WEBVTT - Week in Tech: Do You Share Your Location? 

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<v Speaker 1>From Kaleidoscope and iHeart podcasts. This is tech stuff.

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<v Speaker 2>I'm as Voloscian and I'm Cara Price.

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<v Speaker 1>Today we'll get into the headlines this week, including Meta's

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<v Speaker 1>multi hundred million dollar hiring spree and why gen Z

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<v Speaker 1>always have locations sharing on Then on chatting me, he

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<v Speaker 1>gives me.

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<v Speaker 3>A tailored meal plan, so like what I should eat,

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<v Speaker 3>how I should eat, when I should eat bananas some nights, yeah,

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<v Speaker 3>some nights no.

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<v Speaker 1>It's kind of crazy, all of that. On the Weekend Tech.

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<v Speaker 1>It's Friday, July twenty fifth.

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<v Speaker 2>Hello Cara, Hello Azzie. I just want to say first

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<v Speaker 2>rest and darkness to the other Ozzy Osbourne who died

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<v Speaker 2>this week, another brit and that is where I find

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<v Speaker 2>you today.

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<v Speaker 1>Indeed, I'm in London and I was a little bit

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<v Speaker 1>nervous to come here because Europe's been experiencing this crazy

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<v Speaker 1>heat wave and most of London has no AC.

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<v Speaker 2>So you've been schitzing, as they say.

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<v Speaker 1>Well, actually the heat wave broke, but it has been

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<v Speaker 1>a very very hot summer here. And you and I

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<v Speaker 1>talked about Wimbledon a couple of weeks ago and Ai

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<v Speaker 1>line judges. But some of the other interesting scenes from

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<v Speaker 1>this year's Wimbledon, which I haven't seen before, were people

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<v Speaker 1>passing out in the stands from heat exhaustion and players

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<v Speaker 1>riding to their rescue.

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<v Speaker 2>The players are like, you're passing out. My memory and

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<v Speaker 2>unfortunate experience of really not just London, but most of

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<v Speaker 2>Europe is that they lack AC. And as a kid

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<v Speaker 2>who grew up in the Northeast during the summer, AC

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<v Speaker 2>is the premium, I do wonder or in a warmer climate,

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<v Speaker 2>how does this continue to actually work?

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<v Speaker 1>Yeah, I mean I think the short answer is it

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<v Speaker 1>may not. The Financial Times recently had an op ed

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<v Speaker 1>with the title Britain and Europe need to get serious

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<v Speaker 1>about air conditioning, and the article points out that, you know,

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<v Speaker 1>in a changing climate, European cities are experiencing more intense heat,

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<v Speaker 1>more frequently and for longer periods of time than just

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<v Speaker 1>ten years ago. And also the article points out that

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<v Speaker 1>AC is not just about comfort, it's no longer a luxury.

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<v Speaker 1>There are some pretty interesting stats in the piece about

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<v Speaker 1>how being too hot indoors affect sleep, cognition and even

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<v Speaker 1>correlates with mortality.

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<v Speaker 2>You know, I do notice a huge difference in my

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<v Speaker 2>ability to sleep and even think when I'm hot, like,

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<v Speaker 2>I don't think people should work in the summer it's

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<v Speaker 2>too hot.

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<v Speaker 1>Well, the article says that when indoor temperatures rise above

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<v Speaker 1>seventy five degrees fahrenheit, sleep duration and quality fall rapidly, and,

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<v Speaker 1>according to studies, so desirability to perform well in tests.

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<v Speaker 1>So it's a blessing to you and our listeners that

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<v Speaker 1>it's a cool week in London and I can think

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<v Speaker 1>relatively straight.

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<v Speaker 2>You're always brilliant.

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<v Speaker 1>But I.

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<v Speaker 2>A little bit earlier you mentioned more tatic it's a

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<v Speaker 2>matter of life and death. Is that really true in

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<v Speaker 2>terms of AC and cooling.

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<v Speaker 1>I was a little bit surprised by that as well.

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<v Speaker 1>But according to the FT, between two thousand and twenty nineteen,

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<v Speaker 1>an average of eighty three thousand Western Europeans per year

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<v Speaker 1>lost their lives due to extreme heat, compared with just

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<v Speaker 1>twenty thousand North Americans, who are much more likely to

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<v Speaker 1>live in buildings with AC. The penetration rate of air

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<v Speaker 1>conditioning is ninety percent in the US and only nineteen

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<v Speaker 1>percent in Europe.

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<v Speaker 2>I was going to say, you know, I never understood

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<v Speaker 2>why Europeans don't adapt to cooling systems and buildings yeah.

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<v Speaker 1>I mean there's a kind of cultural resistance because it

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<v Speaker 1>uses so much energy. But of course, with a changing climate,

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<v Speaker 1>what was once seen as an extravagance becomes a potential necessity.

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<v Speaker 1>And the FT article makes the point that new developments

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<v Speaker 1>in more efficient solar can actually potentially offset some of

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<v Speaker 1>the new demands of more widely deployed ac you know,

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<v Speaker 1>I was particularly struck by this FT article because it

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<v Speaker 1>referenced Li Quan Yu, who is known as the father

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<v Speaker 1>of modern Singapore, and he was often asked this question,

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<v Speaker 1>how did you transform was effectively a fishing village into

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<v Speaker 1>one of the most important commercial hubs in Asia and

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<v Speaker 1>the world, And he would say, well, two things. First,

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<v Speaker 1>multi ethnic tolerance and diverse society. Second, air conditioning.

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<v Speaker 2>Britain seems to have one but not the other. I mean,

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<v Speaker 2>maybe that's the key.

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<v Speaker 1>Well, it's funny. We host this podcast called tech Stuff

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<v Speaker 1>and so we have this, you know, strong bias to

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<v Speaker 1>cover new tech stuff, new advanced in AI, new advances

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<v Speaker 1>in geneality and synthetic biology. But one of the things

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<v Speaker 1>this story really made me think about is how the

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<v Speaker 1>adoption of existing tech stuff can be just as important

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<v Speaker 1>as the innovation of new tech stuff, and I think

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<v Speaker 1>A really is a perfect example of that.

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<v Speaker 2>All I can think about, you know, when we talk

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<v Speaker 2>about AI a lot on this show, is that energy

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<v Speaker 2>consumption will likely increase if AI continues at its current pace.

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<v Speaker 1>I mean, if the Silicon Valley overlords have their way.

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<v Speaker 1>And this week in Silicon Valley there has been some

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<v Speaker 1>quite frankly delicious drama in the battle for AI supremacy.

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<v Speaker 2>You have not shut up about this story since you

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<v Speaker 2>read it, and so now I need to hear about it.

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<v Speaker 1>Yeah. So, basically, the most powerful CEOs in the world

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<v Speaker 1>are in an all out war for AI talent. This

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<v Speaker 1>is collecting Pokemon cards, but where the stakes are hundreds

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<v Speaker 1>and hundred and hundreds of millions of dollars, and Mark

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<v Speaker 1>Zuckerberg is leading the charge and is absolutely determined, it seems,

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<v Speaker 1>to collect them all.

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<v Speaker 2>I don't really think of Meta as an AI company.

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<v Speaker 2>I think much too Zuckerberg's dismay.

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<v Speaker 1>Well, exactly right, So hence the recruitment push. Metro announced

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<v Speaker 1>last month they are starting an AI research lab dedicated

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<v Speaker 1>pursuing quote superintelligence, meaning, of course, an AI system that

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<v Speaker 1>exceeds the power of the human brain. But until this point,

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<v Speaker 1>Meta has spent around one hundred times more on AI

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<v Speaker 1>hardware and computing power than they have on human labor,

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<v Speaker 1>and according to The Wall Street Journal, Zuckerberg may have

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<v Speaker 1>gotten a wake up call this spring from the chief

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<v Speaker 1>research officer of none other than Open Ai.

