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Speaker 1: I'll get a team mcraig, Anthony Harper, Patrick, James Bonillo.

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Speaker 1: The name of the show is the You Project. Every

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Speaker 1: second week, young Patrick and I just saddle up, usually

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Speaker 1: young Tiff and is Tiffin? Who's Tiffin? Sounds like some

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Speaker 1: kind of stage show. Usually Tiff is here, She's not today,

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Speaker 1: So it's just us two alpha males just fucking holding

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Speaker 1: down the fort. But he reckons more alpha male.

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Speaker 2: You or me, ah, neither of us. Fritz, that's true.

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Speaker 2: I think it said he's nuts cut off? Can I

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Speaker 2: just ask a question? How can I never do the opener?

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Speaker 2: I know it's your show, and.

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Speaker 1: Let's start again. Let's start again? Okay, yep, hey groovers,

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Speaker 1: Welcome to the You Project. I'm joined by one of

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Speaker 1: the people I most respect in all the world. In fact,

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Speaker 1: I am humbled in his presence and in a lot

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Speaker 1: of ways I wish I was him. Not only is

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Speaker 1: he smarter, better looking, and more talented, he shares the

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Speaker 1: same birthday with the Dali Lama, which goes a long

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Speaker 1: way to explaining who he is. So, without further ado,

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Speaker 1: welcome back to the You Project. Patrick Bonello.

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Speaker 2: Hey ha, good? Was that fuck?

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Speaker 1: And? Hell? Now I know what you did. I'm quite terrified.

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Speaker 1: Tell people I did not know that was coming. Everybody

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Speaker 1: that wasn't me saying that? Wow? When did you do that?

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Speaker 1: And how explain to people what that was?

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Speaker 2: So I subscribed to a service called eleven Labs. It's

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Speaker 2: an AI voice generator. I sampled just one minute of

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Speaker 2: your voice from one of your podcasts. I uploaded it

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Speaker 2: and then I profiled you. So I put middle aged

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Speaker 2: Australian male, just a very brief descriptions, you know, deep voice,

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Speaker 2: that sort of stuff, and it generated that so effectively.

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Speaker 2: I could you could give me a sentence now and

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Speaker 2: I could get you to say it back in AI.

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Speaker 2: Something simple.

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Speaker 1: That's all right. I've got a big crush on Patrick,

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Speaker 1: right my type. I don't know that this is very

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Speaker 1: good live, but anyway, here we go, Here we go. Yep,

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Speaker 1: I've got a big crush on Patrick.

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Speaker 2: Oh no, not as good? That is it?

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Speaker 1: It's not bad?

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Speaker 2: Drop it back, let me try again.

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Speaker 1: I've got a big crush on Patrick. It's kind of

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Speaker 1: it's good until it gets to your name.

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Speaker 2: Yeah. So what you can do is you can keep

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Speaker 2: uploading additional audio and then as it profiles your voice,

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Speaker 2: then it'll be able to get it a lot better. Like,

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Speaker 2: for example, I don't think you remember saying this earlier,

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Speaker 2: but I'm sure you said this earlier. Craig.

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Speaker 1: It just occurred to me that if all of our

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Speaker 1: listeners sent Patrick five dollars each, I will match that

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Speaker 1: with whatever we come up with. Fuck you, fuck you

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Speaker 1: and your AI skills.

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Speaker 2: So I might throw a few of these just randomly

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Speaker 2: through the show, just when it you know, if a pause,

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Speaker 2: I'll just throw something in.

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Speaker 1: That is very funny and a little bit terrifying. I've

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Speaker 1: never thought, I think it's I've seen that done to

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Speaker 1: other people. I did not expect anyone to be doing

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Speaker 1: that to me anytime soon. But thanks for introducing the

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Speaker 1: world to that. Thanks for giving people that idea. Wow,

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Speaker 1: how long did that take? I mean you're very tech savvy,

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Speaker 1: but how long did that take for you to figure that? Like,

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Speaker 1: you could literally do a whole podcast of me when

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Speaker 1: I'm not even present.

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Speaker 2: Well, you could do both of us and then just

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Speaker 2: create it and put it together. It would take a

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Speaker 2: little bit of work, but they are getting so much better.

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Speaker 2: And an answer to your question, probably having never used

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Speaker 2: the software, never done anything with it before, I would say,

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Speaker 2: maybe three or four minutes. Once I found the clip

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Speaker 2: and uploaded it, it profiled it with a short amount

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Speaker 2: of time. I took the phrase, typed it up for

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Speaker 2: the intro to the show, and then I played it

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Speaker 2: through about four times, and you can alter it, and

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Speaker 2: then I've chose the one I thought sounded the best.

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Speaker 1: Wow, so you could get some famous speech and get

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Speaker 1: me to say that famous speech. So could you just

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Speaker 1: upload the upload the dialogue and then is that how

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Speaker 1: it works?

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Speaker 2: Yeah? Yeah, I can type anything, so I can either

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Speaker 2: type it in or I can just copy and paste,

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Speaker 2: hit the generate speech button, and off it goes.

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Speaker 1: Now some famous there's some famous Star Wars quote, like

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Speaker 1: in a Galaxy Far far whatever. This is probably not

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Speaker 1: something we should do in the middle of recording a podcast, everyone,

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Speaker 1: but fuck it. Stand by, Let's see what happens. Is

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Speaker 1: there some wrong in this one? The force is strong

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Speaker 1: in this one.

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Speaker 2: There you go, Well, it kind of sounds funny you're

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Speaker 2: saying that because I know you.

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Speaker 1: It doesn't give it any inflection, does it? Like, there's

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Speaker 1: no emotion. It's very it's very flat. The force is

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Speaker 1: strong in this one. That's a little bit better. Yeah,

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Speaker 1: that's what did you do? Then?

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Speaker 2: Like what? Yep, there's more variable, so you can either

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Speaker 2: make it more stable or more variable. So there's there's

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Speaker 2: three controls. There's similarity, stability, and then style exaggeration yeah yeah,

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Speaker 2: wow wow, and then you can use other languages as well.

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Speaker 1: Force is strong in this one.

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Speaker 2: It doesn't sound too bad, does it.

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Speaker 1: That's not too bad. It's not too bad. Interesting, you

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Speaker 1: are interesting, you are all right? Well, I'm sure we'll

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Speaker 1: jump in and out of fake me through the show.

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Speaker 1: I can't wait to see how you're going to fucking,

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Speaker 1: you know, destroy me as we move on. What are

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Speaker 1: we talking about in today's episode? If Patrick does typ

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Speaker 1: one of my favorite porn films.

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Speaker 2: My next big gadget I reckon and I've been looking

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Speaker 2: at these quite closely. Ironically, they're glasses, so I guess

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Speaker 2: you would be. But smart glasses. Now, there are two

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Speaker 2: different types of smart glasses when we think about them.

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Speaker 2: One is where we talked and we've talked about the

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Speaker 2: augmented reality ones where it's super composes a picture. They're

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Speaker 2: not quite there yet, but aahweh has released a new

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Speaker 2: version of what they call their eyewear two and what

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Speaker 2: I like about it is you can wear the glasses

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Speaker 2: and you can use them just every day. They last

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Speaker 2: about eleven hours on charge, which is pretty a long time.

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Speaker 2: You don't need to have earphones plugged in, so you

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Speaker 2: can use them as your virtual assistance, so you could,

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Speaker 2: you know, call somebody, use them as a hands free

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Speaker 2: device you But what I really like about the Huawei

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Speaker 2: Ones is they've come up with a posture kind of assistance.

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Speaker 2: And what it does is will actually look at your

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Speaker 2: posture or work out whether you're slouching and then remind you.

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Speaker 2: So it will monitor so it actually is able to

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Speaker 2: check on your posture. And it's got a lot of

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Speaker 2: features built into it, so you know you they're lightweight,

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Speaker 2: they're comfortable, and you can tap it to play music,

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Speaker 2: you can make calls.

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Speaker 1: And you missed out a chunk of info, like you

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Speaker 1: just said glasses, So it's not glasses. Yeah, there's glasses,

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Speaker 1: but is it a phone? What is it?

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Speaker 2: It pairs to your phone, So if you imagine the

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Speaker 2: glasses you've got on now, you just touch the arm

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Speaker 2: of the glasses to activate it, and you could say,

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Speaker 2: be walking and it would be giving you directions turn

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Speaker 2: left at the next street, that sort of stuff. So

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Speaker 2: anything that your phone can do, you can be able

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Speaker 2: to connect your glasses to as your smart assistant. So

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Speaker 2: take phone calls, make phone calls, all that sort of stuff,

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Speaker 2: and just listen to me music. One of the things

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Speaker 2: I like about this is you know, quite often you

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Speaker 2: see people with earbuds and you wonder how dangerous that

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Speaker 2: is because they can't hit traffic and it's easy to

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Speaker 2: kind of be lost in your own world. The good

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Speaker 2: thing is that this because they're not plugged into your

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Speaker 2: ear and they conduct through the top of your ear.

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Speaker 2: It means that if the doorbell goes, or if you're

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Speaker 2: walking down the street, you can still hear things around you.

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Speaker 2: So I kind of like that feature as well.

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Speaker 1: Isn't Huawei the brand that got booted out of Australia

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Speaker 1: and the US their phones?

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Speaker 2: Yeah, it was there, Well, not the phones. You can

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Speaker 2: still buy Wa Hwei phones but you can't. It was

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Speaker 2: more the high end stuff they were using for telecommunications.

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Speaker 2: So they had a big contract in Australia to provide

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Speaker 2: telecommunication technology and both Australia and in China. The big

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Speaker 2: concern is not so much well, I mean, there was

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Speaker 2: some controversy around Huawei, but it was more that you

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Speaker 2: can't guarantee in China that a large company isn't getting

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Speaker 2: nudged and looked at by Beijing. That's the problem with

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Speaker 2: the communist government is and that's the big concern. Soanies

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Speaker 2: like Dji, the drone manufacturer, they've pulled out all drones

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Speaker 2: from the US high end drone markets, so where they're

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Speaker 2: using them in say law enforcement or fires and things

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Speaker 2: like that, and they're doing the same in Australia as well,

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Speaker 2: So they're saying they don't want the potential for China

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Speaker 2: to be monitoring what these drones are doing. Effectively, it's surveillance.

