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Speaker 1: I get a team. It's Harps and Patrick, it's you project.

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Speaker 1: For the first time in twenty twenty six, we're back.

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Speaker 1: And to those of you who are thinking to yourselves self,

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Speaker 1: where is the answer to my question that Harps asked

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Speaker 1: me to write in the group, It's coming. I apologize.

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Speaker 1: I said, I'm going to do a Q and a

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Speaker 1: pod or two, which I'm doing. I've started. I just

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Speaker 1: got a bit caught up in things, as is my way,

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Speaker 1: a little bit of Ron and Mary business, and so

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Speaker 1: the time that I put aside to record that episode

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Speaker 1: or two selfishly got taken up by Ron and Mary.

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Speaker 1: So blame them, get mad at them them. It could

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Speaker 1: never be me. Patrick. James Bonello joins me, as he

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Speaker 1: does on a regular basis. Happy New Year Champion.

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Speaker 2: Hey, it's great. This is exciting for me. I don't

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Speaker 2: think I've done the very first episode of a New

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Speaker 2: Year before because we've been doing this about three years.

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Speaker 1: We've been doing it for a while, and you are

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Speaker 1: very much part of the furniture here typ studio, the

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Speaker 1: human furniture that is you. So we're recording this on

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Speaker 1: the third, Satdy. The third will be out on Monday

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Speaker 1: the fifth. Yeah, what have you been doing?

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Speaker 2: Well? Right the second of being licked?

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Speaker 1: Wow? Yeah, And to that young man in front of you,

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Speaker 1: if you could go and make Patrick some breakfast? Oh really, Well,

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Speaker 1: you opened the door, you started.

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Speaker 2: It, but no you asked me how I've been what

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Speaker 2: I'm doing, and I'm being licked, literally being licked by

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Speaker 2: my dog. So look, it was a bit of a

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Speaker 2: traumatic day yesterday because Fritzy apparently when we went out

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Speaker 2: running at the park, he ran into something and it

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Speaker 2: sliced a gash into his chest, but I didn't notice.

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Speaker 2: He was fine. And then when he was at home

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Speaker 2: he started licking incessantly and I rolled him over and

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Speaker 2: he whimpered and there was a visible hole in his chest,

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Speaker 2: and I panicked and rushed him to the veton. So

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Speaker 2: we had a very difficult night trying to get him

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Speaker 2: to stop lick at himself. You know, ordinarily I would

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Speaker 2: encourage that because it's I'm jealous, but in this instance, so.

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Speaker 1: That's twice in one minute. You don't need to go for.

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Speaker 2: Me, one for you. That's one age. Now we can

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Speaker 2: get off that topic. So he's here next to me

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Speaker 2: in my little broadcast area, and I'm trying to get

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Speaker 2: him not to lick his wound. He's little wounds, He's

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Speaker 2: got medication and I've been bathing it in saline solution,

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Speaker 2: doing all the right things.

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Speaker 1: Nurse Patrick, Well, let's send our healing vibes a little

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Speaker 1: Fritzi and hope that he gets better quick and for Ittz,

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Speaker 1: stop licking your fucking wounds. Uncle harps here, stop licking

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Speaker 1: yourself in that area, and when the wound's better, then

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Speaker 1: you can return to business as usual with the other

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Speaker 1: leaking area, as trained by Dad. But yeah, what did

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Speaker 1: you what did you do for Christmas? You don't drink?

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Speaker 2: Right?

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Speaker 1: Do you ever drink booze? Very?

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Speaker 2: Very occasionally? I might have one little drink, you know,

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Speaker 2: have a Guinness renown again, it's a little pub that

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Speaker 2: I go to, and Fritz and I both go to actually,

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Speaker 2: and we sit in the front bar and I have

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Speaker 2: a Guinness. But that's maybe once a month. I think

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Speaker 2: I would have a drink.

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Speaker 1: I shouldn't know this, well maybe I shouldn't, but I

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Speaker 1: know beer is made from hops and shiit. What is

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Speaker 1: guinness made from? Do you know?

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Speaker 2: Probably the same thing? I reckon. It's supposed to have

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Speaker 2: lots of vitamin B in it, you know, it's that black,

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Speaker 2: dark color. And in Ireland they used to give it

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Speaker 2: to pregnant women after they had their babies because it

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Speaker 2: was restorative to their health and well being.

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Speaker 1: Let's ask to please ask, let's ask chat jp T.

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Speaker 2: All right, So in the meantime, this is not.

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Speaker 1: No, no, no, We're going to We're going to We're going

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Speaker 1: to chat to it. Ah, hey chat jp tea. What

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Speaker 1: is guinness made from?

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Speaker 3: Of course, guinness is me from four key ingredients. Water

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Speaker 3: malted barley, some of which is roasted to give it

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Speaker 3: that dark color, Hops for bitterness and flavor, and he

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Speaker 3: used for fermentation. It's the roasted barley that gives it

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Speaker 3: that signature, deep flavor and dark color.

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Speaker 1: How does it differ from beer?

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Speaker 3: A great question. So guinness is indeed a tape of beer,

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Speaker 3: but it's a stout, which is a darker, richer and

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Speaker 3: often creamier style compared to a lighter lagger or ale.

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Speaker 3: It has roasted barley, giving it more of a coffee

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Speaker 3: or chocolate note, and that creamy head comes from the

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Speaker 3: natridgen using the poor So it's just a specific delicious

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Speaker 3: category within the big world of beer.

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Speaker 2: Well, what the hell am I you for?

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Speaker 1: Yeah? You know what I love about chat GPT is

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Speaker 1: it can answer your questions but also make you feel

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Speaker 1: good by telling you what a great question you asked.

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Speaker 1: It can also it can build your self esteem while

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Speaker 1: educating you.

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Speaker 2: Yeah, and you know what make you dumber?

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Speaker 1: Why? I just learned something.

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Speaker 2: No, no, it's making you dumber. Okay, explain how an

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Speaker 2: article in the BBC I was reading just recently.

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Speaker 1: So this is not your thought. This is some one

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Speaker 1: else has thought.

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Speaker 2: Yeah, because this is research that's been done by the

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Speaker 2: Massachusetts So you're.

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Speaker 1: Doing exactly what I just did. You're outsourcing your knowledge.

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Speaker 2: No, you asked chat gbt did all the work for you.

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Speaker 2: I had to research this, go through and read an

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Speaker 2: entire article. You just asked the stupid AI chatbot.

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Speaker 1: Well, my way is just way more efficient. You're still out.

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Speaker 1: You're still going somewhere to get the answer. I went somewhere.

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Speaker 1: That's much quicker.

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Speaker 2: Yeah. Well, MIT published a study showing used chat GPT

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Speaker 2: to write essays showed less activity in the brain networks

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Speaker 2: associated with cognitive processing while undertaking that particular exercise. So

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Speaker 2: the more that we rely on AI, the less No.

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Speaker 1: No, no, stop stop stop. Stop. You just said people

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Speaker 1: who write essays. That's a very specific thing, which is

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Speaker 1: not what I am doing. So you can't extrapolate and

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Speaker 1: generalize on one thing. So what you do is you

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Speaker 1: take you take a grain of sand and go. Let

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Speaker 1: me tell you about the each right used in the

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Speaker 1: way that we do, which is, hey, we don't know something,

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Speaker 1: tell us what this is? Now we know? How is

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Speaker 1: that bad?

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Speaker 2: Well? One of the things is that by reading, do

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Speaker 2: you ever get anything wrong?

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Speaker 1: Come on, do you ever go are you ever going

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Speaker 1: to go on this show? Actually, Craig, that's a good point.

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Speaker 2: Can I give you a quote from the BBC?

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Speaker 1: And so not your quote, someone else's quote.

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Speaker 2: AI makes it too easy to find answers. Okay. So

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Speaker 2: a Carnegie mailon University in Microsoft, which I operates Copilot,

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Speaker 2: found people's problem solving skills could diminish if they become

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Speaker 2: too reliant on aim.

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Speaker 1: According to them, according to the research, why when you

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Speaker 1: read something, do you go, oh, well, now, that's what

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Speaker 1: I think?

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Speaker 2: No, I think that when you're reading an article, you're

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Speaker 2: spending more time on it and taking more in. You're

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Speaker 2: thinking through the process, reading the paragraphs, taking that information in.

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Speaker 2: We're when you're asking an AI, it's just doing the

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Speaker 2: summary for you. Everything's been done for you at least.

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Speaker 1: It isn't the point of both of them to find

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Speaker 1: out the answer to a question.

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Speaker 2: Sure, yeah it is, But the other thing is the

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Speaker 2: And this is what we kind of I mean, I guess.

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Speaker 2: AI summaries is one of the big things that came

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Speaker 2: out of twenty twenty five where first time ever Google

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Speaker 2: and look, most of us do use Google for our

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Speaker 2: online searching, and now when you do a search, it

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Speaker 2: means that you get this AI overview. And this is

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Speaker 2: a concern for websites, people who are writing news articles

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Speaker 2: because what we found is that between sixty and seventy

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Speaker 2: percent of people are now no longer going to the

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Speaker 2: actual website where the content's from. They're just relying on

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Speaker 2: the AI overview information. And the big concern is that

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Speaker 2: sometimes that AI overview is actually wrong. And this is

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Speaker 2: the big concern because people are getting their news from

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Speaker 2: AI and they're reading the summer summary, but they're not

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Speaker 2: delving any deeper into it, and they're relying on that

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Speaker 2: and AI is wrong quite often, it can be wrong,

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Speaker 2: and that could mean critical things for people if they're

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Speaker 2: researching things like you know, with my cancer treatment, should

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Speaker 2: I be doing X, Y Z. And these are specific

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Speaker 2: examples I was reading about where the concerns are that

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Speaker 2: people are relying on it too heavily, and particularly medical

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Speaker 2: advice is something that you know, you want to make

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Speaker 2: sure you're getting that from a legitimate site, which is

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Speaker 2: a medical authority or health government health authority, rather than

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Speaker 2: just relying on an overview. So it is concerning. And look,

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Speaker 2: I love the fact that AI is here and can

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Speaker 2: do some great things. I've got to go to a

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Speaker 2: funeral service next week, and you know, I'm putting together

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Speaker 2: the booklet for the service, and there was a photo,

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Speaker 2: a family photo that my cousin gave to me, and

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Speaker 2: there were two people in the family that weren't in

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Speaker 2: the photo, and so she said, look, can you put

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Speaker 2: those people into the photograph? And I was able to

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Speaker 2: put it together. And the reality of it is, you know,

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Speaker 2: traditionally I would have to have cut out all the

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Speaker 2: people from the photo using traditional photoshop tools, which is

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Speaker 2: quite priceiss and one of the difficult things, not so

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Speaker 2: much for you and I, because we you know, in

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Speaker 2: your case, you've got cropped hair. In my case, I

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Speaker 2: have none, so cutting us out of a photograph is

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Speaker 2: pretty easy. But for somebody who's got lushes long lengths

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Speaker 2: of air, it actually is really difficult to cut the

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Speaker 2: hair out. But now AI allows you to instantly remove

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Speaker 2: backgrounds and then you can layer that, put new people in,

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Speaker 2: arrange them around, take the backgrounds, put the background back

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Speaker 2: in again, and suddenly you've got this family photo. And

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Speaker 2: it was great to be able to use those tools

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Speaker 2: which normally would have taken me ours. So yeah, I

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Speaker 2: use stacks of AI and it's great in some applications.

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Speaker 1: Yeah, I think there are pros and cons for everything.

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Speaker 1: But I think back just quickly to the AI summaries. Yeah, well,

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Speaker 1: I think everybody knows we don't get our health advice

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Speaker 1: from the end to that period, do we. I mean,

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Speaker 1: who's going, I'm not going to a doctor. But hang on,

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Speaker 1: how studio like you can get misinformation and you do everywhere.

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Speaker 1: It's not just AI summaries, it's YouTube, it's Instagram, it's Facebook,

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Speaker 1: it's every fucking post that every person puts up. So

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Speaker 1: I think to go, you know, like, you can go

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Speaker 1: to actual websites and get bullshit because they sell bullshit

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Speaker 1: and promote bullshit, and they've got a vested interest in

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Speaker 1: you buying what they're selling. So I think to assume that,

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Speaker 1: you know, like I agree with you, but I think,

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Speaker 1: but that's just that's you know, everywhere like to be

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Speaker 1: able to if you're going to any website that sells anything,

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Speaker 1: then you're not getting objectivity. You're getting a version of

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Speaker 1: a sales pitch. And most most websites that we go

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Speaker 1: to are commercial, you know, like it's not like it's

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Speaker 1: just this amazing resource that nobody's making money from.

