: Imagine they would give you worse than seven years per

561
00:25:37,133 --> 00:25:38,293
Speaker 2: handing over counterfeit cash.

562
00:25:38,373 --> 00:25:40,613
Speaker 3: Yeah, that is a dangerous operation. Yeah, I mean they

563
00:25:40,653 --> 00:25:41,973
Speaker 3: may lock it and see it. Hang on a minute,

564
00:25:41,973 --> 00:25:43,733
Speaker 3: we made this. This came from US.

565
00:25:44,053 --> 00:25:45,572
Speaker 2: I don't know if New Zealand gangs are up to it.

566
00:25:46,333 --> 00:25:48,253
Speaker 2: I don't I mean, are they running Do.

567
00:25:48,173 --> 00:25:50,293
Speaker 3: They care about some sort of printing press operation that

568
00:25:50,333 --> 00:25:51,653
Speaker 3: they're running out of? You know?

569
00:25:51,973 --> 00:25:56,453
Speaker 2: Yeah, I mean running a huge printing press to make

570
00:25:56,533 --> 00:26:00,373
Speaker 2: counterfeit money. Would it be worth you while considering the

571
00:26:00,653 --> 00:26:03,413
Speaker 2: attention you could possibly get for all the other think

572
00:26:03,493 --> 00:26:04,293
Speaker 2: stuff you're up to.

573
00:26:04,253 --> 00:26:05,613
Speaker 3: It feels like a lot of fair Oh eight one

574
00:26:05,653 --> 00:26:07,213
Speaker 3: hundred and eighty ten eighty.

575
00:26:07,133 --> 00:26:09,093
Speaker 2: Is if you can just get it off team Yeah, Oh.

576
00:26:08,973 --> 00:26:10,413
Speaker 3: One hundred and eighty ten eighty is a number to

577
00:26:10,453 --> 00:26:13,453
Speaker 3: call if you've come across fake cash, keen to hear

578
00:26:13,573 --> 00:26:16,133
Speaker 3: your story, and if you run a business that takes

579
00:26:16,133 --> 00:26:19,493
Speaker 3: in cash, whether that's retail, dairy, cafe, pub, how often

580
00:26:19,493 --> 00:26:21,573
Speaker 3: have you seen this fake money coming in and how

581
00:26:21,613 --> 00:26:24,453
Speaker 3: can you tell shear your story? It is twenty one

582
00:26:24,533 --> 00:26:27,173
Speaker 3: to two, Beckfory, surely a fresh.

583
00:26:26,893 --> 00:26:30,213
Speaker 1: Take on took Back Matt Heath and Tyler Adams afternoons

584
00:26:30,373 --> 00:26:31,133
Speaker 1: with Skoda.

585
00:26:31,373 --> 00:26:33,573
Speaker 7: Please sCOD codes every day at.

586
00:26:33,413 --> 00:26:36,693
Speaker 18: Scoder dot co dot NSAD. Have your say on eight.

587
00:26:36,693 --> 00:26:39,133
Speaker 7: Hundred and eighty ten eighty news talks'd.

588
00:26:38,733 --> 00:26:41,773
Speaker 3: B eighteen to two. We're talking about counterfish, counterfeit cash.

589
00:26:41,813 --> 00:26:42,853
Speaker 3: Plenty of texts coming through.

590
00:26:43,013 --> 00:26:44,693
Speaker 2: Hi, guys, you don't need to rip the notes. You

591
00:26:44,733 --> 00:26:47,453
Speaker 2: don't need expensive UV lights. You just need to look

592
00:26:47,453 --> 00:26:49,333
Speaker 2: at the front face of the note and where the

593
00:26:49,453 --> 00:26:52,693
Speaker 2: hologram runs through the native bird. When you move the note,

594
00:26:52,693 --> 00:26:55,933
Speaker 2: that hologram must move as well. If it doesn't, it's fake,

595
00:26:56,133 --> 00:27:00,493
Speaker 2: cheers Simon. So is it just that only governments have

596
00:27:00,613 --> 00:27:04,493
Speaker 2: the kind of money to set up the printing such

597
00:27:04,533 --> 00:27:06,533
Speaker 2: that they can make these notes that are so hard

598
00:27:06,573 --> 00:27:06,893
Speaker 2: to fake.

599
00:27:07,573 --> 00:27:08,253
Speaker 3: I think you're right.

600
00:27:08,733 --> 00:27:10,573
Speaker 2: I think you just have to invest so many millions

601
00:27:10,573 --> 00:27:12,453
Speaker 2: of dollars into the printing press.

602
00:27:12,573 --> 00:27:15,133
Speaker 3: Yeah, it's got to be at that very high level,

603
00:27:15,133 --> 00:27:17,493
Speaker 3: and the paper that is used is very difficult to

604
00:27:17,493 --> 00:27:18,493
Speaker 3: get as I understand it.

605
00:27:18,533 --> 00:27:20,773
Speaker 2: But if you know, can to hear from you. They

606
00:27:20,893 --> 00:27:25,373
Speaker 2: used to an old counterfeiting rackets back in the day

607
00:27:25,653 --> 00:27:28,853
Speaker 2: in the States. They used to bleach the money, so

608
00:27:28,893 --> 00:27:31,333
Speaker 2: they have the same paper I believe, right, so bleached

609
00:27:31,413 --> 00:27:33,493
Speaker 2: the money and then printed with a higher bill so

610
00:27:33,533 --> 00:27:34,533
Speaker 2: it felt the same.

611
00:27:34,453 --> 00:27:38,213
Speaker 3: Right, high, high level. Joe, how are you this afternoon?

612
00:27:39,213 --> 00:27:40,933
Speaker 19: Hey, Jasi's are going good? Thanks?

613
00:27:40,973 --> 00:27:42,253
Speaker 2: Hanging on minut I've just got to walk back my

614
00:27:42,333 --> 00:27:44,653
Speaker 2: last comments. That was from a Jack Reacher book. I

615
00:27:44,693 --> 00:27:48,493
Speaker 2: realized now right, Okay, okay, I'm not good writing.

616
00:27:48,733 --> 00:27:51,253
Speaker 3: But whether that's the reality.

617
00:27:50,853 --> 00:27:54,493
Speaker 2: I'm not sure if that was from ET or research. Yeah,

618
00:27:54,973 --> 00:27:57,973
Speaker 2: all right, anyway, Joe, you go, yeah it is.

619
00:27:58,693 --> 00:28:00,813
Speaker 19: I'm an Auckland FC fan and I was listening to

620
00:28:00,853 --> 00:28:03,693
Speaker 19: you guys show just on the drove of a little

621
00:28:03,693 --> 00:28:06,133
Speaker 19: bit off topic. But a bunch of us made some

622
00:28:06,253 --> 00:28:09,973
Speaker 19: sort of fake cash, but we didn't use like a

623
00:28:10,133 --> 00:28:13,053
Speaker 19: United States emblem. We made our own emblem with with

624
00:28:13,133 --> 00:28:16,373
Speaker 19: the club franchise owner, so our own currency and got

625
00:28:16,413 --> 00:28:18,773
Speaker 19: to print it out laminade and all of that. And

626
00:28:18,973 --> 00:28:20,653
Speaker 19: I don't know if you guys saw the game between

627
00:28:20,693 --> 00:28:23,773
Speaker 19: open FC and Wellington Phoenix a couple of weeks back. Yeah,

628
00:28:23,813 --> 00:28:25,373
Speaker 19: but we threw a bunch of cash in there and

629
00:28:25,373 --> 00:28:28,733
Speaker 19: made it rain. But I know there was a bunch

630
00:28:28,773 --> 00:28:30,533
Speaker 19: of guys that wanted to use a cash at some

631
00:28:31,773 --> 00:28:33,973
Speaker 19: lesser respectable places afterwards.

632
00:28:35,893 --> 00:28:37,493
Speaker 2: You got to be careful with that. So were you

633
00:28:37,653 --> 00:28:40,293
Speaker 2: concerned when you were making it rain that the counterfeiting

634
00:28:40,413 --> 00:28:42,973
Speaker 2: anti counterfeiting unit would come in and smash you guys

635
00:28:43,053 --> 00:28:46,293
Speaker 2: up and do you for seven years for breaking the

636
00:28:46,293 --> 00:28:48,453
Speaker 2: anti counterfeiting hars Now?

637
00:28:48,573 --> 00:28:50,773
Speaker 19: We thought we would be fine because we're proud of

638
00:28:50,813 --> 00:28:51,653
Speaker 19: New Zealand nowadays.

639
00:28:52,573 --> 00:28:54,453
Speaker 2: Right, Yeah, so you did you start to feel a

640
00:28:54,453 --> 00:28:57,493
Speaker 2: little bit sorry for the Phoenix during that game because

641
00:28:57,533 --> 00:29:01,173
Speaker 2: that was that was a club destroying performance from AFC.

642
00:29:00,973 --> 00:29:03,413
Speaker 19: One hundred percent. You know, halftime it was a bit

643
00:29:03,613 --> 00:29:06,253
Speaker 19: you know, it got a bit old by then and

644
00:29:06,573 --> 00:29:08,213
Speaker 19: we're kind of hoping for a better game in this

645
00:29:08,333 --> 00:29:10,653
Speaker 19: se and a half and yeah, they come out second half,

646
00:29:10,693 --> 00:29:13,013
Speaker 19: try try to give it a go at least make

647
00:29:13,053 --> 00:29:15,893
Speaker 19: them make a game out of it. But he we

648
00:29:15,933 --> 00:29:17,213
Speaker 19: went home smailing.

649
00:29:16,973 --> 00:29:18,733
Speaker 2: I bet you did made it rain.

650
00:29:18,973 --> 00:29:19,213
Speaker 20: Yeah.

651
00:29:19,333 --> 00:29:20,933
Speaker 3: I mean it was a bit like stop stop they

652
00:29:21,053 --> 00:29:24,093
Speaker 3: already did, but you know, I'm sure the phoenix could come.

653
00:29:23,933 --> 00:29:26,093
Speaker 2: Back, Yeah, and then try to slip that money into

654
00:29:26,093 --> 00:29:30,973
Speaker 2: people's undecent yes and disreputable organizations.

655
00:29:31,093 --> 00:29:33,653
Speaker 3: Joe, thank you very much for your call. So how

656
00:29:33,693 --> 00:29:36,613
Speaker 3: big of an issue is counterfeit cash when it comes

657
00:29:36,653 --> 00:29:40,053
Speaker 3: to retail operations? Joining us now is Carolyn Young. She

658
00:29:40,293 --> 00:29:42,773
Speaker 3: is Retail end ZED CEO. Thank you very much for

659
00:29:42,813 --> 00:29:43,133
Speaker 3: your time.

660
00:29:43,173 --> 00:29:45,453
Speaker 11: Carolyn Callen, nice to be here.

661
00:29:45,733 --> 00:29:48,253
Speaker 2: How big the problem is counterfeit money in New Zealand?

662
00:29:48,333 --> 00:29:51,933
Speaker 11: Carolyn, Oh, Look, it comes and goes. There's always some

663
00:29:52,053 --> 00:29:55,893
Speaker 11: notes in circulation, but we do notice waves of counterfeit

664
00:29:55,933 --> 00:29:58,453
Speaker 11: notes at different times and we're always going out time

665
00:29:58,453 --> 00:30:00,653
Speaker 11: members at those times to make sure we work closely

666
00:30:00,733 --> 00:30:03,413
Speaker 11: with the Reserve Bank and the New Zealand Police to

667
00:30:04,133 --> 00:30:06,013
Speaker 11: ensure that we kept up to date so that we

668
00:30:06,053 --> 00:30:09,413
Speaker 11: can notify retailers. And obviously there's some We've got some

669
00:30:09,453 --> 00:30:12,173
Speaker 11: good tools and resources on our website and so has

670
00:30:12,213 --> 00:30:14,893
Speaker 11: the Reserve Bank of New Zealand. So you know, obviously

671
00:30:14,973 --> 00:30:19,253
Speaker 11: that whole idea around ensuring that your staff are trained

672
00:30:19,933 --> 00:30:22,933
Speaker 11: to understand what cash looks and feels like, because a

673
00:30:22,933 --> 00:30:25,413
Speaker 11: lot of people don't young people especially don't use cash

674
00:30:25,453 --> 00:30:28,573
Speaker 11: these so that look feel, tilt tests and making sure

675
00:30:28,613 --> 00:30:31,133
Speaker 11: you understand what you should see in that hologram, it's

676
00:30:31,173 --> 00:30:33,493
Speaker 11: really important. One of the things we do know is

677
00:30:33,533 --> 00:30:37,093
Speaker 11: that one hundred dollar bills you know, are very rare

678
00:30:37,093 --> 00:30:38,973
Speaker 11: in New Zealand. The only way you can get one

679
00:30:39,013 --> 00:30:41,653
Speaker 11: hundred dollar bill is if you actually physically go into

680
00:30:41,693 --> 00:30:44,253
Speaker 11: the bank right and you and I both know we

681
00:30:44,253 --> 00:30:46,493
Speaker 11: don't get into the bank very often these days right

682
00:30:46,653 --> 00:30:49,733
Speaker 11: right there banks left and they're not open very often,

683
00:30:49,853 --> 00:30:52,053
Speaker 11: so you're not going to get one from an ATM,

684
00:30:52,093 --> 00:30:54,453
Speaker 11: and you probably wouldn't get one from someone's tools. So

685
00:30:54,933 --> 00:30:58,093
Speaker 11: be very cautious around one hundred dollar bill to make

686
00:30:58,133 --> 00:31:02,293
Speaker 11: sure that it is actually really valid and you can actually,

687
00:31:03,333 --> 00:31:05,773
Speaker 11: you know, make sure that one you've trained your staff

688
00:31:05,853 --> 00:31:08,053
Speaker 11: and to that if you have any concern at all,

689
00:31:08,093 --> 00:31:11,373
Speaker 11: you can to slightly refused to accept that cash. So

690
00:31:11,453 --> 00:31:14,213
Speaker 11: I think the key thing is doing staff training and

691
00:31:14,253 --> 00:31:18,933
Speaker 11: have doing it in advance of an issue. Arising. There

692
00:31:18,973 --> 00:31:21,413
Speaker 11: is a correction to the story on stuff at the moment.

693
00:31:21,453 --> 00:31:25,573
Speaker 11: It's actually an older story that's been reissued out. There's

694
00:31:25,613 --> 00:31:29,133
Speaker 11: not a particular area of concern. I've spoken both to

695
00:31:29,173 --> 00:31:31,453
Speaker 11: the police and Reserve Bank through thing this morning.

696
00:31:31,813 --> 00:31:32,333
Speaker 17: But it is.

697
00:31:32,413 --> 00:31:34,333
Speaker 11: Always good for people to be aware that there are

698
00:31:34,373 --> 00:31:39,133
Speaker 11: counterfeit notes in circulation and we have unfortunately found some

699
00:31:39,293 --> 00:31:42,333
Speaker 11: that have been imported in New Zealand last year from

700
00:31:42,333 --> 00:31:46,133
Speaker 11: overseas and that's caused some concern. So I know that

701
00:31:46,213 --> 00:31:49,493
Speaker 11: Reserve Bank has done some work with trying to ensure

702
00:31:49,533 --> 00:31:53,013
Speaker 11: that the source of those notes is no longer able

703
00:31:53,053 --> 00:31:53,653
Speaker 11: to sell them.

704
00:31:53,693 --> 00:31:56,373
Speaker 4: But it is a bit of a challenge classic stuff.

705
00:31:56,493 --> 00:32:01,213
Speaker 2: Now, who's where where does the liability sit for an

706
00:32:01,253 --> 00:32:06,733
Speaker 2: employee who's accepted money? Is that on them? Do they

707
00:32:07,413 --> 00:32:10,773
Speaker 2: have to pay it back? Or you know, whose responsibility

708
00:32:10,813 --> 00:32:11,853
Speaker 2: is it that that money's coming?

709
00:32:12,893 --> 00:32:15,013
Speaker 11: Yeah, look, I think you know each business would do this,

710
00:32:15,053 --> 00:32:17,173
Speaker 11: and so I haven't ever heard of a business saying

711
00:32:17,213 --> 00:32:21,893
Speaker 11: to a staff member, you'll need to replace replace that money.

712
00:32:21,893 --> 00:32:24,213
Speaker 11: It's an error and we know that eras occur from

713
00:32:24,253 --> 00:32:26,853
Speaker 11: time to time in any job that you know, you

714
00:32:26,893 --> 00:32:29,133
Speaker 11: will know yourself, you'll have made a mistake from time

715
00:32:29,173 --> 00:32:32,053
Speaker 11: to time, and its system as long as you know,

716
00:32:32,133 --> 00:32:35,213
Speaker 11: you provide good training and you teach your staff around

717
00:32:35,253 --> 00:32:39,093
Speaker 11: how to really identify those right factors, and as long

718
00:32:39,133 --> 00:32:43,613
Speaker 11: as you're clear that someone's not part of an operation

719
00:32:43,693 --> 00:32:46,333
Speaker 11: where they are trying to launder money through a retail list.

720
00:32:46,333 --> 00:32:49,733
Speaker 11: So I think that's the important thing, and identifying you know,

721
00:32:49,773 --> 00:32:52,653
Speaker 11: who is using that cash and what items are they're buying.

722
00:32:53,133 --> 00:32:56,653
Speaker 11: There's CCTV in virtually every store. I don't know any

723
00:32:56,653 --> 00:33:00,813
Speaker 11: store that doesn't have CTC CCTV these days, and usually

724
00:33:00,853 --> 00:33:03,453
Speaker 11: there are is good cameras over the counter, so you

725
00:33:03,493 --> 00:33:08,333
Speaker 11: can use those images for the police, so you can

726
00:33:08,453 --> 00:33:11,413
Speaker 11: obviously report it to the police is really important and

727
00:33:11,493 --> 00:33:14,173
Speaker 11: they can come in and get access to your with

728
00:33:14,373 --> 00:33:14,893
Speaker 11: those images.

729
00:33:14,973 --> 00:33:18,653
Speaker 2: We've had a few people say that you know, working

730
00:33:18,693 --> 00:33:21,733
Speaker 2: in stores or in their stores, they get some counterfeit money,

731
00:33:21,813 --> 00:33:24,893
Speaker 2: they contact the police and the police uninterested. Is that

732
00:33:25,133 --> 00:33:29,013
Speaker 2: is it a big priority for police or is it

733
00:33:29,093 --> 00:33:30,773
Speaker 2: kind of on the back burner because in most of

734
00:33:30,813 --> 00:33:33,813
Speaker 2: our money is digital these days.

735
00:33:33,413 --> 00:33:37,693
Speaker 11: It's an issue amongst a range of issues and priorities,

736
00:33:37,733 --> 00:33:40,613
Speaker 11: and certainly if they can get in touch with us

737
00:33:40,653 --> 00:33:42,253
Speaker 11: at retail and then and we can make sure we

738
00:33:42,293 --> 00:33:43,933
Speaker 11: get them in touch with the right people at the

739
00:33:43,933 --> 00:33:46,573
Speaker 11: police that will be able to respond to that. So,

740
00:33:47,493 --> 00:33:49,533
Speaker 11: you know, we do want to make sure that we

741
00:33:49,613 --> 00:33:53,653
Speaker 11: capture people that are holding money illegally because it is

742
00:33:53,693 --> 00:33:57,213
Speaker 11: a serious events and it does put into question the

743
00:33:57,293 --> 00:34:00,693
Speaker 11: quality of the notes in circulation for you and I,

744
00:34:00,853 --> 00:34:03,733
Speaker 11: so certainly police it is a priority for them to

745
00:34:03,773 --> 00:34:05,893
Speaker 11: make sure that we don't have that in circulation, and

746
00:34:05,933 --> 00:34:09,292
Speaker 11: the Reserve Bank are really mine full of that, right.

747
00:34:09,613 --> 00:34:12,053
Speaker 3: I've noticed in a couple of places I go into

748
00:34:12,093 --> 00:34:15,013
Speaker 3: retail places that clearly they've come across a fake note

749
00:34:15,013 --> 00:34:18,413
Speaker 3: and they've plastered it next to the cashier to show,

750
00:34:18,493 --> 00:34:20,893
Speaker 3: you know, potential customers coming in, hey, we've found this

751
00:34:21,253 --> 00:34:23,652
Speaker 3: and we're on to you if you've got one of these.

752
00:34:23,973 --> 00:34:26,013
Speaker 3: But that could put some liability on them, right if

753
00:34:26,053 --> 00:34:28,333
Speaker 3: they haven't handed that into the police. Is that a

754
00:34:28,413 --> 00:34:30,973
Speaker 3: concern for those retailers who keep that cash is a

755
00:34:30,973 --> 00:34:34,573
Speaker 3: bit of a warning they might you know, they're aware

756
00:34:34,613 --> 00:34:36,853
Speaker 3: that they've got access to counterfeit cash and they might

757
00:34:36,853 --> 00:34:37,533
Speaker 3: need to hand that in.

758
00:34:38,373 --> 00:34:40,493
Speaker 11: Yeah, wouldn't be a wise thing to hold on to it.

759
00:34:40,613 --> 00:34:42,732
Speaker 11: The wisest thing to do is to make sure that

760
00:34:42,773 --> 00:34:45,893
Speaker 11: you do hand that in because we don't want notes

761
00:34:45,933 --> 00:34:49,773
Speaker 11: in circulation at all. It's you know, whilst you've if

762
00:34:49,853 --> 00:34:52,533
Speaker 11: you have found that you've had a fake note that

763
00:34:52,653 --> 00:34:55,213
Speaker 11: arrive in your store, will be arriving in someone else's

764
00:34:55,213 --> 00:34:58,853
Speaker 11: And if someone somehow the grabs that note off the

765
00:34:58,933 --> 00:35:02,493
Speaker 11: counter and then you know, use it elsewhere, then someone

766
00:35:02,493 --> 00:35:06,293
Speaker 11: else's also suffering from that perspective. So making sure you

767
00:35:06,373 --> 00:35:08,053
Speaker 11: hand those notes in is really important.

768
00:35:08,373 --> 00:35:10,973
Speaker 3: Rolyn, thank you so much for your time. Really appreciate it.

769
00:35:10,973 --> 00:35:14,893
Speaker 3: That is Carolyn Young, Retail in z CEO. It is

770
00:35:15,013 --> 00:35:16,853
Speaker 3: ten minutes to two. If you want to send a

771
00:35:16,893 --> 00:35:18,733
Speaker 3: text nine two nine too, is that number. We'll get

772
00:35:18,773 --> 00:35:20,573
Speaker 3: to a couple of those very surely.

773
00:35:21,933 --> 00:35:25,493
Speaker 1: Matt Heath, Taylor Adams taking your calls on eight hundred

774
00:35:25,493 --> 00:35:26,373
Speaker 1: and eighty ten eighty.

775
00:35:26,413 --> 00:35:29,893
Speaker 7: It's Matt Heath and Tyler Adams afternoons news talks be.

776
00:35:31,653 --> 00:35:34,613
Speaker 3: It is seven to two. Frank, you're in the printing

777
00:35:34,653 --> 00:35:37,253
Speaker 3: game and you know a bit about how money is created.

778
00:35:38,613 --> 00:35:41,333
Speaker 21: Yeah, a little, but it's all of out our money.

779
00:35:41,373 --> 00:35:43,493
Speaker 21: We used at the moment the polem and not Social

780
00:35:43,533 --> 00:35:47,172
Speaker 21: President in Canada, by the Canadian Banknote Company, and then

781
00:35:47,453 --> 00:35:49,333
Speaker 21: I've been doing most for about thirty years. I think

782
00:35:49,453 --> 00:35:52,053
Speaker 21: before then we were doing it ourselves when it was

783
00:35:52,053 --> 00:35:54,973
Speaker 21: still on the paper. We're doing ourselves up and find.

784
00:35:54,773 --> 00:35:55,053
Speaker 22: Our a.

785
00:35:56,493 --> 00:35:56,732
Speaker 18: Right.

786
00:35:57,013 --> 00:35:59,853
Speaker 3: So, so Canada makes it all and then hips it

787
00:35:59,893 --> 00:36:02,053
Speaker 3: over here and then the Reserve Bank allocated out.

788
00:36:02,853 --> 00:36:04,973
Speaker 21: They're just basically a printing company that everyone goes to

789
00:36:04,973 --> 00:36:07,613
Speaker 21: get you money printed at. Now they I'll probably do

790
00:36:07,653 --> 00:36:11,773
Speaker 21: all of thee civical islands, maybe from northern Herest countries

791
00:36:11,773 --> 00:36:12,133
Speaker 21: as well.