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Speaker 2: There's no suggestion and Dji I kind of feel for

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Speaker 2: those companies because if they're doing the right thing and

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Speaker 2: they're saying, well, we're not actively monitoring you, but there's

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Speaker 2: no way to really believe it. And the suggestion is

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Speaker 2: that well, if Beijing walks up to the front door,

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Speaker 2: and I mean that in general terms, someone representing the

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Speaker 2: government knocks on the door and sees, we want all

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Speaker 2: your records, well, you know, do they have any ability

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Speaker 2: to be able to say no? And that's the question, right, Yeah.

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Speaker 1: I just googled it because I didn't believe you, But

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Speaker 1: you are right. Australia has been Huawei Technology Co. From

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Speaker 1: supplying equipment for Australian five G mobile. Why would I

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Speaker 1: ever fucking doubt you. That's why have you Australian five

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Speaker 1: G mobile network, citing national security risks. But they have

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Speaker 1: not banned the phones.

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Speaker 2: Correct, yep, okay, okay, yeah.

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Speaker 1: Wow, Well there you go. But apparently their phones are great.

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Speaker 1: They're high end phones are meant to be great.

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Speaker 2: They're really good.

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Speaker 1: Yeah.

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Speaker 2: I've got a friend that was just we were comparing photos.

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Speaker 2: I was going to chat about this on the show

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Speaker 2: at some point. I've got some gorgeous photos and I

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Speaker 2: think I sent you a couple of the aurora, the

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Speaker 2: southern Aurora that we had last weekend. I was just

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Speaker 2: lucky to be at the right place at the right

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Speaker 2: time and got some gorgeous photographs and just that beautiful

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Speaker 2: red and green glow. Fritzie and I went out there.

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Speaker 2: He jumped in the car with me. We drove out

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Speaker 2: about I don't know five minutes away, were in total darkness,

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Speaker 2: and it was gorgeous. It was great. Got some really

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Speaker 2: nice photos. But for a lot of people who may

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Speaker 2: have been out there and wondered why they weren't seeing

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Speaker 2: in real life what our phones were actually showing when

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Speaker 2: we took photos. So the photos I sen chew and

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Speaker 2: for all of us have been on social media and

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Speaker 2: had a look on all those photos. You may say, well,

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Speaker 2: they didn't look anything like that, But when I took

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Speaker 2: the photo, it looked amazing, and that was the case

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Speaker 2: for me as well, and it was interesting. I did

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Speaker 2: a bit of research and there are a number of

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Speaker 2: reasons why, and one of them, of course, is that

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Speaker 2: they take an extended exposure. In my case, my phone

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Speaker 2: took a six second exposure to get the image. But

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Speaker 2: the other thing is that the cones inside our eye,

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Speaker 2: the light receptors in our eye, when it gets really dark,

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Speaker 2: they effectively switch over from one sensor to another sensor,

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Speaker 2: and one of them is about to get as much

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Speaker 2: information and to pull in as much light, so it

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Speaker 2: kind of drops the use of color and goes to

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Speaker 2: almost black and white. So if you're stumbling around at

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Speaker 2: night and you've only got a faint glow in your room,

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Speaker 2: more than likely you will you will see in much

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Speaker 2: more muted tones. So if you're standing out looking out

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Speaker 2: at what we saw as the aurora. Effectively, what you're

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Speaker 2: looking at is something that's much more muted because you're

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Speaker 2: just not getting enough light to the receptors in the

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Speaker 2: back of your eye as well. So that's the reason

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Speaker 2: why most people's phones showed some really awesome pictures, but

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Speaker 2: you weren't seeing the aurora look anywhere near in the

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Speaker 2: quality that your phone was taking pictures of.

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Speaker 1: I'm looking at that picture that you sent me right now.

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Speaker 1: I'm wondering if I might I don't know if I'll

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Speaker 1: be able to use that in the promo for the show,

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Speaker 1: But it does look it looks it literally looks like

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Speaker 1: something made up. It looks like something sci fi because

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Speaker 1: there's there's just this blend that starts at the top

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Speaker 1: being almost black through to this burgundy indigo color, goes

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Speaker 1: into this light green dark green, and then but down

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Speaker 1: through the middle of that, it's almost like there's shards

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Speaker 1: of light and it looks it looks like a computer

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Speaker 1: generated thing. Doesn't look like a photo at all. I mean,

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Speaker 1: I'm feeling dumb at the moment. Can you explain that

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Speaker 1: to me like I was a three year old? I'm sorry,

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Speaker 1: could you stop playing fake me. People are not going

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Speaker 1: to go what's real? No, what's real and fake me?

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Speaker 2: Yeah, that's although what you've said it seems kind of

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Speaker 2: on par don't you reckon?

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Speaker 1: Well, I know what it is. Yeah, I am dumb though,

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Speaker 1: but thanks thanks for making me. Of course you were right.

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Speaker 1: I'm always wrong and you are one hundred percent right

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Speaker 1: all the time. Huh oh god. How many of those

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Speaker 1: do you have? Ah?

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Speaker 2: There a couple more?

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Speaker 1: All right? Now, before we go on with your little

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Speaker 1: kind of little that isn't it? Don't you hate it

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Speaker 1: when people say your little thing? Last week you and I.

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Speaker 2: Had no one's ever said that, Tommy greg Yeah, you're

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Speaker 2: right right, John Holmes.

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Speaker 1: Everyone's going to be googling that now. A couple of

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Speaker 1: weeks ago, last time we were together, we had a bet.

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Speaker 1: I can't even remember what the bet was about, but

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Speaker 1: that was something to do with something that Tiff would know.

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Speaker 2: Yes, it was a picture of Richard Nixon. I sent

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Speaker 2: you a picture of Richard Nixon. You forwarded that picture

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Speaker 2: to Tiff and I said, of course Tiff will know

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Speaker 2: who that is, and you said, not a chance. It

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Speaker 2: started to ten dollar bet and then you doubled it

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Speaker 2: to twenty dollars and I burned and crashed and burned.

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Speaker 1: Yeah, you did crash and burn. And then this week

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Speaker 1: I went outside and just under my gate was an

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Speaker 1: Australia Post parcel and it was like weird. It was

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Speaker 1: shaped like a thick, fat long sausage roll and I

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Speaker 1: picked it up and it felt like a very thick

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Speaker 1: fat sausage roll and it was kind.

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Speaker 2: Of felt like a John Holmes.

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Speaker 1: Yeah, it was limp and heavy, speaking of John Holmes.

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Speaker 1: And I opened it and it said from Bland, from

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Speaker 1: the Tooth Fairy. And I'd forgotten all about our bet.

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Speaker 1: In fact, I didn't know until today when Melissa enlightened

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Speaker 1: me because she'd listened to the show. And I said,

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Speaker 1: Patrick sent me like a fucking million five cent pieces,

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Speaker 1: and I got, I got this this, Well, let's see,

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Speaker 1: you sent me apparently twenty dollars worth, and there's twenty

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Speaker 1: and that so twenty times twenty, so four hundred and

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Speaker 1: five cent pieces.

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Speaker 2: I guess was it actually healers?

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Speaker 1: Was it actually twenty bucks?

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Speaker 2: Because it was twenty bucks and it cost me. What

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Speaker 2: you'll really enjoy is it cost me eleven bucks to

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Speaker 2: send it to you.

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Speaker 1: That's what I said to her. It must have cost

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Speaker 1: nearly that much to send it because it weighed a lot.

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Speaker 2: It did one point.

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Speaker 1: And also it's been brought to my attention by you

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Speaker 1: that you're actually breaking the law and doing that.

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Speaker 2: So I went to the bank, called the bank first,

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Speaker 2: our local little community branch, and said if you got

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Speaker 2: twenty bucks in five cent pieces, and they kind of

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Speaker 2: umed an out for a little bit and said, yeah, sure,

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Speaker 2: come in and grab them. So I went in there

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Speaker 2: and they gave them to me in all these cute

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Speaker 2: little neat bags, and I've got my post pack and

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Speaker 2: I'm just opening up the bags, tipping them in, open

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Speaker 2: up the bag, tipping in. And then I went to

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Speaker 2: the post office and the girls at the post office

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Speaker 2: were pissing themselves laughing when I told them what it

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Speaker 2: was for. And then after i'd sent it to you,

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Speaker 2: of course, I started telling lots of people what i'd done,

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Speaker 2: because you know, I'm trying to get a bit of

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Speaker 2: a pat on the back for myself. And someone said

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Speaker 2: to me, you know that's illegal. I said, what because

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Speaker 2: the post office accepted it, And so I did a

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Speaker 2: good search and yeah, it's illegal to send any sort

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Speaker 2: of cash via mail delivery service.

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Speaker 1: Who would have thought, I wonder why no idea? I

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Speaker 1: guess because they don't want that to be a common

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Speaker 1: practice because if if the bad guys think that there's

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Speaker 1: money floating around in the mail, then there are Yeah,

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Speaker 1: it kind of makes sense, but I don't see why

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Speaker 1: you should get penalized if you're if you're the one

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Speaker 1: pinching money, but if you're the one putting money, and

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Speaker 1: I don't think you should I get penalized. Where we

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Speaker 1: going next? Obi wan?

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Speaker 2: Can I be well? Look, I guess I was really

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Speaker 2: interested in a couple of health related stories talking about

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Speaker 2: AI because Google has got its AI interface called Gemini,

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Speaker 2: and what they're saying is it's going to really help

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Speaker 2: blind people, so people who are vision impaired. And there's

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Speaker 2: two little things that I thought was really cool. It's

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Speaker 2: called talkback and it's using generative AI, and what it

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Speaker 2: means is that it will be able to run offline. Okay,

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Speaker 2: So one of the biggest issues with AI at the

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Speaker 2: moment is that it's a giant service somewhere, and there's

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Speaker 2: a lot of controversy over how much you know that

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Speaker 2: data generating costs in terms of power and is there

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Speaker 2: a real impact. But this language model is actually designed

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Speaker 2: for people with low vision, and it creates descriptions of

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Speaker 2: objects for blind users, but it runs totally off the

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Speaker 2: cloud and on the device itself, so they would be

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Speaker 2: able to refer back to articles of clothing. They can say, well,

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Speaker 2: this is a close up of a T shirt and

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Speaker 2: so it.

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Speaker 1: Will but people are blind, what do you mean They

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Speaker 1: can say this is a close up, Well, because you

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Speaker 1: would use so it's describing.

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Speaker 2: Yeah, so it describes, it describes it's seen, so right, yeah, yeah,

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Speaker 2: And it can get really really quite specific. It's not

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Speaker 2: just this is address, but this is a floral dress

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Speaker 2: and it's green and red and it has fringes and

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Speaker 2: that sort of stuff. And they're doing the training of

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Speaker 2: the AI with quite a fair bit of my neuche.