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Speaker 2: I guess the one thing that I was saying before

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Speaker 2: is that like for specific things like medical advice, legal advice,

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Speaker 2: there's certainly are legitimate sites that you can go to.

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Speaker 2: I would go to a government and even if you

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Speaker 2: look at the extension of a website, is that if

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Speaker 2: it's a dot gov, dot au, then you know that

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Speaker 2: it's a government site. You know, if you want a

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Speaker 2: specific weather related information, you go to the Weather Bureau,

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Speaker 2: you know, for information there, or for help to a

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Speaker 2: medical site. So I think it's discerning where you are

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Speaker 2: in relation to the type of information that you're getting.

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Speaker 2: But you're right, that is a difficult thing to kind

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Speaker 2: of discern because there's so much slop out there. That

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Speaker 2: was the word of the year. Remember AI slop was

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Speaker 2: one of the dictionaries, the big Dictionaries word of the year.

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Speaker 2: And if you create a new YouTube account right now,

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Speaker 2: so you've never used YouTube, so you jump on and

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Speaker 2: you create a new account to start using YouTube. From

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Speaker 2: absolute scratch, twenty percent of video is more than twenty

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Speaker 2: percent of videos that you will be shown. You know

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Speaker 2: when you start scrolling through your feed, well, twenty percent

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Speaker 2: more than twenty will be AI slop. There's guaranteed, so

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Speaker 2: you know already one in five will be you know,

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Speaker 2: this generated AI stuff. Do you when you flick through

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Speaker 2: and whether it's X or any of those, do you

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Speaker 2: struggle with that? Do you look at that and think

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Speaker 2: to yourself, am I looking at something that's real? Is

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Speaker 2: this fake? Is that something that's a concern for you?

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Speaker 1: Well, yeah, but I don't worry about it. I don't

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Speaker 1: believe it's like even when you go the government, do

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Speaker 1: you think the government doesn't get shit wrong? Do you

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Speaker 1: think that everything on government websites is like I just

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Speaker 1: think it's not about being negative or I'm not anti

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Speaker 1: government at all. I thank God for the government, we'd

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Speaker 1: be living in fucking whatever, you know, But the government

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Speaker 1: gets stuff wrong, the government gets stuff right. I think

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Speaker 1: the reality like putting aside whatever the medium is or

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Speaker 1: the delivery system, be it Facebook, be at x, be

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Speaker 1: it Instagram, be at a government website. The human experience

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Speaker 1: is we get things wrong. We give Have I ever

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Speaker 1: gotten things wrong every fucking day of my life? Have

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Speaker 1: I ever said things that aren't true every day of

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Speaker 1: my life? Have I ever misled people unintentionally a million times?

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Speaker 1: So I think that we need to go you know, like,

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Speaker 1: if you've got the two one hundred episodes of this show,

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Speaker 1: I would say on every episode, we've said something that

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Speaker 1: was bullshit, if not once, ten times on each episode.

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Speaker 1: So this kind of thing that we have of oh,

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Speaker 1: that's good over there and this is bad over here,

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Speaker 1: I think you've got to turn down the volume on

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Speaker 1: that because to say, oh, and it always with me

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Speaker 1: and I am literally a fucking researcher at a PhD level.

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Speaker 1: I don't like to play that card. But when people

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Speaker 1: go sixty percent of this, really it's not fifty seven,

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Speaker 1: it's not sixty two. I'm not talking about you, by

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Speaker 1: the way, but there are all of these very convenient

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Speaker 1: research kind of numbers that come out. I was talking

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Speaker 1: with somebody the other day about a particular thing in

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Speaker 1: big farm, this particular drug and the efficacy of this drug.

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Speaker 1: And you know when you go through it. I was

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Speaker 1: talking with David Gillespie about treatment for cholesterol, right, And

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Speaker 1: then you start digging and you go, yeah, this is

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Speaker 1: science and it is science, and you can read the

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Speaker 1: report and you can read the paper and you go, fuck,

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Speaker 1: but this is in this journal. This is a Tier one,

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Speaker 1: very credible Q one journal. And then you dig and

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Speaker 1: you dig and you dig and you go, oh, this

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Speaker 1: is financed by big farmer, which it was, and then

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Speaker 1: you go, oh, but it's science. You go no, no,

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Speaker 1: Like people get too hysterical about the validity of science.

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Speaker 1: It's like, you've got to remember this, who designed the study,

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Speaker 1: a human who's financing the study big farmer? Well as

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Speaker 1: if they want you to produce outcomes that make them

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Speaker 1: look bad when they are literally paying your fucking wage, right,

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Speaker 1: so you have and who interpreted the data. Oh, and

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Speaker 1: for this one study we spoke about, they wouldn't reveal

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Speaker 1: the data because the data disproved their theory, their hypothesis.

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Speaker 1: So what they did was they just revealed the interpretation

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Speaker 1: of the scientists of the data, right. But for the

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Speaker 1: average panta, we go, Oh, Craig said this. Craig's smart.

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Speaker 1: So this is how it is. No, Craig's not smart.

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Speaker 1: Craig's a fucking human who gets things wrong all the time.

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Speaker 1: Scientists get things wrong all the time. Over the years,

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Speaker 1: we've constantly been you know, like low fad eating in

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Speaker 1: the early seventies was meant to revolutionize the health state

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Speaker 1: of all First world countries, and in fact, what it's

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Speaker 1: done since the fifties or since the seventies, there's been

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Speaker 1: an increase in obesity and obesity related diseases. Sense the

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Speaker 1: introduction of low fat food because low fat food equaled

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Speaker 1: high sugar food, right, And so which is not to

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Speaker 1: say donat carbs or donat sugar. It's just to say

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Speaker 1: that science is constantly getting it wrong. When the pandemic struck,

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Speaker 1: it was estimated one hundred and fifty thousand Australians would die.

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Speaker 1: It was on the front of the paper, it was

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Speaker 1: on the Herald Sun, and it was on the age

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Speaker 1: and this was this was the estimates by the best

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Speaker 1: scientist virologist, except they got it wildly fucking wrong. Nobody

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Speaker 1: comes out and goes, oh, you know that thing we said,

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Speaker 1: we fucked up right, This is the world that we

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Speaker 1: live in. Politicians tell me a politician who comes out

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Speaker 1: and goes, that thing that we did, we got it wrong.

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Speaker 1: That thing that we said, we got it wrong. So

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Speaker 1: I think, like, for me, I'm I'm not I read

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Speaker 1: everything and I pay attention or everything I can, and

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Speaker 1: I pay attention, but I'm more about let me see

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Speaker 1: the results over time. So rather than going, oh, I

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Speaker 1: read this here and it said that, therefore that's true,

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Speaker 1: I'm like no, or I heard this, therefore that's true.

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Speaker 1: I'm like maybe maybe. And I just think that that

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Speaker 1: assigning a certain value or worth or respect to something

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Speaker 1: just because someone said it to me, I think is

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Speaker 1: actually the opposite of critical thinking. Like I think, like,

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Speaker 1: you're super smart, and I'm not saying that disingenuously. You're

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Speaker 1: super smart, and I think that all of us have

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Speaker 1: the ability to go, all right, this is what they said,

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Speaker 1: but let me And by the way, research is not

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Speaker 1: reading a paper that someone wrote that's not research and

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Speaker 1: watching a video that's not research. Research is actually research,

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Speaker 1: you know, steps down off soapbox. But that's all I think.

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Speaker 1: I just get I get frustrated when people go, oh,

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Speaker 1: you're wrong because I read this here. I'm like, well, fuck, okay,

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Speaker 1: let's see over time.

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Speaker 2: Look. One of the interesting things is I trained to

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Speaker 2: be a journalist. We were told never to believe one source.

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Speaker 2: That you check multiple sources, You interview more than one

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Speaker 2: person on the topic, You get both sides of the story,

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Speaker 2: try to get as much information in so that you

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Speaker 2: could give both sides, you know. And that's where I

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Speaker 2: think a lot of the mainstream media has diverged a lot.

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Speaker 2: If you look at Sky Television for example, and look

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Speaker 2: at some of the extreme more extreme you know, reporting,

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Speaker 2: and there's lots of reasons for that. I think that

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Speaker 2: one of the challenges for journalism now is that, you know,

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Speaker 2: there's less resources going into journalism because people are now

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Speaker 2: using Facebook to disseminate information, people using X to seminate information.

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Speaker 2: So the checks and measures aren't there anymore. There's no editors,

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Speaker 2: there's no sub editors that are deciding that this person

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Speaker 2: who's on X is being vetted in any way. And

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Speaker 2: that's problematic because you know, if you go down that

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Speaker 2: rabbit hole, X will continue to serve up the same stuff.

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Speaker 2: That is, you know, they just want to keep you

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Speaker 2: there as long as you can, whether it's Facebook or X.

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Speaker 2: And that way, the information you're being given, it may

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Speaker 2: not be credible, but it will keep serving it up

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Speaker 2: if you keep clicking on it, and it will try

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Speaker 2: to keep you. So, if your rabbit hole is the

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Speaker 2: Earth is actually legitimately flat, that and I know somebody

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Speaker 2: who has a sibling who dead set believes the world

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Speaker 2: is flat, absolutely black and blue believes the world is flat.

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Speaker 1: And I have a friend who believes the world is flat.

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Speaker 1: And you know this friend. I won't say this person's name,

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Speaker 1: but i'll tell you after. I have a good friend

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Speaker 1: who they are going further and further. They're not one

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Speaker 1: hundred percent, but they're about ninety percent sure the Earth's flat.

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Speaker 1: I'm like, oh, okay, okay, like all right and all that.

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Speaker 1: You know, Yeah, go on, though, but if.

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Speaker 2: You if you then mix with those Facebook groups, if

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Speaker 2: you if you're a flat earther and then you talk

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Speaker 2: to other flat earth you're going to have that reinforced constantly.

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Speaker 2: But with social media, So I would talk to you

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Speaker 2: you reinforce my mindset. But what happened on social media

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Speaker 2: is it's got an algorithm that's built into it to

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Speaker 2: keep serving that up. So it's not just me catching

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Speaker 2: up with Craig over a beer and you say, yeah,

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Speaker 2: the world is definitely flat and I say, well, Craig

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Speaker 2: reckons it is. So there you go. Now you've got

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Speaker 2: all these voices in the wilderness, and then your algorithm

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Speaker 2: just serves you up that. So if you're far left

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Speaker 2: or far right, then you're going to get more far

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Speaker 2: left or far right information via your social media. Because

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Speaker 2: the big thing to bear in mind with socials is

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Speaker 2: that it's not government vetted, it's not government run. It's

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Speaker 2: run by corporations that just want to make advertising revenue.

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Speaker 2: That's all there about the AI slop we were talking

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Speaker 2: about before on YouTube, so you sign up to get

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Speaker 2: onto YouTube for the first time, twenty percent of videos

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Speaker 2: are going to be AI slop. But last year AI

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Speaker 2: slop general id one hundred and seventeen million dollars US

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Speaker 2: a year in ad revenue. That's why people are generating

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Speaker 2: the crap because they've got money out of.

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Speaker 1: It, of course, but also think you're exactly right but

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Speaker 1: also Patrick James Kevin, Patrick James Bonello think about this.

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Speaker 1: So you go, oh, when I open I start watching

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Speaker 1: fucking you know, videos on how I'm going to heal

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Speaker 1: my exma, and I get all these weird products from

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Speaker 1: the Amazon, and then I keep getting more and more

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Speaker 1: and then this one will heal my fucking whatever. Right,

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00:21:34,520 --> 00:21:38,760
Speaker 1: and it's all similar stuff from So it's like, now

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00:21:38,800 --> 00:21:41,840
Speaker 1: you're in this echo chamber, but walk away from the

400
00:21:41,920 --> 00:21:44,560
Speaker 1: virtual world and the Internet. And then you go into

401
00:21:44,600 --> 00:21:48,600
Speaker 1: a church. What do you hear everybody preaching the same message,

402
00:21:48,640 --> 00:21:51,960
Speaker 1: telling you the same thing, and if anybody questions that message,

403
00:21:52,000 --> 00:21:54,240
Speaker 1: you're bad, You're evil, You're going to hell. You go

404
00:21:54,359 --> 00:21:58,040
Speaker 1: to a synagogue, same except without the Jesus bit, right.

