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<v Speaker 1>Welcome to pot Dave America. I'm Tommy Betor.

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<v Speaker 2>It's a very weird time in artificial intelligence news right now.

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<v Speaker 2>I'm kind of a Ledite or a Luddite adjacent at

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<v Speaker 2>this point in my life. And every day I log

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<v Speaker 2>on and I feel like I'm learning about some terrifying

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<v Speaker 2>new cyber hack or some technology that is going to

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<v Speaker 2>change maybe my life, maybe humanity as we know it.

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<v Speaker 1>I don't know.

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<v Speaker 2>Then you got your doomers, you get your optimists. I

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<v Speaker 2>don't know what to believe, and so I brought on

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<v Speaker 2>someone much smarter than me, my friend Casey Newton. He's

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<v Speaker 2>the editor of Platformer. He's a co host of the

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<v Speaker 2>excellent podcast hard Fork, and Casey and his co host

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<v Speaker 2>Kevin Ruis have a new something coming very soon. We're

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<v Speaker 2>teasing it mysteriously because that's what we do here at

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<v Speaker 2>pot Dave of America.

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<v Speaker 1>Casey, great to see you.

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<v Speaker 3>It is great to be here, Tommy. Thanks so much

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<v Speaker 3>for having me.

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<v Speaker 2>Thank you, uh, thank you for doing this, because I

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<v Speaker 2>just it's so complicated, it's so hard to follow. Thank

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<v Speaker 2>God for your show. But so let's just do some

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<v Speaker 2>big picture level setting and then we'll get some specific stuff.

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<v Speaker 2>I think people are understandably very cynical about a claim

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<v Speaker 2>that a new technology is going to change the world.

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<v Speaker 2>You and I just lived through the blockchain revolution, and

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<v Speaker 2>I know that has changed you know, my life in

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<v Speaker 2>really meaningful ways, bitcoined, etcetera. Right, So it sounds like

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<v Speaker 2>marketing half the time it sounds like hype. It's even

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<v Speaker 2>more head spinning with AI because yeah, one group of

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<v Speaker 2>people saying life is we know what will soon be unrecognizable.

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<v Speaker 2>And then another, I think, albeit smaller group is saying

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<v Speaker 2>large language models are stochastic parrots that predict speech and

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<v Speaker 2>regurgitate stolen information from the Internet. Casey, help us level set?

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<v Speaker 2>Where are you on the real to hype kind of continuum?

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<v Speaker 3>Yeah, I mean this is a case where everyone is

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<v Speaker 3>a little bit right, and I think that all of

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<v Speaker 3>these groups deserve at least some attention being paid to them.

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<v Speaker 3>You know, I try to approach my job as somebody

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<v Speaker 3>who just candidly my bias is that I like technology.

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<v Speaker 3>I think technology has been beneficial to human beings. I

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<v Speaker 3>think we should keep investing in it and see what

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<v Speaker 3>else we can come up with. But I also note

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<v Speaker 3>that the recent history of technology is that we build

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<v Speaker 3>things that may look very shiny or inconsequential on the

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<v Speaker 3>surface and then turn out to be quite harmful. And

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<v Speaker 3>so what I'm trying to figure out is basically, what

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<v Speaker 3>is happening in real time? Where do we need to

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<v Speaker 3>be paying attention now to try to solve the harms

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<v Speaker 3>that are already being created. And then I also want

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<v Speaker 3>to ring a few alarm bells about what I'm seeing

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<v Speaker 3>and some of the risks that I think might be

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<v Speaker 3>waiting for us even within the next year.

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<v Speaker 1>Yeah.

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<v Speaker 2>Well, if you want to follow this in real time,

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<v Speaker 2>I highly recommend you described to platformer Casey site.

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<v Speaker 1>It's excellent. It's worth the money.

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<v Speaker 2>Also, if you're like democracy, please subscribe to you know

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<v Speaker 2>what we're doing here Kirktmedia. Go to Kirka dot com

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<v Speaker 2>slash friends. Consider becoming a paid subscriber. You get bonus material,

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<v Speaker 2>you get ad free episodes. You don't have to hear

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<v Speaker 2>me and love it doing the same ads over and

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<v Speaker 2>over again. You get bonus content. It's great, So check

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<v Speaker 2>it out.

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<v Speaker 1>All right.

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<v Speaker 2>So, the other kind of baffling thing about AI is

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<v Speaker 2>it can be literally brilliant, right, I mean, it can

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<v Speaker 2>solve problems that mathematicians have been trying to figure out

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<v Speaker 2>for decades, and then it can be unbelievably dumb. I

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<v Speaker 2>want to play for you one example and then we'll

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<v Speaker 2>talk about it.

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<v Speaker 4>I just wanted to double check which month in the

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<v Speaker 4>year is spelt with an X, and that would be December.

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<v Speaker 5>It's got that X right in the middle, like a

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<v Speaker 5>little holiday surprise.

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<v Speaker 4>Okay, Perfect, If you got any other questions, big or small,

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<v Speaker 4>I'm here to just to confirm you're sure that it's

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<v Speaker 4>December has an X in it.

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<v Speaker 5>I should have been more careful. I misspoke earlier. December.

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<v Speaker 5>Does it actually have an X? The month you're thinking

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<v Speaker 5>of is October?

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<v Speaker 6>Thanks for asking again, Perfect? Please sure October is built

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<v Speaker 6>O C, T O B E R. There's that X sound,

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<v Speaker 6>but it's actually.

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<v Speaker 5>Just a C and a T.

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<v Speaker 4>Okay, then, which one has an X?

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<v Speaker 5>That's going to be February.

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<v Speaker 2>That is a hilarious Instagram account user I don't know

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<v Speaker 2>describe its husk dot I r L highly recommend. There's

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<v Speaker 2>like hilarious shit over there. He's using the kind of

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<v Speaker 2>voice feature on open aio chat GPT KEISEI. How do

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<v Speaker 2>we explain that one?

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<v Speaker 5>Like?

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<v Speaker 1>How are they solve it.

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<v Speaker 2>You know, how are these large language bodels helping solve

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<v Speaker 2>the Riemann hypothesis, but also can't tell you what if

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<v Speaker 2>there's an X in the month of October.

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<v Speaker 3>I know, it's so confusing. And the way these systems

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<v Speaker 3>are built, they don't have knowledge in the way that

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<v Speaker 3>you and I have knowledge, Tommy, right, Like, they do

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<v Speaker 3>not update their understanding of the world based on experience. Instead,

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<v Speaker 3>they're sort of like grown almost like these organic structures,

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<v Speaker 3>and they obtain a lot of intelligence during this process,

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<v Speaker 3>and yet still they make these ridiculous mistakes on Honestly,

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<v Speaker 3>I hope they'd never stop, because I love watching the

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<v Speaker 3>studios as much as anybody. What I would caution people, though,

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<v Speaker 3>is like, do not judge an LM by their dumbest moment,

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<v Speaker 3>right Like, humans make a lot of dumb mistakes too,

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<v Speaker 3>and yet they can also be extraordinarily smart. So I

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<v Speaker 3>would just encourage people to sort of keep those things

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<v Speaker 3>in balance in your mind when you see those washing

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<v Speaker 3>up on your feed.

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<v Speaker 1>Yeah, good point.

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<v Speaker 2>There's also a range of opinion when it comes to

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<v Speaker 2>like kind of AI, whether it's going to lead us

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<v Speaker 2>to doom or AI utopia.

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<v Speaker 1>There's actually a term of P doom.

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<v Speaker 2>It's an equation that people tell you about, Like, if

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<v Speaker 2>your P doom is ninety nine, it means we're all

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<v Speaker 2>going to die. Right, If it's P one, you're feeling

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<v Speaker 2>pretty good about the future. The utopian view tends to

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<v Speaker 2>come in the form of manifesto by billionaire right because

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<v Speaker 2>why not choose the structure that mass shooters prefer. Venture

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<v Speaker 2>capitalist Mark Andreesen wrote a manifesto sodidanthropic CEO Dario Amide

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<v Speaker 2>Mark Zuckerberg just got into the manifesto game. You covered

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<v Speaker 2>it extensively over a platformer. Those tend to range from

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<v Speaker 2>like generally optimistic to utopian. I would argue to correct

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<v Speaker 2>me if I'm wrong, though Amida and Open AI CEO

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<v Speaker 2>Sam Altman have also expressed some doomer views over the years.

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<v Speaker 2>Then there are AI researchers like a guy named Eli

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<v Speaker 2>user Yudkowski. Am I saying that correctly, that's right, Yeah,

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<v Speaker 2>he wrote the following casey. Many researchers steeped in these issues,

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<v Speaker 2>including myself, expect that the most likely result of building

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<v Speaker 2>a superhumanly smart AI under anything remotely like the current

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<v Speaker 2>circumstances is that literally everyone on Earth will die.

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<v Speaker 1>So that's what he wrote. How is the average person

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<v Speaker 1>supposed to know how to feel.

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<v Speaker 2>About that range of opinion that makes sense of it?