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Speaker 2: So if you're going shopping and your vision impaired, this

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Speaker 2: could be really really useful, even just matching clothing colors

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Speaker 2: and that sort of thing. And I guess the other

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Speaker 2: thing I love about it is it makes people a

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Speaker 2: lot more independent, so there are less inhibitions because it

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Speaker 2: is harder for people to shop, and we take it

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Speaker 2: for granted. I mean, you work so hard to look

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Speaker 2: so uncoordinated, says he who's wearing a rainbow colored and

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Speaker 2: a black tea.

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Speaker 1: Hey, fuck you, Brad Pitt, just fuck now, talk about

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Speaker 1: the clock calling the kettle black. Mister Cardigan wearing fucking

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Speaker 1: beret wearer.

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Speaker 2: I'm not wearing a beret or a cardigan today.

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Speaker 1: Yeah, that's just today. You're wearing an ABC logo on

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Speaker 1: a T shirt.

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Speaker 2: That's because I started doing Actually no, it's a Pride

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Speaker 2: logo because today's idahol a day. But also today I

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Speaker 2: started doing a regular segment on ABC Regional Radio.

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Speaker 1: Can I tell you that I have a fan I

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Speaker 1: won't say his name, but I have a fan on

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Speaker 1: my IG who's very very keen to catch up with me,

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Speaker 1: sending me nice messages.

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Speaker 2: That's nice.

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Speaker 1: He's a bit of a sweetheart too, he's nice.

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Speaker 2: I'm pretty sure I know no friendship. I'm thinking friendship

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Speaker 2: that you doesn't have to go. I mean, he knows

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Speaker 2: it doesn't.

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Speaker 1: Is requesting a bit more than friendship, But that's all right.

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Speaker 2: Personally, training.

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Speaker 1: There's something like that. That's yeah, yeah, that's I might

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Speaker 1: pour it into you. Thanks for that, friends though, and

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Speaker 1: go on.

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Speaker 2: No, so I was just saying how exciting this is

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Speaker 2: and using things like AI offline to be able to

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Speaker 2: assist people who are vision impaired. And the other thing

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Speaker 2: that relates to this, there's a Seattle startup at the

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Speaker 2: moment and they've got this really really really cool gadget

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Speaker 2: called one court. So if you imagine you're sitting down

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Speaker 2: at a sporting game, or you're watching a sporting game tennis,

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Speaker 2: you know, grid iron or whatever it happens to be,

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Speaker 2: and you lay your hands on the screen if your

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Speaker 2: vision impaired, and it gives you haptic feedback of what's

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Speaker 2: actually happening on the court. So if you're playing tennis,

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Speaker 2: I could you could feel it and the vibrations match

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Speaker 2: what's being played out on the court.

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Speaker 1: Oh wow wow yeah yeah, actual you're watching good. What

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00:21:36,200 --> 00:21:38,359
Speaker 1: if you're watching a porno? Does it do the same?

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Speaker 2: You had to go there, didn't you? No?

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Speaker 1: I didn't. I choose to. You know, by the way,

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00:21:43,440 --> 00:21:46,439
Speaker 1: everyone Patrick, that was he? That was fake me? That

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00:21:46,520 --> 00:21:47,400
Speaker 1: wasn't real MEE.

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00:21:50,240 --> 00:21:52,360
Speaker 2: Say that? Yeah that was Patrick.

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00:21:52,960 --> 00:21:55,560
Speaker 1: So now I can get you in trouble just quickly

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00:21:55,600 --> 00:21:57,879
Speaker 1: before we move on. You know what I like about

406
00:21:57,920 --> 00:22:02,960
Speaker 1: those the glasses that essentially describe what's happening in front

407
00:22:03,000 --> 00:22:07,119
Speaker 1: of people. Think about the potential applications for safety, you know,

408
00:22:07,240 --> 00:22:11,240
Speaker 1: crossing the road, holes in the footpath, you know, obstacles

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00:22:11,880 --> 00:22:13,920
Speaker 1: like that's a pretty cool application as well.

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Speaker 2: Yeah, that's a nice little seguay because there's a really

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Speaker 2: great story about a guy in the United States who.

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Speaker 1: Would just point out to put everyone how much you

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Speaker 1: just fobbed me off? Then did I you went?

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Speaker 2: You went established that, she went. Yeah, it was my topic.

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00:22:32,680 --> 00:22:34,280
Speaker 2: I was telling you how exciting it is.

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Speaker 1: You were talking about choosing fucking clothes. No, like, oh,

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Speaker 1: here's a close up of a T shirt? What about

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Speaker 1: saving someone's life, your dickhead.

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Speaker 2: You gave me the perfect segue to the next segment.

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Speaker 2: It's a really keep.

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00:22:51,119 --> 00:22:53,440
Speaker 1: Going, say keep going segway. Boy.

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00:22:53,800 --> 00:22:56,679
Speaker 2: So this, this guy in the United States got a

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Speaker 2: black T shirt with just a stop sign on the

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Speaker 2: front of it and then just stood by the side

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00:23:02,000 --> 00:23:05,240
Speaker 2: of the road and autonomous cars was stopping because they

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Speaker 2: thought he was a stop sign.

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Speaker 1: That's great, isn't it.

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00:23:08,760 --> 00:23:10,200
Speaker 2: I near'd like it.

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Speaker 1: That's but also, I mean, I wonder if he could

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Speaker 1: get charged with anything.

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00:23:16,000 --> 00:23:19,280
Speaker 2: Right years I don't know. So this guy's his name's

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Speaker 2: Jason Carr is from Arizona. And look, I think he

433
00:23:23,000 --> 00:23:26,159
Speaker 2: was doing it to prove a point. So Waimo is

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Speaker 2: the company that has robotaxis and they're running tests at

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Speaker 2: the moment. So initially he just stood at the edge

436
00:23:33,080 --> 00:23:35,800
Speaker 2: of the road, and yeah, the car came to a

437
00:23:35,840 --> 00:23:39,679
Speaker 2: complete stop, and then it eventually resumed driving once he

438
00:23:39,800 --> 00:23:43,639
Speaker 2: walked away or hid the T shirt. But look, he

439
00:23:43,920 --> 00:23:46,320
Speaker 2: said that it was something that he was doing. It

440
00:23:46,320 --> 00:23:48,159
Speaker 2: was a bit of a publicity stunt, I guess, or

441
00:23:48,600 --> 00:23:51,120
Speaker 2: you know, to kind of to be able to emphasize

442
00:23:51,119 --> 00:23:54,600
Speaker 2: a point that these self driving vehicles still have a

443
00:23:54,600 --> 00:23:57,480
Speaker 2: long way to go to differentiate between a sign on

444
00:23:57,560 --> 00:24:00,680
Speaker 2: a stick by the side road and an intersect and

445
00:24:00,760 --> 00:24:03,159
Speaker 2: just someone standing in a T shirt. But yeah, I

446
00:24:03,160 --> 00:24:05,240
Speaker 2: mean my first reaction was to have a bit of

447
00:24:05,280 --> 00:24:08,679
Speaker 2: a chuckle as well. But it does show, you know,

448
00:24:08,720 --> 00:24:12,639
Speaker 2: the risks of how an autonomous system like that and

449
00:24:12,680 --> 00:24:16,320
Speaker 2: a vehicle is a major heavy vehicle, you know, particularly

450
00:24:16,800 --> 00:24:20,240
Speaker 2: if it's an electric powered vehicle. They're even heavier, aren't they.

451
00:24:20,560 --> 00:24:22,520
Speaker 2: You can you can fool them, And there was all

452
00:24:22,520 --> 00:24:25,720
Speaker 2: the controversy a few years ago, well not that long ago, actually,

453
00:24:25,840 --> 00:24:29,240
Speaker 2: over whether or not the totally autonomous driving of the

454
00:24:29,240 --> 00:24:32,520
Speaker 2: Tesla's was able to pick up a child and differentiate

455
00:24:32,600 --> 00:24:35,360
Speaker 2: between a child walking across the road, and so there

456
00:24:35,400 --> 00:24:37,679
Speaker 2: was again a little bit of controversy around that. At

457
00:24:37,680 --> 00:24:39,320
Speaker 2: the end of the day, we want to make sure

458
00:24:39,320 --> 00:24:42,880
Speaker 2: we've got driver safety. But the current driver safety that's

459
00:24:42,880 --> 00:24:45,520
Speaker 2: built into a lot of vehicles is phenomenal. I know

460
00:24:45,560 --> 00:24:47,439
Speaker 2: I'm always crying about this, but it is good. It's

461
00:24:47,480 --> 00:24:49,840
Speaker 2: getting better. It means that people are less likely to

462
00:24:49,920 --> 00:24:52,080
Speaker 2: fall asleep at the will because their car will notify

463
00:24:52,160 --> 00:24:54,400
Speaker 2: them if they not off or if they drift out

464
00:24:54,400 --> 00:24:56,000
Speaker 2: of their lane, and that's got to be good.

465
00:24:56,840 --> 00:25:02,080
Speaker 1: Yeah. One of the challenges I think though, is that

466
00:25:02,520 --> 00:25:04,720
Speaker 1: some of the cars are so high tech. Now. I

467
00:25:04,760 --> 00:25:07,520
Speaker 1: love cars, I love motorbikes. I watch reviews all the time,

468
00:25:07,560 --> 00:25:10,359
Speaker 1: as you know, which is ironic because I drive a

469
00:25:10,520 --> 00:25:14,200
Speaker 1: fucking old Suzuki Swift. But you know, like I haven't

470
00:25:14,240 --> 00:25:17,280
Speaker 1: had a nice car for years because I kind of

471
00:25:17,440 --> 00:25:19,720
Speaker 1: went through a phase. But I still love watching reviews,

472
00:25:19,960 --> 00:25:23,400
Speaker 1: and I've been watching lots of reviews lately on new

473
00:25:23,440 --> 00:25:28,600
Speaker 1: fancy cars, electric cars, and I watched this guy testing

474
00:25:28,680 --> 00:25:32,680
Speaker 1: a car called the Tank five hundred, which is essentially

475
00:25:32,760 --> 00:25:36,879
Speaker 1: the size of a Land Cruiser. It's Chinese. It looks

476
00:25:36,920 --> 00:25:39,240
Speaker 1: like a two hundred thousand dollars car at seventy grand,

477
00:25:39,240 --> 00:25:41,800
Speaker 1: give or take, except one of the problems. And he

478
00:25:41,880 --> 00:25:43,879
Speaker 1: jumps in and he's talking, and he takes off and

479
00:25:43,880 --> 00:25:46,920
Speaker 1: he's been driving for one hundred meters and the car

480
00:25:46,960 --> 00:25:52,040
Speaker 1: tells him you're tired, pull over and have a rest. Right.