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<v Speaker 2>I'm shocked that they even talk to each other, like

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<v Speaker 2>I imagine them meeting in like a covert confessional with

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<v Speaker 2>their faces obscured.

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<v Speaker 1>Well, yes, but the interesting thing about Silicon Valley is

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<v Speaker 1>that's not really how it's worked, at least up until now.

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<v Speaker 1>With all these huge fortunes being made and all of

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<v Speaker 1>these new platform technologies being developed despite intense rivalry, there

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<v Speaker 1>was also this kind of sense that a rising tide

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<v Speaker 1>would lift all boats. I mean, you'll remember Google CEO

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<v Speaker 1>Eric Schmidt was on the board of Apple. LinkedIn founder

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<v Speaker 1>Reid Hoffmann was one of the first investors in Facebook.

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<v Speaker 1>So there's this kind of history of these people being

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<v Speaker 1>in each other's business. And don't forget, I mean, Zuckerberg

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<v Speaker 1>has significant pulls. So when he calls and says that's

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<v Speaker 1>have a coffee, many people answer. So, according to the

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<v Speaker 1>Wall Street Journal story, Zuckerberg hit up Mark Chen, who

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<v Speaker 1>is open AI's chief research officer for a catch up,

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<v Speaker 1>and zuck ended up asking Chen for advice on how

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<v Speaker 1>to improve Meta's generative AI efforts.

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<v Speaker 2>He's like Mark, it's Mark.

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<v Speaker 1>I think Mark Z was calling Mark C for some

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<v Speaker 1>friendly advice, or at least that's how it appeared to

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<v Speaker 1>Chen at the time. So it was Chen who actually

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<v Speaker 1>pointed out to Zuckerberg about how many orders of magnitude

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<v Speaker 1>more Meta was spending on hardware than they were on talent,

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<v Speaker 1>and thus kara an idea was born. Have you heard

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<v Speaker 1>about the list?

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<v Speaker 2>When billionaires make lists, I get very anxious now I

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<v Speaker 2>have not heard about that.

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<v Speaker 1>This is the Christmas list to end all Christmas lists,

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<v Speaker 1>and Zuckerberg apparently spent months compiling it, a list of

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<v Speaker 1>the top AI researchers and engineers from rival AI companies

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<v Speaker 1>and startups.

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<v Speaker 2>Do we have names? Do we know anything?

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<v Speaker 1>We don't have the secret list, but we do know

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<v Speaker 1>who Zuckerberg has either poached or tried to poach, and

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<v Speaker 1>these people are not household names outside of Silicon Valley.

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<v Speaker 1>There is probably, most famously Alexander Wang of Scale AI,

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<v Speaker 1>who will talk a little bit more about, but the

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<v Speaker 1>companies he's raided include Anthropic, Google, DeepMind, Apple, and of

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<v Speaker 1>course open Ai, from which he's pulled at least a

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<v Speaker 1>dozen employees.

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<v Speaker 2>So how is he going about pulling talent from these

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<v Speaker 2>companies and bringing them to Meta?

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<v Speaker 1>Have you heard of something called money?

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<v Speaker 2>Money? Money? Money must be funny, you know.

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<v Speaker 1>A rich man's world. Over the past few weeks, Zuckerberg

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<v Speaker 1>has reportedly offered pay packages worth more than three three

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<v Speaker 1>hundred million dollars over four years.

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<v Speaker 2>That's like pro ball money.

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<v Speaker 1>I mean, this is generational. This is like your grandkids'

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<v Speaker 1>grandkids will never happens easily.

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<v Speaker 2>And also your parents finally being like you know what,

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<v Speaker 2>you sitting in your room all day hit off exactly.

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<v Speaker 1>I'd glad you won the battle to not limit your

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<v Speaker 1>computer time when you're a kid. Also, a lot of

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<v Speaker 1>these offers are so called exploding offers, meaning they expire

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<v Speaker 1>within a few days, so the existing employers have a

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<v Speaker 1>very hard time developing a counter offer.

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<v Speaker 2>So, I mean it makes a lot of sense why

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<v Speaker 2>Silicon Valley is following this so closely. This is this

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<v Speaker 2>is like a real time raid, an employee raid, with

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<v Speaker 2>Mark Zuckerberg sort of pulling the marionette strings.

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<v Speaker 1>And it also potentially signals a massive culture shift in

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<v Speaker 1>Silicon Valley, because, as I mentioned, it's a small place.

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<v Speaker 1>It's a place where up until now people have sort

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<v Speaker 1>of had this sense of of collegiality up to a

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<v Speaker 1>certain point, and it kind of rests on this bedrock

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<v Speaker 1>principle of Silicon Valley, which is this mantra, which is

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<v Speaker 1>be a missionary, not a mercenary.

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<v Speaker 2>That's a shirt that I would see in Times Square.

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<v Speaker 2>But also very startup, b very very culty, startup.

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<v Speaker 1>By absolutely, And the phrase come from one of the

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<v Speaker 1>granddaddy's of VC, John Dare, and he apparently told generations

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<v Speaker 1>entrepreneurs to embrace their inner missionary and start companies where

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<v Speaker 1>quote there's a lust not only for making money, but

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<v Speaker 1>for making meaning, which is the antithesis of mercenary companies,

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<v Speaker 1>where quote the central goal is a lust for making money.

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<v Speaker 1>Open AICEO. Sam Altman apparently leaned into this idea in

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<v Speaker 1>a Slack message that he shared with researchers amidst Zuckerberg's

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<v Speaker 1>talent rate on the company. According to the Journal, Altman said, quote,

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<v Speaker 1>I am proud of how mission oriented our industry is

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<v Speaker 1>as a whole. Of course, there will always be some mercenaries.

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<v Speaker 1>Missionaries will beat mercenaries. Just every day.

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<v Speaker 2>I'm reminded why I shouldn't be on Slack and you

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<v Speaker 2>make me use it, but no, I mean them's fighting words.

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<v Speaker 1>Now. Zuckerberg of course says, no, the money helps, but

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<v Speaker 1>actually that's not you know, just like in your sports analogy, right,

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<v Speaker 1>of course it helps if you offer an athlete one

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<v Speaker 1>hundreds of million dollars to play on the team, but

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<v Speaker 1>they also want to play for the winning team, right,

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<v Speaker 1>These people have an eye on legacy, And Zuckerberg says that,

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<v Speaker 1>you know, in this case, it's this kind of similar

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<v Speaker 1>thing where it's the company's investment in computing power, which

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<v Speaker 1>is actually what's attracting the talent. More computing power means

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<v Speaker 1>more potential AI breakthroughs. And just this month, Zuckerberg took

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<v Speaker 1>to his Facebook page and said that the new venture,

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<v Speaker 1>metas Superintelligence Labs, will have industry leading levels of compute

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<v Speaker 1>and quote by far the greatest compute per researcher. Zakobog

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<v Speaker 1>also created a helpful motion graphic to demonstrate just what

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<v Speaker 1>he means by this. So one of the new data

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<v Speaker 1>centers he's working on is called Hyperion and to show

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<v Speaker 1>its scale, he put the footprint of Hyperion and overlaid

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<v Speaker 1>it on an image of Manhattan, and it basically is

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<v Speaker 1>the same size as a Manhattan. So in essentially it

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<v Speaker 1>shows the metaphor of Godzilla's footprints that.