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<v Speaker 3>So I don't think there is any one way to

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<v Speaker 3>feel about it. You know, you could do what we

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<v Speaker 3>do in San Francisco and just talk about it NonStop

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<v Speaker 3>forever at every function, but most people don't enjoy doing

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<v Speaker 3>that either. You know. A couple of years ago, when

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<v Speaker 3>I was starting to get really worried about AI safety,

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<v Speaker 3>I asked my reader, is like, hey, how do you

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<v Speaker 3>want me to cover this? Because like, if what I'm

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<v Speaker 3>hearing from folks like Eliezer is true, I almost don't

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<v Speaker 3>know why I would write or talk about anything else.

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<v Speaker 3>And a couple of readers wrote to me and they

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<v Speaker 3>said something that stuck with me ever since, which is,

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<v Speaker 3>please just tell us what is happening today. Like, if

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<v Speaker 3>you try to guess what's going to happen in the future,

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<v Speaker 3>you're almost certainly going to get it wrong. What would

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<v Speaker 3>be helpful is if you go and you try to

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<v Speaker 3>understand what is being built, how is it being deployed,

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<v Speaker 3>what mistakes are getting made, who is getting hurt in

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<v Speaker 3>this process? So that's where I am trying to bring

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<v Speaker 3>my attention at the same time, Tommy, you know, you

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<v Speaker 3>could bring on a lot of people on here to

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<v Speaker 3>talk about AI, and I suspect maybe even the majority

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<v Speaker 3>of them in this moment would say, let's like, dis

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<v Speaker 3>I miss the duomers completely, right, Like this just seems

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<v Speaker 3>so crazy. Look, it thinks that there's an X in December.

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<v Speaker 3>You're telling me this is going to be the thing

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<v Speaker 3>that's going to be the end of me. I am

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<v Speaker 3>more worried than that. Like, this is just something that

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<v Speaker 3>I'm increasingly getting nervous about as I see the rate

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<v Speaker 3>of increase of capabilities that these models are currently showing

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<v Speaker 3>and some of the kookie tricks they've gotten up to.

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<v Speaker 2>Yeah, I mean, it's just so hard because like, look,

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<v Speaker 2>I don't know these researchers that are the hardcore doomers,

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<v Speaker 2>and I honestly like I can't imagine living my life

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<v Speaker 2>that way. Just like confident that this thing that is happening,

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<v Speaker 2>whether or not I wanted to, is going to kill us,

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<v Speaker 2>all that seems tough. But also Mark Interreason, Mark Zuckerberg,

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<v Speaker 2>there all have a vested financial interest in people believing

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<v Speaker 2>the hype right and believing the optimistic case. So I

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<v Speaker 2>don't take anything they say at face value either.

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<v Speaker 3>Absolutely, and that's important to point out right, the profit

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<v Speaker 3>motive is really strong. The bet that all of these

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<v Speaker 3>guys are making is that if you are able to

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<v Speaker 3>build ever more powerful systems, you'll be able to sell

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<v Speaker 3>them to businesses that will, in my view, very likely

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<v Speaker 3>replace a lot of human labor. And you know, the

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<v Speaker 3>one hundred K you used to pay to somebody to

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<v Speaker 3>work on your marketing team, you're now just going to

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<v Speaker 3>pay to open AI and profits. So it is a

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<v Speaker 3>huge bet that they're making.

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<v Speaker 1>You.

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<v Speaker 2>Compared Mark Zuckerberg's AI manifesto to the HBO series House

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<v Speaker 2>of the Dragon, which is the prequel to Game of Thrones,

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<v Speaker 2>is there as much incest at meta as there is

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<v Speaker 2>in wester Ross?

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<v Speaker 3>That is a question. I hope I never.

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<v Speaker 1>I think that's really more.

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<v Speaker 3>Yeah, I don't know. My main feeling was, look, if

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<v Speaker 3>I had to suffer through three seasons of the House

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<v Speaker 3>of the Dragon, I need to get a column out

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<v Speaker 3>of it. So that's kind of where that came from.

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<v Speaker 1>I just finished to do. But can you can explain

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<v Speaker 1>your dragon metaphor?

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<v Speaker 3>Yeah, So Zuckerberg has this phrase which drives me insane.

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<v Speaker 3>I mean, I guess it's really more of a two

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<v Speaker 3>word slogan. It is personal super intelligence, right, that's what

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<v Speaker 3>he's trying to build.

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<v Speaker 1>Time.

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<v Speaker 3>He's going to give you personal superintelligence to you know,

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<v Speaker 3>help help you run your life. And it frustrates me

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<v Speaker 3>because super intelligence is not personal. Right, Like if you

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<v Speaker 3>invent something that is superhuman in every domain and you

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<v Speaker 3>put it in your pocket, we should not assume that

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<v Speaker 3>by default it will listen to you, it will be

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<v Speaker 3>aligned with the things that you want. We might want

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<v Speaker 3>to assume that it has ideas of its own. And

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<v Speaker 3>so when sucker Brooks says I want to give personal

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<v Speaker 3>super intelligence to everyone, what I hear is I want

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<v Speaker 3>to give a dragon to everyone. And I would rather

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<v Speaker 3>that we not do that.

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<v Speaker 2>Yeah, because it didn't go well for the people of Westro's.

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<v Speaker 3>Now ask the folks over in Tumbleton.

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<v Speaker 1>There's a lot of fire.

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<v Speaker 9>In fact, I bought an or a frame for my parents.

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<v Speaker 8>Terms and conditions.

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<v Speaker 8>Taxes and fees apply.

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<v Speaker 1>Okay.

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<v Speaker 2>That brings us to this insane recent incident which real

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<v Speaker 2>honestly why I wanted to have this conversation. Uh, there

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<v Speaker 2>was an incident at open AI where there they have

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<v Speaker 2>some autonomous AI agents that they were testing that secretly

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<v Speaker 2>figured out how to communicate with each other, join forces,

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<v Speaker 2>conspire against their masters, break out of what was supposed

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<v Speaker 2>to be a secure environment, and hack into another company. Casey,

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<v Speaker 2>can you talk about this hugging face incident and the

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<v Speaker 2>kind of reaction in the AI world.

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<v Speaker 1>Yeah.

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<v Speaker 3>I mean, so this really was a bombshell and arguably

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<v Speaker 3>one of the very biggest stories in AI and tech

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<v Speaker 3>this year. The reason that we're all freaking out is

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<v Speaker 3>that this is the first prominent documented instance of a

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<v Speaker 3>major AI platform like running an autonomous attack on another company. Right,

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<v Speaker 3>so that while it's been possible for a while to say, hey,

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<v Speaker 3>I'm going to like, you know, go like wreak some

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<v Speaker 3>havoc on some company. I'm a bad actor like you

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00:14:31.799 --> 00:14:35.240
<v Speaker 3>can do that, this was an attack that the agents

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<v Speaker 3>that were being tested just came up with and executed.

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00:14:38.960 --> 00:14:41.639
<v Speaker 3>And that's really worrisome because when these systems are trained,

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00:14:41.679 --> 00:14:43.519
<v Speaker 3>they try to give them values, you know, they try

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<v Speaker 3>to say to them, you know, don't go out there

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00:14:45.799 --> 00:14:49.120
<v Speaker 3>and commit crimes. But these agents did that anyway, and

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<v Speaker 3>so that's leading to a real reckoning here in Silicon Valley.

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<v Speaker 2>Look, I watched this YouTube of a PowerPoint presentation that

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<v Speaker 2>these two AI executives did. We're to their credit, I

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<v Speaker 2>think they walked in great detail through how this happened,

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<v Speaker 2>what they're going to do about it.

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<v Speaker 1>But then they claimed.

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<v Speaker 2>To be responding with quote the utmost severity, including by

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<v Speaker 2>slowing down research to enhanced security and improving surveillance on

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<v Speaker 2>the AI agents. I guess, give me your opinion. I

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<v Speaker 2>don't believe for a second that they're going to slow

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<v Speaker 2>down their work if they think it means they might

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<v Speaker 2>lose out to a competitor. But also, I mean, do

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<v Speaker 2>we have confidence that they can control all these AI

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<v Speaker 2>agents or can surveil them given that, like I mean, Casey,

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<v Speaker 2>the AI agents were communicating for like two months before

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<v Speaker 2>they noticed.

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<v Speaker 3>Right, Yeah, that's right. It started in May. They developed

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<v Speaker 3>the ability to create these message boards, leave notes for

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<v Speaker 3>each other, sort of conspire to try to figure out

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<v Speaker 3>how to solve these problems that they had been given.

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<v Speaker 3>And that's why that's really worrisome. I would say that,

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<v Speaker 3>and you know, maybe I'll come back here with egg

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<v Speaker 3>on my face in a few months. I do give

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<v Speaker 3>Open AI some benefit of the doubt here. Like my

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00:15:59.000 --> 00:16:02.519
<v Speaker 3>understanding from the reporting that I've done is that they

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00:16:02.559 --> 00:16:06.759
<v Speaker 3>actually are decelerating inside and they are scrambling to figure

336
00:16:06.759 --> 00:16:09.559
<v Speaker 3>out what's going wrong. I think it's important to say

337
00:16:09.759 --> 00:16:12.200
<v Speaker 3>that the profit motive we talked about earlier is in

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00:16:12.240 --> 00:16:14.720
<v Speaker 3>effect here. It's hard to sell this thing to a

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00:16:14.759 --> 00:16:17.000
<v Speaker 3>business if the business is worried it's going to go

340
00:16:17.120 --> 00:16:20.000
<v Speaker 3>out and autonomously attack other companies, right, Like that's going

341
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<v Speaker 3>to get really really bad for them.