481
00:25:52,160 --> 00:25:54,640
Speaker 1: It keeps telling him because it's got all of these

482
00:25:54,680 --> 00:26:00,239
Speaker 1: senses that it can allegedly sense fatigue or tiredness or

483
00:26:00,280 --> 00:26:03,720
Speaker 1: however it does. And so every two hundred meters that

484
00:26:03,840 --> 00:26:05,919
Speaker 1: was telling him to pull over because he was tired,

485
00:26:06,320 --> 00:26:09,119
Speaker 1: and he just literally jumped in and started driving. So

486
00:26:10,080 --> 00:26:13,560
Speaker 1: they're sorting out the kinks. But you know, I wonder,

487
00:26:13,840 --> 00:26:15,720
Speaker 1: like I kind of love the fact that I have

488
00:26:15,800 --> 00:26:19,760
Speaker 1: a five year old car that's kind of basic. You know.

489
00:26:19,840 --> 00:26:22,880
Speaker 1: It's like there's I don't need to be a buddy

490
00:26:23,119 --> 00:26:25,040
Speaker 1: tech journeius to be able to get in it and

491
00:26:25,080 --> 00:26:25,680
Speaker 1: operate it.

492
00:26:27,359 --> 00:26:32,240
Speaker 2: Yeah. Look, I love the more safety you have in

493
00:26:32,240 --> 00:26:34,720
Speaker 2: a car, but I still love to drive a manual

494
00:26:34,760 --> 00:26:37,480
Speaker 2: every now and again. I love, you know, stick shift.

495
00:26:37,720 --> 00:26:40,480
Speaker 2: It's nice to go through the gears and feel the

496
00:26:40,560 --> 00:26:43,199
Speaker 2: car and know when to change. And as you know,

497
00:26:43,520 --> 00:26:47,800
Speaker 2: you've driven sticks many times on the power of the vehicle,

498
00:26:48,000 --> 00:26:52,119
Speaker 2: you remember the term powerband. Yeah, and I love that.

499
00:26:52,560 --> 00:26:56,199
Speaker 2: I love the people of our generation understand what that means.

500
00:26:56,520 --> 00:26:57,919
Speaker 2: And the other thing is, I've taught a lot of

501
00:26:57,920 --> 00:27:01,320
Speaker 2: people to drive in my Nissan on this had NXR coop.

502
00:27:01,680 --> 00:27:04,080
Speaker 2: And the good thing about teaching a young person how

503
00:27:04,080 --> 00:27:05,960
Speaker 2: to drive and a manual is they have a lot

504
00:27:06,000 --> 00:27:09,560
Speaker 2: more respect for how an engine works, because you know

505
00:27:09,840 --> 00:27:11,960
Speaker 2: that when you go from first gear to second gear

506
00:27:12,000 --> 00:27:16,160
Speaker 2: to third gear, you can feel and hear how your

507
00:27:16,200 --> 00:27:19,520
Speaker 2: engine is being taxed and how much effort the engine

508
00:27:19,560 --> 00:27:23,439
Speaker 2: is going through and the car. I like that, And

509
00:27:23,480 --> 00:27:26,040
Speaker 2: I'm not a petrol head by a long shot, but

510
00:27:26,080 --> 00:27:28,320
Speaker 2: I still love the feeling. And a friend of mine

511
00:27:28,440 --> 00:27:31,040
Speaker 2: she had to look for so many different models before

512
00:27:31,080 --> 00:27:33,720
Speaker 2: she was even able to purchase a manual car. I

513
00:27:33,760 --> 00:27:35,840
Speaker 2: think the WRX is one of the few cars on

514
00:27:35,880 --> 00:27:38,800
Speaker 2: the road that still is a manual. It's very very

515
00:27:38,840 --> 00:27:39,639
Speaker 2: hard to buy a manual.

516
00:27:39,720 --> 00:27:42,880
Speaker 1: View. Yeah, mine's manual. Mine's five speed. It's a little

517
00:27:42,920 --> 00:27:46,600
Speaker 1: one point four turbo little Suzuki sport. It's great, It's great.

518
00:27:47,400 --> 00:27:51,040
Speaker 1: Here's something that caught my eye. I don't know why

519
00:27:51,840 --> 00:27:55,879
Speaker 1: researchers build AI driven sarcasm detector.

520
00:27:56,119 --> 00:27:56,520
Speaker 2: Oh I.

521
00:27:58,240 --> 00:28:00,840
Speaker 1: Was that built for me?

522
00:28:01,640 --> 00:28:06,400
Speaker 2: It feels like it doesn't it It really, really really

523
00:28:06,480 --> 00:28:10,879
Speaker 2: does that. There is a seriousness behind this because being

524
00:28:11,000 --> 00:28:14,720
Speaker 2: able to detect sarcasm. I know we call it the

525
00:28:14,760 --> 00:28:18,360
Speaker 2: lowest form of whip, but I believe also it shows intelligence.

526
00:28:18,920 --> 00:28:25,879
Speaker 2: Potentially maybe, but evidently knowing sarcasm means your interaction with

527
00:28:26,000 --> 00:28:30,840
Speaker 2: people is a lot more natural. So what it means,

528
00:28:30,840 --> 00:28:36,080
Speaker 2: So this is some researchers who have basically looked at

529
00:28:36,119 --> 00:28:41,640
Speaker 2: sarcasm as a way to make the AI model understand

530
00:28:41,760 --> 00:28:47,640
Speaker 2: more about how language works. And sarcasm can be hard

531
00:28:47,680 --> 00:28:50,720
Speaker 2: to detect even if you're just an average person. But

532
00:28:50,840 --> 00:28:53,920
Speaker 2: if you're trying to train an AI model to be

533
00:28:54,080 --> 00:28:59,120
Speaker 2: more clever to understand how people work, the sarcasm director

534
00:28:59,640 --> 00:29:03,960
Speaker 2: detect certainly has a lot of benefits. So I kind

535
00:29:03,960 --> 00:29:07,200
Speaker 2: of like it that it's an interesting idea, and then

536
00:29:07,240 --> 00:29:09,280
Speaker 2: when you start to dig down a little bit deeper,

537
00:29:09,520 --> 00:29:12,120
Speaker 2: it makes a lot of sense because we have a

538
00:29:12,160 --> 00:29:16,000
Speaker 2: lot of nuances in communication and in our conversation, I mean,

539
00:29:16,040 --> 00:29:20,200
Speaker 2: look at my shows when we get let's face it.

540
00:29:20,680 --> 00:29:22,640
Speaker 1: I mean, that's why we have people who love it

541
00:29:22,680 --> 00:29:25,880
Speaker 1: and people who hate it. Speaking of sarcasm. This afternoon,

542
00:29:25,920 --> 00:29:29,800
Speaker 1: I had a meeting with my senior academic supervisor, Chris,

543
00:29:29,960 --> 00:29:35,680
Speaker 1: and my other supervisor, Lucy, and another guy called Campbell

544
00:29:35,680 --> 00:29:39,000
Speaker 1: who helps with analytics and data and shout out to Campbell,

545
00:29:39,040 --> 00:29:42,800
Speaker 1: and and anyway, we're all on this call and we're

546
00:29:42,800 --> 00:29:45,480
Speaker 1: trying to figure out we're talking about this, you know,

547
00:29:45,560 --> 00:29:48,440
Speaker 1: looking at I won't bore everyone, but we're looking at

548
00:29:48,480 --> 00:29:54,400
Speaker 1: different variables that we could correlate with what too, Sorry, anyway,

549
00:29:54,760 --> 00:29:57,240
Speaker 1: we're thinking, we're talking about different things that we could

550
00:29:57,320 --> 00:30:01,920
Speaker 1: correlate with or explore, being a relationship between meta accuracy

551
00:30:02,160 --> 00:30:05,640
Speaker 1: and so meta accuracy and age meta accuracy and income

552
00:30:05,680 --> 00:30:09,560
Speaker 1: metaaccuracy and all these different things. And I said, like,

553
00:30:09,760 --> 00:30:12,440
Speaker 1: as you know, Sarka as a manajoke, I go, what

554
00:30:12,480 --> 00:30:16,920
Speaker 1: about meta accuracy and star scigens and like every like

555
00:30:17,080 --> 00:30:20,640
Speaker 1: maybe virgos are really fucking good at it, right, or

556
00:30:20,720 --> 00:30:23,840
Speaker 1: capricorns maybe they can just you know, they're great at this.

557
00:30:24,360 --> 00:30:26,320
Speaker 1: And all three of them just looked at me like

558
00:30:26,360 --> 00:30:30,720
Speaker 1: I was a complete fuck with and Chris, my senior supervisor,

559
00:30:30,760 --> 00:30:35,560
Speaker 1: didn't even respond and he just kept he just kept talking,

560
00:30:35,960 --> 00:30:38,840
Speaker 1: Oh and ah, there it is, and that's probably why

561
00:30:38,880 --> 00:30:42,680
Speaker 1: I shouldn't be in this environment anyway, keep going, I'm

562
00:30:42,680 --> 00:30:43,480
Speaker 1: really getting bored.

563
00:30:43,520 --> 00:30:46,280
Speaker 2: No, oh, I didn't pick up and that I said

564
00:30:46,360 --> 00:30:50,880
Speaker 2: no instead of now, oh, there you go. Keep going. Yeah,

565
00:30:50,880 --> 00:30:52,520
Speaker 2: that was it. That was just the sarcasm thing. I

566
00:30:52,520 --> 00:30:56,760
Speaker 2: thought it was great. Do you Another little AI story

567
00:30:56,800 --> 00:30:58,560
Speaker 2: that I had to kind of throw in here is

568
00:30:58,560 --> 00:31:01,520
Speaker 2: how people are using AI now for insurance fraud. Did

569
00:31:01,560 --> 00:31:03,560
Speaker 2: you see that? It came up a little while ago.

570
00:31:03,960 --> 00:31:07,360
Speaker 2: So what they're doing, yeah, because when you put in

571
00:31:07,520 --> 00:31:11,480
Speaker 2: an accident claim, you show your vehicle and the damage.