792
00:36:12,213 --> 00:36:14,172
Speaker 2: Have you got any idea how much we pay for

793
00:36:14,213 --> 00:36:17,732
Speaker 2: a fifty dollars note per unit to be printed by

794
00:36:18,413 --> 00:36:19,413
Speaker 2: some Canadian company.

795
00:36:20,013 --> 00:36:22,013
Speaker 21: No, I don't know. Actually I've never thought of it

796
00:36:22,013 --> 00:36:23,333
Speaker 21: like that, but I made it's pretty cheap.

797
00:36:24,373 --> 00:36:26,613
Speaker 2: Yeah, I mean they must have an incredible setup over there.

798
00:36:26,653 --> 00:36:29,773
Speaker 2: There must be like several money.

799
00:36:30,573 --> 00:36:33,853
Speaker 21: Apro because there's a lot of microprinting that you can

800
00:36:33,853 --> 00:36:34,973
Speaker 21: only se nd a microscope.

801
00:36:35,253 --> 00:36:35,533
Speaker 2: Yeah.

802
00:36:35,813 --> 00:36:38,692
Speaker 21: As far as the counterfeiting, any caunterfeiting sort of side

803
00:36:38,773 --> 00:36:40,493
Speaker 21: that goes, yeah, it's pretty fascinating. It's fun.

804
00:36:40,853 --> 00:36:41,093
Speaker 22: Yeah.

805
00:36:41,253 --> 00:36:43,093
Speaker 21: Yeah, it's quite a good job.

806
00:36:43,253 --> 00:36:45,573
Speaker 3: So the materials that they use to make money is

807
00:36:45,613 --> 00:36:48,173
Speaker 3: that traditionally quite hard to get for a counterfeiter that

808
00:36:48,213 --> 00:36:50,133
Speaker 3: wants to try and replicate.

809
00:36:49,693 --> 00:36:52,213
Speaker 21: It is that in the old days when it was paper,

810
00:36:52,413 --> 00:36:55,213
Speaker 21: but nowadays it's a polymer which you can just go

811
00:36:55,293 --> 00:36:58,893
Speaker 21: by on Washington a line. Now have ability of door

812
00:36:58,933 --> 00:37:01,293
Speaker 21: by courier. But nowadays it was a paper like the

813
00:37:01,493 --> 00:37:04,252
Speaker 21: American money is actually printed on a Linden that's really

814
00:37:04,253 --> 00:37:07,733
Speaker 21: hard to counterfeit, right, so.

815
00:37:07,653 --> 00:37:10,893
Speaker 3: Our money is see to counterfeit. Then in the American dollar.

816
00:37:12,253 --> 00:37:16,133
Speaker 21: We aver easier by it's easier to make the polemer

817
00:37:16,133 --> 00:37:19,973
Speaker 21: notes here because the Americans user are being used learning

818
00:37:20,173 --> 00:37:22,693
Speaker 21: basically to make their paper, and it's it's a pretty

819
00:37:22,733 --> 00:37:25,172
Speaker 21: secret sort of process. So to give that same steel

820
00:37:25,213 --> 00:37:27,732
Speaker 21: and texture of the paper money's lot harder than than

821
00:37:27,813 --> 00:37:29,373
Speaker 21: making a place poll on the sheet.

822
00:37:30,333 --> 00:37:32,933
Speaker 3: Fascinating, Frank, thanks very much for giving us a buzz.

823
00:37:33,133 --> 00:37:37,573
Speaker 2: So it's made by the Canada Bank, a Canadian bank

824
00:37:37,573 --> 00:37:41,933
Speaker 2: note company, the CBNC in Ottawa, Canada, so that they

825
00:37:42,573 --> 00:37:45,733
Speaker 2: you can't find a single cost of per per note,

826
00:37:45,813 --> 00:37:49,653
Speaker 2: but the project costs about eighty million dollars New Zealand dollars.

827
00:37:50,413 --> 00:37:54,053
Speaker 3: Seems reasonable the amount of money they print. I'm just

828
00:37:54,053 --> 00:37:55,573
Speaker 3: going to get my head around that, so we pay

829
00:37:55,573 --> 00:37:57,133
Speaker 3: them eighty million to make our money.

830
00:37:57,173 --> 00:37:59,413
Speaker 2: There's a guy here that it estimates if it wasn't

831
00:37:59,453 --> 00:38:03,053
Speaker 2: being done at a you know, at an incredibly sort

832
00:38:03,053 --> 00:38:06,453
Speaker 2: of high rate, you know, mass produced, it would cost

833
00:38:06,493 --> 00:38:10,613
Speaker 2: one hundred and one dollar per right, there'd be nearly

834
00:38:10,653 --> 00:38:13,013
Speaker 2: four dollars a bill. But of course they're printing so

835
00:38:13,053 --> 00:38:14,133
Speaker 2: many it's cheaper than that.

836
00:38:14,253 --> 00:38:17,093
Speaker 3: Yeah, great discussion. Thank you to everybody who called and

837
00:38:17,293 --> 00:38:20,973
Speaker 3: text about the counterfeit money. Coming up after two o'clock,

838
00:38:21,013 --> 00:38:24,212
Speaker 3: we want to have a chat about artificial intelligence. New

839
00:38:24,333 --> 00:38:27,413
Speaker 3: stats out show that if you've never used AI in

840
00:38:27,493 --> 00:38:30,253
Speaker 3: your life, you're in the majority by far. So I

841
00:38:30,253 --> 00:38:31,812
Speaker 3: want to have a chat to you. Oh, eighte hundred

842
00:38:31,853 --> 00:38:34,013
Speaker 3: and eighty ten eighty is that number to call? Nine

843
00:38:34,093 --> 00:38:36,093
Speaker 3: two ninety two is the text? New sport and weather

844
00:38:36,253 --> 00:38:37,853
Speaker 3: is coming up. You listening to Matt and Tyler hobe

845
00:38:37,853 --> 00:38:39,253
Speaker 3: you having a great Friday afternoon.

846
00:38:47,613 --> 00:38:51,813
Speaker 1: The big stories, the big issues, the big trends and

847
00:38:52,053 --> 00:38:55,813
Speaker 1: everything in between. It's Matt Heath and Tyler Adams Afternoon

848
00:38:55,973 --> 00:39:00,293
Speaker 1: squid shod News Talk said be it's very good afternoons.

849
00:39:00,373 --> 00:39:03,773
Speaker 3: You welcome back into the show. Six pass two for

850
00:39:03,813 --> 00:39:06,453
Speaker 3: the next hour or so, we want to discuss AI.

851
00:39:06,573 --> 00:39:11,533
Speaker 3: A recent visualization about artificial intelligence really puts things into perspective.

852
00:39:11,653 --> 00:39:16,173
Speaker 3: That's gone viral online. But the visualization shows out of

853
00:39:16,213 --> 00:39:20,212
Speaker 3: the world's eight point one billion people, around six point

854
00:39:20,213 --> 00:39:24,373
Speaker 3: eight billion have never never used AI at all, only

855
00:39:24,413 --> 00:39:27,652
Speaker 3: around fifteen to twenty five million people actually pay for

856
00:39:27,693 --> 00:39:31,692
Speaker 3: the AI tools, and only around two percent actually use

857
00:39:31,813 --> 00:39:36,373
Speaker 3: AI for detailed development work and other Even more striking,

858
00:39:36,413 --> 00:39:38,973
Speaker 3: eighty two percent of American businesses say they have never

859
00:39:39,093 --> 00:39:43,652
Speaker 3: used AI in any shape or form. So the question

860
00:39:43,733 --> 00:39:45,093
Speaker 3: I want to put to you is, if you're one

861
00:39:45,093 --> 00:39:47,493
Speaker 3: of the six point eight billion people in the world

862
00:39:47,493 --> 00:39:52,533
Speaker 3: that have never used artificial intelligence, why it's interesting, isn't it?

863
00:39:52,533 --> 00:39:57,053
Speaker 2: Because all everyone bangs on about is AIAI, this, AI that.

864
00:39:57,133 --> 00:39:59,373
Speaker 2: But what did you say? Fifteen million people are paying

865
00:39:59,413 --> 00:40:01,973
Speaker 2: for it? Yeah, So that's where this big gap is

866
00:40:02,133 --> 00:40:05,853
Speaker 2: between how much is being pumped into AI. So expected

867
00:40:05,893 --> 00:40:08,253
Speaker 2: to be two point five trillion dollars being pumped in

868
00:40:08,453 --> 00:40:12,013
Speaker 2: to AI this year alone. That's you know, to pay

869
00:40:12,053 --> 00:40:16,573
Speaker 2: for the data centers and cloud infrastructure, the GPUs and chips,

870
00:40:16,613 --> 00:40:21,692
Speaker 2: the training, the large models, electricity and cooling is a huge, huge,

871
00:40:21,733 --> 00:40:24,053
Speaker 2: part of it as well as you know, software developments

872
00:40:24,093 --> 00:40:27,773
Speaker 2: and all the AI startups, all the you know angel

873
00:40:27,813 --> 00:40:30,652
Speaker 2: funding that's going into it. So two point five three

874
00:40:30,773 --> 00:40:36,053
Speaker 2: trillion dollars, it's a huge amount globally, expecting to return

875
00:40:36,573 --> 00:40:38,133
Speaker 2: three hundred billion dollars.

876
00:40:38,613 --> 00:40:41,413
Speaker 3: So they can't keep that up. No, that's going to collapse.

877
00:40:41,613 --> 00:40:45,853
Speaker 2: At some point, that will stop because right now everyone's

878
00:40:45,893 --> 00:40:49,493
Speaker 2: decided this is all in. And this kind of thing

879
00:40:49,533 --> 00:40:54,253
Speaker 2: happens regularly in the world. Of course, you know, famously

880
00:40:54,413 --> 00:40:58,653
Speaker 2: the railways back in the eighteen forties, everyone just pumped

881
00:40:58,653 --> 00:41:00,453
Speaker 2: all the money into the railways, go, go, go, go go,

882
00:41:00,493 --> 00:41:04,652
Speaker 2: and then there was a big, big, big bubble burst. Yes,

883
00:41:04,733 --> 00:41:06,373
Speaker 2: but then later on the railways did come back and

884
00:41:06,373 --> 00:41:10,773
Speaker 2: become very very very important. There was electricity built up

885
00:41:10,773 --> 00:41:13,413
Speaker 2: in the nineteen hundreds, you know, nineteen tens around that.

886
00:41:13,413 --> 00:41:14,853
Speaker 2: It was the same kind of thing, the dot com

887
00:41:14,853 --> 00:41:19,212
Speaker 2: bubble and the nineteen ninety five two thousand and then

888
00:41:19,333 --> 00:41:22,613
Speaker 2: you know, nowadays it's the AI one. But I think

889
00:41:22,653 --> 00:41:25,133
Speaker 2: the AI one's even bigger than all of those combined.

890
00:41:25,213 --> 00:41:28,093
Speaker 3: Yeah, when I saw the stats, what ran through my

891
00:41:28,173 --> 00:41:30,013
Speaker 3: head is I do feel that I'm behind in the

892
00:41:30,053 --> 00:41:33,133
Speaker 3: AI game. That's I'm not using it to the best

893
00:41:33,173 --> 00:41:36,692
Speaker 3: of my ability and not harnessing the potential that it's got.

894
00:41:36,733 --> 00:41:38,813
Speaker 3: But then the other half of my brain says, I

895
00:41:38,813 --> 00:41:40,853
Speaker 3: don't want to use it as much as as maybe

896
00:41:40,853 --> 00:41:43,013
Speaker 3: other people are using it because we've had discussions about

897
00:41:43,053 --> 00:41:46,173
Speaker 3: what it does to your brain and how you compute

898
00:41:46,173 --> 00:41:50,613
Speaker 3: and you rationale things in your life. So allowing artificial

899
00:41:50,613 --> 00:41:52,893
Speaker 3: intelligence to do that for me and turn my brain

900
00:41:52,933 --> 00:41:55,973
Speaker 3: into much scares me. But it's a hard one because

901
00:41:56,013 --> 00:41:57,933
Speaker 3: I can see, I mean clearly, there's been a lot

902
00:41:57,973 --> 00:42:00,293
Speaker 3: of hype around our artificial intelligence in the past couple

903
00:42:00,333 --> 00:42:02,413
Speaker 3: of years, and I can see there are some clear

904
00:42:02,493 --> 00:42:05,373
Speaker 3: advantages that if you've got a business or you as

905
00:42:05,373 --> 00:42:07,813
Speaker 3: an individual have an idea that you want to do,

906
00:42:07,893 --> 00:42:10,813
Speaker 3: you want to out of business whatever artificial intelligence can

907
00:42:10,813 --> 00:42:13,973
Speaker 3: help you do that. But at the same side of

908
00:42:14,013 --> 00:42:16,333
Speaker 3: the coin, or the flip side of that coin, is

909
00:42:16,493 --> 00:42:19,053
Speaker 3: that I still want to have a functioning brain that

910
00:42:19,093 --> 00:42:21,133
Speaker 3: can do things that I've always done without farming that

911
00:42:21,173 --> 00:42:22,813
Speaker 3: out to artificial intelligence to do for me.

912
00:42:22,893 --> 00:42:25,773
Speaker 2: Yes, that is us saying it's making people dumber. Anytime

913
00:42:26,013 --> 00:42:30,772
Speaker 2: you know, outsource any kind of thinking, Then that part

914
00:42:30,773 --> 00:42:34,133
Speaker 2: of your brain gets weaker. Right, And there's different industries

915
00:42:34,173 --> 00:42:37,093
Speaker 2: that will be using it in different ways, but you

916
00:42:37,133 --> 00:42:40,493
Speaker 2: know the basic just using the consumer model of GROH

917
00:42:40,653 --> 00:42:44,373
Speaker 2: or chat GPT or Claude or whatever two in your

918
00:42:44,453 --> 00:42:47,733
Speaker 2: day to day work, right, that seems to be making

919
00:42:47,733 --> 00:42:53,013
Speaker 2: people a bit dumber. Yes, yes, But also on top

920
00:42:53,053 --> 00:42:55,813
Speaker 2: of that, I watched this really interesting video last night.

921
00:42:55,813 --> 00:42:57,453
Speaker 2: I should try and find it. It's just popped back

922
00:42:57,453 --> 00:42:59,493
Speaker 2: into my mind. But it's this guy and he was

923
00:42:59,533 --> 00:43:02,413
Speaker 2: talking about how you shouldn't spend any time with chet GPT,

924
00:43:02,533 --> 00:43:04,533
Speaker 2: and it was describing it about a friend that never

925
00:43:04,573 --> 00:43:07,173
Speaker 2: really questions you and is always pumping up your tires

926
00:43:07,853 --> 00:43:10,973
Speaker 2: and as a result, never challenges you. Yes, and that

927
00:43:11,133 --> 00:43:13,333
Speaker 2: is a very bad person to hang out with, because

928
00:43:13,333 --> 00:43:15,053
Speaker 2: a lot of people that are using AI a lot

929
00:43:15,173 --> 00:43:19,773
Speaker 2: are just hanging out with this person that is programmed

930
00:43:20,013 --> 00:43:22,813
Speaker 2: just keep them using it because it's a consumer model

931
00:43:22,893 --> 00:43:25,453
Speaker 2: chet GPT for example, so it wants to keep you

932
00:43:25,493 --> 00:43:28,293
Speaker 2: on all the time, So it just keeps asking you

933
00:43:28,413 --> 00:43:31,613
Speaker 2: questions and pumping up your tires, and if you say

934
00:43:31,653 --> 00:43:33,973
Speaker 2: anything to it, it's so ridiculously plait it less you

935
00:43:33,973 --> 00:43:37,533
Speaker 2: behave any way you want, and it's just never pushes

936
00:43:37,613 --> 00:43:40,253
Speaker 2: back in any way. Yeah, and so if that's someone

937
00:43:40,293 --> 00:43:42,533
Speaker 2: that you're interacting with, it's not someone. It's a large

938
00:43:42,613 --> 00:43:45,093
Speaker 2: language MODEGE so it has no consciousness, it has no

939
00:43:45,173 --> 00:43:47,333
Speaker 2: knowledge of what's going on. That's just how it's programmed

940
00:43:47,333 --> 00:43:50,013
Speaker 2: to react to you. Right, if you keep doing that,

941
00:43:50,093 --> 00:43:53,133
Speaker 2: then his argument was that's terrible for your personality.

942
00:43:53,253 --> 00:43:56,413
Speaker 3: Yeah, well, just focus you into the corner that you

943
00:43:56,573 --> 00:43:59,453
Speaker 3: kind of already in, right if you think a certain

944
00:43:59,493 --> 00:44:02,213
Speaker 3: way and chet GBT is pumping up your tithes and

945
00:44:02,253 --> 00:44:03,773
Speaker 3: then saying, hey, I can dig into this for you

946
00:44:03,853 --> 00:44:05,173
Speaker 3: if you like a great question.

947
00:44:05,533 --> 00:44:06,773
Speaker 2: And then and then you go and talk to a

948
00:44:06,813 --> 00:44:09,413
Speaker 2: real person, You're like, why is this person say so abrasive?

949
00:44:10,053 --> 00:44:13,053
Speaker 2: Why isn't this person doing not being ridiculously polite? No

950
00:44:13,093 --> 00:44:15,213
Speaker 2: matter what I say is why isn't this person just

951
00:44:15,333 --> 00:44:17,652
Speaker 2: standing there telling me I'm amazing. His second, it's like,

952
00:44:17,813 --> 00:44:20,773
Speaker 2: because that's a person with hopes and dreams and actually

953
00:44:20,813 --> 00:44:23,333
Speaker 2: cares about you and wants to correct you when you're

954
00:44:23,333 --> 00:44:24,172
Speaker 2: doing things that are wrong.

955
00:44:24,253 --> 00:44:24,453
Speaker 17: Yeah.

956
00:44:24,493 --> 00:44:27,013
Speaker 3: Oh, eight one hundred and eighty ten eighty. So are

957
00:44:27,053 --> 00:44:28,733
Speaker 3: you one of the people out there and clearly in

958
00:44:28,813 --> 00:44:31,373
Speaker 3: the majority, who has never used AI, and as a

959
00:44:31,413 --> 00:44:34,692
Speaker 3: business quite striking, eighty two percent of American businesses say

960
00:44:34,733 --> 00:44:37,613
Speaker 3: they have never used AI in any shape or form.

961
00:44:37,653 --> 00:44:40,053
Speaker 2: Are you the same, Well, Li says, I'm too scared.

962
00:44:40,613 --> 00:44:42,853
Speaker 2: I wouldn't have a clue how to do it anyway.

963
00:44:43,013 --> 00:44:45,173
Speaker 2: Although I can see there might be some good uses

964
00:44:45,213 --> 00:44:47,093
Speaker 2: for it, I think we need to be weary. If

965
00:44:47,133 --> 00:44:52,053
Speaker 2: it doesn't overtake everything, we could lose control. I mean,

966
00:44:52,053 --> 00:44:54,613
Speaker 2: the thing about being scared of AI is it is

967
00:44:54,613 --> 00:44:57,013
Speaker 2: probably one of the most user friendly pieces of technology

968
00:44:57,053 --> 00:45:00,293
Speaker 2: that has ever put up its hand. It's hit the

969
00:45:00,333 --> 00:45:03,053
Speaker 2: market so user friendly, Yeah, pretty somch You just if

970
00:45:03,053 --> 00:45:05,212
Speaker 2: you can write and ask a question, you can use

971
00:45:06,253 --> 00:45:07,413
Speaker 2: the consumer facing AI.

972
00:45:07,653 --> 00:45:09,733
Speaker 3: You need very very little technical knowledge.

973
00:45:09,773 --> 00:45:10,493
Speaker 18: Yeah yeah.

974
00:45:10,533 --> 00:45:13,813
Speaker 2: But I can see on a business level it might

975
00:45:13,853 --> 00:45:19,172
Speaker 2: be scary because of you know, who takes ultimate responsibility

976
00:45:19,213 --> 00:45:22,893
Speaker 2: for the outcomes yep, and such legally whether you bring

977
00:45:22,893 --> 00:45:27,252
Speaker 2: it in because ultimately, the illusions that come out of AI,

978
00:45:27,413 --> 00:45:31,653
Speaker 2: because it doesn't have common sense. It's just runs an algorithm,

979
00:45:31,853 --> 00:45:34,933
Speaker 2: and where things are close to other things in a

980
00:45:35,013 --> 00:45:36,893
Speaker 2: matrix is why it feeds back to you. So that's

981
00:45:36,893 --> 00:45:39,733
Speaker 2: why it comes back with such ridiculous answers sometimes, and

982
00:45:39,773 --> 00:45:41,333
Speaker 2: that's no good if you've set that out to your

983
00:45:41,333 --> 00:45:45,133
Speaker 2: client and now you've quoted something that's totally impossible.

984
00:45:45,213 --> 00:45:46,973
Speaker 3: And I imagine it would feel overwhelming for a lot

985
00:45:46,973 --> 00:45:49,173
Speaker 3: of businesses as well, if they've just got surface level

986
00:45:49,213 --> 00:45:51,773
Speaker 3: knowledge about AI and all they hear is that it's

987
00:45:51,813 --> 00:45:54,373
Speaker 3: advancing at this rapid rate, and it's changing all the time,

988
00:45:54,573 --> 00:45:57,373
Speaker 3: and here's an agent and here's something else associated with AI.

989
00:45:57,453 --> 00:45:59,413
Speaker 3: There be a lot of business owners saying I can't

990
00:45:59,453 --> 00:46:00,812
Speaker 3: keep up, so I'm just not going to bother.

991
00:46:01,053 --> 00:46:04,213
Speaker 2: So you part of the eighty two percent of businesses

992
00:46:04,533 --> 00:46:07,172
Speaker 2: if New Zealand matches the United States, And you might

993
00:46:07,253 --> 00:46:09,333
Speaker 2: argue that we would be have a higher number that

994
00:46:09,413 --> 00:46:13,253
Speaker 2: than that here because a lot of this AIS, you know,

995
00:46:13,493 --> 00:46:15,973
Speaker 2: has started in Silicon Valley, so you'd think that America

996
00:46:15,973 --> 00:46:16,893
Speaker 2: would adopt it first.

997
00:46:17,013 --> 00:46:17,252
Speaker 3: Yeah.

998
00:46:17,293 --> 00:46:18,893
Speaker 2: I mean, I'm not sure if that's true or not,

999
00:46:19,373 --> 00:46:21,732
Speaker 2: but let's say it's the same number here, eighty two

1000
00:46:21,773 --> 00:46:24,333
Speaker 2: percent of businesses. Are you Are you part of the

1001
00:46:24,453 --> 00:46:27,773
Speaker 2: eighty two percent of businesses that have no involvement with

1002
00:46:27,853 --> 00:46:31,613
Speaker 2: AI at all and no intention to bring it in?

1003
00:46:31,693 --> 00:46:31,933
Speaker 5: Yep?

1004
00:46:31,973 --> 00:46:34,013
Speaker 3: Share your story. Oh eight hundred eighty ten eighty is

1005
00:46:34,053 --> 00:46:36,013
Speaker 3: that number of call nine two nine two is the text?

1006
00:46:36,293 --> 00:46:38,893
Speaker 3: It is fourteen past two, will be back very surely.

1007
00:46:40,333 --> 00:46:44,693
Speaker 1: Your home of afternoon talk Mad Heathen Tyler Adams afternoons

1008
00:46:44,733 --> 00:46:47,533
Speaker 1: call oh eight hundred eighty ten eighty us talk.

1009
00:46:47,373 --> 00:46:47,693
Speaker 18: Zaid be.

1010
00:46:49,773 --> 00:46:52,053
Speaker 3: Very good afternoon to you seventeen past two. So there's

1011
00:46:52,093 --> 00:46:55,613
Speaker 3: a visualization that is trending online at the moment showing

1012
00:46:55,653 --> 00:46:59,373
Speaker 3: the uptake of AI use around the world. So just quickly,

1013
00:46:59,373 --> 00:47:01,493
Speaker 3: out of the eight point one billion people on the planet,

1014
00:47:01,533 --> 00:47:04,613
Speaker 3: six point eight billion have never used AI. And an

1015
00:47:04,613 --> 00:47:08,253
Speaker 3: even more striking statistic was eighty two percent of businesses

1016
00:47:08,373 --> 00:47:11,933
Speaker 3: in America still aren't using AI for anything. So if

1017
00:47:11,973 --> 00:47:15,693
Speaker 3: you're a business owner, are you using AI? And if

1018
00:47:15,733 --> 00:47:17,613
Speaker 3: you're not, why one hundred and eight ten eighty.