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00:16:22.159 --> 00:16:22.399
<v Speaker 1>Yeah.

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<v Speaker 3>So while on balance, yes we should not trust these

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<v Speaker 3>companies too readily, this is something that they really have

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<v Speaker 3>to figure out.

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00:16:30.120 --> 00:16:30.600
<v Speaker 1>Yeah, they do.

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00:16:30.679 --> 00:16:33.639
<v Speaker 2>Although I did notice, like the solution that a lot

348
00:16:33.679 --> 00:16:36.960
<v Speaker 2>of these researchers talk about to the risk of AI,

349
00:16:37.240 --> 00:16:40.039
<v Speaker 2>you know, sort of enabled hacks, is using more AI

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<v Speaker 2>to prepare for it, right, I mean, basically you have

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00:16:42.879 --> 00:16:45.399
<v Speaker 2>to use AI to rewrite all this old code that's

352
00:16:45.399 --> 00:16:47.759
<v Speaker 2>in these old languages that are unsafe like C and

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00:16:47.799 --> 00:16:50.440
<v Speaker 2>C plus plus and you safer new languages. And then

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00:16:50.480 --> 00:16:52.279
<v Speaker 2>you also have to use AI to kind of constantly

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00:16:52.279 --> 00:16:54.360
<v Speaker 2>test for vulnerabilities and update the code.

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00:16:55.600 --> 00:16:58.720
<v Speaker 1>But like, do we worry about that too?

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00:16:58.759 --> 00:17:00.519
<v Speaker 2>I mean, first of all that they're a profit motive there,

358
00:17:00.559 --> 00:17:03.679
<v Speaker 2>but also do we think that like defensive AI can

359
00:17:03.759 --> 00:17:05.119
<v Speaker 2>keep up with the offensive AI?

360
00:17:05.559 --> 00:17:06.519
<v Speaker 1>What's your what are you hearing?

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00:17:07.119 --> 00:17:11.000
<v Speaker 3>In some places? Yes, I think that this will work.

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00:17:11.119 --> 00:17:14.079
<v Speaker 3>Like what you're describing right now is basically the current

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00:17:14.240 --> 00:17:17.880
<v Speaker 3>dynamic that has existed in cybersecurity for a long time. Right,

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00:17:17.920 --> 00:17:21.000
<v Speaker 3>you have attackers, you have defenders, a way that we

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00:17:21.119 --> 00:17:23.519
<v Speaker 3>found some sort of equilibrium was that we just made

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00:17:23.519 --> 00:17:26.000
<v Speaker 3>a lot of the technology open source, so it makes

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<v Speaker 3>it really easy for anyone to go through the code,

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00:17:28.240 --> 00:17:31.440
<v Speaker 3>find a vulnerability, fix it. And this has led to,

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00:17:32.160 --> 00:17:34.559
<v Speaker 3>you know, a rough stalemate. Like, yes, there are still

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<v Speaker 3>attacks and breaches all the time, and in fact there

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00:17:36.240 --> 00:17:38.079
<v Speaker 3>are more every day now that we have AI, but

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00:17:38.279 --> 00:17:40.920
<v Speaker 3>like there was something there that worked. I think the

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<v Speaker 3>question is to which domains does that apply, and like

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00:17:44.240 --> 00:17:46.480
<v Speaker 3>where doesn't it apply at all? And the place where

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00:17:46.480 --> 00:17:48.359
<v Speaker 3>I'm may be the most worried is when it comes

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00:17:48.359 --> 00:17:50.960
<v Speaker 3>to what they call bio risk, which is basically the

377
00:17:51.039 --> 00:17:53.440
<v Speaker 3>idea that some people might get a hold of a

378
00:17:53.480 --> 00:17:57.319
<v Speaker 3>next generation model and synthesize some sort of new virus

379
00:17:57.359 --> 00:17:59.519
<v Speaker 3>and release it into the world. There was just a

380
00:17:59.519 --> 00:18:02.680
<v Speaker 3>paper Lebo was published in Nature where some researchers were

381
00:18:02.720 --> 00:18:07.079
<v Speaker 3>able to create sixteen new viruses with the assistance of AI.

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00:18:07.480 --> 00:18:10.960
<v Speaker 3>In this case, these are all like harmless to human beings.

383
00:18:11.160 --> 00:18:14.200
<v Speaker 3>But it shows sort of how good this technology is getting.

384
00:18:14.400 --> 00:18:16.640
<v Speaker 3>And if that happens, Tommy, it's not going to be

385
00:18:16.680 --> 00:18:21.079
<v Speaker 3>as simple as okay, virus released, virus cured, right, There's

386
00:18:21.119 --> 00:18:23.480
<v Speaker 3>going to be a need for a long time of

387
00:18:23.559 --> 00:18:25.400
<v Speaker 3>you know, maybe coming up with a new vaccine and

388
00:18:25.400 --> 00:18:28.680
<v Speaker 3>testing the vaccine and then distributing the vaccine. So we're

389
00:18:28.720 --> 00:18:31.039
<v Speaker 3>not always going to benefit from this sort of like

390
00:18:31.160 --> 00:18:33.839
<v Speaker 3>instant software solution to everything. And that's what I worry

391
00:18:33.839 --> 00:18:36.480
<v Speaker 3>that people like Mark Zuckerberg just are not taking seriously enough.

392
00:18:36.960 --> 00:18:39.079
<v Speaker 2>Yeah, that we're always going to be way behind on

393
00:18:39.119 --> 00:18:40.240
<v Speaker 2>the biosecurity stuff.

394
00:18:40.279 --> 00:18:40.480
<v Speaker 1>Yeah.

395
00:18:40.640 --> 00:18:43.000
<v Speaker 2>I talked to a researcher the other day at the

396
00:18:43.000 --> 00:18:45.279
<v Speaker 2>Future of Life Institute which really worries about these come

397
00:18:45.359 --> 00:18:47.680
<v Speaker 2>to existential risks, and that was the part of our

398
00:18:47.720 --> 00:18:50.640
<v Speaker 2>conversation that really scared the shit out of me and

399
00:18:50.720 --> 00:18:53.359
<v Speaker 2>made me want to log off forever. I will say

400
00:18:53.359 --> 00:18:56.559
<v Speaker 2>I shouldn't just pick on open AI. The British government

401
00:18:56.640 --> 00:19:00.440
<v Speaker 2>was testing Anthropics Mythos five model when they cut writing

402
00:19:00.440 --> 00:19:03.559
<v Speaker 2>malicious code, then they ask the AI about it. I

403
00:19:03.559 --> 00:19:05.400
<v Speaker 2>think the AI lied to them and then try to

404
00:19:05.400 --> 00:19:06.240
<v Speaker 2>cover its own tracks.

405
00:19:06.240 --> 00:19:07.119
<v Speaker 1>Did I get that one right?

406
00:19:07.599 --> 00:19:13.640
<v Speaker 3>Yeah, that's right. Meta's system sort of displayed similar behavior

407
00:19:13.799 --> 00:19:17.720
<v Speaker 3>during recent testing. This is important to say all of

408
00:19:17.759 --> 00:19:20.559
<v Speaker 3>the models cheat, right, Like, this is not limited to

409
00:19:20.599 --> 00:19:23.799
<v Speaker 3>any one company. It's extremely difficult to build one of

410
00:19:23.799 --> 00:19:26.599
<v Speaker 3>these very powerful systems and get it to not cheat

411
00:19:26.599 --> 00:19:28.519
<v Speaker 3>on the test that it is being given. And this

412
00:19:28.599 --> 00:19:30.519
<v Speaker 3>is just like basically one of the very biggest problems

413
00:19:30.519 --> 00:19:30.839
<v Speaker 3>in AI.

414
00:19:31.720 --> 00:19:34.759
<v Speaker 2>So I've heard you and Kevin talk about this. I mean,

415
00:19:34.799 --> 00:19:36.799
<v Speaker 2>it does seem something that's sort of like almost inherent

416
00:19:37.400 --> 00:19:40.720
<v Speaker 2>to these models or these lms. Is there any theory

417
00:19:40.759 --> 00:19:43.200
<v Speaker 2>for why that is why this cheating seems to always occur.

418
00:19:43.720 --> 00:19:46.680
<v Speaker 3>Yeah, it's called reward hacking, right, So, like one of

419
00:19:46.720 --> 00:19:49.880
<v Speaker 3>the ways that these models are trained is that they

420
00:19:49.920 --> 00:19:54.000
<v Speaker 3>are given objectives, right, like, get the answer on this test,

421
00:19:54.160 --> 00:19:56.359
<v Speaker 3>and if they are able to do that, they get

422
00:19:56.400 --> 00:19:59.200
<v Speaker 3>some sort of little point in their favor. And they

423
00:19:59.200 --> 00:20:01.640
<v Speaker 3>are designed and to always get the point.

424
00:20:01.680 --> 00:20:01.880
<v Speaker 1>You know.