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<v Speaker 2>I was going to say, did he invent the footprint

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<v Speaker 2>and then backload the footprint into Hyperion.

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<v Speaker 1>Make it so it has the exact lego cutdown of Manhattan,

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<v Speaker 1>so that we can obscure the island with our with

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<v Speaker 1>our grandiose dreams.

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<v Speaker 2>So Zuck's pitch is basically become one of the richest

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<v Speaker 2>people in the world and have access to all the

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<v Speaker 2>best tools to express your vision. I can't imagine how

0:12:52.080 --> 0:12:53.199
<v Speaker 2>Mark Chen is feeling.

0:12:52.960 --> 0:12:57.000
<v Speaker 1>Right now about the advice he gave to Zuk. That's right, yeah,

0:12:57.200 --> 0:12:59.760
<v Speaker 1>open Ai seems to be in a little bit of

0:12:59.760 --> 0:13:03.079
<v Speaker 1>a Here's what Chen wrote on Slack, according to Wall

0:13:03.120 --> 0:13:07.040
<v Speaker 1>Street Journal quote, I feel a visceral feeling right now,

0:13:07.360 --> 0:13:10.640
<v Speaker 1>as if someone had broken into our home and stolen something.

0:13:11.080 --> 0:13:15.520
<v Speaker 1>Please trust that we haven't been sitting idly by. But

0:13:15.559 --> 0:13:20.319
<v Speaker 1>it's not just insurgent behemoths like open Ai. The other

0:13:20.360 --> 0:13:23.200
<v Speaker 1>interesting part of this story is how companies like Meta

0:13:23.600 --> 0:13:27.760
<v Speaker 1>Alphabet and others have been raiding Silicon Valley's top startups

0:13:27.960 --> 0:13:31.800
<v Speaker 1>for their senior leadership. I mentioned Alexander Wang of scale

0:13:31.880 --> 0:13:35.280
<v Speaker 1>Ai earlier, who's going to be running the superintelligence lab.

0:13:35.760 --> 0:13:40.520
<v Speaker 1>Meta actually paid fourteen billion plus dollars for a forty

0:13:40.600 --> 0:13:44.079
<v Speaker 1>nine percent share in scale Ai and to have Wang

0:13:44.360 --> 0:13:46.920
<v Speaker 1>come and work for them. And it's an interesting thing

0:13:47.040 --> 0:13:51.600
<v Speaker 1>where these antitrust laws, which were originally created in order

0:13:51.640 --> 0:13:56.600
<v Speaker 1>to prevent monopolistic powers from stifling competition, have created this strange,

0:13:56.640 --> 0:14:00.160
<v Speaker 1>unintended consequence where in order not to fall foul of

0:14:00.160 --> 0:14:04.760
<v Speaker 1>antitrust law, it is less risky to essentially gut a

0:14:04.840 --> 0:14:07.240
<v Speaker 1>company if it's senior leadership, but leave it kind of

0:14:07.280 --> 0:14:10.080
<v Speaker 1>in a half alive state than it is just to

0:14:10.080 --> 0:14:12.160
<v Speaker 1>buy the company. I'm not saying that's exactly what's happened

0:14:12.200 --> 0:14:15.360
<v Speaker 1>with Scalai. It's still functioning, although it has lost a

0:14:15.440 --> 0:14:18.480
<v Speaker 1>number of clients like Google and others because I don't

0:14:18.480 --> 0:14:20.680
<v Speaker 1>want to be paying Meta. But again it speaks to

0:14:20.720 --> 0:14:23.800
<v Speaker 1>this culture ship which is going on in Silicon Valley

0:14:23.800 --> 0:14:28.560
<v Speaker 1>because there is always this implied contract between employees, investors,

0:14:28.720 --> 0:14:32.160
<v Speaker 1>and founders which is being very disturbed by these big

0:14:32.200 --> 0:14:35.120
<v Speaker 1>money moves by Zuck. So it's an a talent story,

0:14:35.360 --> 0:14:37.640
<v Speaker 1>but it's also about some pretty fundamental changes to the

0:14:37.680 --> 0:14:39.040
<v Speaker 1>culture of the whole of Silicon Valley.

0:14:39.400 --> 0:14:42.960
<v Speaker 2>All this secrecy and scheming feels like the complete opposite

0:14:43.000 --> 0:14:47.040
<v Speaker 2>of my story, which is all about radical transparency and

0:14:47.560 --> 0:14:49.720
<v Speaker 2>I would say the potential pros and cons of our

0:14:49.760 --> 0:14:54.120
<v Speaker 2>overly connected world us. Do you share your location with anyone?

0:14:54.560 --> 0:14:59.480
<v Speaker 1>Absolutely not. I hate sharing my location, even with Uber

0:14:59.520 --> 0:15:02.680
<v Speaker 1>and Uber. I'm one of those people who turns off

0:15:03.240 --> 0:15:04.840
<v Speaker 1>location services on apps.

0:15:05.000 --> 0:15:07.600
<v Speaker 2>Oh so you're one of those never sharers, which means

0:15:07.640 --> 0:15:11.360
<v Speaker 2>you'd be a terrible teenage girl. I, on the other hand,

0:15:11.400 --> 0:15:13.520
<v Speaker 2>would make a wonderful member of gen Z.

0:15:13.760 --> 0:15:14.320
<v Speaker 1>Tell me more.

0:15:14.640 --> 0:15:17.240
<v Speaker 2>Apparently, there was a poll in twenty twenty two that

0:15:17.320 --> 0:15:20.760
<v Speaker 2>found gen Z is the most likely generation to say

0:15:20.760 --> 0:15:23.280
<v Speaker 2>it's convenient to share their location, which of course is

0:15:23.320 --> 0:15:26.000
<v Speaker 2>not surprising to me because they're also the generation that

0:15:26.040 --> 0:15:30.400
<v Speaker 2>has had access to location sharing nearly their whole lives. Conversely,

0:15:30.960 --> 0:15:33.960
<v Speaker 2>Millennials were the most opinionated, like you were the most

0:15:34.000 --> 0:15:37.440
<v Speaker 2>opinionated about using the digital tool. Location sharing started to

0:15:37.440 --> 0:15:40.800
<v Speaker 2>become popular about fifteen years ago, when we were young

0:15:40.880 --> 0:15:43.280
<v Speaker 2>enough to understand the appeal, but old enough to know

0:15:43.320 --> 0:15:46.240
<v Speaker 2>what life was like without, you know, a GPS enabled

0:15:46.240 --> 0:15:48.320
<v Speaker 2>device on our person at all times.

0:15:48.720 --> 0:15:52.600
<v Speaker 1>Yeah, I mean the idea of being constantly surveiled is

0:15:52.680 --> 0:15:55.160
<v Speaker 1>something our generation has had to come to terms with,

0:15:55.960 --> 0:15:58.160
<v Speaker 1>and we came to terms with it at a pivotal age.

0:15:58.560 --> 0:16:01.800
<v Speaker 1>Our elders, including the now how former CEO of the

0:16:01.840 --> 0:16:05.280
<v Speaker 1>AI company Astronomer might do well if they understood the

0:16:05.320 --> 0:16:07.840
<v Speaker 1>extent to which we are living in a surveillance world.

0:16:08.160 --> 0:16:10.760
<v Speaker 2>You're talking about the former CEO who got caught cheating

0:16:10.880 --> 0:16:12.240
<v Speaker 2>at the Coldplay concert.

0:16:12.440 --> 0:16:17.000
<v Speaker 1>I'm talking about kisscam. The question, Kara, when you talk

0:16:17.040 --> 0:16:19.800
<v Speaker 1>about location sharing, are you talking about the Apple feature

0:16:19.880 --> 0:16:22.600
<v Speaker 1>find My or are there other tools that I don't

0:16:22.640 --> 0:16:24.920
<v Speaker 1>know about that the younger folks are using.