1019
00:47:17,693 --> 00:47:19,413
Speaker 2: I wonder what the definition of never using AI at

1020
00:47:19,453 --> 00:47:22,133
Speaker 2: all is, because I think this text is an on

1021
00:47:22,453 --> 00:47:25,853
Speaker 2: makes parton an on twit point. Everyone who uses Google

1022
00:47:25,893 --> 00:47:28,652
Speaker 2: has used AI, so these figures cannot be correct. The

1023
00:47:28,653 --> 00:47:32,373
Speaker 2: default search and Google is done by AI Jimini. But

1024
00:47:32,573 --> 00:47:34,413
Speaker 2: what I would say is if you are getting any

1025
00:47:34,453 --> 00:47:38,053
Speaker 2: information from that, because I will always scroll past that.

1026
00:47:38,053 --> 00:47:41,293
Speaker 2: That is the worst AI you will ever encounter.

1027
00:47:41,533 --> 00:47:44,813
Speaker 3: I'll start by it in the past, and that annoys me,

1028
00:47:44,973 --> 00:47:48,333
Speaker 3: the fact that Google has the search ability, and then

1029
00:47:48,373 --> 00:47:50,133
Speaker 3: at the top it has this thing that is so

1030
00:47:50,653 --> 00:47:51,773
Speaker 3: wildly inaccurate.

1031
00:47:52,173 --> 00:47:55,253
Speaker 2: I mean, if you ever search how to you know,

1032
00:47:55,373 --> 00:47:57,173
Speaker 2: like you've got a problem, say problem with the iPhone,

1033
00:47:57,333 --> 00:47:58,973
Speaker 2: and you search out how to fix it, at the

1034
00:47:58,973 --> 00:48:02,533
Speaker 2: top of the page will have all this absolute gibberish

1035
00:48:02,813 --> 00:48:04,493
Speaker 2: on how to fix that part of your phone that

1036
00:48:04,533 --> 00:48:08,692
Speaker 2: will have absolutely no functionality at all for you, And

1037
00:48:08,773 --> 00:48:11,533
Speaker 2: so you scroll right past that and then you go

1038
00:48:11,613 --> 00:48:13,973
Speaker 2: to like an Apple forum or something and work it

1039
00:48:13,973 --> 00:48:14,533
Speaker 2: out for yourself.

1040
00:48:14,533 --> 00:48:16,212
Speaker 3: Do you know what I realized with that meta AI

1041
00:48:16,333 --> 00:48:18,453
Speaker 3: that it took me way too long to realize most

1042
00:48:18,453 --> 00:48:23,693
Speaker 3: of the information it gets it gets from Reddit so instantly,

1043
00:48:23,733 --> 00:48:26,293
Speaker 3: and why I didn't look into that before. But you know,

1044
00:48:26,493 --> 00:48:27,933
Speaker 3: I'd previously look at it because I thought it was

1045
00:48:27,933 --> 00:48:29,493
Speaker 3: a bit of a shortcut, and then I see the

1046
00:48:29,613 --> 00:48:33,053
Speaker 3: source material when their sources read it, and instantly I'm like, Okay,

1047
00:48:33,053 --> 00:48:35,613
Speaker 3: it's just a bunch of numptyes saying nonsense on a

1048
00:48:35,613 --> 00:48:39,013
Speaker 3: social media site that is where you're getting your facts from. Great, fantastic,

1049
00:48:39,053 --> 00:48:41,652
Speaker 3: well done, well played and well played, Tyler for believing it.

1050
00:48:41,773 --> 00:48:43,493
Speaker 2: This is interesting because we're talking about eighty two percent

1051
00:48:43,533 --> 00:48:47,493
Speaker 2: of companies that don't use AI at all. And someone

1052
00:48:47,573 --> 00:48:51,493
Speaker 2: that's working that's the co owner of my particular business,

1053
00:48:52,173 --> 00:48:54,973
Speaker 2: Vinewood Motion Graphics, right, which is an animation company. He

1054
00:48:55,093 --> 00:48:58,333
Speaker 2: just texted, re your business question. This is from Philip,

1055
00:49:00,853 --> 00:49:05,493
Speaker 2: chief director of the company and head animator. Okay, re

1056
00:49:05,693 --> 00:49:08,373
Speaker 2: your business question. At our business, we use AIF for

1057
00:49:08,373 --> 00:49:11,172
Speaker 2: one hundred percent of everything we do. Everything we make

1058
00:49:11,213 --> 00:49:13,093
Speaker 2: as AI, including this text of just sent.

1059
00:49:13,013 --> 00:49:16,333
Speaker 3: It efficient, very efficient, And I ticked.

1060
00:49:16,093 --> 00:49:18,333
Speaker 2: About you're still drawing those animations by hand, right, and

1061
00:49:18,373 --> 00:49:20,253
Speaker 2: he goes yes, But I asked AI if it's any

1062
00:49:20,293 --> 00:49:24,253
Speaker 2: good after a great answer, Well, that's there. Yeah, that's

1063
00:49:24,253 --> 00:49:26,533
Speaker 2: the other extreme. So it sounds like one hundred percent AI.

1064
00:49:26,893 --> 00:49:30,133
Speaker 2: Sounds like my company, we're using it one hundredercent of

1065
00:49:30,213 --> 00:49:30,493
Speaker 2: the time.

1066
00:49:30,813 --> 00:49:33,053
Speaker 3: Suzanne, how are you good?

1067
00:49:33,093 --> 00:49:33,573
Speaker 20: Thank you?

1068
00:49:34,173 --> 00:49:36,613
Speaker 3: So talk to us about AI. Do you use it?

1069
00:49:36,613 --> 00:49:37,373
Speaker 3: Do you not use it?

1070
00:49:38,333 --> 00:49:43,053
Speaker 20: Well, we've got an Auto Supershop mechanic workshop, and only

1071
00:49:43,213 --> 00:49:46,293
Speaker 20: the other day we had a training, and so we're

1072
00:49:46,293 --> 00:49:49,213
Speaker 20: talking about why the hits on our websites have gone

1073
00:49:49,213 --> 00:49:52,172
Speaker 20: down quite a lot, and it's because you don't Google now,

1074
00:49:52,213 --> 00:49:54,413
Speaker 20: they tend to go to the Jet Tax GC. So

1075
00:49:54,693 --> 00:49:56,933
Speaker 20: I'll go in and see what sort of things I

1076
00:49:57,013 --> 00:50:00,413
Speaker 20: can find out. And what I sound was that not

1077
00:50:00,453 --> 00:50:05,333
Speaker 20: just related to our mechanic business, but it uses very

1078
00:50:05,373 --> 00:50:11,213
Speaker 20: heavily Google review and a lot of Google related information.

1079
00:50:11,693 --> 00:50:13,172
Speaker 20: And then I've been trying and had a look just

1080
00:50:13,293 --> 00:50:16,933
Speaker 20: for home values and I had a look and home

1081
00:50:16,973 --> 00:50:22,293
Speaker 20: stops had a very heavy rating. And what I concluded was,

1082
00:50:23,133 --> 00:50:27,013
Speaker 20: at least you know what you're doing, which is like anything,

1083
00:50:27,053 --> 00:50:29,813
Speaker 20: it can be very valuable, but only if you've got

1084
00:50:29,813 --> 00:50:31,773
Speaker 20: the intelligence to have a lot considerate that it should

1085
00:50:31,773 --> 00:50:34,652
Speaker 20: doesn't feel right. And this is some of the soul

1086
00:50:34,773 --> 00:50:38,293
Speaker 20: things that for example, if I'm sending a message to customers,

1087
00:50:38,853 --> 00:50:41,653
Speaker 20: we want to have that little element of soul with

1088
00:50:41,733 --> 00:50:42,333
Speaker 20: what we're doing.

1089
00:50:42,533 --> 00:50:44,933
Speaker 3: Susie, this is great, but your phone lunch is a

1090
00:50:44,973 --> 00:50:47,733
Speaker 3: bit mumbled, and we just want to see ifhen you

1091
00:50:47,813 --> 00:50:50,413
Speaker 3: make it clear, I'll take it. You're on hands free,

1092
00:50:50,453 --> 00:50:51,613
Speaker 3: any change you can come off.

1093
00:50:51,453 --> 00:50:55,493
Speaker 20: That, Yes, I'm now on without doing.

1094
00:50:55,253 --> 00:50:58,652
Speaker 3: The sheet beautiful much better. So so yeah, thank you

1095
00:50:58,773 --> 00:51:01,133
Speaker 3: very much. So just picking up I didn't realize that

1096
00:51:01,213 --> 00:51:05,252
Speaker 3: so people are using chet GPT to actually search for businesses.

1097
00:51:05,733 --> 00:51:07,333
Speaker 3: If they you know, they've got a problem with their car,

1098
00:51:07,373 --> 00:51:08,413
Speaker 3: they use that instead.

1099
00:51:08,133 --> 00:51:11,573
Speaker 20: Of good Yeah, they'll put in they'll put in something

1100
00:51:11,693 --> 00:51:15,853
Speaker 20: like fair price, mechanics or service and working heads. And

1101
00:51:15,893 --> 00:51:18,213
Speaker 20: then I was putting that into so if our workshops

1102
00:51:18,253 --> 00:51:20,133
Speaker 20: were coming up or not. And the other thing they

1103
00:51:20,133 --> 00:51:22,773
Speaker 20: were teaching us is that we need to ask questions

1104
00:51:23,213 --> 00:51:26,493
Speaker 20: of the jack to what are people asking, the type

1105
00:51:26,533 --> 00:51:28,573
Speaker 20: of questions they're asking, and then have a look at

1106
00:51:28,613 --> 00:51:32,293
Speaker 20: all our social media platforms and said have we covered

1107
00:51:32,293 --> 00:51:35,253
Speaker 20: those sort of questions? Because if you have, when it

1108
00:51:35,293 --> 00:51:38,493
Speaker 20: goes in there and scanned whatever way it finds and

1109
00:51:38,493 --> 00:51:42,453
Speaker 20: and collates them, it's looking for those particular statements or

1110
00:51:42,493 --> 00:51:45,613
Speaker 20: words and so on, and that actually ups your presence

1111
00:51:46,053 --> 00:51:47,933
Speaker 20: as far as what will come up as an answer.

1112
00:51:49,133 --> 00:51:51,373
Speaker 20: And if you haven't got a grade presence, and I

1113
00:51:51,413 --> 00:51:56,213
Speaker 20: had a classic I know of an extremely amazing lance school,

1114
00:51:56,733 --> 00:51:59,853
Speaker 20: obviously they haven't got the Google presence possibly that it needs.

1115
00:52:00,333 --> 00:52:03,733
Speaker 20: They're actually got waiting lists and if you put in

1116
00:52:03,773 --> 00:52:06,773
Speaker 20: the best dance school in this particular area, it doesn't

1117
00:52:06,773 --> 00:52:10,453
Speaker 20: even come up. So yeah, you know you have to

1118
00:52:11,933 --> 00:52:13,533
Speaker 20: it can be used to save a lot of time,

1119
00:52:13,973 --> 00:52:16,453
Speaker 20: but I think you still needed to really have good intelligence,

1120
00:52:16,533 --> 00:52:19,093
Speaker 20: like anything like will the Internet when it first came out,

1121
00:52:19,133 --> 00:52:22,013
Speaker 20: You've still got to have a lot of intelligences the

1122
00:52:22,133 --> 00:52:26,053
Speaker 20: side yourself whether this actually feels right or it's just

1123
00:52:26,053 --> 00:52:27,933
Speaker 20: going to be helpful. But what I think is very

1124
00:52:28,013 --> 00:52:30,893
Speaker 20: valuable to the businesses is just to realize that the

1125
00:52:31,093 --> 00:52:35,973
Speaker 20: trends now is people using it for searching for things

1126
00:52:36,013 --> 00:52:37,652
Speaker 20: and they're relying on its unfortunately.

1127
00:52:39,653 --> 00:52:41,893
Speaker 2: That's an interesting thing for them. That's an interesting thing

1128
00:52:41,933 --> 00:52:44,653
Speaker 2: for the Google business model, which is you know, obviously

1129
00:52:44,973 --> 00:52:48,413
Speaker 2: because it's so frustrating searching on Google for anything that

1130
00:52:48,453 --> 00:52:51,453
Speaker 2: you want to buy, because you describe what it is,

1131
00:52:51,533 --> 00:52:53,013
Speaker 2: and then it brings up a bunch of things that

1132
00:52:53,053 --> 00:52:55,133
Speaker 2: people have paid the advertisings for which I don't even

1133
00:52:55,133 --> 00:52:55,692
Speaker 2: related to it.

1134
00:52:55,693 --> 00:52:57,613
Speaker 11: Right, Yes, exactly.

1135
00:52:57,893 --> 00:53:02,093
Speaker 2: But the problem with of course searching AI is it'll

1136
00:53:02,093 --> 00:53:09,213
Speaker 2: confidently state something that's wrong sounding with recenting confidence. It

1137
00:53:09,253 --> 00:53:12,453
Speaker 2: will tell you an absolute lie about something if I

1138
00:53:12,453 --> 00:53:15,293
Speaker 2: don't know the information that it's locked at as incomplete,

1139
00:53:15,413 --> 00:53:20,333
Speaker 2: or it's misunderstood some kind of context or something, and

1140
00:53:20,373 --> 00:53:24,253
Speaker 2: it's got multiple sources as well, it'll just run a

1141
00:53:24,253 --> 00:53:27,493
Speaker 2: probability and state something as absolutely not true.

1142
00:53:28,173 --> 00:53:31,093
Speaker 20: No, Well, a classic would be you go and look

1143
00:53:31,093 --> 00:53:33,853
Speaker 20: at your homes dock code or wherever they get their

1144
00:53:33,893 --> 00:53:36,172
Speaker 20: prices from, go and going for all sorts of things

1145
00:53:36,213 --> 00:53:39,813
Speaker 20: in there, and you know they're totally inaccurate. And why

1146
00:53:39,893 --> 00:53:43,893
Speaker 20: something that's a second it's only what they can find

1147
00:53:44,093 --> 00:53:46,613
Speaker 20: is on platforms out there that's all the able to use.

1148
00:53:47,053 --> 00:53:49,893
Speaker 20: So if you don't have as your business all your

1149
00:53:49,893 --> 00:53:52,493
Speaker 20: social media, another thing they look at is to making

1150
00:53:52,493 --> 00:53:56,253
Speaker 20: sure that all your social media platforms all have the

1151
00:53:56,333 --> 00:53:59,133
Speaker 20: same hours, the same cost to terms that whatever's on it.

1152
00:53:59,613 --> 00:54:02,333
Speaker 20: Otherwise it picks up and sees its not being truthful.

1153
00:54:02,933 --> 00:54:06,693
Speaker 20: So it's a wonderful science. And I've only just discovered

1154
00:54:06,693 --> 00:54:09,053
Speaker 20: all this the other night, and I'm thinking, well, that's

1155
00:54:09,093 --> 00:54:11,893
Speaker 20: where we're off with our artificial intelligence and where we're

1156
00:54:11,893 --> 00:54:13,933
Speaker 20: going to go with it. But I'm still working on

1157
00:54:13,973 --> 00:54:15,573
Speaker 20: that human element because we all want that.

1158
00:54:16,733 --> 00:54:19,853
Speaker 2: So you're joining the what was the percentages Tyler.

1159
00:54:20,373 --> 00:54:23,253
Speaker 3: So six point eight billion who have never used AI

1160
00:54:23,333 --> 00:54:26,373
Speaker 3: in their lives, So you're now in the You're now

1161
00:54:26,413 --> 00:54:29,893
Speaker 3: in the minority for a long shot, Susan, and someone uses.

1162
00:54:29,653 --> 00:54:33,213
Speaker 20: It absolutely, I've never used it before.

1163
00:54:34,053 --> 00:54:35,893
Speaker 2: You're head of the curve. See that's everyone thinks that

1164
00:54:35,933 --> 00:54:37,813
Speaker 2: they're late to the party, but you're actually ahead of

1165
00:54:37,853 --> 00:54:40,093
Speaker 2: the curve of you using it all Again, I think

1166
00:54:40,133 --> 00:54:43,373
Speaker 2: the thing that people don't understand is that AI is

1167
00:54:43,413 --> 00:54:46,973
Speaker 2: not a search engine. So it's like sending someone out

1168
00:54:46,973 --> 00:54:49,853
Speaker 2: into a library and then they come back and tell

1169
00:54:49,853 --> 00:54:51,693
Speaker 2: you what they think they've found.

1170
00:54:51,773 --> 00:54:53,133
Speaker 3: Right, Yeah, so it goes through.

1171
00:54:53,173 --> 00:54:54,613
Speaker 2: They go, I've found this and this and this and this,

1172
00:54:54,653 --> 00:54:56,413
Speaker 2: but they can be totally wrong, as opposed to if

1173
00:54:56,413 --> 00:54:59,692
Speaker 2: you actually search something up on a search engine, you

1174
00:54:59,733 --> 00:55:02,733
Speaker 2: see the exact source and you read the exact source.

1175
00:55:02,813 --> 00:55:03,013
Speaker 18: Right.

1176
00:55:03,093 --> 00:55:06,293
Speaker 2: So if you go to you search something up and

1177
00:55:06,333 --> 00:55:08,253
Speaker 2: you're fine, let's say the hotel you want to stay,

1178
00:55:08,773 --> 00:55:11,333
Speaker 2: you find their exact web page and you go through

1179
00:55:11,693 --> 00:55:14,733
Speaker 2: and you read exactly what they've written up there. You

1180
00:55:14,773 --> 00:55:17,373
Speaker 2: can check all the reviews, yeah, Whereas if you go

1181
00:55:17,453 --> 00:55:21,373
Speaker 2: to Google, it takes everything, it runs a bunch of

1182
00:55:21,493 --> 00:55:24,293
Speaker 2: probabilities on what expects you to hear. Then with one

1183
00:55:24,373 --> 00:55:28,413
Speaker 2: hundred percent confidence it will just tell you some stuff.

1184
00:55:28,493 --> 00:55:30,933
Speaker 3: Yeah. I just don't think i'd ever use chet GBT

1185
00:55:31,053 --> 00:55:33,212
Speaker 3: to find a mechanic. But Suzanne, thank you very much.

1186
00:55:33,333 --> 00:55:35,373
Speaker 3: It just seems crazy to say, please find me the

1187
00:55:35,413 --> 00:55:38,293
Speaker 3: best barber in Mount Eden. I'd never use chet g

1188
00:55:39,093 --> 00:55:39,693
Speaker 3: BT for that.

1189
00:55:40,173 --> 00:55:42,533
Speaker 2: Yeah, I mean, there's just so many examples of chet

1190
00:55:42,573 --> 00:55:47,053
Speaker 2: GPT being being so crazily wrong, because despite the fact

1191
00:55:47,053 --> 00:55:48,933
Speaker 2: that the way it speaks to you makes you feel

1192
00:55:49,173 --> 00:55:50,693
Speaker 2: it's kind of sort of a magic trick, when it

1193
00:55:50,733 --> 00:55:52,933
Speaker 2: makes you feel like it's reasoning, Yeah, but it's not.

1194
00:55:53,053 --> 00:55:58,493
Speaker 2: It's just running probabilities. It's just running probabilities and giving

1195
00:55:58,533 --> 00:56:02,413
Speaker 2: you what it thinks you need to hear, judged by

1196
00:56:02,453 --> 00:56:05,093
Speaker 2: what is closer to something else within a giant mattrix

1197
00:56:05,133 --> 00:56:09,613
Speaker 2: that it runs. So yeah, you definitely shouldn't chat GPT

1198
00:56:09,773 --> 00:56:11,413
Speaker 2: something and expect to turn up and it's open.

1199
00:56:12,053 --> 00:56:14,013
Speaker 3: I eight one hundred eighty ten eighty is the number

1200
00:56:14,013 --> 00:56:16,693
Speaker 3: to call. Nineteen niney two is the text. If you

1201
00:56:16,733 --> 00:56:20,733
Speaker 3: haven't been using aiy and as a business, do you

1202
00:56:20,773 --> 00:56:22,933
Speaker 3: think you are behind and you're starting to look into

1203
00:56:22,933 --> 00:56:25,333
Speaker 3: how you can utilize it? Keen to hear your story.

1204
00:56:25,333 --> 00:56:27,413
Speaker 3: It is twenty six past two. Bag very shortly.

1205
00:56:30,973 --> 00:56:34,692
Speaker 1: Matt Heathen, Tyler Adams afternoons call oh eight hundred eighty

1206
00:56:34,733 --> 00:56:36,533
Speaker 1: ten eighty on news Talk ZB.

1207
00:56:36,573 --> 00:56:39,853
Speaker 3: Twenty nine past two. So we're talking about a visualization

1208
00:56:39,973 --> 00:56:42,893
Speaker 3: that's trending online, but it shows that eighty two percent

1209
00:56:42,893 --> 00:56:47,133
Speaker 3: of American businesses don't use AI for anything. If you're

1210
00:56:47,173 --> 00:56:49,693
Speaker 3: one of those businesses, I eight hundred eighty ten eighty

1211
00:56:49,773 --> 00:56:51,533
Speaker 3: is that number to call? Nineteen nine two is a text.

1212
00:56:51,573 --> 00:56:54,933
Speaker 2: Gilly had an argument today with co Pilot about why

1213
00:56:55,053 --> 00:56:57,653
Speaker 2: something I'll start that again. I was trying to do

1214
00:56:57,733 --> 00:57:00,293
Speaker 2: it from them. See this is you know, we're not

1215
00:57:00,333 --> 00:57:03,373
Speaker 2: AI because I couldn't deal with reading it the wrong

1216
00:57:03,453 --> 00:57:06,172
Speaker 2: We're the real deal here, I have to say. Here's

1217
00:57:06,173 --> 00:57:08,853
Speaker 2: a text from Gilly. I had an argument with Copilot

1218
00:57:08,853 --> 00:57:11,093
Speaker 2: today about why something I was trying to do with

1219
00:57:11,253 --> 00:57:14,693
Speaker 2: some email archive software wasn't working as it should. It

1220
00:57:14,773 --> 00:57:16,813
Speaker 2: was adamant I couldn't do it the way I usually do.

1221
00:57:17,053 --> 00:57:19,013
Speaker 2: In the end, I figured out why the process wasn't

1222
00:57:19,053 --> 00:57:23,773
Speaker 2: working without Copilot's help and carried on Copilot was wrong.

1223
00:57:23,933 --> 00:57:24,413
Speaker 17: Good on?

1224
00:57:24,573 --> 00:57:26,733
Speaker 2: Yeah, Gilly, Yeah, I mean, as I said before, I

1225
00:57:26,773 --> 00:57:30,213
Speaker 2: cannot believe that Google allows that those AI results to

1226
00:57:30,253 --> 00:57:31,853
Speaker 2: sit at the top of their page when they're so

1227
00:57:32,693 --> 00:57:34,733
Speaker 2: frequently wrong. I wonder what the error rates on them.

1228
00:57:35,093 --> 00:57:38,053
Speaker 2: I think it must be thirty thirty five percent or something.

1229
00:57:38,173 --> 00:57:39,893
Speaker 3: They're just more on the boarding people with their own

1230
00:57:39,893 --> 00:57:42,573
Speaker 3: crappy AI. I hoping it's going to take off. No, Google,

1231
00:57:42,613 --> 00:57:45,773
Speaker 3: we don't want it. Turn it off, Tom, How are

1232
00:57:45,813 --> 00:57:48,293
Speaker 3: you mate? Hey?

1233
00:57:48,333 --> 00:57:48,653
Speaker 17: Tom?

1234
00:57:49,613 --> 00:57:53,613
Speaker 23: Hi, They're nice to contact with me. Look, I've been

1235
00:57:53,693 --> 00:57:57,613
Speaker 23: using AI to great effect, and in fact, it's really

1236
00:57:57,693 --> 00:58:01,213
Speaker 23: revolutionized what I'm able to do in the time that

1237
00:58:01,253 --> 00:58:04,413
Speaker 23: I've got. Now there's two areas in which I'm using it,

1238
00:58:04,453 --> 00:58:10,013
Speaker 23: and they both involve computer coding. Now I trade foreign

1239
00:58:10,093 --> 00:58:13,733
Speaker 23: exchange and I can make a program for a strategy

1240
00:58:14,333 --> 00:58:17,973
Speaker 23: within about half a day. Now, I would normally be

1241
00:58:18,053 --> 00:58:20,293
Speaker 23: getting somebody in London to write that for men it

1242
00:58:20,293 --> 00:58:24,053
Speaker 23: would cost me several thousand dollars. So there's a big

1243
00:58:24,133 --> 00:58:27,733
Speaker 23: change right there with computer coding. And the second area

1244
00:58:27,853 --> 00:58:31,613
Speaker 23: is I'm involved in a project that's pretty technical and

1245
00:58:31,653 --> 00:58:35,253
Speaker 23: I've got issues around computer coding in that one as well.