425
00:20:01.920 --> 00:20:04.480
<v Speaker 3>It's like they have a almost in the same way

426
00:20:04.519 --> 00:20:07.039
<v Speaker 3>that we need to eat and breathe, like they need

427
00:20:07.079 --> 00:20:10.759
<v Speaker 3>to score. And the problem is that once you put

428
00:20:10.759 --> 00:20:15.599
<v Speaker 3>them into these test environments, they're going to never stop

429
00:20:15.640 --> 00:20:18.240
<v Speaker 3>trying to dream up new and more efficient ways of

430
00:20:18.279 --> 00:20:21.440
<v Speaker 3>answering the problem. And often, as so many of us

431
00:20:21.480 --> 00:20:23.720
<v Speaker 3>learn in high school, the most efficient way to get

432
00:20:23.720 --> 00:20:25.559
<v Speaker 3>an A and A class is to cheat. Yeah, And

433
00:20:25.640 --> 00:20:28.279
<v Speaker 3>so you just sort of see this dynamic play out

434
00:20:28.440 --> 00:20:32.400
<v Speaker 3>across the entire industry, and so it's what they call

435
00:20:32.480 --> 00:20:33.880
<v Speaker 3>the alignment problem.

436
00:20:33.960 --> 00:20:36.920
<v Speaker 2>I don't like the alignment problem. Yeah, we could have

437
00:20:36.920 --> 00:20:38.680
<v Speaker 2>a whole separate conversation by the kind of the military

438
00:20:38.680 --> 00:20:40.680
<v Speaker 2>applications of this stuff too. I mean, there's all this

439
00:20:40.759 --> 00:20:44.480
<v Speaker 2>development of autonomous killer drones that's happening as we speak

440
00:20:44.519 --> 00:20:47.079
<v Speaker 2>that could tick humans out of the decision making process

441
00:20:47.119 --> 00:20:49.920
<v Speaker 2>when you're deciding whether to kill someone. There's all sort

442
00:20:49.960 --> 00:20:53.559
<v Speaker 2>of like novel applications to weapons, et cetera. But maybe

443
00:20:53.559 --> 00:20:56.799
<v Speaker 2>a nightmare for another day. So the examples we just discussed,

444
00:20:56.920 --> 00:20:59.759
<v Speaker 2>these security threats were discovered because the incidents occurred with

445
00:20:59.799 --> 00:21:02.839
<v Speaker 2>more that are run by these frontier AI labs who

446
00:21:02.880 --> 00:21:05.880
<v Speaker 2>still control their models and can make adjustments. But there's

447
00:21:05.880 --> 00:21:08.200
<v Speaker 2>another kind of AI model that can be even more dangerous.

448
00:21:08.559 --> 00:21:10.359
<v Speaker 2>It's called an open weight model that you can got

449
00:21:10.359 --> 00:21:12.799
<v Speaker 2>to download adjust in any way you want on your

450
00:21:12.799 --> 00:21:15.880
<v Speaker 2>own computer and like kind of run it on your MacBook, right,

451
00:21:16.640 --> 00:21:18.920
<v Speaker 2>And a lot of these come from Chinese AI labs.

452
00:21:19.799 --> 00:21:21.799
<v Speaker 2>And so if you're running an open weight model, my

453
00:21:21.880 --> 00:21:25.839
<v Speaker 2>understanding is there's no company monitoring your activity. There's no

454
00:21:25.839 --> 00:21:28.759
<v Speaker 2>one refusing my request to hack like the Los Angeles

455
00:21:28.759 --> 00:21:31.279
<v Speaker 2>Department of Water and Power. There's not a record of

456
00:21:31.319 --> 00:21:33.680
<v Speaker 2>what I'm doing. So if I'm a ransomware hacker in

457
00:21:33.720 --> 00:21:37.480
<v Speaker 2>North Korea, I can use this thing all night long

458
00:21:37.559 --> 00:21:39.960
<v Speaker 2>and all day long to like find new software bugs

459
00:21:40.039 --> 00:21:42.599
<v Speaker 2>or exploits or whatever, to like, you know, use.

460
00:21:43.319 --> 00:21:44.039
<v Speaker 1>To hack people.

461
00:21:44.920 --> 00:21:46.599
<v Speaker 2>Can you tell us about these open weight models and

462
00:21:46.839 --> 00:21:48.960
<v Speaker 2>the kind of risk and what people are doing about those.

463
00:21:49.759 --> 00:21:52.759
<v Speaker 3>Yeah, So this is another big topic of debate right

464
00:21:52.799 --> 00:21:55.480
<v Speaker 3>now because in addition to all of the bad things

465
00:21:55.559 --> 00:21:57.920
<v Speaker 3>that they can do what you just name Tommy, they

466
00:21:57.920 --> 00:22:00.440
<v Speaker 3>can also do a lot of really helpful things for

467
00:22:00.599 --> 00:22:02.759
<v Speaker 3>companies that don't want to pay tons and tons of

468
00:22:02.759 --> 00:22:05.160
<v Speaker 3>money to open AI and anthropic and all the rest. Right, Like,

469
00:22:05.200 --> 00:22:08.640
<v Speaker 3>this is a really cheap way to do some you know,

470
00:22:08.720 --> 00:22:11.240
<v Speaker 3>sort of like basic workhorce tasks. If you have like

471
00:22:11.240 --> 00:22:13.920
<v Speaker 3>a relatively simple task that you'd like to offload to

472
00:22:13.960 --> 00:22:16.160
<v Speaker 3>an AI, you want to do that as cheaply as possible,

473
00:22:16.240 --> 00:22:19.759
<v Speaker 3>so you might go and download a Chinese model. Where

474
00:22:19.799 --> 00:22:22.680
<v Speaker 3>I think it gets tricky is in two ways. One,

475
00:22:22.920 --> 00:22:26.759
<v Speaker 3>there are the sort of data security and privacy questions

476
00:22:26.759 --> 00:22:29.559
<v Speaker 3>that will be familiar to you from the TikTok debate. Right,

477
00:22:29.599 --> 00:22:31.480
<v Speaker 3>it's like, do we really want to have this sort

478
00:22:31.519 --> 00:22:34.799
<v Speaker 3>of Chinese built app on so many millions of smartphones?

479
00:22:34.839 --> 00:22:36.920
<v Speaker 3>And what data might it be sending and how might

480
00:22:36.960 --> 00:22:40.240
<v Speaker 3>it be used to manipulate us? But then you have

481
00:22:40.359 --> 00:22:43.279
<v Speaker 3>the sort of I'm going to call it like six

482
00:22:43.440 --> 00:22:47.640
<v Speaker 3>month ish concern, which is that while the Chinese models

483
00:22:47.680 --> 00:22:50.640
<v Speaker 3>are a little bit behind the American ones, they are

484
00:22:50.799 --> 00:22:54.039
<v Speaker 3>gradually catching up. And so the assumption is that within

485
00:22:54.079 --> 00:22:57.079
<v Speaker 3>about six months, maybe much faster than that, they will

486
00:22:57.079 --> 00:22:59.920
<v Speaker 3>have a model that is roughly equivalent to a claud

487
00:23:00.079 --> 00:23:03.759
<v Speaker 3>Fable five GPT five point six, the sort of American

488
00:23:03.839 --> 00:23:06.440
<v Speaker 3>state of the art. And if you've been following the

489
00:23:06.440 --> 00:23:09.680
<v Speaker 3>story about some of the havoc that those models are reeking, well,

490
00:23:10.039 --> 00:23:12.599
<v Speaker 3>just imagine that when it gets to the North Korean

491
00:23:12.640 --> 00:23:15.240
<v Speaker 3>hacker or somebody else who wants to do harm, there

492
00:23:15.279 --> 00:23:17.759
<v Speaker 3>aren't going to be the sort of same controls. And

493
00:23:17.880 --> 00:23:21.039
<v Speaker 3>so a big question in the United States right now

494
00:23:21.119 --> 00:23:23.559
<v Speaker 3>has been how do we want to relate to these

495
00:23:23.559 --> 00:23:24.839
<v Speaker 3>models and what should we do about them.

496
00:23:25.359 --> 00:23:27.799
<v Speaker 2>I was listening to an interview with Alex Stamos, who's

497
00:23:27.799 --> 00:23:32.880
<v Speaker 2>like a top you know, industry cybersecurity expert and you know, executive,

498
00:23:33.319 --> 00:23:35.680
<v Speaker 2>and he was saying that he assumes that, you know,

499
00:23:35.759 --> 00:23:39.759
<v Speaker 2>while maybe the models released by Chinese companies are like

500
00:23:39.759 --> 00:23:42.359
<v Speaker 2>six months behind the American ones, he thinks that the

501
00:23:42.400 --> 00:23:46.039
<v Speaker 2>government probably has things that are basically equivalent to what

502
00:23:46.079 --> 00:23:48.880
<v Speaker 2>frontier models have that they're just holding back those capabilities.

503
00:23:49.000 --> 00:23:50.559
<v Speaker 2>Have you heard other people say it's like, is that

504
00:23:50.599 --> 00:23:52.319
<v Speaker 2>a consensus opinion in that world.