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00:21:58,480 --> 00:22:02,120
Speaker 1: You go to a Buddhist temple where, well they're you know,

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Speaker 1: they they don't really have a god per se, they

407
00:22:05,800 --> 00:22:09,200
Speaker 1: don't have a deity. You go to a Carlton football club, Well,

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00:22:09,240 --> 00:22:12,959
Speaker 1: Collingwood fans are fucking idiots, right. It's like the world

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00:22:13,080 --> 00:22:17,000
Speaker 1: is full of these echo chambers where you essentially belong

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Speaker 1: to a group, whether or not you chose it, you

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Speaker 1: belong to a group who keeps reinforcing the same message,

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Speaker 1: and if you question the message, then you're somehow penalized.

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Speaker 1: This is how people control and manipulate and coerce and

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Speaker 1: get the outcomes they want. And I grew up very

415
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Speaker 1: much in an echo chamber of theology and philosophy, where

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Speaker 1: if I questioned anything, I was basically criticized and humiliated

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Speaker 1: and all of these things, and so was everyone, by

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Speaker 1: the way, And that's how you control people. And that's

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00:22:53,480 --> 00:22:56,920
Speaker 1: how you manipulate people. Is you go, no, there's only one.

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Speaker 1: It's like when people go to me, what's the best way? Okay,

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Speaker 1: So if I am an expert in anything, it's probably

422
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Speaker 1: exercise science, what's the best way to achieve this outcome

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Speaker 1: with my body? And I go, well, there actually is

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Speaker 1: an a best way. There's probably one hundred and sixty

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00:23:10,920 --> 00:23:13,640
Speaker 1: seven different best ways, depending on your body, your genetics,

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Speaker 1: your background, your medical state, your chronological your biological agent.

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Speaker 1: So the idea that there's a best way, we need

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Speaker 1: to dispense with that. It's like you and the way

429
00:23:24,200 --> 00:23:26,280
Speaker 1: that you live. So you're a single bloke, you live

430
00:23:26,320 --> 00:23:31,640
Speaker 1: in the country. You like blokes, right, that's not good

431
00:23:31,720 --> 00:23:35,000
Speaker 1: or bad. That's how you live. Right, for you, living

432
00:23:35,040 --> 00:23:39,199
Speaker 1: with your dog, having a great social network, having life

433
00:23:39,880 --> 00:23:42,800
Speaker 1: and work that for you is meaningful and purposeful. I

434
00:23:42,880 --> 00:23:44,960
Speaker 1: know you're not driven by money. You need to make

435
00:23:45,000 --> 00:23:46,719
Speaker 1: money because you've got to pay the bills, but I

436
00:23:46,760 --> 00:23:51,040
Speaker 1: know that you know for you, you're more about emotional and

437
00:23:51,200 --> 00:23:54,639
Speaker 1: I guess spiritual and social connection and that's kind of

438
00:23:54,720 --> 00:23:57,920
Speaker 1: your bank account right now. That's perfect for you. It's

439
00:23:57,960 --> 00:24:01,600
Speaker 1: going to be the worst model ever for some other bloke. Yeah, right,

440
00:24:01,840 --> 00:24:05,199
Speaker 1: So we're all trying to find like what is in

441
00:24:05,240 --> 00:24:08,040
Speaker 1: the middle of the myriad of ways that we can

442
00:24:08,119 --> 00:24:11,240
Speaker 1: live and think and do and be. Not what's the

443
00:24:11,320 --> 00:24:13,840
Speaker 1: right way, but what's the best way for me based

444
00:24:13,880 --> 00:24:17,400
Speaker 1: on who I am. And so it's like I haven't

445
00:24:17,400 --> 00:24:19,520
Speaker 1: had a job since I was twenty four, Would I

446
00:24:19,560 --> 00:24:24,359
Speaker 1: recommend that? Definitely? Not if you're a clone of me, yes,

447
00:24:25,200 --> 00:24:28,000
Speaker 1: But if you're not, which nobody is, will then figure

448
00:24:28,000 --> 00:24:30,520
Speaker 1: it out for yourself. But what I'll do is I

449
00:24:30,560 --> 00:24:32,239
Speaker 1: will tell you what I did and how I did

450
00:24:32,280 --> 00:24:34,439
Speaker 1: it and why I did it, and I'll tell you

451
00:24:34,480 --> 00:24:37,840
Speaker 1: what my outcomes were. But then, because you're not me,

452
00:24:37,960 --> 00:24:40,480
Speaker 1: you're going to think for yourself and you're going to

453
00:24:40,600 --> 00:24:42,800
Speaker 1: maybe try a couple of things and see what the

454
00:24:42,840 --> 00:24:45,480
Speaker 1: outcome is, and then based on your own data and experience,

455
00:24:45,960 --> 00:24:49,120
Speaker 1: you'll figure out the best model for you. Craig Harper

456
00:24:49,200 --> 00:24:52,040
Speaker 1: cannot tell you what is the path for you because

457
00:24:52,119 --> 00:24:54,159
Speaker 1: I'm not you and you're not me, you know, And

458
00:24:54,200 --> 00:24:57,800
Speaker 1: I think that's true for everything from how should I eat?

459
00:24:58,119 --> 00:25:00,760
Speaker 1: To what's the best way for me to learn? What's

460
00:25:00,800 --> 00:25:04,920
Speaker 1: the best relationship kind of paradigm for me? Is living

461
00:25:04,960 --> 00:25:07,000
Speaker 1: in the country good for me? I know people have

462
00:25:07,040 --> 00:25:08,760
Speaker 1: moved to the country to have a kind of a

463
00:25:09,680 --> 00:25:12,040
Speaker 1: what do they call it a tree change, and they're

464
00:25:12,040 --> 00:25:14,760
Speaker 1: back in fucking twelve months they go fuck the country

465
00:25:15,160 --> 00:25:17,200
Speaker 1: and then you go up there, you're like, this is

466
00:25:17,240 --> 00:25:18,040
Speaker 1: the best shit ever.

467
00:25:18,560 --> 00:25:20,800
Speaker 2: Yeah, seventeen years.

468
00:25:21,320 --> 00:25:24,440
Speaker 1: That's it, mate. It's just everyone trying to figure out

469
00:25:24,680 --> 00:25:28,000
Speaker 1: how they best fit and how they best work. In

470
00:25:28,040 --> 00:25:31,600
Speaker 1: the middle of all of this overwhelm of you should

471
00:25:31,600 --> 00:25:34,200
Speaker 1: do this, you should do that, you shouldn't do those things.

472
00:25:35,280 --> 00:25:38,479
Speaker 2: Yeah, it's interesting. I know people who bought in the

473
00:25:38,480 --> 00:25:41,159
Speaker 2: town that I live in during COVID they did the

474
00:25:41,160 --> 00:25:43,479
Speaker 2: tree change, They got out of the Ring of Steel

475
00:25:43,640 --> 00:25:45,760
Speaker 2: and they did the move and then they moved back

476
00:25:45,800 --> 00:25:48,919
Speaker 2: to Melbourne. Yeah, they just don't you know. The lifestyle

477
00:25:49,040 --> 00:25:51,760
Speaker 2: is just not to their liking. They don't have a

478
00:25:51,920 --> 00:25:54,879
Speaker 2: ray of cafes to go down to and have their

479
00:25:55,480 --> 00:25:56,600
Speaker 2: avocado on toast.

480
00:25:57,880 --> 00:26:00,560
Speaker 1: Listen to you, listen to you. But I mean, but

481
00:26:00,640 --> 00:26:04,880
Speaker 1: that's okay. Yeah, like not everyone. It's like I say

482
00:26:04,880 --> 00:26:07,200
Speaker 1: to people all the time, don't fucking do what I do,

483
00:26:07,880 --> 00:26:10,520
Speaker 1: like you would hate it, Like it works for me,

484
00:26:10,760 --> 00:26:13,679
Speaker 1: And I don't think, oh, Craig's got it right. I

485
00:26:13,760 --> 00:26:15,760
Speaker 1: look at people who go out and get shit faced

486
00:26:15,760 --> 00:26:19,240
Speaker 1: and talk all night for seven hours and fucking party

487
00:26:19,280 --> 00:26:20,960
Speaker 1: on and have the best time, and part of me

488
00:26:21,040 --> 00:26:23,000
Speaker 1: is a bit jealous. I definitely don't want to do

489
00:26:23,080 --> 00:26:25,919
Speaker 1: that because I'm not wired that way. But I definitely

490
00:26:26,000 --> 00:26:27,720
Speaker 1: look at people who do that and have the best

491
00:26:27,720 --> 00:26:30,160
Speaker 1: time ever and go fuck good for them. That's amazing.

492
00:26:30,480 --> 00:26:32,080
Speaker 2: That's their idea of a good time. I went to

493
00:26:32,080 --> 00:26:34,840
Speaker 2: bed at ten o'clock on New Year's Eve. I had

494
00:26:34,840 --> 00:26:37,280
Speaker 2: some friends over. We played some board games, had a

495
00:26:37,280 --> 00:26:40,600
Speaker 2: bit of a laugh, listened to some vinyl records. I

496
00:26:40,680 --> 00:26:43,880
Speaker 2: managed to draw some vinyl records from a neighbor recently,

497
00:26:44,000 --> 00:26:49,280
Speaker 2: including Elton John's Yellow Brick Road eight, an eight box

498
00:26:49,320 --> 00:26:53,000
Speaker 2: set of the Beatles, and the record we were listening

499
00:26:53,000 --> 00:26:57,880
Speaker 2: to was seventies disco music. It was great. So and

500
00:26:57,920 --> 00:27:00,359
Speaker 2: then I went to bed like just after ten clock.

501
00:27:00,560 --> 00:27:03,000
Speaker 2: You know, I'm not a New Year's Eve person. Well,

502
00:27:03,160 --> 00:27:04,960
Speaker 2: I guess you had an early night too, I'm assuming

503
00:27:05,119 --> 00:27:05,280
Speaker 2: you know.

504
00:27:05,560 --> 00:27:07,920
Speaker 1: Yeah, yeah, I did fuck all. I did fuck all.

505
00:27:07,960 --> 00:27:10,520
Speaker 1: I was like, to me, it was Wednesday or Thursday

506
00:27:10,560 --> 00:27:13,879
Speaker 1: or whatever it was, But that's okay. It's like I

507
00:27:13,920 --> 00:27:16,800
Speaker 1: was talking with somebody about this, max this morning. In fact,

508
00:27:16,840 --> 00:27:18,920
Speaker 1: I out of coffee with Maxie shout out to Maxie

509
00:27:18,920 --> 00:27:22,440
Speaker 1: and yeah, like you mate, you go. I'm well aware

510
00:27:22,520 --> 00:27:24,439
Speaker 1: that the way that I do things is not the

511
00:27:24,480 --> 00:27:27,560
Speaker 1: way most people should. And I don't think I'm better

512
00:27:27,640 --> 00:27:32,240
Speaker 1: or worse or special or I just know that. You know, firstly,

513
00:27:33,640 --> 00:27:36,280
Speaker 1: I'm an old bloke who lives by himself. Don't fucking

514
00:27:36,320 --> 00:27:39,639
Speaker 1: do what I do. It's like most people that listen

515
00:27:39,680 --> 00:27:42,119
Speaker 1: to this show are not a version of me. So

516
00:27:42,200 --> 00:27:45,480
Speaker 1: that's why, you know, I'm so fascinated with theory of mind,

517
00:27:45,520 --> 00:27:50,640
Speaker 1: which is understanding other people's mind, understanding how other people think. Like,

518
00:27:50,840 --> 00:27:53,680
Speaker 1: I'm not even that interested in the Craig experience. I'm

519
00:27:53,720 --> 00:27:55,760
Speaker 1: more interested in why does Patrick think the way that

520
00:27:55,800 --> 00:27:57,399
Speaker 1: he has? Why does he do this? And that? Not

521
00:27:57,440 --> 00:28:01,479
Speaker 1: good or bad? No judgment, just curiosity, just awareness, Like

522
00:28:01,880 --> 00:28:04,280
Speaker 1: what is it like for our listeners when you and

523
00:28:04,320 --> 00:28:06,920
Speaker 1: I argue? And I love when we argue, by the way,

524
00:28:07,080 --> 00:28:09,560
Speaker 1: I'm glad that we don't fucking agree on everything? Right?