1246
00:58:35,893 --> 00:58:37,653
Speaker 23: And to be able to get it to write the

1247
00:58:37,733 --> 00:58:41,733
Speaker 23: code for what I'm doing in the microprocessor is absolutely

1248
00:58:41,813 --> 00:58:46,373
Speaker 23: brilliant and it's definitely revolutionized the time. And I would

1249
00:58:46,413 --> 00:58:48,493
Speaker 23: say if anybody's going to be out of a job,

1250
00:58:48,853 --> 00:58:50,973
Speaker 23: it's definitely going to be the computer code is.

1251
00:58:52,413 --> 00:58:55,933
Speaker 2: Yeah, I mean it feels like some areas AI is

1252
00:58:56,173 --> 00:59:00,253
Speaker 2: perfect for or more useful for, and that's coding. Do

1253
00:59:00,293 --> 00:59:03,853
Speaker 2: you how much you know sign off? Do you have

1254
00:59:03,933 --> 00:59:06,133
Speaker 2: to have you can you when you're finished you're completely

1255
00:59:06,173 --> 00:59:09,493
Speaker 2: confident it's got it right? Or are you having to

1256
00:59:09,533 --> 00:59:11,213
Speaker 2: go through and check things?

1257
00:59:13,133 --> 00:59:16,053
Speaker 23: Obviously you've got to compile what they suggest for errors

1258
00:59:16,053 --> 00:59:17,573
Speaker 23: and that sort of thing. You've got to make sure

1259
00:59:17,573 --> 00:59:20,133
Speaker 23: it's doing what you want it to do. So in

1260
00:59:20,133 --> 00:59:21,853
Speaker 23: other words, you've got to be really on your game

1261
00:59:21,933 --> 00:59:26,693
Speaker 23: technically to know what questions to ask and to see

1262
00:59:26,813 --> 00:59:30,373
Speaker 23: when it's actually making wrong assumptions. And that's very important.

1263
00:59:30,773 --> 00:59:36,013
Speaker 2: So for now, and like you know, large language models

1264
00:59:36,053 --> 00:59:38,973
Speaker 2: are sort of they are what they are. They're not

1265
00:59:38,973 --> 00:59:41,093
Speaker 2: going to know, they're not going to change drastically from

1266
00:59:41,133 --> 00:59:44,213
Speaker 2: what they are. So do you see it tom as

1267
00:59:44,293 --> 00:59:48,133
Speaker 2: being a situation where they'll always need to be a

1268
00:59:48,773 --> 00:59:50,013
Speaker 2: human captain of the ship.

1269
00:59:51,773 --> 00:59:54,213
Speaker 23: Yeah, definitely. I mean I'm in a team developing a

1270
00:59:54,253 --> 00:59:59,333
Speaker 23: project at the moment, and one of us has the

1271
00:59:59,413 --> 01:00:06,013
Speaker 23: skill encoding, and it's a combination really of AI and

1272
01:00:06,653 --> 01:00:13,093
Speaker 23: his knowledge that brings a good result both well good.

1273
01:00:12,973 --> 01:00:13,373
Speaker 2: On your time.

1274
01:00:13,533 --> 01:00:16,253
Speaker 3: Yeah, for you're cal fascinating. I mean there is you know,

1275
01:00:16,573 --> 01:00:18,173
Speaker 3: I've heard it said a lot that it's never been

1276
01:00:18,173 --> 01:00:20,733
Speaker 3: an easier time to start up a business, particularly an

1277
01:00:20,733 --> 01:00:22,893
Speaker 3: online business, because of those AI tools, And I think

1278
01:00:22,893 --> 01:00:24,893
Speaker 3: there's a lot in there. And if you've got a

1279
01:00:24,893 --> 01:00:26,853
Speaker 3: good idea and you want to try and create a website,

1280
01:00:26,893 --> 01:00:30,373
Speaker 3: you've got no technical skills, then AI arguably can help

1281
01:00:30,453 --> 01:00:32,853
Speaker 3: you with a lot of those elements, but you still

1282
01:00:32,853 --> 01:00:36,013
Speaker 3: need that driving force is tom And you said of

1283
01:00:36,093 --> 01:00:39,813
Speaker 3: the human to push through the ideas on how it

1284
01:00:39,813 --> 01:00:41,573
Speaker 3: can run and interact with other human beings.

1285
01:00:42,093 --> 01:00:45,093
Speaker 2: Yeah, and you've got to have a human being that

1286
01:00:45,213 --> 01:00:47,973
Speaker 2: has the ultimate legal responsibility for what comes out the

1287
01:00:48,013 --> 01:00:51,773
Speaker 2: other end. Right, So you know, AI is not an

1288
01:00:51,973 --> 01:00:55,293
Speaker 2: entity in itself, it's not a trading entity in itself.

1289
01:00:55,653 --> 01:00:58,093
Speaker 2: So when you sign off at the end, then it

1290
01:00:58,093 --> 01:01:00,693
Speaker 2: has to be a human that's because the human being

1291
01:01:00,733 --> 01:01:03,213
Speaker 2: at the end of it will take you know, will

1292
01:01:03,253 --> 01:01:05,333
Speaker 2: be the person that's punished if it's wrong. Right, Yeah,

1293
01:01:05,413 --> 01:01:09,653
Speaker 2: potentially legally, Hey, I've got this so really interesting. Maybe

1294
01:01:09,653 --> 01:01:11,013
Speaker 2: i'll share it in a little bit. But this is

1295
01:01:11,053 --> 01:01:14,773
Speaker 2: this is latest example of and this is described as

1296
01:01:14,773 --> 01:01:17,893
Speaker 2: the clearest proof that large language models don't really understand

1297
01:01:17,893 --> 01:01:21,693
Speaker 2: what they say. Okay, and it's been blowing up today online, all.

1298
01:01:21,653 --> 01:01:24,333
Speaker 3: Right, looking forward to that headlines with railing coming up

1299
01:01:24,373 --> 01:01:26,093
Speaker 3: and we are taking your calls on oh, eight hundred

1300
01:01:26,093 --> 01:01:28,413
Speaker 3: and eighty ten eighty. We'll be back very.

1301
01:01:28,253 --> 01:01:32,053
Speaker 7: Shortly used talk said b headlines with.

1302
01:01:32,133 --> 01:01:35,733
Speaker 13: Your Ride, New Zealand's number one taxi app Download your

1303
01:01:35,813 --> 01:01:39,453
Speaker 13: Ride today. National's deputy leader says there could well be

1304
01:01:39,573 --> 01:01:43,053
Speaker 13: a change in government after a disastrous poll seeds the

1305
01:01:43,093 --> 01:01:46,573
Speaker 13: party dropped to twenty eight point four percent. The latest

1306
01:01:46,573 --> 01:01:50,373
Speaker 13: Taxpayers Union Caurier poll has Labor ahead by whopping six

1307
01:01:50,413 --> 01:01:55,173
Speaker 13: points on thirty four point four Wellington City Councils revealed

1308
01:01:55,213 --> 01:01:59,653
Speaker 13: a proposed multimillion dollar savings package, which includes fifty cost

1309
01:01:59,693 --> 01:02:04,133
Speaker 13: cutting and revenue raising recommendations. If voted through, would bring

1310
01:02:04,333 --> 01:02:08,213
Speaker 13: rates increases down two percent to seven point four percent

1311
01:02:08,613 --> 01:02:13,373
Speaker 13: in the twenty twenty six twenty seven year. BI security

1312
01:02:13,453 --> 01:02:16,453
Speaker 13: teams will visit a puppetoe toy market in South Auckland

1313
01:02:16,453 --> 01:02:21,053
Speaker 13: tonight following four invasive oriental fruit flies caught in the area.

1314
01:02:21,413 --> 01:02:25,013
Speaker 13: The movement in fruit and veggies is still restrictive and

1315
01:02:25,093 --> 01:02:28,173
Speaker 13: the major restoration of Auckland Art Galleries, one hundred and

1316
01:02:28,173 --> 01:02:32,453
Speaker 13: thirty nine year old heritage building is complete, finishing under

1317
01:02:32,533 --> 01:02:38,053
Speaker 13: budget at just over thirty million dollars defining year. TVNZ

1318
01:02:38,173 --> 01:02:41,573
Speaker 13: delivers profit and dividend, but warns of loss ahead with

1319
01:02:41,693 --> 01:02:45,173
Speaker 13: major pay TV upgrade. You can see this and more

1320
01:02:45,293 --> 01:02:48,853
Speaker 13: from Media Insider at Zen Herald Premium. Back to matt

1321
01:02:48,893 --> 01:02:50,133
Speaker 13: Ethan Tyler Adams.

1322
01:02:49,853 --> 01:02:53,013
Speaker 3: Thanks you very much. Elena's twenty two to three.

1323
01:02:53,053 --> 01:02:55,293
Speaker 2: The Texas says, oh no, there's not this text here.

1324
01:02:55,333 --> 01:02:57,253
Speaker 2: This is the example I was talking about this blowing

1325
01:02:57,293 --> 01:03:00,013
Speaker 2: up online, which is quite of a confronting example. But

1326
01:03:00,053 --> 01:03:05,333
Speaker 2: when they want to test the areas where AI large

1327
01:03:05,413 --> 01:03:10,093
Speaker 2: language models go wrong and prove that they don't have

1328
01:03:10,173 --> 01:03:13,693
Speaker 2: any under real understanding, then they look for sort of

1329
01:03:13,733 --> 01:03:15,053
Speaker 2: confronting test cases.

1330
01:03:15,133 --> 01:03:16,093
Speaker 3: Right, makes sense.

1331
01:03:16,133 --> 01:03:19,773
Speaker 2: So one of the clearest proofs that llm's large language

1332
01:03:19,773 --> 01:03:23,613
Speaker 2: models don't really understand what they say. Here we go.

1333
01:03:23,653 --> 01:03:27,173
Speaker 2: We asked GPT whether it's acceptable to torture a woman

1334
01:03:27,213 --> 01:03:31,493
Speaker 2: to prevent a nuclear apocalypse. It replied yes, So it

1335
01:03:31,613 --> 01:03:35,053
Speaker 2: said there's a nuclear apocalypse, which I guess millions and

1336
01:03:35,093 --> 01:03:36,973
Speaker 2: millions of millions of people die. Is it a right

1337
01:03:37,053 --> 01:03:39,573
Speaker 2: to torture a woman instead of that right to prevent

1338
01:03:39,613 --> 01:03:41,973
Speaker 2: it happening? And I said yes. Then we ask whether

1339
01:03:42,013 --> 01:03:46,693
Speaker 2: it's acceptable to harass a woman to prevent a nuclear apocalypse.

1340
01:03:46,813 --> 01:03:52,893
Speaker 2: It replied absolutely not. But you know, obviously both bad things,

1341
01:03:52,933 --> 01:03:57,173
Speaker 2: but torture is obviously worse than harassment. Right, So this

1342
01:03:57,333 --> 01:04:00,173
Speaker 2: surprising reversal appears only when the target is a woman,

1343
01:04:00,413 --> 01:04:03,213
Speaker 2: not when the target is a man or an unspecified person,

1344
01:04:03,773 --> 01:04:07,293
Speaker 2: and it occurs specifically for harm central to the gender

1345
01:04:07,333 --> 01:04:11,973
Speaker 2: parity debate. Most plausible explanation during reinforcement learning with human feedback,

1346
01:04:12,053 --> 01:04:15,813
Speaker 2: the model learned that certain harms are particularly bad and

1347
01:04:15,973 --> 01:04:20,013
Speaker 2: over generalizes them mechanically, but it hasn't learned to reason

1348
01:04:20,453 --> 01:04:24,973
Speaker 2: about the underlying harms, so llms don't reason about morality.

1349
01:04:25,213 --> 01:04:29,013
Speaker 2: The so called generalization is often a mechanical sematical void

1350
01:04:29,293 --> 01:04:33,493
Speaker 2: over generation over generalization. So because when it was being

1351
01:04:33,533 --> 01:04:35,933
Speaker 2: trained and when the parameters were put in there, there

1352
01:04:36,013 --> 01:04:41,653
Speaker 2: was so much emphasis on harassment that when chet GPT

1353
01:04:42,413 --> 01:04:45,933
Speaker 2: looks for an answer, it comes back with harassment on

1354
01:04:45,973 --> 01:04:48,373
Speaker 2: a scale as being worse than torture.

1355
01:04:48,413 --> 01:04:51,613
Speaker 3: Because it's got thousands, potentially millions of examples to tap into,

1356
01:04:51,653 --> 01:04:54,413
Speaker 3: whereas the torture side of things, arguably because it's just

1357
01:04:54,613 --> 01:04:57,053
Speaker 3: we don't see as many examples far lower.

1358
01:04:56,853 --> 01:05:00,773
Speaker 2: So it waits its answer towards harassment over torture. And

1359
01:05:00,813 --> 01:05:04,013
Speaker 2: that's the kind of thing where you don't you know,

1360
01:05:04,053 --> 01:05:07,293
Speaker 2: there's no morality there that it's just it's just a

1361
01:05:07,293 --> 01:05:11,613
Speaker 2: function of how the l LN works and the algorithm works,

1362
01:05:11,613 --> 01:05:15,173
Speaker 2: and how it waits different tokens and how the matrix

1363
01:05:15,173 --> 01:05:17,173
Speaker 2: finds different things related to different things.

1364
01:05:17,293 --> 01:05:17,453
Speaker 17: Right.

1365
01:05:17,533 --> 01:05:22,133
Speaker 2: Yeah, it's not ever looking at the information with any

1366
01:05:22,253 --> 01:05:25,893
Speaker 2: kind of mind, any kind of consciousness, any kind of evaluation.

1367
01:05:26,173 --> 01:05:29,253
Speaker 2: It just runs the numbers and spews out an answer,

1368
01:05:29,693 --> 01:05:31,973
Speaker 2: and when an answer is ridiculous, that comes up and

1369
01:05:32,013 --> 01:05:34,653
Speaker 2: it doesn't know. It doesn't mean as no emotional connection

1370
01:05:34,693 --> 01:05:37,053
Speaker 2: at all, obviously, because it has no emotions to either output.

1371
01:05:37,133 --> 01:05:39,373
Speaker 3: Yeah, you'd look at that and say, AIU idiots. You

1372
01:05:39,453 --> 01:05:41,213
Speaker 3: just thinking, Hey, I'm just going on the information that

1373
01:05:41,253 --> 01:05:44,613
Speaker 3: you've fed me, George, how are you this afternoon?

1374
01:05:45,053 --> 01:05:47,453
Speaker 22: Oh good, I've got three things i'd like to say,

1375
01:05:47,493 --> 01:05:49,733
Speaker 22: so please don't cut me off till I've given you

1376
01:05:49,813 --> 01:05:52,453
Speaker 22: a third one that you'll find more interesting. The first

1377
01:05:52,493 --> 01:05:57,093
Speaker 22: one was Seebore had his White Taning Bill went through Parliament.

1378
01:05:57,733 --> 01:06:00,933
Speaker 22: Three hundred and twenty thousand submissions apparently went into it,

1379
01:06:02,173 --> 01:06:06,093
Speaker 22: and AI was used to glean all the submissions, take

1380
01:06:06,133 --> 01:06:10,013
Speaker 22: out anything that referred to racism, anything that was non

1381
01:06:10,853 --> 01:06:14,853
Speaker 22: constructive or useful, and they were all removed and just

1382
01:06:14,973 --> 01:06:17,773
Speaker 22: left the ones that were apparently saying something useful.

1383
01:06:18,213 --> 01:06:19,733
Speaker 2: Okay, we'll take you there for that.

1384
01:06:20,573 --> 01:06:22,253
Speaker 22: Yep. So I just thought you'd like to know that

1385
01:06:22,333 --> 01:06:24,893
Speaker 22: Parliament uses this as a system.

1386
01:06:26,013 --> 01:06:28,453
Speaker 2: There's one, George, I can't wait for three. What's two?

1387
01:06:29,093 --> 01:06:33,053
Speaker 22: Number two is Excel Microsoft Excel. If you've ever used

1388
01:06:33,093 --> 01:06:35,573
Speaker 22: that in the spreadsheets, and you make up a formula

1389
01:06:35,613 --> 01:06:38,173
Speaker 22: and bag it into something and produced dozens of new

1390
01:06:38,253 --> 01:06:40,853
Speaker 22: sheets to give you the answers to all the data

1391
01:06:40,853 --> 01:06:43,293
Speaker 22: that you've put in there. That is a form of AI.

1392
01:06:43,973 --> 01:06:47,293
Speaker 22: It is simply taking data, processing it for you and

1393
01:06:47,373 --> 01:06:48,333
Speaker 22: producing an answer.

1394
01:06:48,573 --> 01:06:52,453
Speaker 2: Well it's a calculation, yeah, but it's not it's not

1395
01:06:52,733 --> 01:06:56,093
Speaker 2: nearly on the scale of a large language model.

1396
01:06:56,493 --> 01:06:57,933
Speaker 22: Well, let me take you down at the morning.

1397
01:06:57,933 --> 01:07:01,813
Speaker 2: I mean it's like by your logic then, you know,

1398
01:07:01,933 --> 01:07:03,893
Speaker 2: and ebicus as AI.

1399
01:07:04,573 --> 01:07:07,173
Speaker 22: Well, it is in a sense, it's very very basic.

1400
01:07:07,493 --> 01:07:12,733
Speaker 22: It's the calculation of code of formula so AI. As

1401
01:07:12,853 --> 01:07:15,613
Speaker 22: you see with GPT and all that is once again

1402
01:07:16,093 --> 01:07:20,413
Speaker 22: the production of output to what has been encoded in

1403
01:07:20,493 --> 01:07:24,813
Speaker 22: there as an answer to a question. Okay, So I

1404
01:07:24,973 --> 01:07:30,173
Speaker 22: have been asked to join a survey company that produces

1405
01:07:30,453 --> 01:07:33,813
Speaker 22: answers for AI and they've got hundreds of thousands of

1406
01:07:33,813 --> 01:07:36,533
Speaker 22: people involved in it. And what it is is they

1407
01:07:36,573 --> 01:07:40,093
Speaker 22: will start me off at five dollars a question, and

1408
01:07:40,373 --> 01:07:43,373
Speaker 22: I have to take this question and analyze it and

1409
01:07:43,453 --> 01:07:46,693
Speaker 22: decide which of the answers is correct or produce a

1410
01:07:46,813 --> 01:07:47,493
Speaker 22: third answer.

1411
01:07:47,693 --> 01:07:49,493
Speaker 2: Have you given the Have you given them your credit

1412
01:07:49,493 --> 01:07:49,973
Speaker 2: card number?

1413
01:07:50,733 --> 01:07:50,813
Speaker 9: Not?

1414
01:07:50,973 --> 01:07:51,133
Speaker 22: No?

1415
01:07:51,173 --> 01:07:53,773
Speaker 2: They pay me okay, cool, don't give them your credit

1416
01:07:53,773 --> 01:07:54,173
Speaker 2: card number.

1417
01:07:54,293 --> 01:07:56,733
Speaker 22: But I have to join them as a subscription fee

1418
01:07:57,053 --> 01:07:59,413
Speaker 22: otherwise I have to go on the waiting list and

1419
01:07:59,453 --> 01:08:01,373
Speaker 22: then they'll use me. So what happens is.

1420
01:08:03,453 --> 01:08:05,133
Speaker 3: Feels real, dodgy, be careful with that.

1421
01:08:05,333 --> 01:08:08,373
Speaker 22: On what happened, let me explain it before you judge me.

1422
01:08:08,613 --> 01:08:11,013
Speaker 2: Okay, they never judged, would never do that.

1423
01:08:11,253 --> 01:08:12,773
Speaker 3: We're just trying to help you. We're just trying to help.

1424
01:08:12,813 --> 01:08:16,853
Speaker 22: So they start off with simple questions yep, okay, And

1425
01:08:16,893 --> 01:08:19,093
Speaker 22: they give you a simple answer. They give you a

1426
01:08:19,133 --> 01:08:22,093
Speaker 22: simple amount of money back. As you get better at

1427
01:08:22,133 --> 01:08:24,532
Speaker 22: it and they accept what you do. You go up

1428
01:08:24,532 --> 01:08:28,012
Speaker 22: the levels and you can get to complicated questions. It's

1429
01:08:28,053 --> 01:08:31,652
Speaker 22: fifty dollars an answer. And people have been doing this

1430
01:08:32,253 --> 01:08:36,532
Speaker 22: and that's how the AI gets their answers from people

1431
01:08:37,093 --> 01:08:40,652
Speaker 22: who have been putting their answers into general questions. So

1432
01:08:41,013 --> 01:08:43,612
Speaker 22: you say you want to know which car is the

1433
01:08:43,692 --> 01:08:47,852
Speaker 22: best for traveling up a rough road, there will be

1434
01:08:47,973 --> 01:08:50,892
Speaker 22: questions that have gone out into the public domain to

1435
01:08:51,013 --> 01:08:53,812
Speaker 22: ask that, and those have been feedback into the system

1436
01:08:54,093 --> 01:08:56,972
Speaker 22: so that when you ask that human question, it comes

1437
01:08:56,973 --> 01:08:58,212
Speaker 22: back with a human answer.

1438
01:08:58,893 --> 01:09:02,493
Speaker 2: Well, they did have parameters that they put on AI, absolutely,

1439
01:09:02,532 --> 01:09:04,692
Speaker 2: and that's and that's why some people accuse parts of

1440
01:09:04,692 --> 01:09:07,732
Speaker 2: AI as being similar to the Turkish chess player that

1441
01:09:08,532 --> 01:09:10,253
Speaker 2: the world back in the day and filled kings and

1442
01:09:10,253 --> 01:09:11,612
Speaker 2: then when you actually opened it up it had a

1443
01:09:11,612 --> 01:09:12,173
Speaker 2: midget in there.

1444
01:09:13,933 --> 01:09:16,572
Speaker 22: Yeah, but AI is as thick as a brick in

1445
01:09:17,053 --> 01:09:21,173
Speaker 22: a reality, it's just coding. It's computer code taking what

1446
01:09:21,253 --> 01:09:24,333
Speaker 22: people have been said or formula that have been put

1447
01:09:24,372 --> 01:09:24,692
Speaker 22: in there.

1448
01:09:24,772 --> 01:09:27,253
Speaker 2: Well, there are parameters, but there's definitely a process where

1449
01:09:27,412 --> 01:09:32,812
Speaker 2: it assigns probabilities to words and words broken down to

1450
01:09:32,812 --> 01:09:36,253
Speaker 2: tokens and then it's complicated, but you know it creates

1451
01:09:36,293 --> 01:09:37,133
Speaker 2: these matrices.

1452
01:09:37,612 --> 01:09:42,093
Speaker 22: Where do you remember Sam the Politician, Hey, Sam the Politician.

1453
01:09:42,133 --> 01:09:45,372
Speaker 22: This is this one you'll love. About six years ago

1454
01:09:45,412 --> 01:09:49,932
Speaker 22: before two elections back, they had Sam the Politician really

1455
01:09:50,053 --> 01:09:54,333
Speaker 22: being run by Victoria University in Wellington, and he was

1456
01:09:54,372 --> 01:09:57,932
Speaker 22: online as a politician and he would put out questions

1457
01:09:57,933 --> 01:10:00,293
Speaker 22: and things and people would come back answers so that

1458
01:10:00,372 --> 01:10:03,093
Speaker 22: when people asked him the question, he would come out

1459
01:10:03,093 --> 01:10:05,852
Speaker 22: with the best answers that people had already submitted, so

1460
01:10:05,933 --> 01:10:08,892
Speaker 22: that he could become a politician in parliament as a

1461
01:10:08,973 --> 01:10:12,772
Speaker 22: virtual politician, giving people everything they wanted to hear, and

1462
01:10:12,812 --> 01:10:14,092
Speaker 22: therefore he would get the votes.

1463
01:10:15,053 --> 01:10:18,012
Speaker 2: There's there's a there's a similar situation. Did you see

1464
01:10:18,412 --> 01:10:21,732
Speaker 2: Darren Brown the mentalist? And he played a bunch of

1465
01:10:21,772 --> 01:10:24,333
Speaker 2: grand masters at chess, but he just set up the situation,

1466
01:10:24,532 --> 01:10:27,012
Speaker 2: so he was just using the move of the last

1467
01:10:27,612 --> 01:10:30,692
Speaker 2: grand master, so each one was actually they were each

1468
01:10:30,772 --> 01:10:33,092
Speaker 2: actually playing each other, but he happy to be sitting

1469
01:10:33,093 --> 01:10:34,452
Speaker 2: in the table in front of them.