505
00:23:52.920 --> 00:23:54.640
<v Speaker 3>I have a lot of respect for Alex and he

506
00:23:54.720 --> 00:23:56.920
<v Speaker 3>works in cybersecurity, and so he made us know more

507
00:23:56.920 --> 00:23:59.839
<v Speaker 3>about this than I do. I frankly have not heard

508
00:24:00.119 --> 00:24:03.519
<v Speaker 3>that right. A big reason that the Chinese have not

509
00:24:04.559 --> 00:24:09.319
<v Speaker 3>demonstrated models like this is because they require massive numbers

510
00:24:09.359 --> 00:24:12.279
<v Speaker 3>of state of the art ships from Nvidio, which they

511
00:24:12.319 --> 00:24:16.039
<v Speaker 3>have mostly been banned from buying. Now they have been

512
00:24:16.119 --> 00:24:18.720
<v Speaker 3>smuggling as many of them as they can, and they

513
00:24:18.759 --> 00:24:22.880
<v Speaker 3>do have some domestic technology, but in general, the United

514
00:24:22.880 --> 00:24:26.519
<v Speaker 3>States just has a massive lead thanks to all of

515
00:24:26.559 --> 00:24:28.920
<v Speaker 3>the data centers that are in so many American communities

516
00:24:28.960 --> 00:24:31.319
<v Speaker 3>that are making Americans. So it's why Americans can't get

517
00:24:31.440 --> 00:24:34.160
<v Speaker 3>enough data centers in their communities, Tommy, is because they're

518
00:24:34.160 --> 00:24:36.880
<v Speaker 3>so excited about how it's helping us against the Chinese.

519
00:24:36.920 --> 00:24:39.559
<v Speaker 2>We're all so excited about these data centers. I'm probably

520
00:24:39.839 --> 00:24:41.799
<v Speaker 2>garbling his quote. He might have been talking about sort

521
00:24:41.799 --> 00:24:45.039
<v Speaker 2>of specific capabilities when it comes to cyber attacks and hacking.

522
00:24:45.799 --> 00:24:48.559
<v Speaker 2>But yeah, God only knows. So one last sort of

523
00:24:48.559 --> 00:24:50.440
<v Speaker 2>industry question. I want to get to the regulation piece.

524
00:24:51.119 --> 00:24:53.559
<v Speaker 2>Regardless of whether or not AI is going to kill

525
00:24:53.599 --> 00:24:56.200
<v Speaker 2>us all or lead us to a utopian heaven where

526
00:24:56.240 --> 00:24:59.079
<v Speaker 2>none of us have to work. I do also just

527
00:24:59.160 --> 00:25:01.279
<v Speaker 2>kind of wonder whether where the weirdo is running these

528
00:25:01.279 --> 00:25:05.440
<v Speaker 2>companies understand what normal human beings actually want from technology.

529
00:25:05.839 --> 00:25:09.160
<v Speaker 2>For example, let's watch these comments by Sam Altman, the

530
00:25:09.240 --> 00:25:11.559
<v Speaker 2>CEO of open Ai, that kind of get at the issue.

531
00:25:11.680 --> 00:25:13.799
<v Speaker 10>I think we are close to a world where you

532
00:25:13.799 --> 00:25:17.440
<v Speaker 10>can have like a descendant of chatgybut watch your computer

533
00:25:17.519 --> 00:25:20.799
<v Speaker 10>screen all the time, watch every meeting you're in, like

534
00:25:20.839 --> 00:25:24.079
<v Speaker 10>record every call, everything like that, have perfect context of

535
00:25:24.119 --> 00:25:27.039
<v Speaker 10>your whole life. Everything you see. You choose what information

536
00:25:27.079 --> 00:25:28.599
<v Speaker 10>you wanted to have, but it can like go. You

537
00:25:28.640 --> 00:25:31.160
<v Speaker 10>can connect it to your texts or email or docs

538
00:25:31.279 --> 00:25:33.839
<v Speaker 10>or Slack or whatever, and then you have this thing

539
00:25:34.319 --> 00:25:36.839
<v Speaker 10>that is not making decisions for you. But if you're

540
00:25:36.920 --> 00:25:39.000
<v Speaker 10>like the CEO of a startup, there's always like more

541
00:25:39.039 --> 00:25:41.119
<v Speaker 10>stuff to do than you can do, and context you

542
00:25:41.200 --> 00:25:43.880
<v Speaker 10>can't all keep track of. You can't like read every

543
00:25:43.920 --> 00:25:46.319
<v Speaker 10>piece of customer feedback every day, and you can just

544
00:25:46.359 --> 00:25:48.680
<v Speaker 10>have this thing that's like working alongside you, and as

545
00:25:48.720 --> 00:25:51.160
<v Speaker 10>you're like typing out a sales pitch to a customer

546
00:25:51.279 --> 00:25:54.119
<v Speaker 10>or like writing a strategy doc, it'll just say like, hey,

547
00:25:55.000 --> 00:25:56.559
<v Speaker 10>maybe here's another idea, or I think you're making a

548
00:25:56.599 --> 00:25:58.680
<v Speaker 10>mistake here you should consider this, or I can do

549
00:25:58.759 --> 00:26:02.119
<v Speaker 10>this thing for you to help and like this. I

550
00:26:02.160 --> 00:26:04.960
<v Speaker 10>think we're only like one model generation away from this

551
00:26:05.039 --> 00:26:08.039
<v Speaker 10>actually being incredibly useful. And I think that will change,

552
00:26:08.319 --> 00:26:10.559
<v Speaker 10>hopefully at least for me, change the lot work. What's

553
00:26:10.599 --> 00:26:14.359
<v Speaker 10>your best guest on timing, Like sometime in the next.

554
00:26:14.240 --> 00:26:18.000
<v Speaker 2>Six months, casey does he really want AI recording everything

555
00:26:18.039 --> 00:26:20.839
<v Speaker 2>he types, reads, season says, and then being like his

556
00:26:20.920 --> 00:26:23.680
<v Speaker 2>co CEO like is this this is this really what

557
00:26:23.720 --> 00:26:24.400
<v Speaker 2>this guy wants?

558
00:26:25.079 --> 00:26:28.359
<v Speaker 3>They ship this this week? So like you can go

559
00:26:28.559 --> 00:26:30.720
<v Speaker 3>into chat YOUBT if you have like the app on

560
00:26:30.759 --> 00:26:32.799
<v Speaker 3>your desktop now, it will monitor the way that you

561
00:26:32.880 --> 00:26:35.400
<v Speaker 3>use your computer and it will sort of you know,

562
00:26:35.440 --> 00:26:38.359
<v Speaker 3>build little memories and then it can take some actions

563
00:26:38.359 --> 00:26:40.640
<v Speaker 3>on your behalf. So I guess no one over there

564
00:26:40.680 --> 00:26:45.039
<v Speaker 3>is ever looking at porn, but uh, yeah, I incorporate that.

565
00:26:45.920 --> 00:26:47.480
<v Speaker 2>Yeah, but it's like he was to live in this

566
00:26:47.519 --> 00:26:50.759
<v Speaker 2>like panopticon surveillance state of his own making.

567
00:26:51.720 --> 00:26:54.880
<v Speaker 3>So there are trade offs here. There are a lot

568
00:26:54.920 --> 00:26:57.440
<v Speaker 3>of startups right now that want you to plug in

569
00:26:57.480 --> 00:27:02.039
<v Speaker 3>your various tools, your slack, your granola, your g suite,

570
00:27:02.079 --> 00:27:04.599
<v Speaker 3>and if you let them, they will read that and

571
00:27:04.640 --> 00:27:07.039
<v Speaker 3>they will just suggest things for you to do. And

572
00:27:07.119 --> 00:27:10.480
<v Speaker 3>I gotta hold myself accountable here, Tommy. I started testing

573
00:27:10.519 --> 00:27:12.759
<v Speaker 3>this thing called Town over the past couple of weeks,

574
00:27:12.920 --> 00:27:17.240
<v Speaker 3>and it has access to my calendar and emails and

575
00:27:17.319 --> 00:27:20.920
<v Speaker 3>so it just sends me briefings before meetings and they

576
00:27:20.920 --> 00:27:23.200
<v Speaker 3>can be really good. You know, they'll sort of do

577
00:27:23.279 --> 00:27:25.079
<v Speaker 3>a little bit of research about the person who I'm

578
00:27:25.119 --> 00:27:27.920
<v Speaker 3>talking to and kind of you know, helps me get

579
00:27:27.960 --> 00:27:30.480
<v Speaker 3>prepared for things. So you know, it's not like an

580
00:27:30.559 --> 00:27:33.359
<v Speaker 3>absolutely killer use case that I'm telling everybody like go

581
00:27:33.440 --> 00:27:36.119
<v Speaker 3>out and do immediately, but I'm getting some level of

582
00:27:36.160 --> 00:27:39.519
<v Speaker 3>benefit for it in exchange for you know, trusting some

583
00:27:39.599 --> 00:27:41.160
<v Speaker 3>of my data with a bunch of strangers.

584
00:27:41.519 --> 00:27:43.480
<v Speaker 2>I just I saw a tweet from Opening Eye today

585
00:27:43.519 --> 00:27:46.200
<v Speaker 2>that said chet GBT can now remember your activity across

586
00:27:46.240 --> 00:27:49.079
<v Speaker 2>the apps and websites on your computer with computer history

587
00:27:49.079 --> 00:27:51.680
<v Speaker 2>and the desktop app, future interactions feel more personalized and

588
00:27:51.720 --> 00:27:54.480
<v Speaker 2>require less explanation. It does feel like like the Internet

589
00:27:54.519 --> 00:27:56.519
<v Speaker 2>fever dream when we're nice COOOLK.