525
00:28:10,240 --> 00:28:10,359
Speaker 2: Like?

526
00:28:10,440 --> 00:28:12,679
Speaker 1: What's that like for them? I think even when you

527
00:28:12,720 --> 00:28:15,199
Speaker 1: and I going at it, I think, uh, is this

528
00:28:15,280 --> 00:28:18,119
Speaker 1: good to listen to? Is this shit to listen to?

529
00:28:18,880 --> 00:28:25,040
Speaker 1: You know? That other awareness, that kind of that kind

530
00:28:25,040 --> 00:28:28,920
Speaker 1: of external self awareness it's called as well as metaperception

531
00:28:29,040 --> 00:28:32,639
Speaker 1: of trying to have an understanding of what something is

532
00:28:32,800 --> 00:28:36,640
Speaker 1: like for somebody else. You know, for me that's that's

533
00:28:36,680 --> 00:28:40,280
Speaker 1: a fascination, but for other people understandably, they're like, shut

534
00:28:40,280 --> 00:28:41,800
Speaker 1: the fuck up, past me a beer.

535
00:28:43,320 --> 00:28:46,600
Speaker 2: You know, yeah, it's I was actually just thinking in

536
00:28:46,640 --> 00:28:50,480
Speaker 2: relation to, you know, where we're heading in the future,

537
00:28:50,920 --> 00:28:54,360
Speaker 2: and how some of us are attracted to the likes

538
00:28:54,360 --> 00:28:57,560
Speaker 2: of say technology, and other people are resistant to it.

539
00:28:57,760 --> 00:28:59,960
Speaker 2: And sometimes you can put it into an age Brad.

540
00:29:00,160 --> 00:29:02,240
Speaker 2: You can say, well, young people have grown up with tech,

541
00:29:02,560 --> 00:29:05,600
Speaker 2: but I'm not a young person. You know, there weren't

542
00:29:05,600 --> 00:29:08,280
Speaker 2: computers around when I first went to school, and yet

543
00:29:08,400 --> 00:29:11,960
Speaker 2: I love tech, you know. And I have people, my peers,

544
00:29:12,360 --> 00:29:15,720
Speaker 2: who say, oh, I'm technically illiterate. That's your choice to

545
00:29:15,760 --> 00:29:18,960
Speaker 2: be technically illiterate. But I get it because you're now

546
00:29:19,080 --> 00:29:21,440
Speaker 2: comfortable with it. You don't like it. But for me,

547
00:29:22,000 --> 00:29:24,360
Speaker 2: you know, I think I've told this story before, and

548
00:29:24,400 --> 00:29:25,960
Speaker 2: I know I'm getting off topic a little bit, But

549
00:29:26,320 --> 00:29:29,360
Speaker 2: when I was a kid, we got our first VHS

550
00:29:29,520 --> 00:29:32,239
Speaker 2: video recorder. It was an Achi and it cost a

551
00:29:32,280 --> 00:29:34,680
Speaker 2: real lot of money. Do you remember the story? Yeah?

552
00:29:34,880 --> 00:29:38,360
Speaker 1: No, I remember though. My old man used to anyway

553
00:29:38,720 --> 00:29:42,240
Speaker 1: run a store where we sold those Ai vhs.

554
00:29:42,320 --> 00:29:44,840
Speaker 2: Yeah, they were expensive. They were over one thousand dollars

555
00:29:45,000 --> 00:29:48,200
Speaker 2: at that time, so we're talking in what the early eighties.

556
00:29:48,560 --> 00:29:50,720
Speaker 2: You were paying over one thousand dollars. That's a lot

557
00:29:50,720 --> 00:29:53,840
Speaker 2: of money for a working class family in Coburg. So

558
00:29:53,960 --> 00:29:57,000
Speaker 2: Dad buys this Achai and it also had things on screen,

559
00:29:57,120 --> 00:29:59,400
Speaker 2: so the counter was on screen whether we're going forward

560
00:29:59,480 --> 00:30:01,600
Speaker 2: or backward. It was very high tech at the time.

561
00:30:02,000 --> 00:30:04,160
Speaker 2: So the first week we had it, Mum and Dad

562
00:30:04,160 --> 00:30:06,200
Speaker 2: get in the car to go shopping on a Saturday morning.

563
00:30:06,320 --> 00:30:10,920
Speaker 2: Patrick gets the screwdriver out because I couldn't cope not

564
00:30:11,120 --> 00:30:14,160
Speaker 2: knowing what was inside and how the mechanism worked. So

565
00:30:14,200 --> 00:30:16,760
Speaker 2: I'm in the poor sucker and I've got all the

566
00:30:16,800 --> 00:30:19,360
Speaker 2: screws out, I've got a handful of screws, I've got

567
00:30:19,360 --> 00:30:21,640
Speaker 2: the cover off, and then Mum and Dad pulled back

568
00:30:21,680 --> 00:30:24,200
Speaker 2: into the driveway. It's like, fuck, what am I going

569
00:30:24,280 --> 00:30:26,360
Speaker 2: to do? So I throw the cover back on, put

570
00:30:26,400 --> 00:30:28,320
Speaker 2: all the screws in the pocket and look guilty as

571
00:30:28,320 --> 00:30:30,120
Speaker 2: shit when they walk back in, because Mum had left

572
00:30:30,120 --> 00:30:33,160
Speaker 2: her purse and that's the reason they'd come back so quickly.

573
00:30:33,480 --> 00:30:35,560
Speaker 2: And of course there's no way they knew what I

574
00:30:35,640 --> 00:30:39,000
Speaker 2: was doing. I mean, I'd hidden the screwdriver and the bolt,

575
00:30:39,040 --> 00:30:41,720
Speaker 2: the screws are all in the pocket. But Jesus shited myself.

576
00:30:41,760 --> 00:30:45,680
Speaker 2: And then anyway, old, how old were you? Maybe thirty one?

577
00:30:47,960 --> 00:30:50,600
Speaker 2: Probably about thirteen or fourteen, I guess at that time?

578
00:30:51,720 --> 00:30:54,640
Speaker 1: Did you fuck it up? Or did you successfully reassemble it?

579
00:30:54,680 --> 00:30:56,280
Speaker 2: Okay? I can tell you that I put it all

580
00:30:56,320 --> 00:30:58,680
Speaker 2: back together again, but there was one screw left over,

581
00:30:58,720 --> 00:31:03,400
Speaker 2: but that happens with everything ever taken. And not only

582
00:31:03,400 --> 00:31:06,280
Speaker 2: did it keep working when I finally moved out of home,

583
00:31:06,640 --> 00:31:09,240
Speaker 2: like a decade later they gave it to me to

584
00:31:09,280 --> 00:31:10,960
Speaker 2: take with me because it still worked.

585
00:31:11,520 --> 00:31:16,040
Speaker 1: It's hilarious. Hey, you tell me about on my little

586
00:31:16,040 --> 00:31:19,520
Speaker 1: list of things that we haven't covered of yours hiring

587
00:31:19,560 --> 00:31:20,160
Speaker 1: a robot.

588
00:31:20,880 --> 00:31:24,640
Speaker 2: Yes, so in China, if you're having a meeting or

589
00:31:24,680 --> 00:31:28,360
Speaker 2: a wedding, you cannot now hire a robot. So there's

590
00:31:28,360 --> 00:31:33,960
Speaker 2: a Chinese firm called Aggie Bot and they're humanoid robot rentals.

591
00:31:34,400 --> 00:31:38,000
Speaker 2: So the price of the rental is dependent on what

592
00:31:38,080 --> 00:31:40,640
Speaker 2: the robot model is and what you wanted to do.

593
00:31:41,280 --> 00:31:44,000
Speaker 2: But they're actually entering the economy in a big way.

594
00:31:44,480 --> 00:31:48,040
Speaker 2: They're not cheap. But basically this has only just happened,

595
00:31:48,080 --> 00:31:49,400
Speaker 2: so this is going to be new. So for a

596
00:31:49,400 --> 00:31:53,040
Speaker 2: lot of people, there's sixteen different event duties that they

597
00:31:53,120 --> 00:31:58,560
Speaker 2: can be deployed for, so weddings, business meetings, concerts, trade shows.

598
00:31:59,760 --> 00:32:04,640
Speaker 2: The Chinese rental market is fascinating. So rather than buying

599
00:32:04,680 --> 00:32:06,880
Speaker 2: a robot, you pay about one hundred and thirty eight

600
00:32:06,920 --> 00:32:11,000
Speaker 2: dollars a day US and you can like, if it's

601
00:32:11,040 --> 00:32:13,320
Speaker 2: a robot dog, it's going to cost you one hundred

602
00:32:13,320 --> 00:32:15,360
Speaker 2: and thirty eight bucks. But if you wanted a one

603
00:32:15,360 --> 00:32:17,480
Speaker 2: of the have you seen the Uni tree U two

604
00:32:17,640 --> 00:32:21,040
Speaker 2: dancing robots. They're awesome, they look fantastic. That's going to

605
00:32:21,080 --> 00:32:24,280
Speaker 2: cost you about six hundred and ninety dollars per day. Okay,

606
00:32:24,360 --> 00:32:27,080
Speaker 2: so wow, This really depends on what you want the

607
00:32:27,240 --> 00:32:29,880
Speaker 2: robot dog to do or the robot dancer to do.

608
00:32:30,360 --> 00:32:33,240
Speaker 2: But how interesting is that? I reckon? I would do that? Definitely.

609
00:32:33,280 --> 00:32:35,240
Speaker 2: I would hire it for a day. I'd try before

610
00:32:35,280 --> 00:32:38,760
Speaker 2: I buy. That would be a me thing, definitely. But

611
00:32:38,880 --> 00:32:40,720
Speaker 2: isn't that interesting that it's now become a thing in

612
00:32:40,880 --> 00:32:42,920
Speaker 2: China that you go and you rent a robot for

613
00:32:42,960 --> 00:32:43,280
Speaker 2: the day.

614
00:32:43,840 --> 00:32:45,240
Speaker 1: I would love that. And you know what would be

615
00:32:45,280 --> 00:32:47,080
Speaker 1: even cooler is once they've got a lot of tech

616
00:32:47,200 --> 00:32:50,680
Speaker 1: right and they can move around and do stuff and

617
00:32:50,840 --> 00:32:52,960
Speaker 1: whatever you need them to do, clean or vacuum or

618
00:32:53,080 --> 00:32:55,360
Speaker 1: chat to you or change the channel or whatever the

619
00:32:55,400 --> 00:32:58,400
Speaker 1: fuck it is, then they start to build retro models

620
00:32:58,440 --> 00:33:01,480
Speaker 1: that look like R two, D two and C three po. Yeah,

621
00:33:01,640 --> 00:33:01,800
Speaker 1: you know.

622
00:33:02,240 --> 00:33:03,240
Speaker 2: So, Like.

623
00:33:04,880 --> 00:33:07,880
Speaker 1: I was listening to another podcast and they were talking

624
00:33:07,880 --> 00:33:12,440
Speaker 1: about this Patrick, you know, humanoid robots, and the guy

625
00:33:12,800 --> 00:33:15,160
Speaker 1: who is the I forget his name, the boss of

626
00:33:15,400 --> 00:33:20,360
Speaker 1: in video. He was talking about all the potential he

627
00:33:20,440 --> 00:33:22,040
Speaker 1: was talking about all the jobs that are going to

628
00:33:22,080 --> 00:33:24,440
Speaker 1: go away, but all the jobs that will come. And

629
00:33:24,560 --> 00:33:27,160
Speaker 1: he's like, but well with all the robots. He's like,

630
00:33:27,240 --> 00:33:29,800
Speaker 1: even think about this. People are going to have personal robots.

631
00:33:31,280 --> 00:33:33,480
Speaker 1: And he goes, you know what's going to become a market?