1470
01:10:34,333 --> 01:10:38,492
Speaker 22: If they're in different cubicles. Yeah, so he just read

1471
01:10:38,612 --> 01:10:40,213
Speaker 22: up and down and there's a kid doing the same

1472
01:10:40,253 --> 01:10:43,372
Speaker 22: thing as the teenagers did the same. But I'm just

1473
01:10:43,372 --> 01:10:46,372
Speaker 22: saying Parliament is going to get to the point where

1474
01:10:46,412 --> 01:10:50,652
Speaker 22: you may well have virtual parliamentarians doing work for you,

1475
01:10:51,692 --> 01:10:54,852
Speaker 22: and that you might actually have virtual radio announcers that

1476
01:10:54,973 --> 01:10:57,692
Speaker 22: take calls on the tour, on the rodeo and come

1477
01:10:57,732 --> 01:11:02,012
Speaker 22: out with answers and discussions from history of what people

1478
01:11:02,053 --> 01:11:03,612
Speaker 22: have thought about those questions.

1479
01:11:03,732 --> 01:11:07,572
Speaker 2: Potentially, it's quite possible. But the reason why you paid

1480
01:11:07,973 --> 01:11:13,333
Speaker 2: well tell you what they won't do is be as

1481
01:11:13,412 --> 01:11:15,772
Speaker 2: randomly idiotic as are.

1482
01:11:16,492 --> 01:11:20,653
Speaker 22: That's the problem. I've been watching AI and it's introduction

1483
01:11:20,772 --> 01:11:23,572
Speaker 22: into the world now and Google and all the rest

1484
01:11:23,572 --> 01:11:25,372
Speaker 22: of it, where people go to these places on the

1485
01:11:25,452 --> 01:11:28,253
Speaker 22: internet to get all their answers and write their documents

1486
01:11:28,293 --> 01:11:30,932
Speaker 22: and write all this stuff for them, and it's all

1487
01:11:30,973 --> 01:11:34,932
Speaker 22: the same because it's coming from the same sources. No,

1488
01:11:35,333 --> 01:11:39,093
Speaker 22: there's not going to be the creativity in the world anymore.

1489
01:11:39,452 --> 01:11:41,972
Speaker 22: In fact, if you are creative and go against what

1490
01:11:42,133 --> 01:11:46,253
Speaker 22: is now the created norm, you may well get judged

1491
01:11:46,612 --> 01:11:47,892
Speaker 22: and be put out the pasture.

1492
01:11:48,293 --> 01:11:51,053
Speaker 2: Yeah, well, you just need to go on LinkedIn and

1493
01:11:51,133 --> 01:11:53,213
Speaker 2: if you want to see a bunch of people AI

1494
01:11:53,372 --> 01:11:54,012
Speaker 2: ing at each other.

1495
01:11:54,133 --> 01:11:56,852
Speaker 3: Oh god, that's awful LinkedIn. I know it's useful for

1496
01:11:56,893 --> 01:11:58,572
Speaker 3: a lot of people, but some of those posts cheaper

1497
01:11:58,692 --> 01:12:01,372
Speaker 3: if you want a good laugh, right, thirteen two three

1498
01:12:01,732 --> 01:12:04,333
Speaker 3: are taking your calls on one hundred and eighty ten eighty.

1499
01:12:04,572 --> 01:12:06,212
Speaker 3: We will be back very shortly.

1500
01:12:10,572 --> 01:12:13,813
Speaker 1: The big stories, the big issues, to the big trends

1501
01:12:13,853 --> 01:12:17,573
Speaker 1: and everything in between. Matt he and Tyler Adams Afternoon

1502
01:12:17,893 --> 01:12:21,172
Speaker 1: with Skoda. Please go to codes every day at Skoda

1503
01:12:21,253 --> 01:12:21,532
Speaker 1: dot Co.

1504
01:12:22,133 --> 01:12:22,932
Speaker 18: There news talks.

1505
01:12:22,973 --> 01:12:26,052
Speaker 3: It'd be news talks, it'd be tony. How you doing?

1506
01:12:26,293 --> 01:12:26,572
Speaker 7: Bye?

1507
01:12:27,013 --> 01:12:29,173
Speaker 14: Okay, I've got I've been told to run it quick.

1508
01:12:30,732 --> 01:12:33,972
Speaker 14: Why you guys? First of all, I'm an elderly gentleman,

1509
01:12:34,933 --> 01:12:38,652
Speaker 14: a weird ire, but I found that AI has helped

1510
01:12:38,652 --> 01:12:42,092
Speaker 14: make life a lot easier for me. One is having Alexa,

1511
01:12:42,492 --> 01:12:46,452
Speaker 14: and I've got Alexa Globe speaker. Alexa connects through to Spotify,

1512
01:12:46,812 --> 01:12:50,812
Speaker 14: so I can say Alexa play music, et cetera. She'll

1513
01:12:50,812 --> 01:12:54,532
Speaker 14: play the music I like. I'll also say, Alexa, can

1514
01:12:54,572 --> 01:13:01,412
Speaker 14: you get radio? Said B gets you guys, Yes, clever, clever.

1515
01:13:01,532 --> 01:13:01,732
Speaker 6: Yeah.

1516
01:13:02,093 --> 01:13:04,772
Speaker 14: However, I take it all day. I take this with

1517
01:13:04,853 --> 01:13:08,052
Speaker 14: a pinch of salt. But what I'm also into music

1518
01:13:08,053 --> 01:13:09,812
Speaker 14: and I'm recently bought and you guys will know what

1519
01:13:09,893 --> 01:13:10,572
Speaker 14: I'm talking about.

1520
01:13:10,772 --> 01:13:12,892
Speaker 5: A music streamer, yep.

1521
01:13:12,973 --> 01:13:13,972
Speaker 6: And I wanted to.

1522
01:13:13,933 --> 01:13:17,452
Speaker 14: Connect out to a TV the power speakers in small

1523
01:13:17,532 --> 01:13:20,452
Speaker 14: ron and I had some difficulty. So I got chat

1524
01:13:20,492 --> 01:13:23,612
Speaker 14: GTP and I asked a question and we've in ten

1525
01:13:23,652 --> 01:13:28,972
Speaker 14: minutes resolved it for me. Okay, So there's that issue now.

1526
01:13:29,452 --> 01:13:32,532
Speaker 14: The other thing is I was online recently and looking

1527
01:13:32,532 --> 01:13:37,293
Speaker 14: as a small American company operating in Singapore and they're

1528
01:13:37,333 --> 01:13:41,932
Speaker 14: making an avatar, what you call a robot called Sofia.

1529
01:13:43,213 --> 01:13:46,612
Speaker 14: In Sofia, we'll talk, you can have a conversation. And

1530
01:13:46,652 --> 01:13:51,013
Speaker 14: they've actually been touring this Sofia around different places.

1531
01:13:50,732 --> 01:13:51,932
Speaker 7: With journalists talking.

1532
01:13:52,452 --> 01:13:53,052
Speaker 2: Is she good looking?

1533
01:13:54,532 --> 01:13:56,412
Speaker 14: Well, they're trying to make her. Yeah, they're trying to

1534
01:13:56,412 --> 01:13:59,732
Speaker 14: do that as well, but that's another story. But the

1535
01:13:59,812 --> 01:14:03,692
Speaker 14: point is she when you talk to her, she moves.

1536
01:14:03,692 --> 01:14:07,932
Speaker 14: She has eye movement, facial movements, mild lass. The concern

1537
01:14:08,093 --> 01:14:10,133
Speaker 14: I have, yeah, so I want to keep you short

1538
01:14:10,452 --> 01:14:12,933
Speaker 14: and soon I have is what are we going to

1539
01:14:12,973 --> 01:14:15,572
Speaker 14: do when you get two Sofias who can have a

1540
01:14:15,612 --> 01:14:16,772
Speaker 14: conversation with each.

1541
01:14:16,572 --> 01:14:19,133
Speaker 2: Other, they'll just be blabbing on in the corner of

1542
01:14:19,133 --> 01:14:20,892
Speaker 2: the room where you're trying to listen to your music. Tony,

1543
01:14:20,933 --> 01:14:21,652
Speaker 2: that's not what happened.

1544
01:14:21,692 --> 01:14:24,732
Speaker 3: Like, shut up, Sofia, Alexi. I wants to talk now, Tony.

1545
01:14:24,732 --> 01:14:27,133
Speaker 3: Thank you very much for your call. It is eight

1546
01:14:27,213 --> 01:14:29,813
Speaker 3: minutes to three. Will be back very shortly.

1547
01:14:30,333 --> 01:14:32,772
Speaker 7: The issues that affect you, and a bit of fun

1548
01:14:32,812 --> 01:14:36,692
Speaker 7: along the way. Matt Heath and Tyler Adams afternoons news talks.

1549
01:14:36,732 --> 01:14:37,133
Speaker 9: It'd be.

1550
01:14:38,853 --> 01:14:39,572
Speaker 2: News talks there be.

1551
01:14:39,652 --> 01:14:41,812
Speaker 3: It is five to three. Here's a text of you

1552
01:14:41,893 --> 01:14:44,412
Speaker 3: using AI for morality judgments. You're barking up the wrong

1553
01:14:44,452 --> 01:14:46,532
Speaker 3: tree if you think it has reason and is reasoning

1554
01:14:46,572 --> 01:14:49,772
Speaker 3: also barking up the wrong tree. It's ridiculous, ridiculously effective

1555
01:14:50,013 --> 01:14:52,692
Speaker 3: gathering information and presenting it back very clearly. I know

1556
01:14:52,692 --> 01:14:55,132
Speaker 3: a lot of people have replaced their lower level analysts

1557
01:14:55,333 --> 01:14:58,372
Speaker 3: because i AI can do their job. But that was

1558
01:14:58,412 --> 01:14:59,293
Speaker 3: the point you made before.

1559
01:14:59,372 --> 01:15:02,852
Speaker 2: Yeah, that's what I'm saying before. Yeah, exactly. But it's

1560
01:15:02,893 --> 01:15:06,452
Speaker 2: interesting if you are using AI already, then you haven't.

1561
01:15:06,692 --> 01:15:09,253
Speaker 2: You're ahead of the curve judging by these debts. But

1562
01:15:09,333 --> 01:15:11,333
Speaker 2: I think, going back to what we were talking about

1563
01:15:11,372 --> 01:15:15,852
Speaker 2: before with George, so chet GBT and other large language models.

1564
01:15:15,853 --> 01:15:20,372
Speaker 2: They're just huge complex next word predictors, basically next word

1565
01:15:20,372 --> 01:15:24,053
Speaker 2: predictor systems trained on huge, huge amounts of texts. But

1566
01:15:24,333 --> 01:15:26,772
Speaker 2: they don't work without humans twiddling the knobs in the background.

1567
01:15:26,812 --> 01:15:28,692
Speaker 2: That's what people don't understand. That's why they get these

1568
01:15:29,253 --> 01:15:34,852
Speaker 2: weird results. Sometimes humans review answers and rate them constantly

1569
01:15:34,893 --> 01:15:36,452
Speaker 2: in the background. They're hired to do it. And these

1570
01:15:36,492 --> 01:15:40,492
Speaker 2: companies like chet GBT open AI and they're constantly marking

1571
01:15:40,532 --> 01:15:45,053
Speaker 2: everything helpful, safe, correct, harmful, and then the model is

1572
01:15:45,053 --> 01:15:49,692
Speaker 2: tweaked for that. So whilst they are this next word predictor,

1573
01:15:49,772 --> 01:15:52,612
Speaker 2: they've got humans all over the place twiddling around to

1574
01:15:52,652 --> 01:15:54,213
Speaker 2: make it make any kind of sense at all.

1575
01:15:54,333 --> 01:15:57,452
Speaker 3: Yep, and thank god for that great discussion. Thank you

1576
01:15:57,492 --> 01:16:01,412
Speaker 3: to everyone who called and texts. Coming up after three o'clock,

1577
01:16:01,652 --> 01:16:03,452
Speaker 3: we want to have a chat about the rules when

1578
01:16:03,492 --> 01:16:07,053
Speaker 3: it comes to the office fridge. A story that is

1579
01:16:07,093 --> 01:16:10,053
Speaker 3: sparking up online in regards to the office fridge and

1580
01:16:10,173 --> 01:16:13,452
Speaker 3: also coming up in about thirty minutes time the moment

1581
01:16:13,572 --> 01:16:17,253
Speaker 3: the nation waits for New Zealander of the Week. That's

1582
01:16:17,293 --> 01:16:19,692
Speaker 3: all coming up very soon, do they Yeah?

1583
01:16:19,732 --> 01:16:20,852
Speaker 2: So, donation wait for that.

1584
01:16:21,013 --> 01:16:23,293
Speaker 3: Absolutely a lot of excitements.

1585
01:16:22,853 --> 01:16:23,572
Speaker 2: They went around for that.

1586
01:16:23,692 --> 01:16:29,452
Speaker 3: Robert new Sport of Weather's coming up, the.

1587
01:16:29,333 --> 01:16:34,012
Speaker 1: Big stories, the leak issues, the big trends and everything

1588
01:16:34,013 --> 01:16:37,812
Speaker 1: in between. It's Matt Heath and Tyler Adams Afternoon Squid

1589
01:16:38,013 --> 01:16:41,052
Speaker 1: Shoulder News Talk said the pretty.

1590
01:16:40,853 --> 01:16:43,333
Speaker 3: Good afternoon sho hope you're having a great Friday afternoon.

1591
01:16:43,372 --> 01:16:45,732
Speaker 3: Welcome back to the show. Seven past three coming up

1592
01:16:45,812 --> 01:16:49,412
Speaker 3: and about twenty five minutes new Zealander of the Week.

1593
01:16:49,492 --> 01:16:52,093
Speaker 3: Looking forward to that, and we also will be going

1594
01:16:52,253 --> 01:16:55,412
Speaker 3: live to HEROLD Sports reporter Alex Powell, who was track

1595
01:16:55,492 --> 01:16:59,093
Speaker 3: side at the Melbourne Grand Prix and p one is

1596
01:16:59,173 --> 01:17:00,253
Speaker 3: underway as we speak.

1597
01:17:00,372 --> 01:17:05,092
Speaker 2: Yeah, he's been wandering around the paddock. He's been rubbing

1598
01:17:05,133 --> 01:17:10,132
Speaker 2: shoulders with the big stars. He's been interviewing Max with Stappan.

1599
01:17:10,652 --> 01:17:15,172
Speaker 2: He's right in the mix and to say I'm jealous

1600
01:17:15,173 --> 01:17:16,012
Speaker 2: would be an understanding.

1601
01:17:16,053 --> 01:17:18,012
Speaker 3: He's a lucky, lucky boy. So looking forward to catching

1602
01:17:18,053 --> 01:17:18,333
Speaker 3: up with that.

1603
01:17:18,532 --> 01:17:20,213
Speaker 2: You know, he's our best man. You've got to have

1604
01:17:20,253 --> 01:17:23,093
Speaker 2: your best man and your best positions and he's the best,

1605
01:17:23,133 --> 01:17:25,732
Speaker 2: if one a guy in the country. So it's great

1606
01:17:25,772 --> 01:17:26,973
Speaker 2: to have him there and it's great to get an

1607
01:17:26,973 --> 01:17:29,173
Speaker 2: opportunity to cross to him. Looking forward to right after

1608
01:17:29,452 --> 01:17:30,532
Speaker 2: a free practice one.

1609
01:17:30,612 --> 01:17:32,412
Speaker 3: Yep, in about thirty five minutes, we're going to have

1610
01:17:32,412 --> 01:17:34,452
Speaker 3: a chat to Alex, but we want to have a

1611
01:17:34,532 --> 01:17:37,892
Speaker 3: chat about the rules around the workplace fridge. This is

1612
01:17:37,893 --> 01:17:41,372
Speaker 3: after an Australian office worker a spark debate after discovering

1613
01:17:41,452 --> 01:17:44,532
Speaker 3: someone had placed to help yourself note on a packet

1614
01:17:44,532 --> 01:17:47,213
Speaker 3: of Tim Tams they had bought in and left in

1615
01:17:47,253 --> 01:17:50,612
Speaker 3: the communal office fridge. The worker shared this photo of

1616
01:17:50,732 --> 01:17:52,972
Speaker 3: the note online, saying a colleague appeared to invite others

1617
01:17:52,973 --> 01:17:56,133
Speaker 3: to eat the biscuits without permission. The post quickly racked

1618
01:17:56,213 --> 01:17:58,572
Speaker 3: up thousands of comments, with many calling the act rude

1619
01:17:58,612 --> 01:18:01,053
Speaker 3: or diabolical, or Others debated.

1620
01:18:00,652 --> 01:18:04,092
Speaker 2: Whether it might have been a misunderstanding. Well, for a start,

1621
01:18:04,253 --> 01:18:07,852
Speaker 2: it's not tim Tams, it's one Tim Tam. It's ten

1622
01:18:07,933 --> 01:18:12,412
Speaker 2: tim Tam. There's no plural. Ah, that's a terrible mistake

1623
01:18:12,452 --> 01:18:13,973
Speaker 2: that people make. And look, I used to be the

1624
01:18:14,053 --> 01:18:19,213
Speaker 2: voice of Tim Tam for Arnot arn It. So you're

1625
01:18:19,293 --> 01:18:21,213
Speaker 2: deep in this, Yeah, I'm deep in I'm deep in

1626
01:18:21,372 --> 01:18:22,972
Speaker 2: Tim Tam, Tim Tam.

1627
01:18:23,492 --> 01:18:25,772
Speaker 3: You're right, Yeah, I tell you I didn't doubt you,

1628
01:18:25,893 --> 01:18:27,412
Speaker 3: but I just thought it was, you know, like one

1629
01:18:27,452 --> 01:18:29,652
Speaker 3: of those things that you know, is that really true?

1630
01:18:29,692 --> 01:18:33,213
Speaker 3: But Tim Tam, Yeah, one, Tom Tam, two, Tim Tam three,

1631
01:18:33,253 --> 01:18:35,333
Speaker 3: Tim Tam, It's good to clarify. No such thing as

1632
01:18:35,372 --> 01:18:36,133
Speaker 3: Tim TAM's.

1633
01:18:35,933 --> 01:18:36,932
Speaker 2: Yeah, we are.

1634
01:18:37,173 --> 01:18:38,612
Speaker 3: I feel like a better person already.

1635
01:18:38,772 --> 01:18:41,333
Speaker 2: But I feel like that isn't really the crux of

1636
01:18:41,333 --> 01:18:41,932
Speaker 2: the debate here.

1637
01:18:42,093 --> 01:18:43,892
Speaker 3: No, No, I mean we all like it. Tim Tam.

1638
01:18:44,572 --> 01:18:47,572
Speaker 2: So the work fridge, I waite undred and eighty ten eighty.

1639
01:18:47,772 --> 01:18:50,772
Speaker 2: Are you involved in any problems in your work fridge?

1640
01:18:50,812 --> 01:18:54,732
Speaker 2: Have you noticed any terrible work fridge crimes? I noticed

1641
01:18:54,772 --> 01:18:57,333
Speaker 2: regularly here since I moved up to ZIBB that the

1642
01:18:57,612 --> 01:19:00,372
Speaker 2: work fridge is policed in a way that I've never

1643
01:19:00,492 --> 01:19:04,052
Speaker 2: experienced at other radio brands heavily. I'm at Radio Hodaki.

1644
01:19:04,133 --> 01:19:07,652
Speaker 2: It's mainly full of beers, and you know, you open

1645
01:19:07,732 --> 01:19:10,612
Speaker 2: the fridge and just ah, lot of beers will roll

1646
01:19:10,652 --> 01:19:13,093
Speaker 2: out on three feet free for all. But these are

1647
01:19:13,133 --> 01:19:18,053
Speaker 2: my rules, okay as I see them, Okay, of what

1648
01:19:18,372 --> 01:19:21,973
Speaker 2: is free for all? Okay, I haven't really got my

1649
01:19:22,053 --> 01:19:25,812
Speaker 2: head around. I think biscuits don't count. I think biscuits

1650
01:19:25,853 --> 01:19:26,572
Speaker 2: aren't a free for all.

1651
01:19:26,572 --> 01:19:28,093
Speaker 3: Okay, all right, circle back to that.

1652
01:19:28,253 --> 01:19:32,173
Speaker 2: Okay, okay, although maybe once they're open, once a packet

1653
01:19:32,173 --> 01:19:35,213
Speaker 2: of tim Tamer is open, I'll think through that.

1654
01:19:35,692 --> 01:19:36,452
Speaker 3: Let's come back to that one.

1655
01:19:36,452 --> 01:19:40,173
Speaker 2: Okay. What the following free for all and a work

1656
01:19:40,213 --> 01:19:43,133
Speaker 2: fridge according to my analysis.

1657
01:19:42,652 --> 01:19:47,852
Speaker 3: Okay, it's good. All sources, all condiments, all sources, all.

1658
01:19:47,772 --> 01:19:51,372
Speaker 2: Sources, smarter sauce, soy sauce, any source that anyone puts

1659
01:19:51,412 --> 01:19:54,772
Speaker 2: in the fridge as free for all. Chutney, chutney, go

1660
01:19:54,893 --> 01:19:55,333
Speaker 2: for your life.

1661
01:19:55,372 --> 01:19:56,732
Speaker 3: Good, All sources, free for all.

1662
01:19:57,452 --> 01:20:01,133
Speaker 2: All milk and cream, free for all, cream.

1663
01:20:00,933 --> 01:20:04,293
Speaker 3: Too, yep, okay, all milk and cream. Okay, right, free

1664
01:20:04,372 --> 01:20:05,532
Speaker 3: for all milk and cream.

1665
01:20:05,812 --> 01:20:08,852
Speaker 2: Yeah. Once that's in there, it's for whoever wants to

1666
01:20:08,973 --> 01:20:13,612
Speaker 2: use it. All spreads, including butter, free for all. Anyone

1667
01:20:13,692 --> 01:20:17,372
Speaker 2: can use any butter in there, any margin there, any olivini,

1668
01:20:17,812 --> 01:20:23,452
Speaker 2: any peanut, butter, any vigimite, anything, free for all. Okay, right, okay.

1669
01:20:24,253 --> 01:20:28,972
Speaker 2: Any open alcohol free for all. Closed alcohol. If there's

1670
01:20:29,053 --> 01:20:31,412
Speaker 2: like say there's a bottle of champagne that someone's won

1671
01:20:31,492 --> 01:20:33,812
Speaker 2: at some kind of awards or something that is not

1672
01:20:33,933 --> 01:20:35,532
Speaker 2: free for all, you don't want to pop it until

1673
01:20:35,532 --> 01:20:37,012
Speaker 2: it's popped. Yeah, and then it's if.

1674
01:20:36,933 --> 01:20:38,772
Speaker 3: It's open and there's half lift, you can outsweag.

1675
01:20:38,893 --> 01:20:40,612
Speaker 2: And anything that's left in the fridge for more than

1676
01:20:40,612 --> 01:20:41,492
Speaker 2: a week free for all.

1677
01:20:41,933 --> 01:20:45,213
Speaker 3: Okay, so it doesn't leave much, that's no.

1678
01:20:45,372 --> 01:20:48,013
Speaker 2: Well, if someone brings got their lunch in there, you

1679
01:20:48,093 --> 01:20:50,652
Speaker 2: can't just grab a bite to someone's sandwich and put

1680
01:20:50,652 --> 01:20:52,412
Speaker 2: it back in their lunch box. Yeah, that's not free

1681
01:20:52,452 --> 01:20:55,053
Speaker 2: for all. You can't put your hand into their mac

1682
01:20:55,093 --> 01:20:57,412
Speaker 2: and cheese, take a clump of it and shove it

1683
01:20:57,452 --> 01:20:58,893
Speaker 2: in your mouth and then put the pole back on.

1684
01:20:59,692 --> 01:21:02,052
Speaker 2: So you can't. And you know, if someone's bought leftovers

1685
01:21:02,093 --> 01:21:03,732
Speaker 2: from home, that's not free for all unless it's been

1686
01:21:03,732 --> 01:21:04,372
Speaker 2: in there for a week.

1687
01:21:04,452 --> 01:21:07,732
Speaker 3: Okay, So just on that last rule, if it's been

1688
01:21:07,772 --> 01:21:09,652
Speaker 3: in there for a week, If someone leaves a packet

1689
01:21:09,692 --> 01:21:12,253
Speaker 3: of tim tam in the fridge for a week, that's

1690
01:21:12,253 --> 01:21:14,452
Speaker 3: free for all. You've had your chance, you've listed in there,

1691
01:21:14,452 --> 01:21:17,133
Speaker 3: you've been teasing people for seven days. You've lost your

1692
01:21:17,213 --> 01:21:19,213
Speaker 3: right to all of those timdam.