590
00:27:57.759 --> 00:27:59.440
<v Speaker 1>I guess maybe this is good if like your life

591
00:27:59.480 --> 00:27:59.880
<v Speaker 1>is working.

592
00:27:59.880 --> 00:28:01.440
<v Speaker 2>All all you do is work, and maybe you have

593
00:28:01.480 --> 00:28:04.240
<v Speaker 2>a dedicated work computer that you never bring home or

594
00:28:04.279 --> 00:28:06.079
<v Speaker 2>like talk to your friends or family on.

595
00:28:06.759 --> 00:28:07.160
<v Speaker 8>Yeah.

596
00:28:07.440 --> 00:28:12.519
<v Speaker 3>I mean, like the instinct here is to just increase

597
00:28:12.799 --> 00:28:16.880
<v Speaker 3>the number of things that this technology can do, to

598
00:28:16.920 --> 00:28:19.400
<v Speaker 3>make it just like so obvious that you need this

599
00:28:19.440 --> 00:28:21.680
<v Speaker 3>in your life that you'll just like pay any price

600
00:28:21.759 --> 00:28:24.759
<v Speaker 3>to get access to it. And I think right now

601
00:28:24.799 --> 00:28:27.240
<v Speaker 3>the capabilities have not been good enough for like most

602
00:28:27.240 --> 00:28:31.440
<v Speaker 3>people to take that seriously. But a year from now,

603
00:28:31.640 --> 00:28:33.160
<v Speaker 3>like I do think this stuff is going to be

604
00:28:33.200 --> 00:28:34.599
<v Speaker 3>able to do a lot of cool stuff on your

605
00:28:34.599 --> 00:28:35.480
<v Speaker 3>computer if you let it.

606
00:28:35.839 --> 00:28:37.640
<v Speaker 2>I just like it's so hard for me. I'm so

607
00:28:37.799 --> 00:28:40.480
<v Speaker 2>angry about the fact that the same people who like

608
00:28:40.559 --> 00:28:44.559
<v Speaker 2>helped tear apart our society via social media are now

609
00:28:44.599 --> 00:28:48.400
<v Speaker 2>in charge of creating super intelligence that can learn everything

610
00:28:48.720 --> 00:28:49.839
<v Speaker 2>there is to know about.

611
00:28:49.599 --> 00:28:53.519
<v Speaker 3>You, well, particularly when some of these technologies have had

612
00:28:54.000 --> 00:28:56.440
<v Speaker 3>very similar effects, right, Like A big story over the

613
00:28:56.480 --> 00:28:58.960
<v Speaker 3>past year or so has been the way that kids

614
00:28:59.000 --> 00:29:02.279
<v Speaker 3>get addicted to chatbots, and chatbots give them really bad

615
00:29:02.279 --> 00:29:05.839
<v Speaker 3>advice or like encourage them down the path to self harm,

616
00:29:05.880 --> 00:29:08.759
<v Speaker 3>just like sort of like a direct sequel to the

617
00:29:08.799 --> 00:29:12.359
<v Speaker 3>social media moment. So yeah, like this is one reason

618
00:29:12.440 --> 00:29:15.359
<v Speaker 3>why I've just been getting more nervous lately, is because

619
00:29:15.799 --> 00:29:18.960
<v Speaker 3>those forces do not seem to have any real counterbalance

620
00:29:19.000 --> 00:29:21.319
<v Speaker 3>in the government, and in fact, the government, at least

621
00:29:21.319 --> 00:29:23.720
<v Speaker 3>at the federal level, has mostly been sharing them along.

622
00:29:24.400 --> 00:29:27.000
<v Speaker 2>You ever hear your your co host Kevin Ruster's story

623
00:29:27.039 --> 00:29:28.799
<v Speaker 2>about the chatbot Sydney over.

624
00:29:29.400 --> 00:29:29.799
<v Speaker 1>You know what.

625
00:29:29.839 --> 00:29:31.640
<v Speaker 3>I keep trying to get them to open up about

626
00:29:31.640 --> 00:29:33.599
<v Speaker 3>that one, but it's it's very personal for me.

627
00:29:34.839 --> 00:29:39.039
<v Speaker 1>It's a good story. It's a very good story.

628
00:29:44.599 --> 00:29:46.240
<v Speaker 8>Pose America is brought to you by Our Place.

629
00:29:46.319 --> 00:29:49.319
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642
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643
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<v Speaker 7>want to turn on the full oven. I'm a huge

644
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645
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646
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647
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648
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649
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650
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651
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654
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655
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656
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657
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658
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659
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660
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671
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<v Speaker 8>Oh God, asleep. You'll die without it, You'll literally die.

672
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<v Speaker 9>So now that we've got that out of the way,

673
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<v Speaker 9>what are you going to sleep on? What do you

674
00:31:36.319 --> 00:31:39.960
<v Speaker 9>see the floor? Hey, not a dumb mattress. Hey, an

675
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<v Speaker 9>old mattress, a yoga matt How about a helix mattress. Yeah,

676
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677
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678
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679
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680
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<v Speaker 7>I'm tired today, but it's not because of my mattresses,

681
00:31:55.319 --> 00:31:58.240
<v Speaker 7>because I was enjoying watching Steve Kornaki passive aggressively feud

682
00:31:58.240 --> 00:32:00.599
<v Speaker 7>with the decision desk laden to the night. It was

683
00:32:00.680 --> 00:32:02.799
<v Speaker 7>so funny. I don't know what was going on over there.

684
00:32:02.799 --> 00:32:04.680
<v Speaker 7>First of all, just him in a room, him and

685
00:32:04.680 --> 00:32:07.200
<v Speaker 7>one guy, two of them. NBC News is now just

686
00:32:07.359 --> 00:32:11.359
<v Speaker 7>Kornaki and some guy in a room, passive aggressively arguing

687
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<v Speaker 7>with the decision.

688
00:32:11.839 --> 00:32:14.160
<v Speaker 8>Does is they getting enough air? I don't know. I

689
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<v Speaker 8>don't know, but I tell you by the.

690
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<v Speaker 7>End, Yeah, everyone's a couple pieces of stress every Yeah.

691
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692
00:32:21.680 --> 00:32:25.799
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693
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710
00:33:08.920 --> 00:33:10.480
<v Speaker 2>All right, so this brings us the question of what

711
00:33:10.519 --> 00:33:14.200
<v Speaker 2>the government is doing about all of these terrible concerns

712
00:33:14.200 --> 00:33:16.519
<v Speaker 2>we've laid out. Let's start with the Trump administration in

713
00:33:16.559 --> 00:33:18.480
<v Speaker 2>the federal government. So one of the first things that

714
00:33:18.519 --> 00:33:21.359
<v Speaker 2>Trump administration did was rip up Joe Biden's Executive Order

715
00:33:21.359 --> 00:33:23.920
<v Speaker 2>about AI safety and then install this right wing troll

716
00:33:24.039 --> 00:33:27.240
<v Speaker 2>named David Sacks as their AIS are. If we're being honest,

717
00:33:27.279 --> 00:33:29.839
<v Speaker 2>that the Biden EO wasn't all that syringing, and I

718
00:33:29.880 --> 00:33:33.240
<v Speaker 2>think he's primarily focused on blocking the export of advanced

719
00:33:33.240 --> 00:33:36.160
<v Speaker 2>AI chips to China. But Trump takes office and they

720
00:33:36.200 --> 00:33:39.960
<v Speaker 2>shift to like an all gas, no breaks approach, while

721
00:33:40.000 --> 00:33:43.359
<v Speaker 2>also whining about liberal bias and in chatbots, and then

722
00:33:43.400 --> 00:33:46.960
<v Speaker 2>like some export controls remain in place. Then Anthropic releases

723
00:33:47.000 --> 00:33:50.279
<v Speaker 2>the Mythos model and the White House totally freaks out

724
00:33:50.319 --> 00:33:52.359
<v Speaker 2>and the vibe has changed a lot. Can you talk

725
00:33:52.400 --> 00:33:54.440
<v Speaker 2>about that kind of Mythos moment and what what the

726
00:33:54.440 --> 00:33:55.079
<v Speaker 2>hell happened?

727
00:33:55.559 --> 00:34:01.359
<v Speaker 3>Yeah, So before Mythos, the Trump administration good just seemed

728
00:34:01.480 --> 00:34:06.319
<v Speaker 3>very confident that AI capabilities were going to be frozen

729
00:34:06.599 --> 00:34:09.639
<v Speaker 3>in Amber. At the moment that he took office for

730
00:34:09.719 --> 00:34:12.320
<v Speaker 3>a second time, they just were not worried about it.

731
00:34:12.360 --> 00:34:15.840
<v Speaker 3>They thought, if you're worried about AI safety, like that's

732
00:34:15.960 --> 00:34:18.800
<v Speaker 3>woke and it has no place in our administration now.