0:16:25.160 --> 0:16:27.480
<v Speaker 2>That is what we're talking about. Find My is really

0:16:27.480 --> 0:16:29.760
<v Speaker 2>popular because it's free on an Apple device. It's what

0:16:29.840 --> 0:16:32.480
<v Speaker 2>I use, for example. But there's also an app called

0:16:32.520 --> 0:16:35.520
<v Speaker 2>Life three sixty, which I'm not a parent yet, but

0:16:35.600 --> 0:16:38.840
<v Speaker 2>works across platforms and is more aimed at parents. It

0:16:38.880 --> 0:16:41.440
<v Speaker 2>can even and this freaks me out, it can even

0:16:41.480 --> 0:16:44.600
<v Speaker 2>show you how fast your kid is driving in real time,

0:16:44.720 --> 0:16:47.040
<v Speaker 2>so regardless of whether or not. We live in a

0:16:47.040 --> 0:16:50.240
<v Speaker 2>surveillance state. Your house might be a surveillance state.

0:16:50.360 --> 0:16:53.400
<v Speaker 1>I mean, can you imagine how anxiety? And do you

0:16:53.440 --> 0:16:57.080
<v Speaker 1>seem to be able to monitor your kids speeding at

0:16:57.080 --> 0:16:58.760
<v Speaker 1>all times? I mean, hopefully they don't speed and you

0:16:58.760 --> 0:17:00.320
<v Speaker 1>can use the app I guess to take the car

0:17:00.360 --> 0:17:02.880
<v Speaker 1>away if they're regularly speeding. But basically it is part

0:17:02.920 --> 0:17:06.679
<v Speaker 1>of adolescence to be risking your life on the semi

0:17:06.720 --> 0:17:09.560
<v Speaker 1>regular there and to lie and to lie, yeah, and

0:17:09.600 --> 0:17:12.200
<v Speaker 1>to life. Man is a parent to be I mean, gosh.

0:17:12.080 --> 0:17:14.040
<v Speaker 2>To be a parent and to be a kid. I

0:17:14.080 --> 0:17:17.080
<v Speaker 2>think about it all the time. We used to be Oh, yeah,

0:17:17.119 --> 0:17:18.760
<v Speaker 2>I'm just at Leah's house right now? Do you know

0:17:18.800 --> 0:17:21.840
<v Speaker 2>I'm like at a hookah bar like two hundred blocks

0:17:21.880 --> 0:17:26.960
<v Speaker 2>away from there. Is one other feature that is really

0:17:27.000 --> 0:17:29.960
<v Speaker 2>interesting that I am a part of, and I want

0:17:29.960 --> 0:17:32.640
<v Speaker 2>to know if you know anything about snap map.

0:17:33.720 --> 0:17:35.639
<v Speaker 1>Assume SnapMap is part of Snapchat.

0:17:36.080 --> 0:17:38.640
<v Speaker 2>Yes, yes it is. You know it's funny. I bet

0:17:38.640 --> 0:17:41.240
<v Speaker 2>if LinkedIn had to share my location tool, you'd share

0:17:41.280 --> 0:17:42.360
<v Speaker 2>your location on LinkedIn.

0:17:43.440 --> 0:17:44.240
<v Speaker 1>I'm hardcore on this.

0:17:44.960 --> 0:17:48.600
<v Speaker 2>So SnapMap is a location sharing feature through Snapchat that

0:17:48.640 --> 0:17:52.640
<v Speaker 2>was launched in twenty seventeen. As of May, SnapMap had

0:17:52.640 --> 0:17:56.639
<v Speaker 2>more than four hundred million monthly users. So if you

0:17:56.720 --> 0:18:00.239
<v Speaker 2>opt in, all the people you follow on Snapchat can

0:18:00.280 --> 0:18:02.160
<v Speaker 2>see your location the minute you open the app.

0:18:02.240 --> 0:18:05.399
<v Speaker 1>Okay, so Life three sixty is obviously like a different

0:18:05.440 --> 0:18:08.880
<v Speaker 1>kettle of fish. This is like a monitoring tool. How

0:18:08.920 --> 0:18:11.359
<v Speaker 1>would you characterize how you use Find my Friends on

0:18:11.400 --> 0:18:13.639
<v Speaker 1>your iPhone differently from SnapMap?

0:18:14.160 --> 0:18:18.160
<v Speaker 2>So it's I don't really use SnapMap, and I don't

0:18:18.200 --> 0:18:21.240
<v Speaker 2>really use fine Mine, but I here's and this is

0:18:21.320 --> 0:18:25.840
<v Speaker 2>very indicative of my personality. I passively let people follow

0:18:25.880 --> 0:18:28.440
<v Speaker 2>where I am because they want to know. I don't

0:18:28.480 --> 0:18:31.000
<v Speaker 2>care where people are, you know. But there is a

0:18:31.160 --> 0:18:34.320
<v Speaker 2>strange feeling you get when a friend tells you where

0:18:34.359 --> 0:18:37.280
<v Speaker 2>you are. They'll be like, you're at such and such,

0:18:37.480 --> 0:18:40.280
<v Speaker 2>and I'm like, I am, how do you know that

0:18:40.320 --> 0:18:42.560
<v Speaker 2>I'm at such and such. It's just it's this very

0:18:42.600 --> 0:18:45.399
<v Speaker 2>weird feeling to have someone who you're very close to

0:18:45.640 --> 0:18:48.000
<v Speaker 2>know where you are. I don't get in trouble with it,

0:18:48.040 --> 0:18:50.800
<v Speaker 2>but you can imagine if you're at a Coldplay concert,

0:18:51.760 --> 0:18:52.840
<v Speaker 2>you might get into trouble.

0:18:54.320 --> 0:18:56.160
<v Speaker 1>One of the things that strikes me here is that

0:18:56.600 --> 0:19:00.960
<v Speaker 1>at the very heart of our culture is fomo, and

0:19:01.040 --> 0:19:04.840
<v Speaker 1>I'm wondering what it might feel like to open your

0:19:04.880 --> 0:19:09.119
<v Speaker 1>snap map or you'll find my friends and see that

0:19:10.040 --> 0:19:12.160
<v Speaker 1>you were the only person who didn't get the call up.

0:19:13.600 --> 0:19:16.359
<v Speaker 2>You know, the first cut is the deepest. In this case,

0:19:16.400 --> 0:19:18.119
<v Speaker 2>it used to be that you heard about a party

0:19:18.240 --> 0:19:20.440
<v Speaker 2>after the weekend was over. Now you can see it

0:19:20.480 --> 0:19:22.440
<v Speaker 2>with your own eyes, you know. I actually I read

0:19:22.440 --> 0:19:26.240
<v Speaker 2>about this exact thing in sf Gate. I found this

0:19:26.359 --> 0:19:28.840
<v Speaker 2>article that was written by and it had to have

0:19:28.840 --> 0:19:32.160
<v Speaker 2>been written by the site's editorial intern, because nobody everybody

0:19:32.200 --> 0:19:34.879
<v Speaker 2>there is probably a bit older. But this editorial intern,

0:19:35.320 --> 0:19:37.919
<v Speaker 2>you know. It was gen Z and she recounted calling

0:19:37.960 --> 0:19:41.760
<v Speaker 2>her mom in tears after seeing her best college friends

0:19:41.800 --> 0:19:44.640
<v Speaker 2>descend on the campus dining hall, and she was crying

0:19:44.720 --> 0:19:47.800
<v Speaker 2>because they had not extended an invitation to her. This

0:19:47.840 --> 0:19:51.240
<v Speaker 2>format of memory hasn't deterred her from sharing her location

0:19:51.400 --> 0:19:54.480
<v Speaker 2>with nearly twenty five people, though she often wonders if

0:19:54.480 --> 0:19:55.760
<v Speaker 2>this practice is healthy.