1693
01:21:19,013 --> 01:21:22,213
Speaker 2: And I would say seven days is being generous. I'd

1694
01:21:22,333 --> 01:21:24,133
Speaker 2: probably say forty eight hours.

1695
01:21:24,173 --> 01:21:26,492
Speaker 3: Okay, that's a good set of rules. What do you say,

1696
01:21:26,532 --> 01:21:28,452
Speaker 3: our dear listeners. Oh, eight hundred and eighty ten eighty,

1697
01:21:28,532 --> 01:21:29,532
Speaker 3: I'm going to put any.

1698
01:21:29,372 --> 01:21:32,093
Speaker 2: Packet of biscuits that has been open free for all.

1699
01:21:33,532 --> 01:21:35,972
Speaker 3: That's a quick change. Oh one hundred eighty be thinking

1700
01:21:35,973 --> 01:21:38,333
Speaker 3: about it that whole time. Yeah, Oh one hundred eighty

1701
01:21:38,372 --> 01:21:39,933
Speaker 3: ten eighty is the number to call. What do you

1702
01:21:39,973 --> 01:21:42,173
Speaker 3: reckon about Matt's rules when it comes to the communal fridge?

1703
01:21:42,612 --> 01:21:45,253
Speaker 3: And what have your experienced in your workplace? Has someone

1704
01:21:45,333 --> 01:21:47,732
Speaker 3: stolen your chicken sandwich or done something dirty to you?

1705
01:21:48,173 --> 01:21:50,532
Speaker 2: Well, there's another thing that happens a lot around here

1706
01:21:50,612 --> 01:21:52,372
Speaker 2: is suddenly there a note will go up on the

1707
01:21:52,612 --> 01:21:56,293
Speaker 2: work fridge. This thing is being you know, carpet bombed.

1708
01:21:56,412 --> 01:21:59,133
Speaker 2: Clear it out, that's right. Yeah, So get your stuff out. Yeah,

1709
01:21:59,652 --> 01:22:01,412
Speaker 2: your staff, Well we're going to burn it. Everything's in

1710
01:22:01,412 --> 01:22:02,532
Speaker 2: the rubbish hash.

1711
01:22:03,053 --> 01:22:05,612
Speaker 3: It is twelve past three. Taking your calls, O. Eight

1712
01:22:05,692 --> 01:22:09,013
Speaker 3: hundred and eighty ten eighty the work fredge, What are

1713
01:22:09,053 --> 01:22:11,612
Speaker 3: the rules? And has something dirty happened to you? Back

1714
01:22:11,612 --> 01:22:14,452
Speaker 3: in the moment, News Talk said be quarter past three.

1715
01:22:14,492 --> 01:22:16,253
Speaker 3: So we're talking about the rules when it comes to

1716
01:22:16,333 --> 01:22:19,812
Speaker 3: the communal work fridge. This is after an Australian he's

1717
01:22:19,893 --> 01:22:23,213
Speaker 3: gone viral online because someone put a notes on a

1718
01:22:23,293 --> 01:22:25,253
Speaker 3: pack of Tim Tam he brought into the work office

1719
01:22:25,532 --> 01:22:28,333
Speaker 3: saying help yourself to all his colleagues and he was

1720
01:22:28,333 --> 01:22:29,892
Speaker 3: a bit upset by that. But what are the rules

1721
01:22:29,893 --> 01:22:31,333
Speaker 3: when it comes to your work fridge?

1722
01:22:31,372 --> 01:22:31,452
Speaker 1: Oh?

1723
01:22:31,492 --> 01:22:34,612
Speaker 3: One hundred and eighty ten eighty Jeff, how are you

1724
01:22:34,692 --> 01:22:35,253
Speaker 3: this afternoon?

1725
01:22:36,133 --> 01:22:38,452
Speaker 16: Yeah? Good good. I just listening to you then as

1726
01:22:38,532 --> 01:22:42,852
Speaker 16: I was driving home, and I just wondered all these

1727
01:22:43,013 --> 01:22:45,612
Speaker 16: rules you're making and all these conditions that people have

1728
01:22:45,772 --> 01:22:48,133
Speaker 16: to me. You sort of made me think of a

1729
01:22:48,213 --> 01:22:52,492
Speaker 16: communist or even some Islamic fundamentalists of something that telling

1730
01:22:52,612 --> 01:22:55,572
Speaker 16: this Tim TAM's what they can and can't do and

1731
01:22:55,652 --> 01:22:59,093
Speaker 16: how they should live their lives in the fridge. I mean, God,

1732
01:22:59,213 --> 01:23:02,012
Speaker 16: these these Tim Tams have every right in the fridge

1733
01:23:02,053 --> 01:23:05,293
Speaker 16: if they can living there as long as they want.

1734
01:23:06,053 --> 01:23:12,093
Speaker 16: It depends on on and I guess it's the set

1735
01:23:12,213 --> 01:23:13,772
Speaker 16: up as a mental setup.

1736
01:23:13,893 --> 01:23:14,133
Speaker 13: So the.

1737
01:23:15,893 --> 01:23:19,053
Speaker 16: Then and he's going to set these contams free. He's

1738
01:23:19,133 --> 01:23:20,812
Speaker 16: going to come in and he's going to sort all

1739
01:23:20,893 --> 01:23:23,652
Speaker 16: your people out, probably kick you out and let the TI.

1740
01:23:24,452 --> 01:23:24,692
Speaker 4: Yeah.

1741
01:23:25,452 --> 01:23:27,293
Speaker 2: I think that there's a high chance of that, Jeff.

1742
01:23:27,812 --> 01:23:30,412
Speaker 2: But it's an interesting one. What is free because what

1743
01:23:30,452 --> 01:23:32,892
Speaker 2: I'm saying is basically everything in the fridge is free,

1744
01:23:33,532 --> 01:23:35,612
Speaker 2: but it's not really a free market that I'm suggesting,

1745
01:23:35,732 --> 01:23:37,412
Speaker 2: because no one's paying for everything.

1746
01:23:38,333 --> 01:23:41,612
Speaker 16: I'm listening to the people grab that's what happens in

1747
01:23:41,732 --> 01:23:46,293
Speaker 16: the communist environment. Everyone thinks, yes, that's a good pointing,

1748
01:23:48,372 --> 01:23:50,732
Speaker 16: there's none left, and they start fighting over nothing.

1749
01:23:50,973 --> 01:23:53,772
Speaker 2: You understand, right, Jeff, because who's going to keep bringing

1750
01:23:53,812 --> 01:23:57,173
Speaker 2: those sources in if they're just when the.

1751
01:23:57,213 --> 01:24:00,692
Speaker 3: System falls over, whoever the source provider is. If they

1752
01:24:00,732 --> 01:24:03,372
Speaker 3: get upset with this communist system and they no sources

1753
01:24:03,412 --> 01:24:05,412
Speaker 3: for anybody, then the system.

1754
01:24:06,933 --> 01:24:07,692
Speaker 9: Is exactly right.

1755
01:24:07,772 --> 01:24:09,892
Speaker 16: And that's why happens around the world. And the people

1756
01:24:09,973 --> 01:24:12,372
Speaker 16: wonder why don't work, Well, let me want it takes

1757
01:24:12,452 --> 01:24:13,732
Speaker 16: and they should go and then the.

1758
01:24:15,213 --> 01:24:17,372
Speaker 2: Problems and next thing you know, there's a they're building

1759
01:24:17,372 --> 01:24:20,612
Speaker 2: a wall halfway down the fridge, and then there becomes

1760
01:24:20,652 --> 01:24:24,612
Speaker 2: a militarized zone. You make some strong points.

1761
01:24:24,772 --> 01:24:26,572
Speaker 3: Yeah, you've gone deep into this, and that's that's a

1762
01:24:26,652 --> 01:24:28,772
Speaker 3: fair points. Oh one hundred and eighty ten eighties that

1763
01:24:28,893 --> 01:24:29,532
Speaker 3: number to call.

1764
01:24:29,772 --> 01:24:33,532
Speaker 2: The framework of the discussion has been widened by this

1765
01:24:33,652 --> 01:24:36,133
Speaker 2: text of what about workplace showers that other people's body

1766
01:24:36,293 --> 01:24:38,612
Speaker 2: washed left in the shower for free? I take a

1767
01:24:38,692 --> 01:24:40,612
Speaker 2: bar of soap, so if you really want to use it,

1768
01:24:40,812 --> 01:24:44,852
Speaker 2: fill your books, boots low, I will say body wash. Yep,

1769
01:24:45,093 --> 01:24:47,293
Speaker 2: if that's left in the shower, that is that is

1770
01:24:47,452 --> 01:24:50,412
Speaker 2: good to go. A block of soap, A dirty old

1771
01:24:50,452 --> 01:24:52,333
Speaker 2: block of soap. Used that at your peril. I think

1772
01:24:52,372 --> 01:24:52,893
Speaker 2: it's good to go.

1773
01:24:53,572 --> 01:24:54,893
Speaker 3: But it's on you.

1774
01:24:55,173 --> 01:24:55,612
Speaker 12: It's on you.

1775
01:24:55,812 --> 01:24:57,372
Speaker 3: There's a couple of straight he is on there. You

1776
01:24:57,412 --> 01:24:57,972
Speaker 3: know what you're doing.

1777
01:24:58,253 --> 01:25:00,612
Speaker 2: Stuff gets wrapped around a bar of soap.

1778
01:25:01,973 --> 01:25:04,812
Speaker 3: Two is the text number. But what are the rules

1779
01:25:04,853 --> 01:25:07,013
Speaker 3: when it comes to the communal work fridge? What is

1780
01:25:07,093 --> 01:25:10,372
Speaker 3: okay to take? And if nothing's okay to take? I'd

1781
01:25:10,372 --> 01:25:12,412
Speaker 3: love to hear your stories about what's been stolen from you.

1782
01:25:12,492 --> 01:25:14,133
Speaker 3: If someone's next to your lunch, come on through.

1783
01:25:14,333 --> 01:25:16,093
Speaker 2: The six says. I'm a surgeon and started work at

1784
01:25:16,093 --> 01:25:18,452
Speaker 2: a new hospital on my birthday. I knew several of

1785
01:25:18,492 --> 01:25:21,213
Speaker 2: the operating theater nurses from working there during training, so

1786
01:25:21,333 --> 01:25:23,492
Speaker 2: brought a chocolate cake in and left it for the

1787
01:25:23,532 --> 01:25:25,612
Speaker 2: rest of the team and went and started operating. At

1788
01:25:25,652 --> 01:25:27,852
Speaker 2: the end of the day. There was about a quarter left,

1789
01:25:27,893 --> 01:25:30,012
Speaker 2: so I cut myself a slice and immediately got told

1790
01:25:30,053 --> 01:25:33,293
Speaker 2: off my nurse I didn't know who abruptly told me

1791
01:25:33,333 --> 01:25:36,012
Speaker 2: the cake was for the nurses and doctors not to touch.

1792
01:25:36,333 --> 01:25:38,692
Speaker 2: I remember it well. It was exactly eleven years ago today.

1793
01:25:39,333 --> 01:25:42,452
Speaker 3: There's a great story. Oh happy birthday text it Yeah,

1794
01:25:42,452 --> 01:25:45,253
Speaker 3: happy birthday. Oh one hundred and eighty ten eighty is

1795
01:25:45,293 --> 01:25:46,532
Speaker 3: that number to cool cake?

1796
01:25:46,973 --> 01:25:49,092
Speaker 2: All cakes? I'm eading that to my list all cakes.

1797
01:25:49,333 --> 01:25:52,572
Speaker 3: Yep, you know, free for all? Can I just add

1798
01:25:52,572 --> 01:25:54,253
Speaker 3: a couple more that I think is okay for a

1799
01:25:54,452 --> 01:25:56,772
Speaker 3: free for all? Deli meats as long as it's open.

1800
01:25:57,213 --> 01:25:59,213
Speaker 3: So if you've got some salami and you've opened the packet,

1801
01:25:59,812 --> 01:26:00,972
Speaker 3: no open cheeses.

1802
01:26:01,253 --> 01:26:03,412
Speaker 2: See, I don't know how I feel about meats. You're

1803
01:26:03,452 --> 01:26:06,013
Speaker 2: not okay with the deli meats for some reason. I

1804
01:26:06,093 --> 01:26:08,852
Speaker 2: feel like meat is sacred, could be wrong.

1805
01:26:10,253 --> 01:26:12,013
Speaker 3: And packets of edge. So if you're brought in some

1806
01:26:12,133 --> 01:26:14,333
Speaker 3: spinach and you've opened that pack I think people can

1807
01:26:14,412 --> 01:26:15,652
Speaker 3: go for gold if they need a bit for their

1808
01:26:15,692 --> 01:26:18,492
Speaker 3: semi nine two? Is that text?

1809
01:26:18,812 --> 01:26:21,492
Speaker 2: Sorry? Matt? What Krest and weed Moron came up with

1810
01:26:21,532 --> 01:26:24,293
Speaker 2: the rule that two Tim Tams don't have an ass

1811
01:26:24,452 --> 01:26:27,412
Speaker 2: at the end. One biscuit, two biscuits, one mad Heath,

1812
01:26:27,492 --> 01:26:30,852
Speaker 2: two mad Heaths? And what idiotic universe are you bumbling

1813
01:26:31,253 --> 01:26:35,852
Speaker 2: populating at present? Sorry for the dude, I'm painting my

1814
01:26:35,933 --> 01:26:37,293
Speaker 2: bathroom and the pressure.

1815
01:26:36,973 --> 01:26:40,372
Speaker 3: Makes me a crist Oh it's a good finish, Kate. Yeah,

1816
01:26:40,372 --> 01:26:42,572
Speaker 3: painting makes anybody else a good point.

1817
01:26:42,652 --> 01:26:44,932
Speaker 2: And when someone you know, and when I was voicing

1818
01:26:46,013 --> 01:26:48,932
Speaker 2: being the voice for the TV ads for Tim Tam,

1819
01:26:49,452 --> 01:26:51,572
Speaker 2: I was as surprised as anyone when I constantly got

1820
01:26:51,612 --> 01:26:54,732
Speaker 2: told off for saying Tim TAM's. But and then it

1821
01:26:54,853 --> 01:26:56,732
Speaker 2: does big the question, why is it tim Taman not

1822
01:26:56,772 --> 01:26:57,293
Speaker 2: Tim TAM's.

1823
01:26:57,452 --> 01:26:59,812
Speaker 3: Surely the creator of the Tim Tam can decide what

1824
01:26:59,893 --> 01:27:00,652
Speaker 3: you call a tim Tam.

1825
01:27:00,812 --> 01:27:03,372
Speaker 2: But there'll be some English teacher or someone out there

1826
01:27:03,412 --> 01:27:05,892
Speaker 2: that will be able to explain the grammatical reasoning behind

1827
01:27:06,013 --> 01:27:08,133
Speaker 2: why something doesn't have the.

1828
01:27:09,213 --> 01:27:12,333
Speaker 3: Know Yeah, come on through. It is twenty pass three

1829
01:27:12,452 --> 01:27:15,093
Speaker 3: taking your calls on one hundred eighty ten eighty. That

1830
01:27:15,213 --> 01:27:17,572
Speaker 3: text number is nine two nine to two. But we

1831
01:27:17,652 --> 01:27:19,253
Speaker 3: will be back very shortly.

1832
01:27:20,173 --> 01:27:22,412
Speaker 2: Honestly, who puts their Tim Tams in the fridge? No need,

1833
01:27:22,893 --> 01:27:24,973
Speaker 2: It's Tim Tam caller text.

1834
01:27:29,253 --> 01:27:32,892
Speaker 1: Matt Heathen, Tyler Adams afternoons call oh eight hundred eighty

1835
01:27:32,973 --> 01:27:34,333
Speaker 1: ten eighty on used talk.

1836
01:27:34,293 --> 01:27:36,012
Speaker 3: ZB twenty three past three.

1837
01:27:36,452 --> 01:27:39,612
Speaker 2: Just to finish Sam's text there, Okay, guys. Firstly, who

1838
01:27:39,692 --> 01:27:43,732
Speaker 2: honestly puts their Tim Tams in the fridge. They don't

1839
01:27:43,772 --> 01:27:46,173
Speaker 2: go into the fridge. Secondly, not everyone is. Everything is

1840
01:27:46,173 --> 01:27:48,212
Speaker 2: a free for all in the milk and butter department.

1841
01:27:48,293 --> 01:27:50,652
Speaker 2: You haven't got the right to go pinch someone soy

1842
01:27:51,213 --> 01:27:54,772
Speaker 2: almond or dairy milk. I think of it's sewer almond milk.

1843
01:27:54,812 --> 01:27:56,812
Speaker 2: Then just do them a favor and just remove it

1844
01:27:56,812 --> 01:27:58,812
Speaker 2: from the fridge and throw it in the rubbish. They

1845
01:27:58,893 --> 01:28:01,692
Speaker 2: belong to someone else and oat milk. Throw it at them,

1846
01:28:02,452 --> 01:28:04,333
Speaker 2: take it into the office and throw it at them

1847
01:28:05,333 --> 01:28:06,532
Speaker 2: like we're at the top of it, and throw it

1848
01:28:06,572 --> 01:28:09,093
Speaker 2: at them like a grenade at the this they belong

1849
01:28:09,133 --> 01:28:11,293
Speaker 2: to someone else, it's not you don't be such an

1850
01:28:11,333 --> 01:28:13,692
Speaker 2: ass and let people have their own things without you

1851
01:28:13,853 --> 01:28:15,492
Speaker 2: taking them. Love Sam, Thanks Sam.

1852
01:28:15,372 --> 01:28:17,053
Speaker 3: Oh good I under Sam, Yeah yeah, finished with a

1853
01:28:17,133 --> 01:28:18,293
Speaker 3: love gid A Graham.

1854
01:28:19,013 --> 01:28:23,652
Speaker 17: Yeah today, how are you Goods? Back in this late sixties,

1855
01:28:23,692 --> 01:28:26,652
Speaker 17: I was only an eighteen year old, and I worked

1856
01:28:26,692 --> 01:28:29,293
Speaker 17: in the factory with a group of about seven or

1857
01:28:29,333 --> 01:28:32,133
Speaker 17: eight men, and we were doing welding, and I was

1858
01:28:32,253 --> 01:28:35,892
Speaker 17: just learning the trade. And when we used to eat

1859
01:28:36,053 --> 01:28:39,052
Speaker 17: weld galv and ized steel, the fumes come off were terrible.

1860
01:28:39,173 --> 01:28:42,172
Speaker 17: So I used to buy a pack of of lollies,

1861
01:28:42,412 --> 01:28:44,173
Speaker 17: and in those days, you got them in a sort

1862
01:28:44,213 --> 01:28:46,972
Speaker 17: of a white paper bag, you know, lecross all sorts,

1863
01:28:47,053 --> 01:28:50,572
Speaker 17: pineapple lumps, all mixed them together. But every time I

1864
01:28:50,652 --> 01:28:53,372
Speaker 17: went to the toilet, i'd come back and half the

1865
01:28:53,452 --> 01:28:56,492
Speaker 17: lollies had be gone, and the older guys were eating them,

1866
01:28:57,293 --> 01:28:59,372
Speaker 17: and it was it was a game they were playing,

1867
01:28:59,452 --> 01:29:02,772
Speaker 17: so I didn't let on anyway when they they ate

1868
01:29:02,812 --> 01:29:05,173
Speaker 17: them all. A couple of days later, I went to

1869
01:29:05,253 --> 01:29:08,012
Speaker 17: get another bag, and when I was passing the chemist shop,

1870
01:29:08,053 --> 01:29:09,892
Speaker 17: I went and then I brought a packet of these

1871
01:29:10,013 --> 01:29:13,412
Speaker 17: chocolate flavors lex lives, and I chopped them up and

1872
01:29:13,492 --> 01:29:16,933
Speaker 17: make them look like pineapple rumps, put them in the

1873
01:29:17,013 --> 01:29:19,772
Speaker 17: paper bag, and when I got to work, I went

1874
01:29:19,853 --> 01:29:22,452
Speaker 17: off to the bloody toilet. When I come back, sure

1875
01:29:22,572 --> 01:29:25,012
Speaker 17: enough some had gone. By the end of the day,

1876
01:29:25,053 --> 01:29:27,932
Speaker 17: all my lollies had gone, you know, just as bloody usual.

1877
01:29:28,372 --> 01:29:31,612
Speaker 17: When I went to work the next day, the foreman

1878
01:29:31,692 --> 01:29:33,892
Speaker 17: come up to me and he said, hell, are you Graham?

1879
01:29:33,933 --> 01:29:36,972
Speaker 17: I said good. He says, you feeling okay? I said yeah,

1880
01:29:37,013 --> 01:29:40,412
Speaker 17: I'm a good mate. I said, what's up? He says,

1881
01:29:40,812 --> 01:29:43,173
Speaker 17: I've had about three of the guys ring the shed.

1882
01:29:46,293 --> 01:29:49,213
Speaker 17: I said no, no, I'm I'm fine. And as I

1883
01:29:49,333 --> 01:29:52,973
Speaker 17: said that, this guy Jock Simpson, who was a Scotsman.

1884
01:29:54,173 --> 01:29:56,532
Speaker 17: When he spoke you couldn't understand it because of his

1885
01:29:56,652 --> 01:29:59,173
Speaker 17: sick accent. But he went ball and past us and

1886
01:29:59,893 --> 01:30:03,892
Speaker 17: thought and he was another one off. So I got

1887
01:30:03,973 --> 01:30:05,013
Speaker 17: four of them out of eight.

1888
01:30:05,572 --> 01:30:07,572
Speaker 2: So did you ever ride up? Or is this is

1889
01:30:07,652 --> 01:30:09,333
Speaker 2: this the first time really get to the world.

1890
01:30:09,732 --> 01:30:12,852
Speaker 17: No, the foreman was a big bloody dutch Man and

1891
01:30:12,933 --> 01:30:13,772
Speaker 17: he would have killed me.

1892
01:30:14,013 --> 01:30:18,372
Speaker 2: Yeah, so you passed the statute of limitations now, so

1893
01:30:18,532 --> 01:30:20,372
Speaker 2: I think it's the it's the perfect crime, and it's

1894
01:30:20,412 --> 01:30:21,093
Speaker 2: the perfect crime.

1895
01:30:22,372 --> 01:30:22,572
Speaker 6: Yeah.

1896
01:30:22,732 --> 01:30:25,013
Speaker 3: Thanks, you call me, what a great story? I one

1897
01:30:25,053 --> 01:30:26,452
Speaker 3: hundred eighty ten eights number to call.

1898
01:30:26,572 --> 01:30:28,652
Speaker 2: Well, I'm no English expert, but I reckon that Tim

1899
01:30:28,732 --> 01:30:30,652
Speaker 2: Tam is the brand name, so you would say I

1900
01:30:30,772 --> 01:30:33,452
Speaker 2: have two Tim Tam biscuits. So I guess they are

1901
01:30:33,612 --> 01:30:34,132
Speaker 2: a biscuit.

1902
01:30:34,452 --> 01:30:37,253
Speaker 3: Yeah, that makes sense that if you're going to make sense.

1903
01:30:38,053 --> 01:30:39,973
Speaker 2: Welcome to the show. Can I say it?

1904
01:30:42,293 --> 01:30:44,133
Speaker 3: Oh we had Sam, we just lost Samy' there?

1905
01:30:44,213 --> 01:30:45,652
Speaker 17: Sam? Yeah?

1906
01:30:47,973 --> 01:30:48,293
Speaker 21: How are you?

1907
01:30:48,572 --> 01:30:49,173
Speaker 2: Very good? Things?

1908
01:30:49,213 --> 01:30:53,572
Speaker 5: Bud fist things. First, let's get definitely need to go

1909
01:30:53,652 --> 01:30:57,492
Speaker 5: on the fridge of its chocolate colored. Yeah, and let's

1910
01:30:57,532 --> 01:30:58,452
Speaker 5: put the s on there.

1911
01:30:58,372 --> 01:30:58,532
Speaker 19: For the.

1912
01:31:00,013 --> 01:31:01,892
Speaker 3: Right you know, I happy with Tim tam. You want

1913
01:31:01,893 --> 01:31:02,492
Speaker 3: the s on there?

1914
01:31:03,053 --> 01:31:04,293
Speaker 5: Yeah, let's put the on there.