572
00:31:11,520 --> 00:31:14,200
Speaker 2: And thankfully I haven't had too many accidents, but I

573
00:31:14,240 --> 00:31:16,680
Speaker 2: did head a kangaroo in my new car after they

574
00:31:16,720 --> 00:31:19,640
Speaker 2: had it three months and wow, yeah, it was a

575
00:31:19,680 --> 00:31:22,640
Speaker 2: really messy hit. And I look it was already dead

576
00:31:22,680 --> 00:31:24,600
Speaker 2: on the road, because that would have made me even

577
00:31:24,640 --> 00:31:26,640
Speaker 2: more distressed if it had been alive and I was

578
00:31:26,680 --> 00:31:30,040
Speaker 2: responsible for killing it. But that's it. Yet took out

579
00:31:30,040 --> 00:31:32,600
Speaker 2: a big chunk of the front of my car. But

580
00:31:32,680 --> 00:31:38,520
Speaker 2: what people are doing is they're actually faking claims by

581
00:31:38,600 --> 00:31:41,560
Speaker 2: putting a picture of their car into AI and say,

582
00:31:41,640 --> 00:31:44,880
Speaker 2: put a DNT in the front right fender and then

583
00:31:45,000 --> 00:31:49,440
Speaker 2: submitting it. Really, so insurance companies are now and this

584
00:31:49,560 --> 00:31:52,520
Speaker 2: was a study in the UK done by Alliance, and

585
00:31:52,600 --> 00:31:55,760
Speaker 2: they're saying that what they're having to do is now

586
00:31:55,920 --> 00:31:59,560
Speaker 2: really look closely at accidents because they may be what

587
00:31:59,600 --> 00:32:03,080
Speaker 2: they call shallow fakes. So we've heard of deep fakes.

588
00:32:03,120 --> 00:32:06,960
Speaker 2: This is a shallow fake. So it's yeah, it's not

589
00:32:07,040 --> 00:32:12,000
Speaker 2: always convincing. And and look, some of them can be close.

590
00:32:12,360 --> 00:32:14,600
Speaker 2: But it wouldn't even have occurred to me to do

591
00:32:14,640 --> 00:32:17,560
Speaker 2: something like this, you know. It's funny some people just

592
00:32:17,680 --> 00:32:21,120
Speaker 2: think that way. So yeah, that was an interesting one.

593
00:32:21,440 --> 00:32:23,320
Speaker 1: Well, I think that's going to happen. Stuff like that's

594
00:32:23,360 --> 00:32:24,960
Speaker 1: going to happen more and more, isn't it. How do

595
00:32:25,000 --> 00:32:28,600
Speaker 1: we use this technology to shaft people, to embezzle, to

596
00:32:29,840 --> 00:32:34,760
Speaker 1: you know, create some kind of unfair advantage you know, Yeah,

597
00:32:34,840 --> 00:32:36,320
Speaker 1: that's gonna it's not going away.

598
00:32:37,000 --> 00:32:40,240
Speaker 2: Yeah, so that's that's a thing now. Crago yep, And

599
00:32:40,520 --> 00:32:43,719
Speaker 2: I look, there were there's been a twenty nine percent

600
00:32:43,840 --> 00:32:48,560
Speaker 2: increase in fraud reported, you know, according to this particular

601
00:32:48,600 --> 00:32:52,760
Speaker 2: report by Alliance and and so it's happening a lot more.

602
00:32:52,920 --> 00:32:54,760
Speaker 2: And they talked about a van and they showed a

603
00:32:54,760 --> 00:32:59,640
Speaker 2: picture of this van free Ai and post Ai and

604
00:32:59,760 --> 00:33:02,440
Speaker 2: the person have created a dint in the in the

605
00:33:02,520 --> 00:33:04,720
Speaker 2: side of the car. So yeah, it's it's a thing.

606
00:33:05,320 --> 00:33:07,640
Speaker 2: Are we giving people bad bad ideas? Though?

607
00:33:08,200 --> 00:33:09,920
Speaker 1: I think the ideas were already out there?

608
00:33:10,000 --> 00:33:10,560
Speaker 2: Okay, good?

609
00:33:11,680 --> 00:33:15,840
Speaker 1: Yeah, I want to know why Pizza Hut got fined

610
00:33:15,880 --> 00:33:17,400
Speaker 1: two and a half million bucks.

611
00:33:17,880 --> 00:33:22,760
Speaker 2: I know the I kind of feel that this is

612
00:33:22,800 --> 00:33:26,560
Speaker 2: a very important message that the you know that the

613
00:33:26,600 --> 00:33:29,680
Speaker 2: authorities are dishing out to companies like this, Oh, dishing

614
00:33:29,680 --> 00:33:30,600
Speaker 2: out like a pizza.

615
00:33:31,120 --> 00:33:33,719
Speaker 1: No pun intended when you said that, I thought of that.

616
00:33:34,120 --> 00:33:37,880
Speaker 2: Well, the thing is, can you get spam on a pizza?

617
00:33:39,040 --> 00:33:40,120
Speaker 1: Oh? Tish book?

618
00:33:40,840 --> 00:33:42,040
Speaker 2: It's getting, isn't it.

619
00:33:42,160 --> 00:33:46,080
Speaker 1: I don't think you want like our our older folk,

620
00:33:46,520 --> 00:33:49,320
Speaker 1: our older listeners know what spam is, but probably our

621
00:33:49,920 --> 00:33:52,520
Speaker 1: forty and under brigade they wouldn't know what spam is.

622
00:33:52,600 --> 00:33:55,200
Speaker 2: Patrick, Yeah, so spam in a can that was just

623
00:33:55,320 --> 00:33:56,600
Speaker 2: I don't know what the meat. Well, I don't think

624
00:33:56,600 --> 00:33:58,720
Speaker 2: anybody knows what's inside spam. They put it in a

625
00:33:58,760 --> 00:34:00,440
Speaker 2: can and you can make a boot out of it.

626
00:34:00,520 --> 00:34:05,160
Speaker 1: Ste I think let's just say it was ham ishh Yeah.

627
00:34:05,200 --> 00:34:08,520
Speaker 1: Any part in that it was in the neighborhood of ham.

628
00:34:08,680 --> 00:34:12,440
Speaker 2: I think snouts and assholes is probably you know, I think.

629
00:34:12,960 --> 00:34:15,440
Speaker 1: I think I'll tell you what it was. It was

630
00:34:16,080 --> 00:34:19,080
Speaker 1: like a canful of salt. It was a saltier shit

631
00:34:19,160 --> 00:34:22,040
Speaker 1: you've ever tasted. They probably put all that salt in

632
00:34:22,080 --> 00:34:23,200
Speaker 1: there to kill.

633
00:34:22,960 --> 00:34:26,319
Speaker 2: The taste, yeah, and also keep it going. Didn't they

634
00:34:26,440 --> 00:34:28,560
Speaker 2: use it during Wasn't it developed for World War II

635
00:34:28,719 --> 00:34:29,680
Speaker 2: or something? I thought?

636
00:34:29,760 --> 00:34:32,400
Speaker 1: I think it was troops. I think like fair bit

637
00:34:32,440 --> 00:34:35,880
Speaker 1: of fat, fair bit of salt. Probably if you're in

638
00:34:35,920 --> 00:34:39,120
Speaker 1: the middle of nowhere and trying to stay alive, who knows,

639
00:34:39,239 --> 00:34:40,879
Speaker 1: I mean, anything would taste pretty good.

640
00:34:41,200 --> 00:34:45,719
Speaker 2: Yeah. So in Australia, the Communications and Media Authority, the ACMA,

641
00:34:46,560 --> 00:34:52,719
Speaker 2: they investigate complaints when people receive unsolicited emails or texts

642
00:34:53,120 --> 00:34:55,480
Speaker 2: and you don't have an ability to be able to

643
00:34:55,520 --> 00:34:58,080
Speaker 2: opt out, So it's laura in Australia. If you get

644
00:34:58,120 --> 00:34:59,920
Speaker 2: a bulk email sent to you or a bulk ten

645
00:35:00,560 --> 00:35:03,359
Speaker 2: and you try to opt out and you can't, then

646
00:35:03,400 --> 00:35:07,759
Speaker 2: the company's doing that is at fault. And evidently in

647
00:35:07,800 --> 00:35:11,160
Speaker 2: this particular instance, it was reported that ten million spam

648
00:35:11,280 --> 00:35:15,280
Speaker 2: marketing text and emails were sent out in four months time,

649
00:35:15,840 --> 00:35:20,520
Speaker 2: and people were trying to unsubscribe to stop receiving them

650
00:35:20,560 --> 00:35:23,600
Speaker 2: and they couldn't so, and then another four point three

651
00:35:23,680 --> 00:35:27,800
Speaker 2: million marketing messages was sent out without the option to unsubscribe.

652
00:35:27,920 --> 00:35:34,000
Speaker 2: So it sends a really clear message that you know, country, countries,

653
00:35:34,040 --> 00:35:37,160
Speaker 2: companies know these laws. These laws have been around for

654
00:35:37,160 --> 00:35:38,919
Speaker 2: a long time now. So I just thought it would

655
00:35:38,920 --> 00:35:41,560
Speaker 2: be an interesting one to mention that, you know, if

656
00:35:41,600 --> 00:35:44,640
Speaker 2: you're receiving unsolicited emails and you want to dub somebody

657
00:35:44,680 --> 00:35:46,160
Speaker 2: in for doing it, gee, I'll tell you what. The

658
00:35:46,200 --> 00:35:47,959
Speaker 2: fine's pretty big, can.

659
00:35:47,920 --> 00:35:52,440
Speaker 1: I'd tell you something in the same ballpark. So I'm

660
00:35:52,480 --> 00:35:54,319
Speaker 1: not going to say what company. But I had this

661
00:35:55,800 --> 00:35:58,600
Speaker 1: kind of what do you call the computer protectiony stuff?

662
00:35:58,840 --> 00:35:59,480
Speaker 1: What do you call that?

663
00:36:00,120 --> 00:36:00,720
Speaker 2: Any virus?