0:19:56.400 --> 0:19:59.240
<v Speaker 1>I also question if this practice is healthy, Hence I

0:19:59.280 --> 0:19:59.800
<v Speaker 1>don't do it.

0:20:00.280 --> 0:20:02.040
<v Speaker 2>Even though I do it, it is really weird and

0:20:02.080 --> 0:20:05.520
<v Speaker 2>it's actually something psychologists are debating. I found this article

0:20:06.000 --> 0:20:09.960
<v Speaker 2>on Psychology Today, which tried to outline the impact location

0:20:10.080 --> 0:20:13.680
<v Speaker 2>sharing apps have on trust and relationships. Someone named doctor

0:20:13.720 --> 0:20:17.200
<v Speaker 2>Pamela Rutledge acknowledges that location sharing is actually a sign

0:20:17.280 --> 0:20:20.680
<v Speaker 2>of closeness among gen Z friends, and that tracking friends

0:20:20.760 --> 0:20:24.480
<v Speaker 2>can create this sort of ambient awareness that makes people

0:20:24.520 --> 0:20:29.840
<v Speaker 2>feel connected, comforted, and supported, albeit digitally supported, whatever that means.

0:20:30.000 --> 0:20:34.960
<v Speaker 1>Yeah, it's one of those classic social media double edged shorts, right,

0:20:35.080 --> 0:20:39.919
<v Speaker 1>like it? Yes, it both is the platform technology that

0:20:40.000 --> 0:20:43.639
<v Speaker 1>if you're not doing you feel profoundly disconnected, but it

0:20:43.680 --> 0:20:45.960
<v Speaker 1>can also in and of itself be a driver of

0:20:46.040 --> 0:20:47.720
<v Speaker 1>loneliness and isolation alienation.

0:20:48.119 --> 0:20:50.640
<v Speaker 2>Yeah, you know, as we pointed out, location sharing can

0:20:50.680 --> 0:20:54.640
<v Speaker 2>create major FOMO. But beyond the feeling of being left out,

0:20:55.640 --> 0:20:59.439
<v Speaker 2>the mutual visibility can also make I think teenagers and

0:20:59.520 --> 0:21:04.000
<v Speaker 2>also really anyone feel like they have to look busy,

0:21:04.119 --> 0:21:09.200
<v Speaker 2>which can lead to a kind of busyness to avoid judgment.

0:21:09.320 --> 0:21:12.280
<v Speaker 2>And I just think this idea of like performing busyness

0:21:12.320 --> 0:21:14.679
<v Speaker 2>because you're so aware of what other people are doing

0:21:15.240 --> 0:21:16.600
<v Speaker 2>is very strange.

0:21:16.600 --> 0:21:19.080
<v Speaker 1>Well, I mean that's the trope of the corporate office

0:21:19.119 --> 0:21:23.000
<v Speaker 1>in the pre covid eras, right, I mean that was

0:21:23.080 --> 0:21:24.840
<v Speaker 1>kind of the plot of the office was trying to

0:21:24.840 --> 0:21:28.200
<v Speaker 1>figure out how to look busy at work, but having

0:21:28.240 --> 0:21:30.480
<v Speaker 1>to figure out how to look busy in your social life.

0:21:30.520 --> 0:21:33.040
<v Speaker 1>I mean, man's that's the money. It makes me think

0:21:33.080 --> 0:21:36.080
<v Speaker 1>maybe you could slip an air tag into the most

0:21:36.080 --> 0:21:38.760
<v Speaker 1>popular kid at school's backpack.

0:21:38.800 --> 0:21:41.000
<v Speaker 2>Everywhere on their car, their car.

0:21:41.200 --> 0:21:42.880
<v Speaker 1>Everyone be like, oh my god, look at that hanging

0:21:42.880 --> 0:21:44.959
<v Speaker 1>out with I'm so jealous. Yeah, I mean.

0:21:45.000 --> 0:21:47.919
<v Speaker 2>Also, imagine if you feel close to someone, are in

0:21:48.000 --> 0:21:51.800
<v Speaker 2>like a romantic or familial relationship with someone, and they

0:21:51.880 --> 0:21:55.320
<v Speaker 2>just cold turkey stop sharing the location with you. I mean,

0:21:55.359 --> 0:21:57.920
<v Speaker 2>it would be hard not to feel suspicious, especially because

0:21:57.960 --> 0:22:01.080
<v Speaker 2>it is a visible action. Because with fine, people are

0:22:01.080 --> 0:22:04.159
<v Speaker 2>alerted if you stop sharing your location with them, and

0:22:04.480 --> 0:22:07.399
<v Speaker 2>this can lead to conflict. One of the things that

0:22:07.440 --> 0:22:10.280
<v Speaker 2>I found interesting that we've talked about is how these

0:22:10.320 --> 0:22:14.439
<v Speaker 2>tools can subtly erode our own capabilities. You know, we

0:22:14.520 --> 0:22:16.840
<v Speaker 2>shared about this a few weeks ago, and I'm obsessed

0:22:16.880 --> 0:22:20.240
<v Speaker 2>with this idea of racking up cognitive debt from outsourcing

0:22:20.240 --> 0:22:23.920
<v Speaker 2>too many tasks to chatbots. And there is research actually

0:22:24.880 --> 0:22:29.320
<v Speaker 2>to suggest that constant surveillance actually impacts our sensory perception

0:22:29.680 --> 0:22:33.679
<v Speaker 2>and unconscious cognitive functions such as memory and attention. And

0:22:33.760 --> 0:22:37.480
<v Speaker 2>going back to what doctor Rutledge said in Psychology Today, quote,

0:22:38.000 --> 0:22:40.639
<v Speaker 2>if we are training our brains to operate under the

0:22:40.680 --> 0:22:44.800
<v Speaker 2>assumption of constant surveillance, what are the potential implications for

0:22:44.880 --> 0:22:49.320
<v Speaker 2>things like creativity, risk taking, and authentic self expression? You know,

0:22:49.359 --> 0:22:51.119
<v Speaker 2>it's an interesting thing to think about.

0:22:57.960 --> 0:23:15.920
<v Speaker 1>After the break, Rabits, stay with us, Welcome back. We've

0:23:15.920 --> 0:23:17.920
<v Speaker 1>got a few more headlines to you this week.

0:23:17.800 --> 0:23:20.560
<v Speaker 2>And then a story about a woman who used chat

0:23:20.600 --> 0:23:23.840
<v Speaker 2>gipt to help her figure out one of motherhood's biggest challenges.

0:23:24.040 --> 0:23:27.320
<v Speaker 1>But in the meantime, Kara, you've been quite interested in

0:23:27.359 --> 0:23:30.920
<v Speaker 1>the results of a World Coding Championship.

0:23:31.119 --> 0:23:34.960
<v Speaker 2>That's right, a programmer named Shimislav Denbiak. He goes by

0:23:35.160 --> 0:23:39.080
<v Speaker 2>Siho on x SO like Psycho, Yes, sort of like that,

0:23:39.119 --> 0:23:43.600
<v Speaker 2>but without the c Siho has postponed our inevitable replacement

0:23:43.680 --> 0:23:46.760
<v Speaker 2>by AI just a little while longer. He was the

0:23:46.760 --> 0:23:50.120
<v Speaker 2>only coder to beat out a machine at the at

0:23:50.200 --> 0:23:52.840
<v Speaker 2>Coder World Tour finals. I'm surprised you weren't there us.