632
00:33:33,600 --> 00:33:38,600
Speaker 1: He goes, clothing for robots. What people dress their robots in? Right,

633
00:33:39,120 --> 00:33:44,480
Speaker 1: There'll be whole lines of clothing for you to I'm like,

634
00:33:44,680 --> 00:33:46,320
Speaker 1: I never thought of that, and he's like, I know,

635
00:33:46,440 --> 00:33:49,640
Speaker 1: that seems crazy, it's absolutely going to happen. Have you

636
00:33:49,720 --> 00:33:51,800
Speaker 1: seen people dress their dogs? I'm like, well, I've seen

637
00:33:51,840 --> 00:33:56,840
Speaker 1: Patrick dress his dog. So if people are dressing fucking animals,

638
00:33:57,360 --> 00:34:01,320
Speaker 1: then people. Yeah. So it's like that. That just fascinating me,

639
00:34:01,920 --> 00:34:09,480
Speaker 1: the the development and the accelerated kind of rate at

640
00:34:10,239 --> 00:34:13,160
Speaker 1: which everything is happening. I'll tell you one quick thing,

641
00:34:13,200 --> 00:34:16,719
Speaker 1: which you'll probably be all over, But so Melissa's gone down.

642
00:34:16,800 --> 00:34:19,080
Speaker 1: Melissa for those three of you who don't know who

643
00:34:19,160 --> 00:34:22,479
Speaker 1: Melissa is, runs my life, is my business partner. She's

644
00:34:23,200 --> 00:34:27,560
Speaker 1: one hundred years younger than me, smarter than me. I'm

645
00:34:27,640 --> 00:34:29,480
Speaker 1: not even being nice to her and bad to me.

646
00:34:29,600 --> 00:34:30,120
Speaker 2: She just is.

647
00:34:30,480 --> 00:34:33,080
Speaker 1: But she's down. The AI rabbit hole At the moment,

648
00:34:33,160 --> 00:34:40,359
Speaker 1: Patrick building AI agents for our business, and she's trying

649
00:34:40,400 --> 00:34:44,799
Speaker 1: to explain to me, right, which is like me trying

650
00:34:44,840 --> 00:34:48,239
Speaker 1: to explain to my mum the functional anatomy of a

651
00:34:49,280 --> 00:34:53,960
Speaker 1: deadlift or a squat or something. But anyway, so one

652
00:34:54,040 --> 00:34:58,080
Speaker 1: of the things that she's building is an agent that

653
00:34:58,800 --> 00:35:01,920
Speaker 1: basically runs the you project from a behind the scenes

654
00:35:01,960 --> 00:35:06,400
Speaker 1: point of view. So it's currently being trained on the

655
00:35:06,560 --> 00:35:09,799
Speaker 1: kind of guests that we want the language to use.

656
00:35:10,200 --> 00:35:13,040
Speaker 1: You know, there's a template to send out, but it

657
00:35:13,200 --> 00:35:16,840
Speaker 1: personalizes it somewhat and like all of these variables that

658
00:35:17,040 --> 00:35:22,120
Speaker 1: will basically save us having an employee from doing that thing.

659
00:35:22,480 --> 00:35:26,000
Speaker 1: And as we've said before, so then you've got this

660
00:35:26,239 --> 00:35:30,960
Speaker 1: agent or this employee in inverted commas that doesn't get tired,

661
00:35:31,000 --> 00:35:34,560
Speaker 1: that doesn't get sick, that doesn't need holiday pay, that

662
00:35:34,760 --> 00:35:39,760
Speaker 1: doesn't you know, have emotional and psychological and relationship issues.

663
00:35:40,560 --> 00:35:43,399
Speaker 1: So that the stuff that's being developed right now that's

664
00:35:43,440 --> 00:35:46,839
Speaker 1: going to become commonplace. I don't think we can even

665
00:35:47,280 --> 00:35:49,080
Speaker 1: even now compared to five years ago.

666
00:35:49,120 --> 00:35:51,400
Speaker 2: It's crazy, it is, yeah, and it looked at some

667
00:35:51,520 --> 00:35:54,279
Speaker 2: great useful tools out there, But it also means that

668
00:35:54,600 --> 00:35:56,040
Speaker 2: there's going to be a lot of people out of

669
00:35:56,120 --> 00:35:59,000
Speaker 2: work as well. I think did we talk about this

670
00:35:59,120 --> 00:36:02,960
Speaker 2: earlier that there were fifty thousand jobs lost to right

671
00:36:04,239 --> 00:36:06,359
Speaker 2: by in the US, I think it's over. It might

672
00:36:06,400 --> 00:36:09,439
Speaker 2: have been fifty five thousand jobs last year, So twenty

673
00:36:09,520 --> 00:36:13,200
Speaker 2: twenty five were lost to AI, is what you know.

674
00:36:13,960 --> 00:36:18,920
Speaker 2: And in some employment research company was put out basically

675
00:36:19,080 --> 00:36:22,200
Speaker 2: fifty five thousand jobs out. But you know, I was

676
00:36:22,239 --> 00:36:24,320
Speaker 2: thinking about clothing for robots. So I'm going back a

677
00:36:24,360 --> 00:36:27,920
Speaker 2: little bit because I do you have your news resolution?

678
00:36:28,040 --> 00:36:30,920
Speaker 2: I know you spend a lot of time planning the future,

679
00:36:30,960 --> 00:36:33,879
Speaker 2: and you usually use New Year's Day and you really

680
00:36:33,920 --> 00:36:36,320
Speaker 2: think through all of that, which I don't normally do.

681
00:36:37,080 --> 00:36:40,920
Speaker 1: Yeah, I'm less kind of New Year's these days, but yeah,

682
00:36:41,239 --> 00:36:43,440
Speaker 1: I'm always kind of thinking about and whether or not

683
00:36:43,520 --> 00:36:46,839
Speaker 1: it's January one or December twenty three or but yeah,

684
00:36:46,960 --> 00:36:50,839
Speaker 1: I'm always kind of I have yearly, weekly goals, monthly goals,

685
00:36:50,960 --> 00:36:55,080
Speaker 1: yearly goals, So yeah, I'm because hopefully my PhD is

686
00:36:55,080 --> 00:36:57,560
Speaker 1: finished in the next month or so, that's the plan anyway,

687
00:36:57,640 --> 00:36:59,160
Speaker 1: and beyond that they're a goals.

688
00:36:59,239 --> 00:37:02,719
Speaker 2: So yes, well, no, in about November last year, even

689
00:37:02,760 --> 00:37:05,000
Speaker 2: before November last year, I was reading a few articles

690
00:37:05,080 --> 00:37:08,480
Speaker 2: on fast fashion and I thought to myself, I've got

691
00:37:08,600 --> 00:37:11,040
Speaker 2: so many clothes I don't need to buy any new clothes.

692
00:37:11,080 --> 00:37:13,560
Speaker 2: So for twenty twenty six, I've decided I'm not going

693
00:37:13,640 --> 00:37:17,359
Speaker 2: to buy a new item of clothing for the next

694
00:37:17,440 --> 00:37:20,640
Speaker 2: twelve months. And so I scattered out my local op

695
00:37:20,719 --> 00:37:23,000
Speaker 2: shop to see if there's anything there that I might

696
00:37:23,120 --> 00:37:25,560
Speaker 2: want to wear in case I do need a new top.

697
00:37:26,040 --> 00:37:28,640
Speaker 2: But that's my little pledge to myself, just to stop

698
00:37:28,760 --> 00:37:31,680
Speaker 2: fast fashion and kind of keep using my current clothing.

699
00:37:31,840 --> 00:37:35,080
Speaker 2: So yeah, that's that's my little promise to myself not

700
00:37:35,320 --> 00:37:38,200
Speaker 2: to buy any clothing except for footwear, because of course,

701
00:37:38,360 --> 00:37:41,480
Speaker 2: you know, particularly if you've got pronate feet, you need

702
00:37:41,600 --> 00:37:43,480
Speaker 2: to make sure you've got the right footwear. But yeah,

703
00:37:43,600 --> 00:37:44,960
Speaker 2: that's my little pledge to myself.

704
00:37:45,040 --> 00:37:46,920
Speaker 1: I hope you've got a lot of jocks in the cupboard.

705
00:37:47,600 --> 00:37:49,399
Speaker 2: Actually I have a lot of jocks, and I get

706
00:37:49,480 --> 00:37:52,480
Speaker 2: my jocks from an Australian company that manufactures locally. I

707
00:37:52,520 --> 00:37:53,719
Speaker 2: think that's really important too.

708
00:37:54,280 --> 00:37:56,359
Speaker 1: So wow, what are they called? Give them a shout out?

709
00:37:56,760 --> 00:38:00,839
Speaker 2: Aussie bum, Aussie bum? You started a couple of gay guys.

710
00:38:00,880 --> 00:38:02,439
Speaker 2: Do you know what can I tell you this story?

711
00:38:02,440 --> 00:38:04,800
Speaker 2: It's getting bit personal here. One of the reasons I

712
00:38:04,840 --> 00:38:08,120
Speaker 2: started wearing them is, well, you remember the old advertising

713
00:38:08,200 --> 00:38:11,120
Speaker 2: for cross your Heart bras and women who have supported

714
00:38:11,200 --> 00:38:13,759
Speaker 2: bras for when they run to keep everything you know

715
00:38:14,080 --> 00:38:14,560
Speaker 2: in place.

716
00:38:15,120 --> 00:38:17,160
Speaker 1: I don't think you needed to explain the second bit.

717
00:38:17,280 --> 00:38:19,600
Speaker 1: I think we could have just said supported bras. Yep,

718
00:38:19,680 --> 00:38:22,520
Speaker 1: we're with you, just trying to spell create a picture

719
00:38:22,680 --> 00:38:25,160
Speaker 1: for everyone. Pretty sure we don't need that.

720
00:38:26,280 --> 00:38:29,279
Speaker 2: Well, these jobs, there's there's a particular range of these

721
00:38:29,800 --> 00:38:32,600
Speaker 2: underwear that have a supporting cup in them as well

722
00:38:33,080 --> 00:38:33,440
Speaker 2: to keep it.

723
00:38:33,520 --> 00:38:36,720
Speaker 1: I love how to our listeners, Patrick's holding his hand

724
00:38:36,840 --> 00:38:40,759
Speaker 1: out like with his palm up like he's supporting a

725
00:38:40,920 --> 00:38:45,520
Speaker 1: cock and some testicles. Yep, thanks fucking hell. Can you

726
00:38:45,680 --> 00:38:49,520
Speaker 1: cut out the visuals today? I haven't had brecky yet, but.

727
00:38:49,600 --> 00:38:52,480
Speaker 2: I still a lot of paragliding and rock climbing, and

728
00:38:52,680 --> 00:38:54,839
Speaker 2: keeping the boys in the right position when you're wearing

729
00:38:54,880 --> 00:38:56,719
Speaker 2: a harness is pretty damn important.

730
00:38:57,640 --> 00:38:59,960
Speaker 1: Can I just say, nobody in the history of probably

731
00:39:00,200 --> 00:39:03,160
Speaker 1: any show has ever started a sentence with but I

732
00:39:03,360 --> 00:39:05,760
Speaker 1: used to do a lot of paragliding and hang gliding,

733
00:39:06,000 --> 00:39:07,520
Speaker 1: rock climbing, now rock climbing.

734
00:39:07,360 --> 00:39:10,240
Speaker 2: Rock climbing, gliding and rock climbing, and those are sports

735
00:39:10,280 --> 00:39:14,000
Speaker 2: where you need to have very good undergarments to make

736
00:39:14,080 --> 00:39:14,759
Speaker 2: sure you don't.

737
00:39:14,960 --> 00:39:16,879
Speaker 1: So what do you what are you saying that you're

738
00:39:17,320 --> 00:39:17,959
Speaker 1: well and doubt?

739
00:39:18,360 --> 00:39:20,840
Speaker 2: Is that the is that the I'm not saying that

740
00:39:20,920 --> 00:39:22,600
Speaker 2: at all. I'm just saying that you're still going to

741
00:39:22,719 --> 00:39:23,600
Speaker 2: keep the boys in place?

742
00:39:24,800 --> 00:39:25,719
Speaker 1: Well, what's wrong?

743
00:39:26,080 --> 00:39:28,320
Speaker 2: Have you been climbing before? Have you worn climbing harness?

744
00:39:30,080 --> 00:39:30,120
Speaker 1: No?

745
00:39:30,600 --> 00:39:32,160
Speaker 2: You do not want to slip out of your climbing

746
00:39:32,200 --> 00:39:36,160
Speaker 2: harness and get something caught in that strap of the harness.

747
00:39:36,160 --> 00:39:36,839
Speaker 2: You've got to be pretty.

748
00:39:36,920 --> 00:39:39,680
Speaker 1: I'm just a free range climber. I'm like an orangutan.

749
00:39:40,760 --> 00:39:41,880
Speaker 1: You fucking scale up?