664
00:36:01,280 --> 00:36:05,239
Speaker 1: Antivirus? Thank you Patrick. So I had that installed, I

665
00:36:05,280 --> 00:36:10,920
Speaker 1: won't say what company, and it like every eight minutes

666
00:36:10,960 --> 00:36:13,719
Speaker 1: it would pop up with whatever, right, and then it

667
00:36:13,840 --> 00:36:18,319
Speaker 1: ran out and I decided to go with something else

668
00:36:18,320 --> 00:36:21,439
Speaker 1: and this one that ran out To try to get

669
00:36:21,440 --> 00:36:24,960
Speaker 1: that out of my fucking computer. It was like it

670
00:36:25,040 --> 00:36:29,319
Speaker 1: was a virus, like it would not go away. I

671
00:36:29,440 --> 00:36:32,000
Speaker 1: tried to uninstall it, or I did what I thought

672
00:36:32,160 --> 00:36:35,880
Speaker 1: uninstall it. I followed the YouTube video, I uninstalled it,

673
00:36:36,040 --> 00:36:39,800
Speaker 1: and then it was back and it kept going, you're expired.

674
00:36:39,880 --> 00:36:41,480
Speaker 1: You need to do this, you need to do that.

675
00:36:41,600 --> 00:36:43,480
Speaker 1: If you don't do this, like the world's going to

676
00:36:43,520 --> 00:36:45,239
Speaker 1: blow up and we're going to you know. It's like,

677
00:36:46,280 --> 00:36:48,640
Speaker 1: in the end, it was more of a problem than

678
00:36:48,680 --> 00:36:51,560
Speaker 1: the fucking viruses I was trying to protect myself from.

679
00:36:52,239 --> 00:36:55,640
Speaker 2: Yeah, so a lot of laptop and computer companies do

680
00:36:55,800 --> 00:36:59,839
Speaker 2: deals with these antivirus companies, starting with Mac. I think

681
00:37:00,000 --> 00:37:04,000
Speaker 2: probably is the one you're thinking of a fee McAfee. Sorry,

682
00:37:04,160 --> 00:37:05,480
Speaker 2: I just had something caught in my throat.

683
00:37:06,080 --> 00:37:06,520
Speaker 1: Yeah, so.

684
00:37:08,120 --> 00:37:11,359
Speaker 2: It's not unusual to have the anti virus installed, but

685
00:37:11,440 --> 00:37:14,280
Speaker 2: it's only a limited trial for say thirty thirty days,

686
00:37:14,560 --> 00:37:16,799
Speaker 2: and it is really painful trying to get rid of it,

687
00:37:16,840 --> 00:37:18,800
Speaker 2: and it is I'm really impressed that you did a

688
00:37:18,920 --> 00:37:21,560
Speaker 2: YouTube and jumped on there and tried to get rid

689
00:37:21,560 --> 00:37:23,720
Speaker 2: of it yourself, Craigi. I thought that was very impressive.

690
00:37:23,800 --> 00:37:25,800
Speaker 1: Yeah, I thought I'd done it, and then about twenty

691
00:37:25,800 --> 00:37:27,480
Speaker 1: minutes later it was back, and then I had to

692
00:37:27,480 --> 00:37:30,359
Speaker 1: get the actual smart person in the organization to come

693
00:37:30,400 --> 00:37:33,319
Speaker 1: over and do it. Liza. Yeah, she came over and

694
00:37:33,320 --> 00:37:36,400
Speaker 1: did it in thirteen seconds and looked at me quizzically.

695
00:37:36,480 --> 00:37:38,400
Speaker 2: And she uses a Mac. Oh are you on a

696
00:37:38,440 --> 00:37:39,000
Speaker 2: Mac as well?

697
00:37:39,480 --> 00:37:42,120
Speaker 1: I'm not on a Mac, so it wasn't that brand,

698
00:37:42,160 --> 00:37:43,920
Speaker 1: you said, But I don't want to say it on

699
00:37:43,960 --> 00:37:46,120
Speaker 1: air because I feel like they might hijack me.

700
00:37:46,480 --> 00:37:50,560
Speaker 2: Yeah, fair enough. It's interesting while you're talking about that

701
00:37:51,120 --> 00:37:53,400
Speaker 2: at the moment, Dell has put out a warning just

702
00:37:53,520 --> 00:37:56,239
Speaker 2: recently in the last few days because they had a

703
00:37:56,320 --> 00:38:00,480
Speaker 2: data breach and they believe forty nine million customers may

704
00:38:00,520 --> 00:38:04,400
Speaker 2: have had information and that that's now gone onto the

705
00:38:04,520 --> 00:38:09,600
Speaker 2: dark web, and that's potentially Yeah, this could be serious

706
00:38:09,600 --> 00:38:10,160
Speaker 2: for a lot of people.

707
00:38:10,440 --> 00:38:15,319
Speaker 1: Nine million. I mean, how does how did they ever

708
00:38:15,520 --> 00:38:19,520
Speaker 1: compensate for that? Because it's like it's almost unknowable, like

709
00:38:19,640 --> 00:38:22,560
Speaker 1: the potential and I'm sure the vast majority of people

710
00:38:22,600 --> 00:38:25,719
Speaker 1: would be fine, but I mean, even if it was

711
00:38:25,880 --> 00:38:29,080
Speaker 1: one percent of forty nine million, that's four hundred and

712
00:38:29,160 --> 00:38:33,279
Speaker 1: ninety thousand people. That's half a million people, give or take.

713
00:38:34,120 --> 00:38:37,440
Speaker 1: I mean, yeah, that's that's the scary thing. Now when

714
00:38:37,960 --> 00:38:41,440
Speaker 1: other when people that don't have your best interests at

715
00:38:41,480 --> 00:38:44,279
Speaker 1: heart have got access to all your shit, that makes

716
00:38:44,320 --> 00:38:45,080
Speaker 1: me nervous.

717
00:38:45,360 --> 00:38:48,759
Speaker 2: Yeah, and look, one of the things they're saying is

718
00:38:48,800 --> 00:38:51,400
Speaker 2: that it could be as much as the name of

719
00:38:51,440 --> 00:38:54,600
Speaker 2: the buyer, the company named the address. So there's quite

720
00:38:54,600 --> 00:38:58,920
Speaker 2: a few markers that are very specific to the individual customer,

721
00:38:58,920 --> 00:39:01,440
Speaker 2: and that's one of the problems. And you know, things

722
00:39:01,520 --> 00:39:03,600
Speaker 2: like your name and your physical address. That sort of

723
00:39:03,600 --> 00:39:06,520
Speaker 2: stuff is really, you know, something that's quite problematic. But

724
00:39:06,600 --> 00:39:09,520
Speaker 2: one of the things that you should do is go

725
00:39:09,640 --> 00:39:12,360
Speaker 2: to the website of the vendor, if it happens to

726
00:39:12,360 --> 00:39:16,359
Speaker 2: be in this case, Dell, and follow their instructions and suggestions.

727
00:39:16,719 --> 00:39:18,799
Speaker 2: But the first thing you need to do is go

728
00:39:18,880 --> 00:39:22,319
Speaker 2: and change your password. Absolute first thing you do. Now,

729
00:39:22,360 --> 00:39:24,760
Speaker 2: I haven't had a Dell computer for quite a few years,

730
00:39:25,200 --> 00:39:27,040
Speaker 2: but that was the first thing I did was jump

731
00:39:27,080 --> 00:39:29,160
Speaker 2: in and see if I still had a Dell account

732
00:39:29,440 --> 00:39:31,840
Speaker 2: and if there was a password, and I generated a

733
00:39:31,880 --> 00:39:35,239
Speaker 2: new password just in case. That was one of the

734
00:39:35,280 --> 00:39:38,239
Speaker 2: first things. And also two factor authentication. You might have

735
00:39:38,280 --> 00:39:40,839
Speaker 2: seen it written down as two FA that's another thing

736
00:39:40,880 --> 00:39:42,640
Speaker 2: that you can do. Make sure then that two factor

737
00:39:42,719 --> 00:39:46,839
Speaker 2: authentication means that before you can sign in, you have

738
00:39:46,960 --> 00:39:51,560
Speaker 2: to either have a second factor authentication, either a text

739
00:39:51,600 --> 00:39:53,640
Speaker 2: message or an email get sent to you with a

740
00:39:53,719 --> 00:39:56,319
Speaker 2: code and then you put the code in. So it's

741
00:39:56,320 --> 00:39:58,400
Speaker 2: not enough just to have the password, you need that

742
00:39:58,440 --> 00:40:00,719
Speaker 2: factor code to then pull it there as well. It's

743
00:40:00,719 --> 00:40:03,840
Speaker 2: a pain, but it's a level of security as well.

744
00:40:04,560 --> 00:40:07,560
Speaker 1: I saw this real today, mate, and a guy was

745
00:40:08,280 --> 00:40:09,920
Speaker 1: I don't know if it was. It was like a

746
00:40:09,960 --> 00:40:13,200
Speaker 1: little almost like a road test of a product. This

747
00:40:13,239 --> 00:40:16,680
Speaker 1: guy was sitting in what looked to be a cafe.

748
00:40:16,760 --> 00:40:19,920
Speaker 1: There was lots of people around. He was talking and

749
00:40:20,520 --> 00:40:22,920
Speaker 1: we could hear what he was hearing. He had like

750
00:40:23,000 --> 00:40:26,800
Speaker 1: this thing in his ear, and then he said, I

751
00:40:26,840 --> 00:40:29,160
Speaker 1: don't know. He gave some instruction to cut out the

752
00:40:29,200 --> 00:40:33,080
Speaker 1: background noise and just to focus on one person across

753
00:40:33,120 --> 00:40:37,040
Speaker 1: the table. Took out all the noise except this bloke's voice,

754
00:40:37,840 --> 00:40:40,920
Speaker 1: and then you could clearly hear what he was saying,

755
00:40:41,440 --> 00:40:44,720
Speaker 1: except he was speaking in Spanish, and then he said,

756
00:40:44,760 --> 00:40:48,080
Speaker 1: now converted into English. So all of a sudden, all

757
00:40:48,120 --> 00:40:50,640
Speaker 1: the noise in the room has gone, or you know,

758
00:40:50,800 --> 00:40:53,719
Speaker 1: it's gone from a ten to or one, and now

759
00:40:53,760 --> 00:40:56,239
Speaker 1: we can hear clearly hear this guy, and then we

760
00:40:57,040 --> 00:41:02,279
Speaker 1: then it gets translated in pretty much real time into English, like.

761
00:41:02,600 --> 00:41:04,279
Speaker 2: Yeah, it makes you feel sad that we don't have

762
00:41:04,320 --> 00:41:06,880
Speaker 2: a Cold war and spies anymore, because that would have

763
00:41:06,880 --> 00:41:08,040
Speaker 2: been really handy, wouldn't it.