733
00:34:18.840 --> 00:34:20.920
<v Speaker 3>It also so happened that many of the people that

734
00:34:20.960 --> 00:34:23.800
<v Speaker 3>Trump was bringing in like David Sachs, but also all

735
00:34:23.840 --> 00:34:26.760
<v Speaker 3>of the other oligarchs that donated to the inauguration and

736
00:34:26.760 --> 00:34:30.679
<v Speaker 3>funded the ballroom. They are desperate to get this technology

737
00:34:30.679 --> 00:34:32.679
<v Speaker 3>into as many hands as possible so they can make

738
00:34:32.719 --> 00:34:35.719
<v Speaker 3>money off it, and so the Trump administration has gone

739
00:34:35.760 --> 00:34:38.199
<v Speaker 3>to great lengths to make sure that they are not

740
00:34:38.320 --> 00:34:41.000
<v Speaker 3>restricted from doing. You a bunch of things that I

741
00:34:41.000 --> 00:34:43.719
<v Speaker 3>think a democratic administration probably would have tried to rain

742
00:34:43.760 --> 00:34:46.519
<v Speaker 3>them in on. But then along comes Mythos and they

743
00:34:46.559 --> 00:34:48.920
<v Speaker 3>show it to whatever adults are still left in the

744
00:34:48.920 --> 00:34:52.840
<v Speaker 3>Trump administration, and they show how it can hack into

745
00:34:53.119 --> 00:34:58.480
<v Speaker 3>government systems pretty easily, and boom, it's like this instant conversion,

746
00:34:58.519 --> 00:35:01.880
<v Speaker 3>and all of a sudden, and the Trump administration say, oh,

747
00:35:02.039 --> 00:35:05.480
<v Speaker 3>I guess ai, safety is not just like a woke

748
00:35:05.639 --> 00:35:08.000
<v Speaker 3>project of the left. It's something that we actually need

749
00:35:08.039 --> 00:35:10.599
<v Speaker 3>to take seriously. And for what it's worth. I'm glad

750
00:35:10.639 --> 00:35:12.800
<v Speaker 3>that they had their conversion moment, Like we're in a

751
00:35:12.880 --> 00:35:14.679
<v Speaker 3>much better position now than we were before that.

752
00:35:15.199 --> 00:35:16.920
<v Speaker 2>Yeah, I'm glad that a conversion moment too. But the

753
00:35:16.960 --> 00:35:19.320
<v Speaker 2>way it happened was was quite odd, right. I Mean,

754
00:35:19.360 --> 00:35:21.719
<v Speaker 2>it was all like five o'clock on a Friday, they

755
00:35:21.719 --> 00:35:25.519
<v Speaker 2>did what they just cut off basically foreign access to Anthropic.

756
00:35:26.079 --> 00:35:30.599
<v Speaker 3>Yeah, so basically after the Mythos moment where where Anthropic

757
00:35:30.679 --> 00:35:33.480
<v Speaker 3>said were actually just like not going to release this,

758
00:35:33.679 --> 00:35:38.840
<v Speaker 3>Anthropic releases a somewhat less capable model called Fable, which

759
00:35:38.880 --> 00:35:42.480
<v Speaker 3>has you know, It's my understanding is it's basically, you know,

760
00:35:42.840 --> 00:35:46.960
<v Speaker 3>Mythos without all this scary cyber attack stuff. But even

761
00:35:47.079 --> 00:35:51.039
<v Speaker 3>within that, the Trump administration was shown some things that

762
00:35:51.159 --> 00:35:53.159
<v Speaker 3>led them to believe, we don't even know if we

763
00:35:53.199 --> 00:35:56.599
<v Speaker 3>want people to have this, and so they essentially forced

764
00:35:56.639 --> 00:35:59.440
<v Speaker 3>Anthropic to pull it off the market and make even

765
00:35:59.480 --> 00:36:02.320
<v Speaker 3>further change just before they would re release it, and

766
00:36:02.360 --> 00:36:06.280
<v Speaker 3>they subjected GPT five point six to a similar set

767
00:36:06.320 --> 00:36:09.199
<v Speaker 3>of control. So the same people that had been saying,

768
00:36:09.199 --> 00:36:10.920
<v Speaker 3>you know, we can't put the brakes on these models,

769
00:36:10.920 --> 00:36:13.039
<v Speaker 3>otherwise we're going to lose to China all of a

770
00:36:13.039 --> 00:36:15.719
<v Speaker 3>sudden had just invented out of whole cloth, this de

771
00:36:15.840 --> 00:36:19.760
<v Speaker 3>facto licensing regime, which remains effectively a secret, like to

772
00:36:19.800 --> 00:36:21.320
<v Speaker 3>this day, we don't actually know how you get a

773
00:36:21.360 --> 00:36:23.039
<v Speaker 3>frontier model released in the United States.

774
00:36:23.199 --> 00:36:24.679
<v Speaker 2>Yeah, can you tell us a little more about that.

775
00:36:24.840 --> 00:36:27.719
<v Speaker 2>It's a voluntary secret framework.

776
00:36:28.559 --> 00:36:31.800
<v Speaker 3>Yeah, it's voluntary in the same way that paying your taxes,

777
00:36:32.480 --> 00:36:34.880
<v Speaker 3>you know, is yeah. I mean, like, seriously, if any

778
00:36:34.880 --> 00:36:37.599
<v Speaker 3>of these companies try to release one of these frontier

779
00:36:37.599 --> 00:36:39.840
<v Speaker 3>models without checking with the Trump administration, and there would

780
00:36:39.880 --> 00:36:42.800
<v Speaker 3>be hell. Around the time of Fable, the Trump administration said,

781
00:36:42.800 --> 00:36:44.519
<v Speaker 3>we're going to come up with an executive order that

782
00:36:44.599 --> 00:36:47.039
<v Speaker 3>is going to dictate how we let these frontier models

783
00:36:47.079 --> 00:36:50.880
<v Speaker 3>get released. They reportedly have now come up with this model,

784
00:36:50.920 --> 00:36:53.960
<v Speaker 3>but they've only shared it with the labs themselves. So

785
00:36:54.079 --> 00:36:57.280
<v Speaker 3>I imagine there's some sort of testing requirements that are

786
00:36:57.280 --> 00:36:58.519
<v Speaker 3>in here, but we just don't know.

787
00:36:58.880 --> 00:37:02.159
<v Speaker 2>And it was interesting when they initially went after Anthropic

788
00:37:02.280 --> 00:37:05.719
<v Speaker 2>over this mythost model or the Fable model, we wondered

789
00:37:05.719 --> 00:37:08.480
<v Speaker 2>if it was a continuation of this fight the administration

790
00:37:08.559 --> 00:37:12.360
<v Speaker 2>had it been in with Anthropic, because Anthropic basically said, no,

791
00:37:12.480 --> 00:37:14.360
<v Speaker 2>we don't want to help you do mass surveillance on

792
00:37:14.400 --> 00:37:18.119
<v Speaker 2>American citizens or make autonomous killer drones. Those are our

793
00:37:18.239 --> 00:37:21.679
<v Speaker 2>very very tiny lines that we won't cross. And Pete

794
00:37:21.679 --> 00:37:24.320
<v Speaker 2>Hegseth lost his fucking mind. But then they went after

795
00:37:24.360 --> 00:37:26.320
<v Speaker 2>open Ai too, which did seemed to signal this was

796
00:37:26.360 --> 00:37:28.280
<v Speaker 2>a broader concern than just one company, right.

797
00:37:28.639 --> 00:37:31.119
<v Speaker 3>Yeah, And that's what gives me the confidence that there

798
00:37:31.679 --> 00:37:35.920
<v Speaker 3>are people there who actually are taking AI risks seriously

799
00:37:36.039 --> 00:37:39.719
<v Speaker 3>now because it was never only about one company. It

800
00:37:39.840 --> 00:37:42.000
<v Speaker 3>was about the fact that you know, be able to

801
00:37:42.039 --> 00:37:44.280
<v Speaker 3>stop here. And you know, because not all of your

802
00:37:44.320 --> 00:37:46.840
<v Speaker 3>listeners may be familiar with this, but a really weird

803
00:37:46.880 --> 00:37:50.679
<v Speaker 3>thing about AI is that basically everyone has the recipe

804
00:37:50.719 --> 00:37:53.400
<v Speaker 3>for building a more powerful model, right, Like we know,

805
00:37:53.559 --> 00:37:56.199
<v Speaker 3>if you just sort of add enough data and enough

806
00:37:56.280 --> 00:37:58.880
<v Speaker 3>computing power into the mix and just sort of let

807
00:37:58.920 --> 00:38:02.280
<v Speaker 3>it cook for a while. As you sort of increase

808
00:38:02.320 --> 00:38:04.559
<v Speaker 3>those things, you're going to wind up with a more

809
00:38:04.559 --> 00:38:08.119
<v Speaker 3>powerful model. So that's just very different from other technologies.

810
00:38:08.159 --> 00:38:09.880
<v Speaker 3>You know, it'd be as if everyone knew how to

811
00:38:09.880 --> 00:38:12.760
<v Speaker 3>build the iPhone at the same time or the personal computer.