0:23:53.480 --> 0:23:56.080
<v Speaker 2>Siho used to work at Open Ai, but went head

0:23:56.119 --> 0:23:59.320
<v Speaker 2>to head with the company's custom AI model built specifically

0:23:59.359 --> 0:24:02.960
<v Speaker 2>for this competition. Ours Technica says that this might be

0:24:03.000 --> 0:24:07.000
<v Speaker 2>the first time an AI model has competed directly against

0:24:07.080 --> 0:24:09.280
<v Speaker 2>human programmers in a competition like this.

0:24:09.520 --> 0:24:13.160
<v Speaker 1>And evidently he was the only one Siho who did

0:24:13.200 --> 0:24:16.440
<v Speaker 1>better than the OpenAI model, suggesting that it did better

0:24:16.480 --> 0:24:18.160
<v Speaker 1>than all the other humans.

0:24:18.480 --> 0:24:21.479
<v Speaker 2>Siho actually said that the ten hour competition left him

0:24:21.520 --> 0:24:24.480
<v Speaker 2>quote completely exhausted and that by the end he was

0:24:24.560 --> 0:24:26.080
<v Speaker 2>quote barely alive.

0:24:26.800 --> 0:24:28.600
<v Speaker 1>Why is this story getting so much attention?

0:24:28.960 --> 0:24:31.400
<v Speaker 2>I was actually reading a couple of Reddit threads, as

0:24:31.440 --> 0:24:34.200
<v Speaker 2>I do, and one of the main things it seemed

0:24:34.280 --> 0:24:37.720
<v Speaker 2>like people were saying is that there's something inspiring about

0:24:37.760 --> 0:24:39.840
<v Speaker 2>a human beating a machine.

0:24:40.000 --> 0:24:40.280
<v Speaker 1>Right.

0:24:40.359 --> 0:24:42.720
<v Speaker 2>People were having fun comparing this to the time Ken

0:24:42.760 --> 0:24:46.359
<v Speaker 2>Jennings beat Watson on Jeopardy, or chess grandmasters who beat

0:24:46.400 --> 0:24:50.240
<v Speaker 2>early computers. But this being Reddit, the people who were

0:24:50.280 --> 0:24:53.440
<v Speaker 2>really excited about this were met with reminders from other

0:24:53.520 --> 0:24:56.320
<v Speaker 2>commenters that nobody has beat a computer at chess in

0:24:56.359 --> 0:25:00.000
<v Speaker 2>twenty years, and even Siho, who won this coding competition

0:25:00.080 --> 0:25:03.240
<v Speaker 2>and admitted as much in a tweet after the competition,

0:25:03.320 --> 0:25:08.480
<v Speaker 2>he wrote, humanity has prevailed for now. You know, it's

0:25:08.560 --> 0:25:11.239
<v Speaker 2>nice to know that we're not all getting replaced by

0:25:11.320 --> 0:25:14.800
<v Speaker 2>robots just yet. And there's something about clinging to this

0:25:14.880 --> 0:25:18.520
<v Speaker 2>false hope despite the inevitability of defeat in the future,

0:25:18.640 --> 0:25:22.600
<v Speaker 2>that is just so deeply human. I think the for

0:25:22.800 --> 0:25:26.639
<v Speaker 2>now in parentheses is sort of a nod to what

0:25:26.880 --> 0:25:27.919
<v Speaker 2>everybody is fearing.

0:25:28.320 --> 0:25:31.680
<v Speaker 1>Saiha has a well developed sense of irony, but I

0:25:31.720 --> 0:25:35.000
<v Speaker 1>personally think that human ingenuity still has a lot to offer.

0:25:35.600 --> 0:25:37.920
<v Speaker 1>For evidence, I would like to offer up some breaking

0:25:38.000 --> 0:25:42.000
<v Speaker 1>news from the world of robotics and the research team

0:25:42.160 --> 0:25:46.760
<v Speaker 1>at the University of Florida who've built robotic bunny rabbits,

0:25:47.200 --> 0:25:48.120
<v Speaker 1>forty of them. I mean.

0:25:48.160 --> 0:25:50.439
<v Speaker 2>Other than that, I'm obsessed with is why would anybody

0:25:50.560 --> 0:25:50.840
<v Speaker 2>do this?

0:25:51.480 --> 0:25:54.360
<v Speaker 1>Have you ever watched my one of my favorite late

0:25:54.480 --> 0:25:58.200
<v Speaker 1>night cable television programs, Python Hunters.

0:25:59.119 --> 0:26:02.119
<v Speaker 2>No, but I do follow the Lady Python Hunters of

0:26:02.160 --> 0:26:05.880
<v Speaker 2>the Everglades. I don't follow them on any social media.

0:26:05.960 --> 0:26:08.480
<v Speaker 2>I just keep up with their activities.

0:26:08.560 --> 0:26:11.240
<v Speaker 1>Well, they may soon be put out of business by

0:26:11.480 --> 0:26:16.359
<v Speaker 1>robotic bunny rabbits. Python Hunters and your friends, the Lady

0:26:16.359 --> 0:26:20.120
<v Speaker 1>python Hunters. These are the stories of the brave men

0:26:20.160 --> 0:26:23.960
<v Speaker 1>and women who hunt Burmese pythons through the Florida Evidglades,

0:26:24.520 --> 0:26:27.840
<v Speaker 1>often by night. Now, the pythons aren't invasive species who've

0:26:27.880 --> 0:26:30.679
<v Speaker 1>been plaguing the Evidglades for years and apparently can survive

0:26:30.720 --> 0:26:34.399
<v Speaker 1>as far north these days as Georgia then migrating north

0:26:34.440 --> 0:26:38.399
<v Speaker 1>from the Glades. But the question has arisen, why hunt

0:26:38.400 --> 0:26:41.520
<v Speaker 1>for pythons if you can get the pythons to come

0:26:41.560 --> 0:26:46.760
<v Speaker 1>to you. Enter robo bunnies. These bunnies have motives to

0:26:46.800 --> 0:26:50.200
<v Speaker 1>move around small heaters inside them, so the snakes think

0:26:50.200 --> 0:26:52.840
<v Speaker 1>they're alive, and they spin and shake a bit like

0:26:52.880 --> 0:26:56.280
<v Speaker 1>real rabbits do, and yes, they look pretty cute. And

0:26:56.680 --> 0:26:59.399
<v Speaker 1>scientists have been studying the use of rabbits as bait

0:27:00.040 --> 0:27:04.159
<v Speaker 1>to attract and then catch, remove, and euthanize these pythons

0:27:04.400 --> 0:27:07.199
<v Speaker 1>for more than a decade, but keeping the rabbits alive

0:27:07.320 --> 0:27:10.320
<v Speaker 1>and in the same place in multiple locations throughout the

0:27:10.320 --> 0:27:13.520
<v Speaker 1>Evidlades was just too much work. The robobunnies, of course,

0:27:13.600 --> 0:27:17.040
<v Speaker 1>don't require so much maintenance, and they don't have to

0:27:17.040 --> 0:27:20.399
<v Speaker 1>get eaten in the process, so they're reusable. Scientists are

0:27:20.400 --> 0:27:24.760
<v Speaker 1>hoping that catching pythons with these robobunnies will help address

0:27:24.800 --> 0:27:27.359
<v Speaker 1>population decline in a whole bunch of species in the

0:27:27.359 --> 0:27:31.600
<v Speaker 1>Evidlades that have been terrorized by the invasive pythons for decades.