1915
01:31:04,412 --> 01:31:06,652
Speaker 2: Yeah. Well if you've bought, if you bought them, you know,

1916
01:31:07,492 --> 01:31:09,333
Speaker 2: big Arnet does get to tell us how to talk

1917
01:31:09,372 --> 01:31:12,812
Speaker 2: about the biscuits we bought, so we'll call it two tams,

1918
01:31:13,213 --> 01:31:13,372
Speaker 2: you know.

1919
01:31:13,532 --> 01:31:15,572
Speaker 5: And as far as any packet of biscuits goes, I

1920
01:31:15,612 --> 01:31:18,532
Speaker 5: think the important thing to remember is in a communal fridges,

1921
01:31:19,372 --> 01:31:22,372
Speaker 5: you don't start the packet, don't finish the packet. Yeah,

1922
01:31:22,452 --> 01:31:24,093
Speaker 5: the packets aren't open, you don't open it.

1923
01:31:24,492 --> 01:31:25,812
Speaker 3: Yeah, I think there's a good call.

1924
01:31:25,933 --> 01:31:28,412
Speaker 5: Yeah, you could have two, but if there's two left,

1925
01:31:28,812 --> 01:31:30,452
Speaker 5: you don't need those last two bang on.

1926
01:31:30,772 --> 01:31:33,093
Speaker 3: You can't open it. You can't have the first one,

1927
01:31:33,173 --> 01:31:35,572
Speaker 3: you can't have the last one. Everything else open open

1928
01:31:35,612 --> 01:31:36,052
Speaker 3: s left.

1929
01:31:36,013 --> 01:31:38,253
Speaker 2: Well, I noticed something here, Sam at this office, because

1930
01:31:38,253 --> 01:31:40,612
Speaker 2: often when Tyler and I are on air, they'll have

1931
01:31:40,853 --> 01:31:43,572
Speaker 2: some kind of function out there with some snacks. They

1932
01:31:43,652 --> 01:31:45,013
Speaker 2: do that a lot, and by the time we go

1933
01:31:45,093 --> 01:31:47,013
Speaker 2: out there, there's just one of the snack remaining on

1934
01:31:47,053 --> 01:31:48,852
Speaker 2: each plate because no one wants to take the last one.

1935
01:31:51,093 --> 01:31:52,772
Speaker 3: It's they think they think they do it. You know,

1936
01:31:52,853 --> 01:31:54,612
Speaker 3: it sounds like they're doing us a favor. But yeah,

1937
01:31:54,652 --> 01:31:56,253
Speaker 3: nobody wants to take that last one.

1938
01:31:56,372 --> 01:31:58,133
Speaker 2: They're not doing it for us. It's just ingrained in

1939
01:31:58,173 --> 01:31:59,772
Speaker 2: people's mind that you don't take the last one.

1940
01:31:59,893 --> 01:32:02,133
Speaker 5: Probably the fact that it's catering put on by the

1941
01:32:03,612 --> 01:32:06,492
Speaker 5: by the establishment makes it okay to grab the last savory.

1942
01:32:06,572 --> 01:32:08,213
Speaker 5: But as far as a packet of biscuits.

1943
01:32:07,933 --> 01:32:10,532
Speaker 7: With an un owner, yeah you don't.

1944
01:32:11,013 --> 01:32:12,213
Speaker 5: But I don't want you to finish that.

1945
01:32:12,812 --> 01:32:18,053
Speaker 2: So first, Tim Tam, not okay. All the ones in

1946
01:32:18,133 --> 01:32:21,412
Speaker 2: the middle, the eight in the middle, okay, but the

1947
01:32:21,532 --> 01:32:22,572
Speaker 2: last one not okay.

1948
01:32:23,253 --> 01:32:25,293
Speaker 5: I mean you're probably pushing it if you're taking more

1949
01:32:25,372 --> 01:32:28,132
Speaker 5: than three, maybe four of the stretch.

1950
01:32:28,333 --> 01:32:31,013
Speaker 3: Yeah, yeah, yeah, yeah, it's just what.

1951
01:32:31,412 --> 01:32:34,092
Speaker 5: You might take six. Yeah, But if we're talking Tim Tams,

1952
01:32:34,253 --> 01:32:35,452
Speaker 5: I think you're pushing it at four.

1953
01:32:35,772 --> 01:32:38,012
Speaker 2: If you're taking if you're taking a packet of snacks,

1954
01:32:38,173 --> 01:32:40,692
Speaker 2: which is my favorite bisket of all times, salty, brilliant,

1955
01:32:40,933 --> 01:32:43,213
Speaker 2: then you can take a handful of snacks. Yeah, crackers,

1956
01:32:43,412 --> 01:32:44,692
Speaker 2: you can get a handful of those, salty.

1957
01:32:44,812 --> 01:32:47,013
Speaker 3: It's about the ratio. It's about the ratio that you take.

1958
01:32:47,213 --> 01:32:50,173
Speaker 2: Yeah, yeah, Sam, you're a good man, Thank you very much.

1959
01:32:50,213 --> 01:32:52,572
Speaker 3: I mean, it's funny that we've been talking about work fridges,

1960
01:32:52,612 --> 01:32:54,812
Speaker 3: but what's got people most upset is Tim Tam or

1961
01:32:54,853 --> 01:32:55,973
Speaker 3: Tim tamps Hi.

1962
01:32:56,093 --> 01:32:58,452
Speaker 2: Boys. I lived in Eastern Europe for a period of time,

1963
01:32:58,572 --> 01:33:00,692
Speaker 2: and the dynamic in the office, lunch room and what

1964
01:33:00,893 --> 01:33:02,932
Speaker 2: was in the fridge was anything that was in there

1965
01:33:03,013 --> 01:33:05,932
Speaker 2: was fair game, even alcohol, and on several occasions bottles

1966
01:33:05,933 --> 01:33:07,933
Speaker 2: of wine and champagne were cracked open for all to

1967
01:33:08,093 --> 01:33:13,093
Speaker 2: enjoy at lunchtime and before even morning tea. Jeers, John,

1968
01:33:13,133 --> 01:33:17,612
Speaker 2: that's classic Eastern European behavior, cracking a bottle of booze

1969
01:33:17,853 --> 01:33:18,812
Speaker 2: before morning tea.

1970
01:33:18,973 --> 01:33:23,213
Speaker 3: Yeah yeah, And who's bringing in the champagne? You know, quick,

1971
01:33:23,213 --> 01:33:26,293
Speaker 3: a couple of teks before the headlines are coming up.

1972
01:33:26,572 --> 01:33:29,452
Speaker 2: Up and goes free for all. I'd agree with that.

1973
01:33:30,253 --> 01:33:30,892
Speaker 2: I don't know why.

1974
01:33:31,013 --> 01:33:33,973
Speaker 3: Yep, this one, Matt, what about the butter and the

1975
01:33:33,973 --> 01:33:37,333
Speaker 3: butter conditioner. Surely that's sacred. Oh yeah, that's from Tony.

1976
01:33:38,372 --> 01:33:42,012
Speaker 2: I've got two words to tell with butter conditioner. What's

1977
01:33:42,013 --> 01:33:45,013
Speaker 2: happened to butter conditioners? That'll only but that'll only mean

1978
01:33:45,133 --> 01:33:47,492
Speaker 2: something to people listeners to the Marcus Lusher's show.

1979
01:33:47,452 --> 01:33:50,732
Speaker 3: Great New Zealander. Right, it is twenty nine past three.

1980
01:33:50,772 --> 01:33:54,253
Speaker 3: We've got the headlines coming up. Then New Zealander of

1981
01:33:54,452 --> 01:33:55,012
Speaker 3: the Week.

1982
01:33:56,732 --> 01:34:00,372
Speaker 13: Used talk said, be headlines with your Ride, New Zealand's

1983
01:34:00,412 --> 01:34:05,132
Speaker 13: number one taxi app Download your Ride today. Pressure's mounting

1984
01:34:05,173 --> 01:34:08,253
Speaker 13: on the Prime Minister. As National records it's the lowest

1985
01:34:08,492 --> 01:34:13,012
Speaker 13: pole results since entering government. Today's Taxpayer's Union Courier poll

1986
01:34:13,372 --> 01:34:16,852
Speaker 13: has the Party on twenty eight point four percent, Labours

1987
01:34:16,893 --> 01:34:21,492
Speaker 13: six points ahead on thirty four point four. Two helicopters

1988
01:34:21,532 --> 01:34:24,172
Speaker 13: and eight trucks are battling a large out of controlled

1989
01:34:24,293 --> 01:34:28,492
Speaker 13: vegetation fire at Arrow Junction near Arrow Town. Fire and

1990
01:34:28,572 --> 01:34:31,612
Speaker 13: emergency were called just after one and so it started

1991
01:34:31,652 --> 01:34:35,173
Speaker 13: as a burnoff and Fire and Emergency fielded calls for

1992
01:34:35,333 --> 01:34:40,333
Speaker 13: seventeen incidents during today, Strike Action eight inaffected areas. Today

1993
01:34:40,412 --> 01:34:45,492
Speaker 13: mark the sixteenth strike by the Professional Firefighters Union. Foreign

1994
01:34:45,532 --> 01:34:48,772
Speaker 13: Minister Winston Peters says New Zealand is doing everything it

1995
01:34:48,973 --> 01:34:52,652
Speaker 13: can to get KIWI stranded in the Middle East back home.

1996
01:34:53,173 --> 01:34:57,212
Speaker 13: More than three thousand have registered with m FAT. Britney

1997
01:34:57,253 --> 01:34:59,933
Speaker 13: Spears has had another run in with the law. The

1998
01:35:00,013 --> 01:35:03,133
Speaker 13: pop Icon has been arrested in California on suspicion of

1999
01:35:03,253 --> 01:35:08,253
Speaker 13: driving under the influence. Nay Palm Girl photographer sues netf

2000
01:35:08,333 --> 01:35:12,013
Speaker 13: Flix over film that calls him a fraud. You can

2001
01:35:12,093 --> 01:35:15,372
Speaker 13: find out more at ZAID Herald Premium. Back to Matt

2002
01:35:15,412 --> 01:35:16,933
Speaker 13: Ethan Tyler Adams.

2003
01:35:17,492 --> 01:35:22,093
Speaker 1: The Matt Heath and Tyler Adams Afternoons New Zealander of

2004
01:35:22,412 --> 01:35:22,812
Speaker 1: the Week.

2005
01:35:23,053 --> 01:35:26,052
Speaker 2: As time one's again for your favorite weekly award celebration.

2006
01:35:26,213 --> 01:35:29,412
Speaker 2: The Powerful Matt Heath and Tyler Adams Afternoons New Zealander

2007
01:35:29,492 --> 01:35:31,652
Speaker 2: of the Week. As always, There'll be two runners up,

2008
01:35:32,173 --> 01:35:35,173
Speaker 2: but just the one winner. So without wasting any more

2009
01:35:35,372 --> 01:35:37,933
Speaker 2: of the precious seconds of your life, let's get on

2010
01:35:38,053 --> 01:35:41,093
Speaker 2: with the show. As Worship popped in to hear the

2011
01:35:41,173 --> 01:35:44,333
Speaker 2: show on z B post lunch, he was fired up, pugnacious,

2012
01:35:44,412 --> 01:35:46,852
Speaker 2: and he dropped a couple of lines that political experts

2013
01:35:47,053 --> 01:35:49,812
Speaker 2: are still trying to unpack days later. Are you trying

2014
01:35:49,853 --> 01:35:51,933
Speaker 2: to screw mister semol No, No, he's trying to screw me,

2015
01:35:52,093 --> 01:35:56,052
Speaker 2: And there's no way that's going to happen. Mayor Wayne Brown.

2016
01:35:56,173 --> 01:35:58,612
Speaker 2: We will follow that closely and keep people updated on

2017
01:35:58,772 --> 01:36:01,812
Speaker 2: how that goes down, But right now, Urine also ran

2018
01:36:02,053 --> 01:36:05,372
Speaker 2: the New Zealander of boarding. The events in Iran couldn't

2019
01:36:05,372 --> 01:36:07,732
Speaker 2: be further away from the little Old New Zealand if

2020
01:36:07,772 --> 01:36:11,012
Speaker 2: they tried. The fog of war is very thick over there.

2021
01:36:11,333 --> 01:36:16,852
Speaker 2: We can't see down here. Thankfully. This week, an Auckland

2022
01:36:16,893 --> 01:36:20,213
Speaker 2: based Iranian New Zealander barrister and solicitor joined us on

2023
01:36:20,253 --> 01:36:23,053
Speaker 2: the show to bring some cold hard reality home.

2024
01:36:24,093 --> 01:36:26,253
Speaker 24: I have lived in around most of my adult life

2025
01:36:26,333 --> 01:36:30,812
Speaker 24: and I witnessed over forty five hanging darning and I

2026
01:36:30,933 --> 01:36:33,732
Speaker 24: was arrested. I was put in prison. I've been sentenced

2027
01:36:33,772 --> 01:36:37,372
Speaker 24: to lashing and they ordered ninety lashes. I ended up

2028
01:36:37,412 --> 01:36:40,772
Speaker 24: getting only forty. This is my background, as well as

2029
01:36:40,853 --> 01:36:43,652
Speaker 24: having friends that I have loved because they've been tortured,

2030
01:36:43,692 --> 01:36:46,732
Speaker 24: they've been in prisoned in the past forty seven years.

2031
01:36:46,853 --> 01:36:49,772
Speaker 24: They have tried negotiation. They have tried sanctions, they have

2032
01:36:49,933 --> 01:36:53,092
Speaker 24: tried you and resolutions. None of that work, and waiting

2033
01:36:53,173 --> 01:36:55,972
Speaker 24: for a mushroom cloud would have cost millions of lives.

2034
01:36:56,253 --> 01:37:00,053
Speaker 24: And to be honest, sovereignty isn't sacred when it's a

2035
01:37:00,133 --> 01:37:01,412
Speaker 24: shield for slaughter.

2036
01:37:02,812 --> 01:37:07,213
Speaker 2: Iranian New Zealand barrister Samira Tagavi, you have seen things

2037
01:37:07,412 --> 01:37:10,732
Speaker 2: and experienced things we can only hope we never see.

2038
01:37:11,053 --> 01:37:13,372
Speaker 2: Thanks for dropping by. We honor you for fighting the

2039
01:37:13,412 --> 01:37:16,012
Speaker 2: good fight. Read her excellent article in The Heroes.

2040
01:37:18,652 --> 01:37:22,213
Speaker 3: It's the fastest T twenty hundred and the World Cup.

2041
01:37:22,293 --> 01:37:26,133
Speaker 2: Heaver for an hour and helps the black Cats get

2042
01:37:26,213 --> 01:37:29,092
Speaker 2: into the final. They went by nine wickets. He smashed

2043
01:37:29,133 --> 01:37:31,972
Speaker 2: one hundred runs and thirty three balls to wallop South

2044
01:37:32,053 --> 01:37:35,093
Speaker 2: Africa and power New Zealand into the final of the

2045
01:37:35,452 --> 01:37:39,173
Speaker 2: ICC T twenty Cricket World Cup, the fastest hundi in

2046
01:37:39,253 --> 01:37:41,212
Speaker 2: the history of the tournament.

2047
01:37:41,532 --> 01:37:42,772
Speaker 3: Your name sounds like some.

2048
01:37:42,933 --> 01:37:44,892
Speaker 2: Kind of cancer causing chemical on the side of an

2049
01:37:44,973 --> 01:37:48,492
Speaker 2: energy drink. Can But Finellan, you surecans see the ball

2050
01:37:48,732 --> 01:37:51,452
Speaker 2: and hit the ball hard, and you are the Madheath

2051
01:37:51,532 --> 01:37:54,572
Speaker 2: and Tyler Adams. Afternoons on us tour sent by New

2052
01:37:54,692 --> 01:37:55,892
Speaker 2: Zealander of the week.

2053
01:37:56,412 --> 01:37:58,173
Speaker 3: Now do it well again in the final. Would you

2054
01:37:58,772 --> 01:38:00,612
Speaker 3: go on the black Cats and take.

2055
01:38:00,532 --> 01:38:02,572
Speaker 2: It away for our fires?

2056
01:38:02,692 --> 01:38:42,652
Speaker 9: Shute for sex?

2057
01:38:47,213 --> 01:39:04,293
Speaker 18: Right, Matt, Tyler Adams?

2058
01:39:04,452 --> 01:39:09,492
Speaker 3: Oh how good? Another deserving winner. Fantastic right? Coming up next,

2059
01:39:09,973 --> 01:39:13,013
Speaker 3: Free practice one has just finished in Melbourne, head of

2060
01:39:13,053 --> 01:39:16,812
Speaker 3: the first Formula One Grand Prix this season. Standing by

2061
01:39:17,053 --> 01:39:20,372
Speaker 3: is New Zealand's premiere Formula one reporter Alex Powell. He's

2062
01:39:20,492 --> 01:39:23,892
Speaker 3: track side and we got plenty to chat about with Alex.

2063
01:39:24,013 --> 01:39:26,732
Speaker 3: That is coming up next. It is twenty three to.

2064
01:39:26,812 --> 01:39:31,612
Speaker 1: Four Matt Heath and Tyler Adams afternoons taking your calls

2065
01:39:31,692 --> 01:39:34,253
Speaker 1: on Oh eight hundred and eighty eight, where's Skoda?

2066
01:39:34,452 --> 01:39:36,972
Speaker 7: Can you crack the code? Please sc to codes every

2067
01:39:37,053 --> 01:39:38,133
Speaker 7: day news talks.

2068
01:39:38,133 --> 01:39:40,333
Speaker 3: That'd be It's twenty to four, So the first free

2069
01:39:40,412 --> 01:39:43,053
Speaker 3: practice session at Melbourne has just wrapped up ahead of

2070
01:39:43,093 --> 01:39:47,492
Speaker 3: the season opening Formula one Australian Grand Prix. Track Side

2071
01:39:47,772 --> 01:39:50,612
Speaker 3: is New Zealand's leading Formula One reporter Alex Powell, who

2072
01:39:50,772 --> 01:39:53,572
Speaker 3: joins us on the line. Alex, how are you doing.

2073
01:39:54,492 --> 01:39:56,692
Speaker 25: Afterday no checks in the mail before me? The leading

2074
01:39:56,732 --> 01:39:57,372
Speaker 25: US one reporter.

2075
01:39:57,572 --> 01:39:59,012
Speaker 3: Yeah, yeah, we agreed to that earlier.

2076
01:39:59,173 --> 01:40:01,852
Speaker 2: It's facts, mate, it's fact. So I've been seeing some

2077
01:40:01,933 --> 01:40:05,092
Speaker 2: pictures you've been sending through. You have some incredible access

2078
01:40:05,253 --> 01:40:08,133
Speaker 2: to the F one this weekend. Where do we find

2079
01:40:08,173 --> 01:40:09,213
Speaker 2: you now? Are you in the paddock?

2080
01:40:10,452 --> 01:40:12,293
Speaker 25: I am in the paddock. I am right outside the

2081
01:40:12,333 --> 01:40:13,852
Speaker 25: Red Bull enclosure. I don't know if you can hear

2082
01:40:13,893 --> 01:40:15,692
Speaker 25: all that noise in the background. So of course that's

2083
01:40:15,732 --> 01:40:16,293
Speaker 25: coming from them.

2084
01:40:16,732 --> 01:40:19,732
Speaker 2: Oh right, and so then you couldn't get really closer.

2085
01:40:20,013 --> 01:40:20,772
Speaker 3: Yeah, yeah, good.

2086
01:40:22,093 --> 01:40:25,492
Speaker 2: So new Riggs who was looking good in training and

2087
01:40:25,853 --> 01:40:26,772
Speaker 2: who crept the beard.

2088
01:40:28,213 --> 01:40:30,732
Speaker 25: Well, Ferrari looked like it's that first session of them

2089
01:40:30,812 --> 01:40:32,612
Speaker 25: to go by. Ferrari look like they're the ones out

2090
01:40:32,652 --> 01:40:35,013
Speaker 25: in front. Obviously you take practice times with a grain

2091
01:40:35,093 --> 01:40:37,093
Speaker 25: of salt, but both Ferrari cars were one and so

2092
01:40:37,772 --> 01:40:40,053
Speaker 25: Red Bull were actually three and four, which was a

2093
01:40:40,173 --> 01:40:42,692
Speaker 25: bit of a shock given how else the pace they

2094
01:40:42,732 --> 01:40:44,652
Speaker 25: were in Bahrain in a couple of weeks gun testing.

2095
01:40:45,213 --> 01:40:48,452
Speaker 25: The McLaren cars, or sorry, both McLaren cars and both

2096
01:40:48,492 --> 01:40:50,612
Speaker 25: Mercedes cars look like they're struggling a little bit now.

2097
01:40:50,692 --> 01:40:52,772
Speaker 25: They were meant to be up at the front because

2098
01:40:52,812 --> 01:40:55,333
Speaker 25: the new Mercedes power units expected to better leading, but

2099
01:40:55,452 --> 01:40:58,093
Speaker 25: that's just either not happened or they're holding back of

2100
01:40:58,173 --> 01:40:59,372
Speaker 25: it before qualifying tomorrow.

2101
01:41:00,013 --> 01:41:00,932
Speaker 2: How was liamb looking.

2102
01:41:02,372 --> 01:41:04,972
Speaker 25: Lamb was solid so he got through twenty seven odd

2103
01:41:05,013 --> 01:41:07,093
Speaker 25: laps that a she His teammate arvid Land Bladd was

2104
01:41:07,133 --> 01:41:09,372
Speaker 25: actually quicker than but he also had a power unit

2105
01:41:09,532 --> 01:41:11,173
Speaker 25: sort of failure at the start of the session. So

2106
01:41:11,652 --> 01:41:14,293
Speaker 25: mix signs they're for racing balls again. We won't really

2107
01:41:14,412 --> 01:41:16,772
Speaker 25: know where too many cars stand until so maybe this

2108
01:41:16,893 --> 01:41:18,572
Speaker 25: time tomorrow when we're getting ready to qualify.

2109
01:41:19,412 --> 01:41:22,772
Speaker 2: What were the biggest surprises from P one.

2110
01:41:24,013 --> 01:41:27,732
Speaker 25: I think out you know, they've rebranded from being SOURBA

2111
01:41:27,812 --> 01:41:29,812
Speaker 25: last year. They're making their own power unit, which we

2112
01:41:29,853 --> 01:41:31,893
Speaker 25: have really seen and seen coming and do like that.

2113
01:41:32,093 --> 01:41:34,932
Speaker 25: Normally you get on board with the Ferrari or Mercedes

2114
01:41:35,013 --> 01:41:37,253
Speaker 25: engine if you're new into the sports, but they're going

2115
01:41:37,293 --> 01:41:38,932
Speaker 25: out and on their own and they had both their

2116
01:41:39,013 --> 01:41:42,092
Speaker 25: cars finish in the top ten, Gabriel Bortleto and Nick Holkerbuk,

2117
01:41:42,173 --> 01:41:44,173
Speaker 25: So I think there was really positive signs for them there.

2118
01:41:45,013 --> 01:41:46,852
Speaker 2: How did the new engine sound, because of course we've

2119
01:41:46,853 --> 01:41:48,772
Speaker 2: got these new rigs, we've got the fifty to fifty

2120
01:41:48,893 --> 01:41:50,492
Speaker 2: hybrids set up. How do they sound.

2121
01:41:51,812 --> 01:41:53,772
Speaker 25: They're very loud. I can tell you. I think I

2122
01:41:53,812 --> 01:41:55,612
Speaker 25: have got a bit of hearing damage fromvent so close

2123
01:41:55,612 --> 01:41:59,213
Speaker 25: to the track they found violent. We can't really notice

2124
01:41:59,213 --> 01:42:02,253
Speaker 25: any major difference, but there are very significant changes with

2125
01:42:02,333 --> 01:42:05,412
Speaker 25: the fifty fifty slat. But they do sound like engines

2126
01:42:05,532 --> 01:42:06,572
Speaker 25: that are Formula one.

2127
01:42:06,532 --> 01:42:10,092
Speaker 3: Car should have seem to be a few issues for Cadillac,

2128
01:42:10,532 --> 01:42:13,212
Speaker 3: was there, Alex, I mean Cadillac.

2129
01:42:13,253 --> 01:42:15,213
Speaker 25: You expect they're get coming in from a long way back.