750
00:39:41,960 --> 00:39:44,560
Speaker 2: Shit, how do we even get there? So anyway, I

751
00:39:44,640 --> 00:39:47,319
Speaker 2: buy a local and I try to buy Australian may

752
00:39:47,400 --> 00:39:49,520
Speaker 2: where possible. But this year, no, I have got enough

753
00:39:49,600 --> 00:39:52,000
Speaker 2: jocks to keep me through the year. I reckon Crago.

754
00:39:52,680 --> 00:39:57,480
Speaker 1: Talk to us about AI pro AI prompt. Yeah, I'm

755
00:39:57,520 --> 00:40:00,960
Speaker 1: fucking taking a left turn AI prompt. So when we

756
00:40:02,000 --> 00:40:04,840
Speaker 1: I think being able to write a good prompt makes

757
00:40:04,960 --> 00:40:08,239
Speaker 1: all the difference, because sometimes and a prompt everybody we're

758
00:40:08,280 --> 00:40:10,640
Speaker 1: just talking about when we're asking chat GPT your question

759
00:40:10,800 --> 00:40:13,040
Speaker 1: or we want it to do something or give it

760
00:40:13,160 --> 00:40:17,360
Speaker 1: an instruction, or any AI for that matter. Yeah, And

761
00:40:17,520 --> 00:40:21,160
Speaker 1: I've found that the quality of what I tell it

762
00:40:21,280 --> 00:40:24,520
Speaker 1: to do or ask it to do makes a huge

763
00:40:24,560 --> 00:40:26,879
Speaker 1: difference to the output it does.

764
00:40:27,040 --> 00:40:29,520
Speaker 2: AI prompting is really interesting because I tend to use

765
00:40:29,760 --> 00:40:33,360
Speaker 2: AI for the most part visually, so if I'm trying

766
00:40:33,400 --> 00:40:36,560
Speaker 2: to edit an image, you know, or trying to create

767
00:40:36,640 --> 00:40:40,400
Speaker 2: something that involves visual aspect. But AI prompting, it's this

768
00:40:40,480 --> 00:40:42,520
Speaker 2: is a skill to it, isn't there getting the prompt

769
00:40:42,640 --> 00:40:47,040
Speaker 2: right and getting it And I don't look, I don't

770
00:40:47,040 --> 00:40:49,920
Speaker 2: know if there's any real secret to it. I think

771
00:40:50,160 --> 00:40:52,839
Speaker 2: being you don't want to be too long winded. One

772
00:40:52,880 --> 00:40:55,440
Speaker 2: of an article I was reading with someone saying, one

773
00:40:55,440 --> 00:40:58,080
Speaker 2: of the mistakes you can make is being too detailed

774
00:40:58,520 --> 00:41:00,719
Speaker 2: when doing an AI prompt. If you do that, you

775
00:41:00,840 --> 00:41:04,399
Speaker 2: can kind of overcomplicate things by trying to say too

776
00:41:04,520 --> 00:41:08,280
Speaker 2: much and maybe start off with very simple basic prompts

777
00:41:08,280 --> 00:41:10,160
Speaker 2: and then if you need to, you know, to kind

778
00:41:10,200 --> 00:41:12,520
Speaker 2: of get more detailed, do it that way. But sometimes

779
00:41:12,560 --> 00:41:16,719
Speaker 2: you can go too long and be concerned about Yeah,

780
00:41:16,960 --> 00:41:19,240
Speaker 2: the detail don't get bogged down in the detail.

781
00:41:20,280 --> 00:41:23,600
Speaker 1: Yeah, And also sometimes yes is the answer. And also

782
00:41:24,560 --> 00:41:31,120
Speaker 1: sometimes I'm writing something and i'm writing a let's say,

783
00:41:31,160 --> 00:41:33,880
Speaker 1: a piece about decision making or something, and I'm using

784
00:41:35,239 --> 00:41:39,120
Speaker 1: metaphors and analogies, and then I'm trying to figure out

785
00:41:39,280 --> 00:41:42,719
Speaker 1: one and I might write nine sentences and I need

786
00:41:42,800 --> 00:41:45,719
Speaker 1: a banger last sentence, so I just go, I put

787
00:41:45,760 --> 00:41:49,000
Speaker 1: it in, see what it says. And so quite often

788
00:41:49,080 --> 00:41:52,120
Speaker 1: it will give a last sentence that's totally out of

789
00:41:53,080 --> 00:41:56,960
Speaker 1: kilter with the nine that I've done. Like I'm writing

790
00:41:57,280 --> 00:42:01,840
Speaker 1: tongue in cheek. It's it's like you have to figure

791
00:42:01,960 --> 00:42:05,520
Speaker 1: it's not clear, and then it writes the clear obvious.

792
00:42:06,480 --> 00:42:10,400
Speaker 1: So it takes a different style altogether. And while the

793
00:42:10,520 --> 00:42:15,440
Speaker 1: sentence kind of makes sense as a reading experience, it

794
00:42:15,640 --> 00:42:16,759
Speaker 1: totally doesn't fit.

795
00:42:17,360 --> 00:42:17,760
Speaker 2: Ye.

796
00:42:18,000 --> 00:42:21,600
Speaker 1: So you've really got to go, Okay, I want you

797
00:42:21,760 --> 00:42:24,840
Speaker 1: to write a bit about this, but it's got to

798
00:42:24,920 --> 00:42:27,440
Speaker 1: be it's got to be it's got to be accurate.

799
00:42:27,520 --> 00:42:29,640
Speaker 1: But also it's got to be fun, it's got to be.

800
00:42:30,320 --> 00:42:32,279
Speaker 1: You know, tongue in cheek it's a bit cheeky da

801
00:42:32,360 --> 00:42:35,440
Speaker 1: data And even then it's like, yeah, there's a lot

802
00:42:35,520 --> 00:42:38,640
Speaker 1: of like creative things. It's not very good.

803
00:42:39,760 --> 00:42:44,680
Speaker 2: Interestingly, Sam Altman, who is the genius, I guess behind

804
00:42:45,760 --> 00:42:50,680
Speaker 2: one of the largest AI models, he's saying his vision

805
00:42:50,840 --> 00:42:55,080
Speaker 2: for AI in the future is where it remembers everything

806
00:42:55,680 --> 00:42:58,960
Speaker 2: and you basically put your whole life into it. Everything

807
00:42:59,000 --> 00:43:01,560
Speaker 2: you've ever written, everything you've ever said. So we'd put

808
00:43:01,600 --> 00:43:04,120
Speaker 2: all of your podcasts in there, all of the emails

809
00:43:04,160 --> 00:43:06,920
Speaker 2: you've ever seen, and it would remember that. Because at

810
00:43:06,960 --> 00:43:08,759
Speaker 2: the moment, it kind of doesn't really do that, and

811
00:43:09,239 --> 00:43:10,960
Speaker 2: I don't know that fills me with a little bit

812
00:43:10,960 --> 00:43:13,879
Speaker 2: of dread. Would you want every single thing you've ever

813
00:43:14,040 --> 00:43:17,120
Speaker 2: emailed out, everything you've ever done, because really, if someone

814
00:43:17,239 --> 00:43:18,800
Speaker 2: was going to mimic you, or someone was going to

815
00:43:18,840 --> 00:43:21,880
Speaker 2: assist you, if you had the ultimate AI assistant, they

816
00:43:21,920 --> 00:43:24,759
Speaker 2: would need the full picture, not a sanitized version of you.

817
00:43:25,640 --> 00:43:28,600
Speaker 1: Yeah. Look, I get what you're saying. I'm not too

818
00:43:28,640 --> 00:43:31,000
Speaker 1: worried about that. I guess some people be real worried

819
00:43:31,040 --> 00:43:34,480
Speaker 1: about that. I don't think there's too much that's fucking

820
00:43:34,560 --> 00:43:41,480
Speaker 1: incriminating or but but what I think about you know

821
00:43:41,680 --> 00:43:43,960
Speaker 1: how we're kind of handing out a lot of information

822
00:43:44,160 --> 00:43:47,640
Speaker 1: to AI, or we're kind of outsourced. It seems like

823
00:43:47,719 --> 00:43:50,799
Speaker 1: we're outsourcing thinking, right, Oh, I don't want to think.

824
00:43:50,840 --> 00:43:53,200
Speaker 1: I'll let it think for me, which I understand that

825
00:43:54,280 --> 00:43:56,799
Speaker 1: and I do actually think depending on how it's used,

826
00:43:57,000 --> 00:44:00,279
Speaker 1: it can be a negative and it can as you

827
00:44:00,480 --> 00:44:06,120
Speaker 1: suggested earlier, there's definitely that, Not that it makes people dumber,

828
00:44:07,120 --> 00:44:10,879
Speaker 1: because IQ is IQ, but I think that it can

829
00:44:11,760 --> 00:44:15,480
Speaker 1: have a negative impact on cognitive function even the structure

830
00:44:15,520 --> 00:44:19,000
Speaker 1: of the brain. Like somebody uses their brain a lot,

831
00:44:20,080 --> 00:44:22,680
Speaker 1: their brain looks different to someone who doesn't use their

832
00:44:22,719 --> 00:44:24,520
Speaker 1: brain a lot. Like there's just a lot of a

833
00:44:24,600 --> 00:44:28,160
Speaker 1: lot more neural pathways, a lot of different stuff physiologically

834
00:44:28,200 --> 00:44:32,920
Speaker 1: and anatomically going on. But I think like for me

835
00:44:34,520 --> 00:44:37,759
Speaker 1: using AI, my brain's working more than ever because I'm

836
00:44:37,920 --> 00:44:40,960
Speaker 1: not only am I it makes it gives me more

837
00:44:41,040 --> 00:44:44,280
Speaker 1: time to do other stuff where I am using my brain,

838
00:44:45,200 --> 00:44:47,960
Speaker 1: whereas it can give me a short cut and it

839
00:44:48,080 --> 00:44:50,600
Speaker 1: can give me an answer to something quite quickly, which

840
00:44:50,680 --> 00:44:54,120
Speaker 1: then I have to verify, of course. But also I'm

841
00:44:54,280 --> 00:44:58,360
Speaker 1: constantly thinking about how do I use this tool optimally,

842
00:44:59,160 --> 00:45:01,719
Speaker 1: Like it's not a rep placement for thinking or for

843
00:45:01,880 --> 00:45:05,520
Speaker 1: my brain or for my knowledge. For me, it's just

844
00:45:05,640 --> 00:45:10,040
Speaker 1: a tool that I can use to do more shit

845
00:45:10,360 --> 00:45:14,759
Speaker 1: and create better outcomes. And it's like, well, sure you

846
00:45:14,880 --> 00:45:17,439
Speaker 1: can cut those bits of wood with that ten and saw,

847
00:45:17,560 --> 00:45:20,520
Speaker 1: it's going to take you five hours, or you can

848
00:45:20,640 --> 00:45:23,360
Speaker 1: use this circular saw. It's going to take you five minutes.

849
00:45:23,960 --> 00:45:27,520
Speaker 1: Oh oh yeah, but now someone's losing a job because

850
00:45:27,560 --> 00:45:30,120
Speaker 1: they're not. No, now we're just all going to use

851
00:45:30,200 --> 00:45:34,600
Speaker 1: these circular saws. Now it's much more efficient. So yeah,

852
00:45:34,680 --> 00:45:38,360
Speaker 1: I think I think every I think with everything. You know,

853
00:45:38,440 --> 00:45:40,759
Speaker 1: when rock and mole music came in, it's like it's

854
00:45:40,800 --> 00:45:41,560
Speaker 1: the end of the world.

855
00:45:42,320 --> 00:45:42,480
Speaker 2: You know.

856
00:45:42,560 --> 00:45:44,840
Speaker 1: When computers came in, people are like, oh, that's not

857
00:45:44,960 --> 00:45:47,120
Speaker 1: going to take on the internet. That was never going

858
00:45:47,200 --> 00:45:49,920
Speaker 1: to work. And I don't know, I just think everybody

859
00:45:50,600 --> 00:45:53,600
Speaker 1: has a negative bent when new things kind of emerge.