764
00:41:08,360 --> 00:41:13,359
Speaker 1: Ah. Yeah, I'm pretty sure we do have spies. I'm

765
00:41:13,360 --> 00:41:14,200
Speaker 1: pretty sure there.

766
00:41:14,040 --> 00:41:16,320
Speaker 2: Are still shout out to everybody at AISIO.

767
00:41:17,239 --> 00:41:20,680
Speaker 1: I'm going to show my age here because I read

768
00:41:20,719 --> 00:41:24,399
Speaker 1: the one of the titles of one of your kind

769
00:41:24,400 --> 00:41:27,719
Speaker 1: of articles or one of your discussion points under social media,

770
00:41:27,760 --> 00:41:31,760
Speaker 1: and it says young people share their experience of being doxed.

771
00:41:32,520 --> 00:41:34,000
Speaker 1: I don't know what dost means.

772
00:41:34,560 --> 00:41:37,319
Speaker 2: This is actually a bit of bit insidious. This it's

773
00:41:37,360 --> 00:41:40,960
Speaker 2: a terrible thing to do to somebody. It's where online. Okay,

774
00:41:40,960 --> 00:41:43,600
Speaker 2: we'll give an example. You're online gaming and you have

775
00:41:43,640 --> 00:41:45,839
Speaker 2: a bit of an altercation with someone because quite often

776
00:41:45,880 --> 00:41:49,200
Speaker 2: online gamers can talk to each other and someone takes

777
00:41:49,200 --> 00:41:52,520
Speaker 2: a dislike to you. But then they get your personal details,

778
00:41:52,560 --> 00:41:55,840
Speaker 2: your address, and then they start sending pizza delivery people

779
00:41:55,840 --> 00:41:58,319
Speaker 2: to your house. And we're not talking one person, we're

780
00:41:58,320 --> 00:42:01,759
Speaker 2: talking fifty people. So suddenly you're getting packages delivered to

781
00:42:01,800 --> 00:42:04,480
Speaker 2: your house. You're getting pizzas delivered to your house, and

782
00:42:05,160 --> 00:42:08,359
Speaker 2: it could be amazingly distressing. This happened to a guy

783
00:42:08,400 --> 00:42:12,320
Speaker 2: who was only seventeen and his whole family was thrown

784
00:42:12,400 --> 00:42:15,480
Speaker 2: in a curveball here and it meant that, you know,

785
00:42:15,480 --> 00:42:17,920
Speaker 2: he got into an argument online playing a game called

786
00:42:18,320 --> 00:42:20,879
Speaker 2: Call of Duty, and then for about three or four

787
00:42:20,960 --> 00:42:24,359
Speaker 2: weeks he kept getting you know, uber eats and pizzas

788
00:42:24,640 --> 00:42:28,279
Speaker 2: and it says sometimes fifty times a day, and that's

789
00:42:28,280 --> 00:42:31,239
Speaker 2: what it is. It's a really malicious thing people can do.

790
00:42:31,440 --> 00:42:34,719
Speaker 2: I mean, I always get distressed when people the keyboard warriors,

791
00:42:34,760 --> 00:42:38,360
Speaker 2: you know, people who are so tough behind the keyboard,

792
00:42:38,719 --> 00:42:40,759
Speaker 2: and they wouldn't say if you wouldn't do it in

793
00:42:40,800 --> 00:42:43,359
Speaker 2: real life if you don't think about it. And look,

794
00:42:43,400 --> 00:42:45,120
Speaker 2: there's always going to be people out there who'll do

795
00:42:45,160 --> 00:42:47,239
Speaker 2: this sort of stuff. But yeah, so that's what dosing is.

796
00:42:48,080 --> 00:42:50,120
Speaker 2: But as you can imagine, the whole family would have

797
00:42:50,120 --> 00:42:52,120
Speaker 2: been pretty distressed about this sort of thing happen.

798
00:42:52,320 --> 00:42:55,640
Speaker 1: I wonder what the solution to this is for the

799
00:42:56,280 --> 00:42:59,720
Speaker 1: food companies or the restaurants, or because you think about

800
00:42:59,840 --> 00:43:02,400
Speaker 1: you you could ring up. I mean, I live on

801
00:43:02,440 --> 00:43:05,759
Speaker 1: a street with fifty restaurants. You've taken cafes. I could

802
00:43:05,800 --> 00:43:08,799
Speaker 1: ring up the pizza joint that's one hundred and eighty

803
00:43:08,840 --> 00:43:11,680
Speaker 1: meters away and order ten pizzas. As long as I

804
00:43:11,719 --> 00:43:14,520
Speaker 1: give them an address and a phone number, they're going

805
00:43:14,560 --> 00:43:15,799
Speaker 1: to make the ten pizzas.

806
00:43:16,239 --> 00:43:18,319
Speaker 2: Look, I think the only way to get around that

807
00:43:18,480 --> 00:43:21,440
Speaker 2: is for people to prepay and to say I mean,

808
00:43:21,440 --> 00:43:22,799
Speaker 2: at the end of the day, if someone sends me

809
00:43:22,800 --> 00:43:27,480
Speaker 2: a pizza and it's been paid for, I'm not too concerned, right, Yeah,

810
00:43:27,520 --> 00:43:30,600
Speaker 2: I mean, look, it's you know, the society is breaking

811
00:43:30,640 --> 00:43:32,880
Speaker 2: down when people start sending a kilo and a half

812
00:43:32,920 --> 00:43:35,000
Speaker 2: of coins in the mail. I mean, that's just kidding.

813
00:43:37,960 --> 00:43:41,280
Speaker 1: Yeah. By the way, Patrick's home address for the Federal

814
00:43:41,320 --> 00:43:44,040
Speaker 1: Police if you're listening, he's in Milan. I don't know

815
00:43:44,080 --> 00:43:46,279
Speaker 1: the exact address. It just occurred to me that if

816
00:43:46,320 --> 00:43:50,120
Speaker 1: all of our listeners sent Patrick five dollars each, I

817
00:43:50,160 --> 00:43:52,319
Speaker 1: will match that with whatever we come up with.

818
00:43:53,920 --> 00:43:55,360
Speaker 2: It's greg that's a great idea.

819
00:43:55,840 --> 00:43:59,200
Speaker 1: You're an idiot. Stop that was fake me. That wasn't

820
00:43:59,239 --> 00:44:03,800
Speaker 1: really everyone that. By the way, fake me is way too.

821
00:44:03,640 --> 00:44:04,960
Speaker 2: Polite, you reckon?

822
00:44:05,640 --> 00:44:11,680
Speaker 1: Yeah, yeah, fake me is too articulate and nice. I

823
00:44:11,719 --> 00:44:13,799
Speaker 1: really need to apologize. I was going to do a

824
00:44:13,840 --> 00:44:16,520
Speaker 1: tai chi class with Patrick, but I weaseled my way

825
00:44:16,560 --> 00:44:21,520
Speaker 1: out of it. There's no apology, there's just relief.

826
00:44:22,040 --> 00:44:24,240
Speaker 2: You're right. Actually, yeah, it's just relief.

827
00:44:25,080 --> 00:44:28,000
Speaker 1: Like fake me, fake me doesn't know real me because

828
00:44:28,040 --> 00:44:31,160
Speaker 1: fake me he would know. Fake me should know that.

829
00:44:31,200 --> 00:44:34,600
Speaker 1: Real me would never apologize for that. Of course you were.

830
00:44:34,960 --> 00:44:37,399
Speaker 1: I'm always wrong and you are one hundred percent right

831
00:44:37,440 --> 00:44:42,359
Speaker 1: all the time. You wish, all right, take us home

832
00:44:42,400 --> 00:44:46,200
Speaker 1: with something. Just round this bad boy up if you could.

833
00:44:46,480 --> 00:44:47,880
Speaker 2: It sounds like you want to get rid of me.

834
00:44:48,680 --> 00:44:50,680
Speaker 1: No, you can do it for as long as I

835
00:44:50,840 --> 00:44:52,920
Speaker 1: just realized. You know why we've gotten through a lot

836
00:44:52,960 --> 00:44:55,840
Speaker 1: in a short time. I don't want to say it's tiff,

837
00:44:55,880 --> 00:45:02,200
Speaker 1: but it's tiff. It's there's a a big conversational whole.

838
00:45:04,960 --> 00:45:09,279
Speaker 2: You know. There's some researchers here in Australia have been

839
00:45:09,520 --> 00:45:15,040
Speaker 2: looking at how children are being educated and they're saying

840
00:45:15,080 --> 00:45:20,399
Speaker 2: that children produce better pieces of writing by hand, so

841
00:45:20,719 --> 00:45:24,799
Speaker 2: their ability to learn and at a certain age. So

842
00:45:24,840 --> 00:45:27,480
Speaker 2: we're talking say grade one and grade two if they

843
00:45:27,520 --> 00:45:30,600
Speaker 2: are still writing. And this is where education sytem in

844
00:45:30,600 --> 00:45:35,640
Speaker 2: Australia is being praised because when you're writing, you're singularly

845
00:45:35,719 --> 00:45:38,759
Speaker 2: focused on what you're doing is spelling every single letter.

846
00:45:38,800 --> 00:45:42,359
Speaker 2: You're writing out every single letter, and it's a much

847
00:45:42,719 --> 00:45:45,000
Speaker 2: a better way to focus and to be able to

848
00:45:45,400 --> 00:45:47,080
Speaker 2: get kids to do that. And I thought, isn't that

849
00:45:47,120 --> 00:45:50,879
Speaker 2: great that handwriting is such a good thing for young

850
00:45:50,960 --> 00:45:54,640
Speaker 2: people and that we still doing. Obviously keyboard skills are

851
00:45:54,719 --> 00:45:58,560
Speaker 2: imperative for kids as they're getting older, but certainly at

852
00:45:58,600 --> 00:46:02,400
Speaker 2: a younger age they're saying, your handwriting is really, really good.

853
00:46:03,160 --> 00:46:05,240
Speaker 2: I've got friends of mine who live around the corner

854
00:46:05,280 --> 00:46:07,520
Speaker 2: from you. I just gave their fourteen year old a

855
00:46:07,560 --> 00:46:11,239
Speaker 2: fountain pin because he was telling likes to write, and

856
00:46:11,280 --> 00:46:14,719
Speaker 2: so it's great. It was funny because I went over

857
00:46:14,760 --> 00:46:16,920
Speaker 2: to their place a few weeks ago and his fingers

858
00:46:16,920 --> 00:46:21,640
Speaker 2: were blue. The bed leaked. I'm so dodgy. Was that

859
00:46:21,719 --> 00:46:23,239
Speaker 2: an expensive one to start off with?