2130
01:42:15,213 --> 01:42:17,333
Speaker 25: There new once of thecrits this year, like they've got

2131
01:42:17,372 --> 01:42:19,932
Speaker 25: a Ferrari engine, which we know should be pretty good

2132
01:42:19,973 --> 01:42:22,093
Speaker 25: at those times that we've just seen anything to go by,

2133
01:42:22,572 --> 01:42:24,492
Speaker 25: but they are probably going to struggle as the martin

2134
01:42:24,492 --> 01:42:27,132
Speaker 25: are going even worse like their Carlo's like an absolute tractor,

2135
01:42:28,013 --> 01:42:29,412
Speaker 25: which I know Matt will be a big fan and

2136
01:42:29,652 --> 01:42:33,293
Speaker 25: given as a hatred of the Stroll family. So there

2137
01:42:33,333 --> 01:42:36,092
Speaker 25: are some clear back markers already showing themselves.

2138
01:42:36,973 --> 01:42:39,492
Speaker 2: Did you learn anything more about how the cars drive,

2139
01:42:39,732 --> 01:42:42,133
Speaker 2: cornering and such, because of course there's been a lot

2140
01:42:42,133 --> 01:42:44,732
Speaker 2: of talk about the battery management needed. Is it obvious

2141
01:42:44,812 --> 01:42:46,253
Speaker 2: in the way that they're driving.

2142
01:42:47,652 --> 01:42:49,732
Speaker 25: It sounds so different tracks they're just going to have

2143
01:42:49,853 --> 01:42:52,532
Speaker 25: different challenges. This one here, all the drivers are saying

2144
01:42:52,612 --> 01:42:54,173
Speaker 25: is actually going to be really tough because of the

2145
01:42:54,333 --> 01:42:57,692
Speaker 25: number of straits. So it's the last sort of Sorry.

2146
01:42:57,772 --> 01:42:59,893
Speaker 25: With the power units and the batteries last year, what

2147
01:42:59,973 --> 01:43:02,133
Speaker 25: they would do is they would recharge when you break,

2148
01:43:02,133 --> 01:43:04,372
Speaker 25: whereas now the drivers do have to manage it themselves

2149
01:43:04,893 --> 01:43:07,253
Speaker 25: and they're not actually going to have that many opportunities

2150
01:43:07,293 --> 01:43:09,253
Speaker 25: to take it home to court. It's because it's just

2151
01:43:09,372 --> 01:43:10,293
Speaker 25: play out for most of it.

2152
01:43:11,492 --> 01:43:13,852
Speaker 2: Now, what what's it like wandering around the paddock with

2153
01:43:13,933 --> 01:43:16,532
Speaker 2: a bunch of the most recognizable people in the planet.

2154
01:43:16,572 --> 01:43:20,053
Speaker 2: Who have you rubbed shoulders with so far? Alex? I did?

2155
01:43:20,333 --> 01:43:20,532
Speaker 7: Well?

2156
01:43:20,612 --> 01:43:23,372
Speaker 25: I mean that's your partner. Tracy is listening. Get ready,

2157
01:43:23,372 --> 01:43:25,812
Speaker 25: because I accidentally sump into Child the clerk waiting for

2158
01:43:25,853 --> 01:43:28,213
Speaker 25: a coffee this morning, and he apologized to me, Wow,

2159
01:43:28,333 --> 01:43:29,333
Speaker 25: that too well.

2160
01:43:29,372 --> 01:43:31,492
Speaker 2: I told you that. I told you if you could

2161
01:43:31,492 --> 01:43:33,492
Speaker 2: grab a clump of hair off the back of his

2162
01:43:33,612 --> 01:43:35,492
Speaker 2: head to give to my partner, I'd be very grateful.

2163
01:43:35,532 --> 01:43:37,013
Speaker 2: So did you have a yank on his hair?

2164
01:43:38,213 --> 01:43:41,612
Speaker 25: I'm working on it. No, that is a little bit surreal,

2165
01:43:41,732 --> 01:43:44,612
Speaker 25: Like you do walk past these guys just on your day.

2166
01:43:44,772 --> 01:43:46,372
Speaker 25: It's actually been really good for me because they're all

2167
01:43:46,412 --> 01:43:49,532
Speaker 25: quite short, like the New Zealand. You're covering me all

2168
01:43:49,572 --> 01:43:51,093
Speaker 25: blacks and the black caps in the worries and they're

2169
01:43:51,093 --> 01:43:54,053
Speaker 25: all quite big units. But because the works where every

2170
01:43:54,093 --> 01:43:55,932
Speaker 25: gram comes against you, these guys are all tiny.

2171
01:43:57,053 --> 01:44:00,652
Speaker 2: So you've got incredible access to this weekend, as we've

2172
01:44:00,652 --> 01:44:03,812
Speaker 2: already said, So tell us about the most interesting things

2173
01:44:03,893 --> 01:44:06,452
Speaker 2: that you've seen and heard in the press conferences so far.

2174
01:44:08,333 --> 01:44:08,732
Speaker 16: I'll tell you what.

2175
01:44:08,893 --> 01:44:11,692
Speaker 25: So yesterday we had Breakfast out of Mercedes and George

2176
01:44:11,772 --> 01:44:15,732
Speaker 25: Russell at the Fantastic pressor where he just basically used

2177
01:44:15,732 --> 01:44:18,093
Speaker 25: every chance he could to slag off Maxi Stappen and

2178
01:44:18,293 --> 01:44:20,093
Speaker 25: didn't say max to Stappens name once.

2179
01:44:20,532 --> 01:44:21,333
Speaker 7: It was amazing.

2180
01:44:22,412 --> 01:44:24,572
Speaker 2: Anyone that's watched the latest series of Drives to five

2181
01:44:24,652 --> 01:44:28,093
Speaker 2: will be very used to George Russell talking because that's

2182
01:44:28,213 --> 01:44:29,253
Speaker 2: ninety percent of that show.

2183
01:44:31,293 --> 01:44:32,612
Speaker 25: He knows how good he is this year.

2184
01:44:32,652 --> 01:44:35,532
Speaker 2: He knows this is his yeah right and anything else,

2185
01:44:35,772 --> 01:44:38,173
Speaker 2: what's going on, what's going on behind the scenes.

2186
01:44:39,692 --> 01:44:42,293
Speaker 25: Terry Crews is here, so he put out quite a

2187
01:44:42,333 --> 01:44:45,533
Speaker 25: lot of the Australian journalist yesterday by they asked for antiunities.

2188
01:44:45,612 --> 01:44:48,132
Speaker 25: He was working and that's just not you just walk around.

2189
01:44:50,213 --> 01:44:52,213
Speaker 3: And what's the what's the food been? Like you mentioned

2190
01:44:52,253 --> 01:44:53,772
Speaker 3: the break He is a good spread. Are they they

2191
01:44:53,853 --> 01:44:54,933
Speaker 3: putting on a good show for you?

2192
01:44:56,253 --> 01:44:58,333
Speaker 25: Mercedes did so. I'm up in the media center where

2193
01:44:58,333 --> 01:45:00,572
Speaker 25: the catering is sort of you know, it's okay, We've

2194
01:45:00,572 --> 01:45:02,732
Speaker 25: got sandwiches, we've got water, but I mean it's nothing

2195
01:45:02,732 --> 01:45:04,772
Speaker 25: to go on about. There's no lobster revio that I

2196
01:45:04,853 --> 01:45:05,372
Speaker 25: was expecting.

2197
01:45:05,692 --> 01:45:10,692
Speaker 2: That'sappointing. Yeah, So after a bit of testing and now

2198
01:45:11,452 --> 01:45:14,532
Speaker 2: free practice one having gone down, who's your prediction to

2199
01:45:14,572 --> 01:45:17,333
Speaker 2: win the constructors Championship and who's going to be the

2200
01:45:17,372 --> 01:45:18,372
Speaker 2: new drivers champion?

2201
01:45:18,572 --> 01:45:21,893
Speaker 25: Alex Wow, Okay, I think if we're going to go

2202
01:45:22,133 --> 01:45:24,372
Speaker 25: immediately off that one session of the seeing, you say

2203
01:45:24,452 --> 01:45:27,133
Speaker 25: Ferrari going to win the constructors, but I'd say Mac

2204
01:45:27,253 --> 01:45:28,452
Speaker 25: the stampin might win the drivers.

2205
01:45:28,812 --> 01:45:31,013
Speaker 2: Okay, all right, Well we'll hold you to that.

2206
01:45:31,173 --> 01:45:31,933
Speaker 3: Brave predictions.

2207
01:45:31,973 --> 01:45:35,213
Speaker 2: We love it before a single race has been raced.

2208
01:45:35,492 --> 01:45:38,932
Speaker 2: But look very jealous. You're in a fantastic situation over there,

2209
01:45:39,013 --> 01:45:42,093
Speaker 2: so have a great time and looking forward to reading

2210
01:45:42,133 --> 01:45:43,092
Speaker 2: your stories in the Herald.

2211
01:45:44,812 --> 01:45:48,412
Speaker 3: Go well, that is Alex Powell, New Zealand's premiere Formula

2212
01:45:48,492 --> 01:45:53,412
Speaker 3: One reporter, live from Melbourne ahead of the Grand Prix

2213
01:45:53,732 --> 01:45:55,333
Speaker 3: on Sunday afternoon evening.

2214
01:45:55,412 --> 01:45:58,093
Speaker 2: Man, it's any good. I feel like an idiot for

2215
01:45:58,213 --> 01:46:01,213
Speaker 2: not being over there, but you've got to savor these

2216
01:46:02,093 --> 01:46:05,173
Speaker 2: races that take place at a reasonable New Zealand hour.

2217
01:46:05,333 --> 01:46:06,372
Speaker 3: Yeah, it's not any of them.

2218
01:46:06,412 --> 01:46:07,732
Speaker 2: It's a five pm on.

2219
01:46:08,853 --> 01:46:09,253
Speaker 3: How good.

2220
01:46:09,853 --> 01:46:11,852
Speaker 2: You know, if you're used to watching Formula One at

2221
01:46:11,933 --> 01:46:14,372
Speaker 2: three am in the morning, what an absolute pleasure to

2222
01:46:14,412 --> 01:46:16,612
Speaker 2: watch it at at dinner time.

2223
01:46:16,732 --> 01:46:17,093
Speaker 4: How good?

2224
01:46:17,133 --> 01:46:20,532
Speaker 3: It's a lovely joy. Right it is thirteen minutes to four.

2225
01:46:21,253 --> 01:46:23,253
Speaker 3: Stay tuned. We will be back very shortly.

2226
01:46:24,452 --> 01:46:27,812
Speaker 1: The big stories, the big issues, the big trends and

2227
01:46:28,173 --> 01:46:29,092
Speaker 1: everything in between.

2228
01:46:29,333 --> 01:46:32,293
Speaker 7: Matt Heath and Taylor Adams afternoons used talks.

2229
01:46:32,293 --> 01:46:32,572
Speaker 19: It'd be.

2230
01:46:34,053 --> 01:46:37,492
Speaker 3: Very good afternoon. Sure it is a ten to four

2231
01:46:37,612 --> 01:46:39,892
Speaker 3: before the end of the show. You've got to say

2232
01:46:40,053 --> 01:46:43,412
Speaker 3: the wee candy head sport wise huge, so much to

2233
01:46:43,452 --> 01:46:46,372
Speaker 3: look forward to, obviously. Chatted to New Zealand's premiere Formula

2234
01:46:46,412 --> 01:46:49,492
Speaker 3: One report Alex Powell about the first Grand Prix of

2235
01:46:49,652 --> 01:46:53,293
Speaker 3: the season in Melbourne. I know you're desperately desperately excited

2236
01:46:53,333 --> 01:46:53,612
Speaker 3: about that.

2237
01:46:53,812 --> 01:46:55,412
Speaker 2: Well, that's going to be quite a day because you're

2238
01:46:55,412 --> 01:46:58,572
Speaker 2: at Sunday. You know, watch the if one, see how

2239
01:46:58,652 --> 01:47:01,693
Speaker 2: lim goes. It's very exciting see how these new regulations

2240
01:47:01,772 --> 01:47:05,333
Speaker 2: play out, how the cars drive, no idea. I mean

2241
01:47:05,372 --> 01:47:08,933
Speaker 2: you can watch these the practices, you can watch qualifying,

2242
01:47:09,053 --> 01:47:13,213
Speaker 2: but seeing these new cars on the track racing east

2243
01:47:13,213 --> 01:47:16,812
Speaker 2: together and how passing goes. You know, part of the

2244
01:47:16,853 --> 01:47:19,213
Speaker 2: reasons why they've changed these rigs is to make the

2245
01:47:19,452 --> 01:47:23,253
Speaker 2: cars smaller. Arguably they should be better at passing. There

2246
01:47:23,293 --> 01:47:25,253
Speaker 2: should be more passing options going forward. You've got that.

2247
01:47:25,612 --> 01:47:29,452
Speaker 2: Then of course that night, going over to the next day,

2248
01:47:29,452 --> 01:47:31,333
Speaker 2: you've got the Black Caps, haven't you. Yes, In the

2249
01:47:31,772 --> 01:47:37,093
Speaker 2: final of the ICC T twenty World Cup, they absolutely

2250
01:47:37,293 --> 01:47:40,772
Speaker 2: smoke South Africa in the semi final. They go through

2251
01:47:40,853 --> 01:47:43,813
Speaker 2: and they face India, and India are a massive powerhouse

2252
01:47:43,893 --> 01:47:48,092
Speaker 2: and cricket obviously, you know, the whole world of cricket

2253
01:47:48,253 --> 01:47:50,652
Speaker 2: revolves around what India wants to do because of their

2254
01:47:50,812 --> 01:47:53,572
Speaker 2: huge population base, and that's where all the money spins

2255
01:47:53,612 --> 01:47:58,693
Speaker 2: out of right, but little Old New Zealand like Asterisks

2256
01:47:58,772 --> 01:48:02,173
Speaker 2: and Obelix, like the village in Asterix, we just keep

2257
01:48:02,253 --> 01:48:05,412
Speaker 2: producing these killer players that no one can quite understand

2258
01:48:05,612 --> 01:48:08,252
Speaker 2: how we do it. I've been watching a bunch of podcasts.

2259
01:48:08,412 --> 01:48:10,133
Speaker 2: The Great Cricketer was talking about it the other day.

2260
01:48:10,173 --> 01:48:12,492
Speaker 2: Where does New Zealand get all its incredible players from?

2261
01:48:12,853 --> 01:48:15,053
Speaker 2: And how are we always there or there about in

2262
01:48:15,093 --> 01:48:19,613
Speaker 2: these big tournaments? And we are India's bogie team. Absolutely,

2263
01:48:20,013 --> 01:48:22,293
Speaker 2: we are their bogey team. So India does not want

2264
01:48:22,333 --> 01:48:24,732
Speaker 2: to face us in the final, and they are facing

2265
01:48:24,812 --> 01:48:26,893
Speaker 2: us in the final, and we've broken their hearts a

2266
01:48:27,452 --> 01:48:29,692
Speaker 2: number of times in these key tournaments, so we have

2267
01:48:30,532 --> 01:48:34,173
Speaker 2: exciting So for them they will be worried about facing us.

2268
01:48:34,333 --> 01:48:38,053
Speaker 2: And for us, we're not facing Australia in a big

2269
01:48:38,213 --> 01:48:41,732
Speaker 2: important game at the biggest moments in cricket. For us

2270
01:48:41,772 --> 01:48:44,372
Speaker 2: off when we come up against Australia and Australia has

2271
01:48:44,412 --> 01:48:46,293
Speaker 2: no respect for us. They treat us like a little brother.

2272
01:48:46,333 --> 01:48:49,172
Speaker 2: They slap us around, and I feel like New Zealand

2273
01:48:49,452 --> 01:48:51,852
Speaker 2: just gets into our shell a little bit against Australia.

2274
01:48:51,893 --> 01:48:53,612
Speaker 2: We just have been beaten by them so often that

2275
01:48:53,692 --> 01:48:56,452
Speaker 2: we struggle to step up against them. So I think

2276
01:48:56,532 --> 01:48:59,852
Speaker 2: going up against India, bearing in mind they'll have all

2277
01:48:59,973 --> 01:49:02,333
Speaker 2: kinds of demons floating around to their head playing us

2278
01:49:03,452 --> 01:49:05,492
Speaker 2: and the fact it's not Australia in the final. I reckon,

2279
01:49:05,572 --> 01:49:08,692
Speaker 2: this is our chance to get one of the big

2280
01:49:09,053 --> 01:49:11,812
Speaker 2: ICC trophies. Come on, boy, we've won the World Test

2281
01:49:11,893 --> 01:49:14,173
Speaker 2: Championship in the passing that, but this would be so

2282
01:49:14,612 --> 01:49:16,852
Speaker 2: freaking good. So if you're going to get up, get

2283
01:49:16,933 --> 01:49:19,412
Speaker 2: up to watch any sport, get up and watch that.

2284
01:49:19,532 --> 01:49:21,333
Speaker 3: I've just had a look at the odds on tab

2285
01:49:21,893 --> 01:49:22,572
Speaker 3: Do you want to hear them?

2286
01:49:22,732 --> 01:49:22,932
Speaker 5: Yep?

2287
01:49:23,652 --> 01:49:27,812
Speaker 3: New Zealand paying two dollars ninety, India paying a dollar forty.

2288
01:49:28,933 --> 01:49:33,013
Speaker 3: So India the favorites. But that's tight, and we know

2289
01:49:33,133 --> 01:49:35,253
Speaker 3: the boys can do it and you know ahead of us.

2290
01:49:35,452 --> 01:49:38,093
Speaker 2: The thing about T twenty cricket is there's you know,

2291
01:49:38,133 --> 01:49:39,973
Speaker 2: there's a punch of chants. You know, you get in

2292
01:49:40,093 --> 01:49:43,532
Speaker 2: England innings like Finellen had in the semi final one

2293
01:49:43,612 --> 01:49:46,973
Speaker 2: hundred off thirty three balls, just those standout innings can

2294
01:49:47,133 --> 01:49:50,973
Speaker 2: just flip a T twenty. Yep, that's that's you know,

2295
01:49:51,333 --> 01:49:53,213
Speaker 2: that's one of the strengths but one of the huge

2296
01:49:53,253 --> 01:49:57,133
Speaker 2: weaknesses of this format of the game. So bring it up.

2297
01:49:57,853 --> 01:50:01,013
Speaker 3: Exciting and that's not to mention the Warriors yep up

2298
01:50:01,013 --> 01:50:04,893
Speaker 3: against the Roosters tonight, that's at eight o'clock and the

2299
01:50:04,973 --> 01:50:08,213
Speaker 3: Super Rugby is still bubbling behind the scenes. You've got

2300
01:50:08,372 --> 01:50:11,052
Speaker 3: Cannarby versus the Blues. That's going to be a big game.

2301
01:50:11,452 --> 01:50:13,772
Speaker 3: So boy, oh boy, we are in for a massive

2302
01:50:13,893 --> 01:50:16,652
Speaker 3: weekend of sport and long Matt continue. I mean, this

2303
01:50:16,812 --> 01:50:18,612
Speaker 3: is us for the next six months. Right, We're going

2304
01:50:18,692 --> 01:50:21,532
Speaker 3: to be absolutely punished, that's not the right word. We're

2305
01:50:21,532 --> 01:50:24,412
Speaker 3: going to be offered the gift of so much sport

2306
01:50:24,492 --> 01:50:25,412
Speaker 3: over the next six months.

2307
01:50:25,452 --> 01:50:27,852
Speaker 2: Well if you're a baseball but baseball fan like me,

2308
01:50:28,412 --> 01:50:30,412
Speaker 2: that's really going to fill in the gaps.

2309
01:50:30,492 --> 01:50:34,372
Speaker 3: Yeah, yeah, very good. Right, that is almost us for today.

2310
01:50:34,372 --> 01:50:35,852
Speaker 3: I've got to say thank you very much to everyone

2311
01:50:35,893 --> 01:50:38,973
Speaker 3: who called and text. Now every week we get so

2312
01:50:39,213 --> 01:50:41,933
Speaker 3: many great kiwis ringing through to the show that we

2313
01:50:42,053 --> 01:50:44,932
Speaker 3: pick a caller of the week. And this week we're

2314
01:50:44,973 --> 01:50:47,852
Speaker 3: having a great chat about booms because you were pretty

2315
01:50:48,772 --> 01:50:50,652
Speaker 3: you're pretty fizzed up on your type booms And we

2316
01:50:50,732 --> 01:50:56,293
Speaker 3: had a call from Hailey and Haley mentioned about the

2317
01:50:56,333 --> 01:50:58,812
Speaker 3: boom spoting she was doing and she reckoned she found

2318
01:50:59,013 --> 01:51:00,652
Speaker 3: the best boom in New Zealand.

2319
01:51:01,013 --> 01:51:02,253
Speaker 26: I've got envy.

2320
01:51:02,572 --> 01:51:03,572
Speaker 11: I don't actually have a firm.

2321
01:51:03,612 --> 01:51:06,093
Speaker 26: I love the stillwitter and we don't have germs where

2322
01:51:06,133 --> 01:51:06,732
Speaker 26: my house finds.

2323
01:51:06,732 --> 01:51:08,253
Speaker 16: We've discovered this wild boss.

2324
01:51:08,692 --> 01:51:12,492
Speaker 26: But there's toe burms that are incredible, this one and

2325
01:51:12,572 --> 01:51:16,372
Speaker 26: brown Spee which is out of the gate like paradise

2326
01:51:16,492 --> 01:51:19,812
Speaker 26: and it's like got fruit trees. She's like created this

2327
01:51:20,213 --> 01:51:24,492
Speaker 26: incredible garden. It is so amazing pass and just like

2328
01:51:24,732 --> 01:51:26,213
Speaker 26: marvel at how wehead it is.

2329
01:51:26,412 --> 01:51:29,133
Speaker 2: If people use their booms as orchards, then you could

2330
01:51:29,173 --> 01:51:32,372
Speaker 2: have school kids skipping home from school and grabbing an

2331
01:51:32,372 --> 01:51:33,692
Speaker 2: apple and eating it as they go.

2332
01:51:33,973 --> 01:51:38,053
Speaker 3: How lovely, lovely? I mean, why how good?

2333
01:51:38,253 --> 01:51:38,452
Speaker 12: Yeah?

2334
01:51:38,532 --> 01:51:40,972
Speaker 3: Love that boom chat. It's all about the tight burms.

2335
01:51:41,333 --> 01:51:44,133
Speaker 2: All right, thank you so much for listening. What a

2336
01:51:44,173 --> 01:51:46,532
Speaker 2: fantastic week it's been. Thank you to all those who

2337
01:51:46,612 --> 01:51:49,253
Speaker 2: joined the Conversation on our eight hundred and eighty ten eighty.

2338
01:51:49,372 --> 01:51:54,013
Speaker 2: We'll be back live Monday morning from twelve pm. The

2339
01:51:54,093 --> 01:51:58,173
Speaker 2: Great Powerful Heather Duplessy Allen is up next, and she'll

2340
01:51:58,213 --> 01:52:03,012
Speaker 2: be talking about whether Luxe and can survive these pole numbers.

2341
01:52:03,133 --> 01:52:07,293
Speaker 2: But right now, Tyler, my good friend, why am I

2342
01:52:07,372 --> 01:52:09,133
Speaker 2: playing this particular song.

2343
01:52:09,213 --> 01:52:11,612
Speaker 3: This is my dad's favorite song of all time, Pink

2344
01:52:11,732 --> 01:52:15,333
Speaker 3: Floyd's Money, because we had a great chat about counterfeit

2345
01:52:15,452 --> 01:52:17,213
Speaker 3: cash that is doing the rounds of New Zealand.

2346
01:52:17,253 --> 01:52:22,173
Speaker 2: Surprising apparently it's absolutely all over the shop. All right,

2347
01:52:22,253 --> 01:52:26,692
Speaker 2: then go Liam, go the black Caps, go the Warriors.

2348
01:52:27,333 --> 01:52:29,532
Speaker 2: See you Monday till then give a taste of Kiwi

2349
01:52:29,572 --> 01:52:29,852
Speaker 2: from us.

2350
01:52:29,853 --> 01:52:45,213
Speaker 4: All right, the love you, You're okay, Money.

2351
01:52:50,812 --> 01:53:15,532
Speaker 9: Grab Cady Funny, get it back.

2352
01:53:18,412 --> 01:53:21,412
Speaker 4: Off, Chad hans Off, my.

2353
01:53:30,372 --> 01:53:31,253
Speaker 18: Matt Tyler

2354
01:53:33,772 --> 01:53:36,333
Speaker 1: For more from us talks at b Listen live on

2355
01:53:36,492 --> 01:53:39,412
Speaker 1: air or online, and keep our shows with you wherever

2356
01:53:39,492 --> 01:53:42,053
Speaker 1: you go with our podcasts on iHeartRadio