860
00:45:54,000 --> 00:45:58,239
Speaker 2: And I had an employee who left last year who

861
00:45:58,920 --> 00:46:01,520
Speaker 2: was with me for about four year years and he

862
00:46:02,400 --> 00:46:05,759
Speaker 2: obviously used a calculator a lot, and we would do

863
00:46:05,800 --> 00:46:07,560
Speaker 2: an end of month's summary of the work that he

864
00:46:07,640 --> 00:46:10,120
Speaker 2: did and come up with totals and all. We're doing

865
00:46:10,239 --> 00:46:13,320
Speaker 2: proposals and we'd have to work out what the you know,

866
00:46:13,360 --> 00:46:16,880
Speaker 2: we're going to quote for a job. Interestingly, I always

867
00:46:17,120 --> 00:46:19,799
Speaker 2: like the challenge of adding up sums in my head,

868
00:46:20,080 --> 00:46:24,200
Speaker 2: just occasionally. But his total reliance on the calculator, and

869
00:46:24,239 --> 00:46:26,920
Speaker 2: I mean a physical, literal calculator, either the on screen

870
00:46:27,320 --> 00:46:29,840
Speaker 2: or he had a calculator on his desk. And this

871
00:46:30,040 --> 00:46:33,400
Speaker 2: is old tech we're talking about now, But the reality

872
00:46:33,680 --> 00:46:37,279
Speaker 2: was that even simple sums he would use in the calculator,

873
00:46:37,680 --> 00:46:41,520
Speaker 2: so that part of his processing brain that did sums

874
00:46:42,200 --> 00:46:44,400
Speaker 2: he just didn't want to use. He just used an

875
00:46:44,440 --> 00:46:47,239
Speaker 2: electronic device. Now, calculators has been out forever, you know,

876
00:46:49,080 --> 00:46:50,799
Speaker 2: they've been out. You know, we grew up with them

877
00:46:50,800 --> 00:46:53,239
Speaker 2: at school. But what does that actually say about the

878
00:46:53,320 --> 00:46:56,040
Speaker 2: brain's ability to do that, you know, to process and

879
00:46:56,160 --> 00:46:59,759
Speaker 2: to take figures. You know, a local supermarket a little

880
00:46:59,760 --> 00:47:05,440
Speaker 2: while ago, the checkout girl was trying to work out

881
00:47:05,480 --> 00:47:07,480
Speaker 2: the price or something and that wasn't in the system,

882
00:47:07,640 --> 00:47:09,759
Speaker 2: and there were a number of them, and she was

883
00:47:09,880 --> 00:47:12,399
Speaker 2: sitting there like she couldn't do anything, she couldn' add

884
00:47:12,400 --> 00:47:14,920
Speaker 2: them up. And I said, well it's this. It was

885
00:47:14,960 --> 00:47:18,000
Speaker 2: a really not relatively simple I mean obviously, and I

886
00:47:18,040 --> 00:47:20,640
Speaker 2: think it was a percentage of something or or a

887
00:47:20,719 --> 00:47:23,560
Speaker 2: half price and then add something else. I can't even

888
00:47:23,560 --> 00:47:25,760
Speaker 2: remember what the sum was, but it was a pretty

889
00:47:25,800 --> 00:47:27,839
Speaker 2: easy one to work out. But she just stood there

890
00:47:27,920 --> 00:47:30,440
Speaker 2: dumbfounded because she a when I gave her the answer,

891
00:47:30,480 --> 00:47:33,239
Speaker 2: she couldn't use it because she couldn't verify it, and

892
00:47:33,440 --> 00:47:35,480
Speaker 2: b ended up having to get someone over to reset

893
00:47:35,520 --> 00:47:38,120
Speaker 2: her computer so she could put it in and recalculate it,

894
00:47:39,280 --> 00:47:39,440
Speaker 2: you know.

895
00:47:39,920 --> 00:47:43,600
Speaker 1: But it was, yeah, I'm with you, But then I think, Okay,

896
00:47:43,719 --> 00:47:46,879
Speaker 1: so the person who can't add maths, you give them

897
00:47:47,040 --> 00:47:49,840
Speaker 1: a canvas and some paint, and they paint something fucking

898
00:47:49,960 --> 00:47:53,560
Speaker 1: phenomenal that I couldn't even begin, Like, I'm really good

899
00:47:53,600 --> 00:47:56,800
Speaker 1: at maths, but that's my default setting. It's not because

900
00:47:56,800 --> 00:47:59,520
Speaker 1: I try to be like I'm that's the way my

901
00:47:59,640 --> 00:48:03,080
Speaker 1: brain works, But some people's Like one of my friends

902
00:48:03,160 --> 00:48:06,640
Speaker 1: is dyslexic. He's a fifty year old grown ass man

903
00:48:07,480 --> 00:48:10,520
Speaker 1: and he struggles to read a paragraph. But that's the

904
00:48:10,600 --> 00:48:14,359
Speaker 1: way his brain works. But you give him some shit

905
00:48:14,440 --> 00:48:17,640
Speaker 1: to build, He'll build a fucking house in an afternoon,

906
00:48:17,840 --> 00:48:19,640
Speaker 1: and I'll still be trying to figure out how the

907
00:48:19,680 --> 00:48:23,560
Speaker 1: hammer works. So intelligence is on a spectrum. And just

908
00:48:23,600 --> 00:48:27,160
Speaker 1: because I think some people using a calculator is the

909
00:48:27,239 --> 00:48:30,720
Speaker 1: right thing, and I don't think I know what you're saying,

910
00:48:31,800 --> 00:48:35,319
Speaker 1: but you're probably naturally good at maths. I'm naturally good

911
00:48:35,360 --> 00:48:37,120
Speaker 1: at maths, but then there are things that I'm not

912
00:48:37,320 --> 00:48:39,439
Speaker 1: naturally good at which I avoid.

913
00:48:40,120 --> 00:48:43,160
Speaker 2: And I go more than you'll lose it. Yeah, I

914
00:48:43,239 --> 00:48:44,800
Speaker 2: was thinking the use it or lose it kind of

915
00:48:44,880 --> 00:48:48,040
Speaker 2: mentality in terms of that side of it. But you're right.

916
00:48:48,800 --> 00:48:51,560
Speaker 2: In fact, the person that I'm thinking of was amazingly

917
00:48:51,719 --> 00:48:53,480
Speaker 2: is amazingly talented and creative.

918
00:48:53,880 --> 00:48:59,719
Speaker 1: So there are so many creative geniuses who are academically

919
00:48:59,840 --> 00:49:00,480
Speaker 1: not brilliant.

920
00:49:00,960 --> 00:49:03,319
Speaker 2: Yeah, yeah, for sure. Hey, just can we get onto

921
00:49:03,360 --> 00:49:06,640
Speaker 2: a different topic. I've got this really interesting tech gadgets,

922
00:49:06,640 --> 00:49:08,640
Speaker 2: and I thought, if there's a couple of little gadgets

923
00:49:08,680 --> 00:49:11,160
Speaker 2: I'm really excited about. But this seems to make so

924
00:49:11,280 --> 00:49:13,360
Speaker 2: much sense to me. I've never even thought about it before.

925
00:49:13,719 --> 00:49:17,920
Speaker 2: You can buy a smart jar lid. Okay, so thinking

926
00:49:18,120 --> 00:49:22,279
Speaker 2: a smart jar lid that uses UV light to keep

927
00:49:22,360 --> 00:49:24,840
Speaker 2: your food fresher longer. So if you've got stuff that

928
00:49:24,880 --> 00:49:27,680
Speaker 2: you're putting in the fridge and you put this lid on,

929
00:49:27,960 --> 00:49:31,520
Speaker 2: it emits ultraviolet light to stop bacteria growing. So obviously

930
00:49:31,560 --> 00:49:33,759
Speaker 2: putting things in the fridge will prolong how long it

931
00:49:33,800 --> 00:49:37,000
Speaker 2: will last because it slows down any movement by bacteria

932
00:49:37,040 --> 00:49:39,759
Speaker 2: or any growth by bacteria. But the addition of a

933
00:49:39,960 --> 00:49:44,120
Speaker 2: smart lid that just shines UV light onto the top

934
00:49:44,160 --> 00:49:45,680
Speaker 2: of whatever it is. Because if you've got a jar

935
00:49:45,800 --> 00:49:49,520
Speaker 2: of jam and you know you spring, the top of

936
00:49:50,080 --> 00:49:52,440
Speaker 2: the bacterial will form at the top because the bottom

937
00:49:52,560 --> 00:49:54,520
Speaker 2: hasn't got any air exposed to it. It's just the

938
00:49:54,600 --> 00:49:57,120
Speaker 2: top part. So how good is that idea? Having a

939
00:49:57,239 --> 00:49:59,920
Speaker 2: UV light just in the jar the lid of your jar.

940
00:50:00,719 --> 00:50:03,560
Speaker 1: Wow, imagine opening the fridge. There's all these little kind

941
00:50:03,600 --> 00:50:06,560
Speaker 1: of looks like science experiments in your fridge. There's just

942
00:50:06,640 --> 00:50:10,359
Speaker 1: all these little illuminated fucking jars of shit. So it's

943
00:50:10,400 --> 00:50:11,239
Speaker 1: not at all.

944
00:50:11,960 --> 00:50:14,960
Speaker 2: It looks like the YouTube podcast backdrop that you've got

945
00:50:15,200 --> 00:50:18,719
Speaker 2: on your screen. So that's glowing blue. There's an ultra

946
00:50:18,800 --> 00:50:19,880
Speaker 2: violet to keep you fresher.

947
00:50:20,600 --> 00:50:24,200
Speaker 1: That is. Yes, I'm actually two under thirteen years old.

948
00:50:25,080 --> 00:50:27,600
Speaker 1: Just unless it comes every day and sprays me with

949
00:50:27,760 --> 00:50:30,520
Speaker 1: something I'm not sure what it is. Yeah, it turns

950
00:50:30,600 --> 00:50:33,160
Speaker 1: on the UV just to get the bacteria off me.

951
00:50:33,480 --> 00:50:36,840
Speaker 2: So Craig is using a fake background on his zoom

952
00:50:37,800 --> 00:50:39,000
Speaker 2: could we not say fake.

953
00:50:39,360 --> 00:50:42,840
Speaker 1: Can we just say it's a virtual it's a virtual studio.

954
00:50:44,040 --> 00:50:48,080
Speaker 2: Fake, it's not real. It's fake. It's just a projected image.

955
00:50:48,280 --> 00:50:50,440
Speaker 2: But it's very blue and it looks like UV. And

956
00:50:50,560 --> 00:50:53,239
Speaker 2: now it suddenly occurred to me that he's probably using

957
00:50:53,320 --> 00:50:55,120
Speaker 2: it to just keep himself fresh.

958
00:50:55,680 --> 00:50:56,880
Speaker 1: It's a real image.

959
00:50:57,800 --> 00:51:01,239
Speaker 2: Okay, hey, other So I know we're running out of time,

960
00:51:01,239 --> 00:51:03,080
Speaker 2: but it's going to tell you. You know, China is

961
00:51:03,280 --> 00:51:08,480
Speaker 2: now officially saying that any cars so predominantly electric car

962
00:51:08,600 --> 00:51:12,920
Speaker 2: companies that have recessed door handles. So in a lot

963
00:51:12,920 --> 00:51:17,040
Speaker 2: of cars, including Tesla, there are recessed handles you kind

964
00:51:17,080 --> 00:51:18,959
Speaker 2: of tap and then they come out of the side

965
00:51:18,960 --> 00:51:22,440
Speaker 2: of the car, so it's for screamlining. The problem is

966
00:51:22,760 --> 00:51:25,440
Speaker 2: if something happens to the battery and the power, then

967
00:51:25,480 --> 00:51:29,000
Speaker 2: the handle won't come out. And so authorities in China

968
00:51:29,040 --> 00:51:31,120
Speaker 2: are saying this is still a couple of years away.

969
00:51:31,120 --> 00:51:33,920
Speaker 2: They're saying from twenty twenty seven, any car sold in

970
00:51:34,080 --> 00:51:38,360
Speaker 2: China has to have a manual door release after electronic

971
00:51:38,440 --> 00:51:41,799
Speaker 2: handles were failing during crashes. So that's an in one.

972
00:51:41,840 --> 00:51:43,480
Speaker 2: I think that's a really good decision.

973
00:51:44,200 --> 00:51:46,319
Speaker 1: I've heard about that I've heard about people who had

974
00:51:46,400 --> 00:51:49,880
Speaker 1: accidents and couldn't get out of the fucking car because

975
00:51:50,239 --> 00:51:54,520
Speaker 1: it was all locked electronically and all the electronics were down.

976
00:51:54,680 --> 00:52:00,000
Speaker 1: So though were just quickly on cars and China and electronics.