860
00:46:24,640 --> 00:46:27,319
Speaker 1: You know? It? Never? I mean, I don't know about you.

861
00:46:27,440 --> 00:46:30,840
Speaker 1: A couple of things here, but we we had to

862
00:46:30,960 --> 00:46:33,600
Speaker 1: use fountain pens like we had in the old days.

863
00:46:33,600 --> 00:46:36,400
Speaker 1: We had like we didn't dip it in a bloody

864
00:46:36,440 --> 00:46:40,279
Speaker 1: thing of ink, but they had these ink cartridges and

865
00:46:40,320 --> 00:46:43,719
Speaker 1: we had to write. Is it called cursive right where

866
00:46:43,760 --> 00:46:45,080
Speaker 1: all the letters are connected?

867
00:46:45,480 --> 00:46:50,480
Speaker 2: Seriously? Yeah, of course I still write cursive, do you? Yeah?

868
00:46:50,520 --> 00:46:51,120
Speaker 2: With the fountain?

869
00:46:52,000 --> 00:46:53,759
Speaker 1: Are you? And are you my mum? Are you an

870
00:46:53,800 --> 00:46:54,719
Speaker 1: eighty five year old?

871
00:46:54,840 --> 00:46:58,000
Speaker 2: I'm writing with a fountain pen. I actually have a

872
00:46:58,080 --> 00:47:01,439
Speaker 2: beautiful mont Blanc fountain pen that I write with every day.

873
00:47:02,440 --> 00:47:04,160
Speaker 1: Yeah, that's clearly.

874
00:47:04,520 --> 00:47:06,080
Speaker 2: I feel like I need to write you a letter.

875
00:47:06,760 --> 00:47:09,880
Speaker 1: I feel for fuck your letter. Don't send me a letter.

876
00:47:10,719 --> 00:47:14,799
Speaker 1: Fuck you know you're so weird. It's so weird. Hey,

877
00:47:14,960 --> 00:47:20,359
Speaker 1: but I never thought about the fact that kids might

878
00:47:20,480 --> 00:47:24,879
Speaker 1: soon stop writing. Like when you see like literally two

879
00:47:25,040 --> 00:47:29,560
Speaker 1: year olds, three year olds using computers, tablets, phones, whatever

880
00:47:30,239 --> 00:47:36,040
Speaker 1: and typing and navigating a keyboard, then I wonder if

881
00:47:36,239 --> 00:47:38,480
Speaker 1: I wonder if there's going to be a time in

882
00:47:38,520 --> 00:47:42,040
Speaker 1: the near future. You know what, he just took off

883
00:47:42,040 --> 00:47:44,320
Speaker 1: and took his headphone off. So are you going to

884
00:47:44,400 --> 00:47:46,439
Speaker 1: pretend that you know what I'm talking about? Now?

885
00:47:47,360 --> 00:47:50,400
Speaker 2: I had Fritz was trying to get out of the office,

886
00:47:50,440 --> 00:47:52,279
Speaker 2: and I thought, I hobe he might need to go

887
00:47:52,320 --> 00:47:54,200
Speaker 2: to the toilet or something, So I.

888
00:47:54,080 --> 00:47:57,239
Speaker 1: Hope he did a big dump on your fucking sofa. Hey,

889
00:47:57,960 --> 00:48:02,239
Speaker 1: I was just saying, before you took rudely, I wish

890
00:48:02,280 --> 00:48:10,279
Speaker 1: I had some fake Patrick, don't look at you. What Yeah,

891
00:48:10,320 --> 00:48:12,680
Speaker 1: you're trying to find some more fake me. I was

892
00:48:12,800 --> 00:48:14,640
Speaker 1: just saying, I wonder if we're going to get to

893
00:48:14,680 --> 00:48:17,120
Speaker 1: a time in the near future where kids don't actually

894
00:48:17,239 --> 00:48:21,080
Speaker 1: learn to write with pen and pencil anymore, because we

895
00:48:21,160 --> 00:48:23,800
Speaker 1: don't need it. The world doesn't need.

896
00:48:23,640 --> 00:48:26,479
Speaker 2: That, not in Australia. Evidently that's still a core part

897
00:48:26,520 --> 00:48:27,680
Speaker 2: of our teaching, which is great.

898
00:48:27,760 --> 00:48:29,520
Speaker 1: I know it is now, but I wonder if it'll

899
00:48:29,560 --> 00:48:33,480
Speaker 1: be in ten years. Like we're trying to eradicate paper.

900
00:48:34,320 --> 00:48:37,560
Speaker 1: We're already almost a cashless society.

901
00:48:38,320 --> 00:48:40,800
Speaker 2: But hasn't Tiff been using one of those tablets in

902
00:48:40,840 --> 00:48:43,000
Speaker 2: a pen because that's the other thing you can do.

903
00:48:43,160 --> 00:48:45,120
Speaker 2: You can just have a tablet that you can write on.

904
00:48:45,200 --> 00:48:48,040
Speaker 2: My laptop flips over and I have a little stylust

905
00:48:48,400 --> 00:48:50,759
Speaker 2: so I can take notes and write them that way.

906
00:48:51,239 --> 00:48:53,040
Speaker 2: You know, I'd played around with it for a little while.

907
00:48:53,080 --> 00:48:56,400
Speaker 2: In fact, your last conference that you did, do you

908
00:48:56,400 --> 00:48:57,920
Speaker 2: remember I went along to that and you had some

909
00:48:57,960 --> 00:48:59,840
Speaker 2: great guests speakers. Well, I took that and I was

910
00:49:00,040 --> 00:49:03,080
Speaker 2: making notes and I flipped the laptop over and I

911
00:49:03,120 --> 00:49:05,080
Speaker 2: was writing my notes on the back of it. But

912
00:49:05,120 --> 00:49:07,600
Speaker 2: it's not the same as having ink on a piece

913
00:49:07,600 --> 00:49:08,040
Speaker 2: of paper.

914
00:49:08,560 --> 00:49:12,360
Speaker 1: Hmmm, Well, think about the trees, bro, Think about the trees.

915
00:49:15,160 --> 00:49:18,160
Speaker 1: Tell people how they can come and break into your

916
00:49:19,440 --> 00:49:23,520
Speaker 1: very unsecure house in Bland and do yoga with you

917
00:49:23,560 --> 00:49:29,239
Speaker 1: and get you to build them all taichi, yoga pillarties.

918
00:49:29,280 --> 00:49:32,000
Speaker 1: It's all the same. I really need to apologize. I

919
00:49:32,040 --> 00:49:34,200
Speaker 1: was going to do a tai chie class with Patrick,

920
00:49:34,320 --> 00:49:37,799
Speaker 1: but I weaseled my way out of it. Stop it,

921
00:49:37,880 --> 00:49:41,920
Speaker 1: stop playing fake me. All right, I'm taking the piece everyone.

922
00:49:42,080 --> 00:49:48,879
Speaker 1: They're definitely not the same thing. They're all boring. Oh,

923
00:49:48,920 --> 00:49:51,040
Speaker 1: he's telling need to apologize. I was going to do

924
00:49:51,120 --> 00:49:53,680
Speaker 1: a tai chie class with Patrick, but I weaseled my

925
00:49:53,719 --> 00:49:59,000
Speaker 1: way out of it. There we go, yep, there we go.

926
00:50:00,000 --> 00:50:04,279
Speaker 1: We say, dot dot com be what smelkod doubt that

927
00:50:04,400 --> 00:50:07,600
Speaker 1: was supposed to be websites now dot com tod au.

928
00:50:07,920 --> 00:50:09,399
Speaker 2: Maybe I have to put gaps in it.

929
00:50:10,640 --> 00:50:13,040
Speaker 1: Go and type it in now, properly, Go and type

930
00:50:13,080 --> 00:50:15,000
Speaker 1: it in. I'll talk while you're doing that and see

931
00:50:15,040 --> 00:50:18,080
Speaker 1: if you can get it right this time. You really,

932
00:50:18,200 --> 00:50:22,080
Speaker 1: you've lowered your colors today.

933
00:50:21,040 --> 00:50:22,360
Speaker 2: Isn't it. Well? You know the other thing is we

934
00:50:22,480 --> 00:50:23,839
Speaker 2: normally do them earlier in the day.

935
00:50:25,640 --> 00:50:27,799
Speaker 1: I don't mind. I don't mind five o'clock. It's five

936
00:50:27,920 --> 00:50:30,800
Speaker 1: fifty and it's dark as fucking hand.

937
00:50:32,040 --> 00:50:34,440
Speaker 2: It's it's well, it's pretty dark everywhere. I guess at

938
00:50:34,480 --> 00:50:34,920
Speaker 2: the moment.

939
00:50:37,200 --> 00:50:38,880
Speaker 1: Websites now, dot com, dot a.

940
00:50:40,719 --> 00:50:43,800
Speaker 2: Not really not really spell it phonetically.

941
00:50:46,680 --> 00:50:52,080
Speaker 1: What if you just write ay dash you.

942
00:50:54,160 --> 00:50:57,000
Speaker 2: That's so weird, that is so strange. I'm gonna have

943
00:50:57,000 --> 00:50:58,839
Speaker 2: to play around with it. Look, we'll try one more time.

944
00:50:58,880 --> 00:51:00,840
Speaker 2: I'm going to move a little of the sliders and

945
00:51:00,920 --> 00:51:02,120
Speaker 2: see what happens.

946
00:51:02,239 --> 00:51:06,760
Speaker 1: Sorry, now, dot com dot a you, that's.

947
00:51:06,600 --> 00:51:09,200
Speaker 2: In terrible yea website, tod a you?

948
00:51:09,800 --> 00:51:12,200
Speaker 1: Yeah? Can you perfect that before the next one? Patrick,

949
00:51:13,640 --> 00:51:16,439
Speaker 1: this has been your worst effort. You're on your first

950
00:51:16,480 --> 00:51:19,760
Speaker 1: warning and you're on thin ice.

951
00:51:20,120 --> 00:51:24,000
Speaker 2: I'm not even going to you're gonna have you.

952
00:51:25,480 --> 00:51:28,080
Speaker 1: No, you know, here's the beauty of your pay I

953
00:51:28,080 --> 00:51:29,920
Speaker 1: can harbor or double it and you're still getting the

954
00:51:29,960 --> 00:51:34,960
Speaker 1: same welcome. Yeah, thanks for that, mate, Thanks mate,