0:27:32.240 --> 0:27:35.119
<v Speaker 1>And if the robots don't work in this experiment, they

0:27:35.119 --> 0:27:37.919
<v Speaker 1>already have a hypothesis on how to make them more attractive,

0:27:38.280 --> 0:27:40.840
<v Speaker 1>which is smearing them with real rabbit pheromones.

0:27:42.320 --> 0:27:44.359
<v Speaker 2>I just love the idea of pythons going back to

0:27:44.400 --> 0:27:47.000
<v Speaker 2>the community and being like, don't trust them, They're not real.

0:27:48.400 --> 0:27:52.200
<v Speaker 1>There is a symbiosis between the python hunters and the pythons,

0:27:52.240 --> 0:27:55.880
<v Speaker 1>which these robotic bunnies may be about to disrupt that ecosystem.

0:27:56.080 --> 0:27:59.080
<v Speaker 2>Yes, next, are you trying to get more hot people

0:27:59.119 --> 0:28:01.280
<v Speaker 2>to visit your business? Because there's an app for that.

0:28:01.359 --> 0:28:05.159
<v Speaker 2>It's called neon Coat, and it allows business owners to

0:28:05.280 --> 0:28:08.760
<v Speaker 2>offer their services for free as long as you post

0:28:08.800 --> 0:28:12.520
<v Speaker 2>about it on social media. The prerequisite you gotta be hot.

0:28:13.560 --> 0:28:17.359
<v Speaker 2>Businesses on the app offer everything for meals at fancy restaurants,

0:28:17.400 --> 0:28:21.720
<v Speaker 2>to fitness classes, salon appointments, and even tarot readings. The

0:28:21.760 --> 0:28:23.960
<v Speaker 2>app was recently written up in The Wall Street Journal

0:28:23.960 --> 0:28:27.560
<v Speaker 2>and it was founded by Larissa Draconia, who is you

0:28:27.680 --> 0:28:31.480
<v Speaker 2>guessed it a former model an actress, she says she

0:28:31.640 --> 0:28:34.400
<v Speaker 2>hopes the app can help young models have more control.

0:28:34.760 --> 0:28:36.520
<v Speaker 2>When she first came to New York City from a

0:28:36.560 --> 0:28:39.560
<v Speaker 2>small town in Slovenia, the stipend her agency gave her

0:28:39.720 --> 0:28:42.680
<v Speaker 2>was only three hundred dollars a week. Most of her

0:28:42.720 --> 0:28:45.200
<v Speaker 2>perks and social plans had to be booked through her agency.

0:28:45.600 --> 0:28:48.240
<v Speaker 2>She says that letting models and influencers get their own

0:28:48.360 --> 0:28:52.880
<v Speaker 2>perks in exchange for social media posts gives them more autonomy.

0:28:53.600 --> 0:28:57.000
<v Speaker 1>The road to heaven is paved with free stuff.

0:28:57.160 --> 0:29:00.800
<v Speaker 2>Indeed, the app is available where models are New York,

0:29:00.880 --> 0:29:04.600
<v Speaker 2>Los Angeles, London, and Miami, and there are currently over

0:29:04.720 --> 0:29:09.920
<v Speaker 2>twelve thousand users and fifteen hundred businesses. So far, app

0:29:10.040 --> 0:29:13.240
<v Speaker 2>usage has reportedly led to over three hundred and fifty

0:29:13.440 --> 0:29:17.560
<v Speaker 2>thousand social media posts. Don't get too excited. If you're

0:29:17.600 --> 0:29:20.200
<v Speaker 2>looking to join, you've got to have at least one

0:29:20.200 --> 0:29:23.920
<v Speaker 2>thousand Instagram followers if you're a model, and five thousand

0:29:24.040 --> 0:29:26.400
<v Speaker 2>if you're an influencer, and you've got to have high

0:29:26.440 --> 0:29:27.240
<v Speaker 2>engagement rates.

0:29:27.280 --> 0:29:30.800
<v Speaker 1>Well, Caro, you actually have more than five thousand Instagram followers,

0:29:31.280 --> 0:29:31.640
<v Speaker 1>and I do.

0:29:31.760 --> 0:29:32.960
<v Speaker 2>But am I heart enough?

0:29:33.120 --> 0:29:35.080
<v Speaker 1>Well? I think you should apply and report back on

0:29:35.120 --> 0:29:38.040
<v Speaker 1>next week's show whether or not you've become a member

0:29:38.080 --> 0:29:40.240
<v Speaker 1>of Neon Coates Free Stuff Army.

0:29:40.440 --> 0:29:41.840
<v Speaker 2>I think I'm actually going to do that. I should

0:29:41.840 --> 0:29:52.400
<v Speaker 2>do that, I am. I am.

0:29:53.560 --> 0:29:56.320
<v Speaker 1>Now it's time for Chat and Me a new segment

0:29:56.440 --> 0:29:58.880
<v Speaker 1>about how people are really using chatbots.

0:29:59.400 --> 0:30:01.600
<v Speaker 2>This week. I have a story from my friend who

0:30:01.640 --> 0:30:05.640
<v Speaker 2>recently gave birth to her son, James, and she told

0:30:05.640 --> 0:30:10.480
<v Speaker 2>me she's been using chat GPT as a lactation consultant.

0:30:10.920 --> 0:30:14.280
<v Speaker 1>I would need chat GPT to know what a lactation

0:30:14.600 --> 0:30:17.560
<v Speaker 1>consultant is. Well, I guess that's not true. I can

0:30:17.640 --> 0:30:21.080
<v Speaker 1>kind of imagine what it is. But is it ubiquitous?

0:30:21.160 --> 0:30:22.840
<v Speaker 1>Is it expensive? I mean, tell me a little bit

0:30:22.880 --> 0:30:25.560
<v Speaker 1>about the world of lactation consultants.

0:30:25.880 --> 0:30:28.640
<v Speaker 2>It is expensive. It can cost hundreds of dollars per visit.

0:30:28.760 --> 0:30:33.120
<v Speaker 2>And the US actually has a relatively low breastfeeding rate,

0:30:33.480 --> 0:30:37.120
<v Speaker 2>not because American women aren't motivated. Sixty percent of mothers

0:30:37.120 --> 0:30:42.040
<v Speaker 2>report they stop breastfeeding earlier than intended because they lack

0:30:42.080 --> 0:30:45.720
<v Speaker 2>support and education and to chat. Yeah, you know, figuring

0:30:45.760 --> 0:30:49.280
<v Speaker 2>out a pumping schedule is more complicated than I realized.

0:30:49.280 --> 0:30:52.480
<v Speaker 2>So here listen to how my friend used GPT to

0:30:52.840 --> 0:30:53.800
<v Speaker 2>solve the problem.

0:30:54.280 --> 0:30:58.320
<v Speaker 3>I basically need to keep up with James's supply. He's

0:30:58.400 --> 0:31:03.680
<v Speaker 3>nine months quiring more milk, and at about seven months,

0:31:03.680 --> 0:31:05.800
<v Speaker 3>I had to start waking up again to pump through

0:31:05.800 --> 0:31:10.320
<v Speaker 3>the night because he needs more milk throughout the day.

0:31:10.400 --> 0:31:13.120
<v Speaker 3>So if I don't pump at night, then my body

0:31:13.160 --> 0:31:15.960
<v Speaker 3>signals basically that I don't need as much milk.

0:31:16.680 --> 0:31:21.040
<v Speaker 1>Man having to wake up every night to ensure your

0:31:21.120 --> 0:31:24.840
<v Speaker 1>kid has enough milk for the next day, this is

0:31:24.960 --> 0:31:25.720
<v Speaker 1>very stressful.