977
00:52:00,760 --> 00:52:02,400
Speaker 1: I don't know if you saw the news last night,

978
00:52:02,440 --> 00:52:08,240
Speaker 1: I'm doubting not so byd the biggest seller of electric

979
00:52:08,360 --> 00:52:10,120
Speaker 1: cars in the world.

980
00:52:10,320 --> 00:52:14,080
Speaker 2: Now, oh yeah, that doesn't SPA. So it was.

981
00:52:14,200 --> 00:52:19,800
Speaker 1: Tesla I think probably in Australia as well. Yeah, so

982
00:52:19,960 --> 00:52:24,080
Speaker 1: they they yeah, they're killing it. At the moment that

983
00:52:24,320 --> 00:52:26,239
Speaker 1: some of the Chinese stuff that's coming out, I know,

984
00:52:26,360 --> 00:52:29,880
Speaker 1: people are like, oh, it's junk. It's like, dude, some

985
00:52:30,080 --> 00:52:33,520
Speaker 1: of the stuff is so fucking amazing. Like if you

986
00:52:33,719 --> 00:52:37,680
Speaker 1: just objectively, you know, cars are an interesting thing. I'll

987
00:52:38,160 --> 00:52:40,279
Speaker 1: talk for thirty seconds then back to you. But I've

988
00:52:40,320 --> 00:52:43,400
Speaker 1: always thought cars are fascinating in that how much of

989
00:52:43,440 --> 00:52:46,800
Speaker 1: an emotional attachment, not all, not you, not me, probably,

990
00:52:47,680 --> 00:52:51,239
Speaker 1: but like people having them. Oh i've got a MERK

991
00:52:51,480 --> 00:52:54,320
Speaker 1: or I've got a BM or Traditionally those European cars

992
00:52:54,360 --> 00:52:57,680
Speaker 1: that were very aspirational, Oh look he's got this or

993
00:52:57,800 --> 00:53:02,080
Speaker 1: she's got that, right, but the actual car wasn't that

994
00:53:02,200 --> 00:53:05,560
Speaker 1: fucking amazing. You know, there were Mazdas that you could

995
00:53:05,600 --> 00:53:08,880
Speaker 1: buy for thirty grand less. Like, you've got a Mazda,

996
00:53:08,880 --> 00:53:11,880
Speaker 1: which is a fucking amazing car. Yeah, I've got a

997
00:53:11,960 --> 00:53:16,840
Speaker 1: Hyundai which is Santa Fe, which is better than some

998
00:53:17,040 --> 00:53:20,000
Speaker 1: of my friends fucking two hundred thousand dollars SUVs. They

999
00:53:20,080 --> 00:53:22,759
Speaker 1: get in my car, which costs less than half of

1000
00:53:22,840 --> 00:53:24,840
Speaker 1: what theirs did, and they're like, oh my god, this

1001
00:53:25,000 --> 00:53:28,280
Speaker 1: is fucking space age. I'm like, yeah, made in Korea.

1002
00:53:28,360 --> 00:53:28,480
Speaker 2: Bro.

1003
00:53:29,239 --> 00:53:33,399
Speaker 1: You know, it's like it's just that psychology of where

1004
00:53:33,520 --> 00:53:36,560
Speaker 1: is this made, and therefore it must be, you know,

1005
00:53:36,880 --> 00:53:39,160
Speaker 1: especially with things like cars, where there are no ASI

1006
00:53:39,239 --> 00:53:42,759
Speaker 1: cars anymore, So fucking why whatever you're going to buy?

1007
00:53:43,440 --> 00:53:45,200
Speaker 2: My first car was amazing. You know, it's funny you

1008
00:53:45,280 --> 00:53:48,440
Speaker 2: say that because I bought my very first brand new

1009
00:53:48,560 --> 00:53:50,560
Speaker 2: car because I'd never bought a brand new car before

1010
00:53:50,680 --> 00:53:53,320
Speaker 2: until just after COVID, when it was very hard to

1011
00:53:53,400 --> 00:53:56,359
Speaker 2: buy a brand new cars. But also the second hand

1012
00:53:56,440 --> 00:53:58,120
Speaker 2: car market had gone through the roof. So for me,

1013
00:53:58,200 --> 00:53:59,799
Speaker 2: I thought, I'm not gonna waste money on a second

1014
00:53:59,800 --> 00:54:02,760
Speaker 2: hand carsick at end problems, and I found a demo

1015
00:54:02,880 --> 00:54:05,680
Speaker 2: model of a particular mas to the Mix thirty. But

1016
00:54:05,760 --> 00:54:08,200
Speaker 2: what I love about it is it's got They call

1017
00:54:08,239 --> 00:54:11,120
Speaker 2: them freedom doors, but everybody in the world calls them

1018
00:54:11,160 --> 00:54:14,200
Speaker 2: suicide doors. You know the doors. The doors open up

1019
00:54:14,239 --> 00:54:16,839
Speaker 2: the opposite way, and I think that you know why

1020
00:54:16,960 --> 00:54:18,480
Speaker 2: they called them suicide doors.

1021
00:54:19,600 --> 00:54:24,760
Speaker 1: I'm sure because well, so, just to reiterate what Patrick

1022
00:54:24,800 --> 00:54:28,440
Speaker 1: said to everyone, So it's like, the door opens the

1023
00:54:28,600 --> 00:54:31,400
Speaker 1: opposite way. So instead of you know, like if you

1024
00:54:31,440 --> 00:54:33,440
Speaker 1: went up, you know, you open the handle, if you

1025
00:54:33,480 --> 00:54:35,360
Speaker 1: went up to the other end of the door, it

1026
00:54:35,560 --> 00:54:38,720
Speaker 1: opens like where you're opening the door to the world.

1027
00:54:39,000 --> 00:54:43,840
Speaker 1: Not yeah, so I guess it's because you were, in

1028
00:54:44,040 --> 00:54:48,040
Speaker 1: some instances basically committing suicide to step out into the traffic.

1029
00:54:48,280 --> 00:54:51,520
Speaker 2: No, well, yeah, kind of. So in the olden days,

1030
00:54:51,719 --> 00:54:54,000
Speaker 2: the front doors would open the normal way that front

1031
00:54:54,040 --> 00:54:56,239
Speaker 2: door would, but the back doors would be hinged at

1032
00:54:56,320 --> 00:54:59,920
Speaker 2: the rear and flip open. But because people didn't have seatbell,

1033
00:55:00,200 --> 00:55:03,080
Speaker 2: occasionally the mechanism would fail and while they were driving

1034
00:55:03,440 --> 00:55:05,960
Speaker 2: the rear door the suicide door would flick open, and

1035
00:55:06,040 --> 00:55:09,000
Speaker 2: they would reach to grab it to stop it flicking open,

1036
00:55:09,080 --> 00:55:11,120
Speaker 2: and it would drag them out of the car. So

1037
00:55:11,280 --> 00:55:14,759
Speaker 2: people died grabbing for the rear door that flicked open

1038
00:55:14,840 --> 00:55:18,520
Speaker 2: the wrong way. But what I was getting at is

1039
00:55:19,080 --> 00:55:21,680
Speaker 2: I've never gone for brands. My first car was a Mazda,

1040
00:55:21,719 --> 00:55:23,160
Speaker 2: and then I had a run of cars. I've only

1041
00:55:23,200 --> 00:55:25,600
Speaker 2: had four cars, Craig go, I know, you can't believe

1042
00:55:25,680 --> 00:55:27,920
Speaker 2: that I've only ever owned four cars in my whole life.

1043
00:55:29,200 --> 00:55:32,320
Speaker 2: First three were secondhand and I had them for ages.

1044
00:55:32,640 --> 00:55:34,839
Speaker 2: In fact, I still got my Nissan. That's I think

1045
00:55:34,880 --> 00:55:37,760
Speaker 2: I've had for thirty two years sitting in my driveway anyway.

1046
00:55:38,120 --> 00:55:41,080
Speaker 2: But the Mazda is my most recent car, and it's

1047
00:55:41,280 --> 00:55:44,319
Speaker 2: those things that I like about it. It's got analogue still,

1048
00:55:44,680 --> 00:55:48,319
Speaker 2: so I've got knobs to control the volume, to turn

1049
00:55:48,360 --> 00:55:50,560
Speaker 2: the temperature up and down. I like that it's still

1050
00:55:50,560 --> 00:55:52,600
Speaker 2: a hybrid between and it is literally a hybrid, but

1051
00:55:52,680 --> 00:55:55,440
Speaker 2: it's got a lot of analog as well as digital.

1052
00:55:55,520 --> 00:55:57,279
Speaker 2: So it's got the heads up display and all the

1053
00:55:57,320 --> 00:55:59,879
Speaker 2: fun things that I love. But it's still not quite

1054
00:56:00,160 --> 00:56:03,000
Speaker 2: a scream like an iPad sitting on a dash, which

1055
00:56:03,040 --> 00:56:05,680
Speaker 2: is what the Tesla is. So I think I like

1056
00:56:05,880 --> 00:56:10,080
Speaker 2: that combination of tech but analogue as well. That's kind

1057
00:56:10,080 --> 00:56:10,759
Speaker 2: of does it for me.

1058
00:56:11,640 --> 00:56:14,680
Speaker 1: Yeah, I love that visceral experience of twisting a nob

1059
00:56:14,880 --> 00:56:18,319
Speaker 1: or sliding something across something that's physical, that I can

1060
00:56:19,239 --> 00:56:20,520
Speaker 1: give us one more than I've got to go.

1061
00:56:20,960 --> 00:56:25,400
Speaker 2: Oh, this is great move over. Bluetooth wired headphones are

1062
00:56:25,520 --> 00:56:28,439
Speaker 2: back and they're super cool. So I watched the last

1063
00:56:28,520 --> 00:56:30,440
Speaker 2: episode of Stranger Things last night.

1064
00:56:31,480 --> 00:56:34,880
Speaker 1: Can I just stop you? Did you say wired? W

1065
00:56:35,200 --> 00:56:37,920
Speaker 1: ir ed or wid no?

1066
00:56:38,160 --> 00:56:41,520
Speaker 2: Wired? So it's become a lot of Hollywood celebrities and

1067
00:56:41,600 --> 00:56:44,719
Speaker 2: now going back to their headphones with a chord on them.

1068
00:56:45,360 --> 00:56:48,600
Speaker 2: So tis well, it's just the cool, trendy, hip thing

1069
00:56:48,640 --> 00:56:50,680
Speaker 2: to do. Man, if you're one of the latest trendy

1070
00:56:50,800 --> 00:56:54,160
Speaker 2: young kids out there, We've got CDs, we've got cassettes,

1071
00:56:54,160 --> 00:56:55,640
Speaker 2: and we've got wired headphones.

1072
00:56:56,800 --> 00:56:59,640
Speaker 1: I'm pretty sure it's just the trendy thing to do. Man,

1073
00:56:59,840 --> 00:57:04,319
Speaker 1: is not a trend not a trendy sentence? Patrick, Where

1074
00:57:04,360 --> 00:57:06,160
Speaker 1: can people find you and connect with you?

1075
00:57:06,719 --> 00:57:09,680
Speaker 2: Well, they can go to websites now, dot com, dot

1076
00:57:09,840 --> 00:57:12,960
Speaker 2: au if they want to kind of just chat. Give

1077
00:57:13,040 --> 00:57:14,840
Speaker 2: us some topics to talk about. If you want us

1078
00:57:14,840 --> 00:57:17,880
Speaker 2: to talk about something in particular that's tech related, then

1079
00:57:17,920 --> 00:57:20,000
Speaker 2: I'll I'll research it, I will and I'll read more

1080
00:57:20,040 --> 00:57:22,040
Speaker 2: than one paper about it too, Craigo.

1081
00:57:22,240 --> 00:57:24,520
Speaker 1: That'd be great. Or if there's something you think Patrick

1082
00:57:24,600 --> 00:57:31,480
Speaker 1: and I should argue about, just same. It's beautiful. I

1083
00:57:31,600 --> 00:57:38,080
Speaker 1: love it all right, mate, fast recovery to Fritzie as well.

1084
00:57:38,160 --> 00:57:43,240
Speaker 2: Fretzie for a lick then, just as you were talking.

1085
00:57:43,600 --> 00:57:46,600
Speaker 1: Yeah, stop licking that ship, all right mate. I'll see

1086
00:57:46,640 --> 00:57:47,680
Speaker 1: you soon, do mate,