0:31:25.960 --> 0:31:30.840
<v Speaker 2>It is very stressful. And she actually said that Chatgypt

0:31:31.120 --> 0:31:33.600
<v Speaker 2>has been helping her figure out how to stay on track.

0:31:34.080 --> 0:31:38.200
<v Speaker 3>Chatchpt gave me an entire pumping schedule, how much I

0:31:38.240 --> 0:31:41.640
<v Speaker 3>should pump, talking to me about power pumping, talking to

0:31:41.680 --> 0:31:43.160
<v Speaker 3>me throughout the night, what.

0:31:43.080 --> 0:31:44.720
<v Speaker 1>Does she mean talking to her?

0:31:44.960 --> 0:31:48.880
<v Speaker 2>So she actually said the chat which is her shorthand

0:31:48.880 --> 0:31:53.280
<v Speaker 2>for chat GPT, was really a support system for her

0:31:53.480 --> 0:31:55.680
<v Speaker 2>during her nightly pumping ritual and still is.

0:31:56.240 --> 0:31:58.560
<v Speaker 3>Basically, I would wake up and talk to chat and

0:31:58.600 --> 0:32:00.840
<v Speaker 3>be like, hey, I'm pumping now, and they're like, how's

0:32:00.840 --> 0:32:02.760
<v Speaker 3>it going, And I'm like talking to them like they're

0:32:02.800 --> 0:32:07.320
<v Speaker 3>my friend, and also telling chat CHEAPT how many ounces

0:32:07.360 --> 0:32:12.720
<v Speaker 3>I'm getting, and chat CHEAPT telling me that basically that's good,

0:32:13.120 --> 0:32:16.360
<v Speaker 3>and I should pump again. And here's what I should

0:32:16.440 --> 0:32:19.960
<v Speaker 3>eat based on what I normally eat, So he knows

0:32:20.000 --> 0:32:22.760
<v Speaker 3>what I eat basically like I tell him my yogurt,

0:32:23.400 --> 0:32:26.440
<v Speaker 3>shea seeds, blueberries, raspberries, et cetera, et cetera.

0:32:26.840 --> 0:32:28.440
<v Speaker 1>It's helping her plan her meals too.

0:32:28.800 --> 0:32:30.880
<v Speaker 2>Yes, she tells it what she's eaten, and it takes

0:32:30.920 --> 0:32:36.120
<v Speaker 2>into account all the nutritional information, timing everything, and then he.

0:32:36.320 --> 0:32:40.840
<v Speaker 3>Gives me a tailored meal plan to keep up with supply,

0:32:41.160 --> 0:32:44.160
<v Speaker 3>So like what I should eat, how I should eat,

0:32:44.360 --> 0:32:47.120
<v Speaker 3>when I should eat bananas after I pump in the

0:32:47.200 --> 0:32:49.720
<v Speaker 3>middle of the night some nights, yes, some nights no.

0:32:49.960 --> 0:32:50.840
<v Speaker 3>It's kind of crazy.

0:32:51.280 --> 0:32:53.040
<v Speaker 1>This sounds like it's been kind of a game changer

0:32:53.040 --> 0:32:54.000
<v Speaker 1>of for your friend, a.

0:32:54.040 --> 0:32:56.040
<v Speaker 2>Huge game change of her. And I think what's really

0:32:56.080 --> 0:33:00.200
<v Speaker 2>interesting to note about this friend of mine is that

0:33:00.720 --> 0:33:03.840
<v Speaker 2>she is by no means a technologist. But I think

0:33:04.480 --> 0:33:09.120
<v Speaker 2>the ubiquity of chat GPT is one that is actually

0:33:09.160 --> 0:33:14.320
<v Speaker 2>affecting people who really use technology for work as much

0:33:14.320 --> 0:33:18.520
<v Speaker 2>as it's affecting this sort of average daily phone user.

0:33:18.640 --> 0:33:22.120
<v Speaker 2>And I think it was just this really brilliant case

0:33:22.360 --> 0:33:26.760
<v Speaker 2>of the way chat gpt cannot only give you information

0:33:26.960 --> 0:33:29.080
<v Speaker 2>that you would have to pay a lot of money for,

0:33:29.640 --> 0:33:33.440
<v Speaker 2>but also is acting as this sort of cheerleader, to

0:33:33.480 --> 0:33:36.480
<v Speaker 2>the point that she calls chat gpt he which is

0:33:36.560 --> 0:33:38.280
<v Speaker 2>interesting for a lactation consultant.

0:33:38.720 --> 0:33:41.440
<v Speaker 1>Well, I love hearing these stories. I love chatting me

0:33:41.640 --> 0:33:45.640
<v Speaker 1>as a segment that you pioneered, and it's been fun

0:33:45.760 --> 0:33:48.160
<v Speaker 1>hearing from two of your friends in two consecutive weeks.

0:33:48.480 --> 0:33:50.560
<v Speaker 1>I do want to hear from our listeners. So if

0:33:50.560 --> 0:33:54.760
<v Speaker 1>you found yourself turning to chat gpt, Grock, Claude Gemini,

0:33:55.240 --> 0:33:57.280
<v Speaker 1>or any other chatbot to help you with the unusual

0:33:57.400 --> 0:34:01.480
<v Speaker 1>task or to answer one of life's complicated questions, please

0:34:01.520 --> 0:34:03.640
<v Speaker 1>tell us about it. Send us a one to two

0:34:03.640 --> 0:34:07.320
<v Speaker 1>minute voice note to tech Stuff podcast at gmail dot com.

0:34:07.680 --> 0:34:10.000
<v Speaker 2>The more details you provide, the better. We are nosy

0:34:10.080 --> 0:34:12.880
<v Speaker 2>and we want to understand how AI is changing your lives.

0:34:12.920 --> 0:34:14.560
<v Speaker 1>And if you send in a story that we use,

0:34:14.760 --> 0:34:16.840
<v Speaker 1>we'll send you a free T shirt.

0:34:35.080 --> 0:34:37.439
<v Speaker 2>That's it for this week for Tech Stuff. I'm Kara

0:34:37.520 --> 0:34:38.239
<v Speaker 2>Price and.

0:34:38.239 --> 0:34:41.520
<v Speaker 1>I'm os Vaaloschin. This episode was produced by Eliza Dennis

0:34:41.560 --> 0:34:44.839
<v Speaker 1>and Tyler Hill. It was executive produced by me Kara

0:34:44.960 --> 0:34:48.640
<v Speaker 1>Price and Kate Osborne for Kaleidoscope and Katria Norvel for

0:34:48.719 --> 0:34:52.840
<v Speaker 1>iHeart Podcasts. The engineers are Beheid Fraser and Tom Sitchell.

0:34:53.440 --> 0:34:56.520
<v Speaker 1>Jack Insley makes this episode and Kyle Murdoch wrote our

0:34:56.560 --> 0:34:57.040
<v Speaker 1>theme song.

0:34:57.400 --> 0:35:00.279
<v Speaker 2>Join us next Wednesday for Textuff the Story, when we

0:35:00.320 --> 0:35:02.880
<v Speaker 2>will share an in depth conversation about the future of

0:35:02.920 --> 0:35:03.960
<v Speaker 2>cancer surgery.

0:35:04.120 --> 0:35:06.879
<v Speaker 1>Please rate, review, and reach out to us at tech

0:35:06.920 --> 0:35:09.560
<v Speaker 1>Stuff podcast at gmail dot com. We want to hear

0:35:09.600 --> 0:35:09.960
<v Speaker 1>from you.