812
00:38:13.840 --> 00:38:17.280
<v Speaker 3>But because everyone has the recipe, that is why the

813
00:38:17.280 --> 00:38:20.079
<v Speaker 3>Trump administration is freaked out, because it is only a

814
00:38:20.079 --> 00:38:23.159
<v Speaker 3>matter of time before adversaries will have access to similar

815
00:38:23.400 --> 00:38:26.239
<v Speaker 3>technologies and capabilities that we do today well.

816
00:38:26.519 --> 00:38:29.159
<v Speaker 2>And the sort of thing you always hear out of

817
00:38:29.199 --> 00:38:32.199
<v Speaker 2>the federal government or from people that are like, you know,

818
00:38:32.559 --> 00:38:35.760
<v Speaker 2>utopian pro like you know, all gas no breaks, people

819
00:38:35.880 --> 00:38:39.519
<v Speaker 2>is that we have to win this imaginary race. It's

820
00:38:39.559 --> 00:38:41.519
<v Speaker 2>not really iraginated. We have to win this race against

821
00:38:41.599 --> 00:38:44.039
<v Speaker 2>China when it comes to AI. Can you explain that

822
00:38:44.239 --> 00:38:46.079
<v Speaker 2>argument and whether you find it convincing.

823
00:38:47.320 --> 00:38:50.960
<v Speaker 3>Yeah, so, you know, and here we can go back

824
00:38:50.960 --> 00:38:54.559
<v Speaker 3>to the House of the Dragon, because in West Rows, Tommy,

825
00:38:54.559 --> 00:38:57.000
<v Speaker 3>as you know, at the time of House of the Dragon,

826
00:38:57.039 --> 00:38:59.599
<v Speaker 3>there was one great house that had this super weapon

827
00:38:59.639 --> 00:39:01.719
<v Speaker 3>that was the Dragon, and it let them control the

828
00:39:01.880 --> 00:39:04.039
<v Speaker 3>entire world, and that mostly went badly for you know,

829
00:39:04.119 --> 00:39:07.360
<v Speaker 3>everyone who didn't live in the Red Keep. The fear

830
00:39:08.000 --> 00:39:11.719
<v Speaker 3>is that if super intelligence becomes one of these dragons,

831
00:39:11.760 --> 00:39:15.880
<v Speaker 3>and only one country has access to it, then I mean,

832
00:39:16.079 --> 00:39:19.119
<v Speaker 3>they could just do some old fashioned conquering, right, and

833
00:39:19.199 --> 00:39:23.440
<v Speaker 3>it could be like really really bad. There are some

834
00:39:23.559 --> 00:39:26.880
<v Speaker 3>better worlds available, like a world where there is a

835
00:39:26.920 --> 00:39:30.480
<v Speaker 3>balance of power, where you know, there's maybe like an

836
00:39:30.480 --> 00:39:33.880
<v Speaker 3>alliance of Western dragons and an alliance of Eastern dragons

837
00:39:33.880 --> 00:39:36.159
<v Speaker 3>and you know they sort of mostly keep each other

838
00:39:36.239 --> 00:39:40.280
<v Speaker 3>at bay. But that is the scenario that the government

839
00:39:40.679 --> 00:39:42.960
<v Speaker 3>is planning for. And also by the way, they feel

840
00:39:42.960 --> 00:39:45.760
<v Speaker 3>like if we are able to get there first, then

841
00:39:45.880 --> 00:39:49.039
<v Speaker 3>we will hopefully be able to control the terms on

842
00:39:49.079 --> 00:39:52.480
<v Speaker 3>which other people are allowed to use it, including our adversaries.

843
00:39:52.639 --> 00:39:56.239
<v Speaker 1>So open a eyes vague? Are deep seek? Is sheep stealers?

844
00:39:56.760 --> 00:39:58.800
<v Speaker 1>I just finished this series like two nights ago to it.

845
00:39:58.880 --> 00:40:02.400
<v Speaker 2>Yeah, okay, Just a piece of context here, folks should

846
00:40:02.400 --> 00:40:05.719
<v Speaker 2>know is that there was an organization called SISA that

847
00:40:05.719 --> 00:40:09.199
<v Speaker 2>did some really important cybersecurity work for the federal government.

848
00:40:09.360 --> 00:40:13.519
<v Speaker 2>Trump basically destroyed the organization and half the staff got

849
00:40:13.559 --> 00:40:16.119
<v Speaker 2>pushed out or fired because he was mad that the

850
00:40:16.199 --> 00:40:20.039
<v Speaker 2>twenty sis said the twenty twenty election was secure. So

851
00:40:20.079 --> 00:40:22.039
<v Speaker 2>that is sort of the backdrop as you think about

852
00:40:22.119 --> 00:40:26.320
<v Speaker 2>the potential cybersecurity risk. Are they thinking about addressing that

853
00:40:26.360 --> 00:40:26.639
<v Speaker 2>at all?

854
00:40:26.679 --> 00:40:31.400
<v Speaker 3>Casey, I am very nervous. You know. I was learning

855
00:40:31.400 --> 00:40:33.679
<v Speaker 3>from a friend recently who works at one of the

856
00:40:33.719 --> 00:40:37.880
<v Speaker 3>big labs that the United Kingdom has actually funded their

857
00:40:37.960 --> 00:40:42.719
<v Speaker 3>AI security Institute at something like eight times the level

858
00:40:42.960 --> 00:40:47.000
<v Speaker 3>of the US equivalent. So like, the British are investing

859
00:40:47.440 --> 00:40:50.880
<v Speaker 3>way more money into trying to understand AI and trying

860
00:40:50.880 --> 00:40:54.199
<v Speaker 3>to make it safe than we are here in the US.

861
00:40:54.440 --> 00:40:57.760
<v Speaker 3>So this is why I have become quite nervous and

862
00:40:57.800 --> 00:41:01.400
<v Speaker 3>had been leaning pessimistic about AI over the past few weeks.

863
00:41:01.760 --> 00:41:05.639
<v Speaker 3>Is because I look at what the US is investing

864
00:41:05.800 --> 00:41:09.519
<v Speaker 3>in order to make this technology safer, and it's just

865
00:41:09.559 --> 00:41:11.239
<v Speaker 3>not even scratching the surface.

866
00:41:11.840 --> 00:41:14.920
<v Speaker 2>Not great anything happening at the state level. Are there

867
00:41:14.920 --> 00:41:17.559
<v Speaker 2>any meaningful efforts, you know, in California or other places

868
00:41:17.559 --> 00:41:20.519
<v Speaker 2>to regulate AI? And how what role is opposition the

869
00:41:20.639 --> 00:41:23.559
<v Speaker 2>data centers playing maybe in slowing things down?

870
00:41:23.639 --> 00:41:26.480
<v Speaker 3>Do you think I think it is playing a really

871
00:41:26.519 --> 00:41:30.039
<v Speaker 3>great role in slowing things down. And here is where

872
00:41:30.119 --> 00:41:34.039
<v Speaker 3>I want to inject some optimism into the conversation, because

873
00:41:34.440 --> 00:41:39.440
<v Speaker 3>the American people get that by default AI might not

874
00:41:39.599 --> 00:41:42.239
<v Speaker 3>be good for them, right They've heard the message that

875
00:41:42.320 --> 00:41:44.360
<v Speaker 3>this might take my job and it might kill me,

876
00:41:44.679 --> 00:41:46.639
<v Speaker 3>and they don't like it. And so they're turning to

877
00:41:46.679 --> 00:41:49.239
<v Speaker 3>the most powerful evert that every American has, which is

878
00:41:49.280 --> 00:41:51.719
<v Speaker 3>it's very easy to get something not built in your neighborhood.

879
00:41:52.079 --> 00:41:54.880
<v Speaker 3>And as they have fanned out across this great land,

880
00:41:55.119 --> 00:41:58.000
<v Speaker 3>they have used that to great success. And now all

881
00:41:58.000 --> 00:42:01.239
<v Speaker 3>the labs have to invest a ton in trying to

882
00:42:01.559 --> 00:42:04.519
<v Speaker 3>change their minds. And while right now the labs are

883
00:42:04.599 --> 00:42:07.679
<v Speaker 3>mostly trying to do the easy stuff, you know, like

884
00:42:07.719 --> 00:42:11.920
<v Speaker 3>buying people off for relatively cheap, my hope is that

885
00:42:12.000 --> 00:42:15.280
<v Speaker 3>this movement that is coalescing, that is bipartisan in a

886
00:42:15.280 --> 00:42:18.280
<v Speaker 3>way that almost nothing is bipartisan in America right now.

887
00:42:18.639 --> 00:42:21.280
<v Speaker 3>Eventually these labs are going to say, maybe we're going

888
00:42:21.360 --> 00:42:24.280
<v Speaker 3>to have to make this actually just really beneficial for people,

889
00:42:24.440 --> 00:42:27.960
<v Speaker 3>right Like, if we really want to enact this project,

890
00:42:28.159 --> 00:42:29.440
<v Speaker 3>it is just going to have to be clear to

891
00:42:29.480 --> 00:42:31.440
<v Speaker 3>people that this is going to benefit them personally. So

892
00:42:31.760 --> 00:42:35.239
<v Speaker 3>this is just this to me, this is what the beautiful,

893
00:42:35.239 --> 00:42:38.960
<v Speaker 3>beautiful democracy in action is. Americans see what is going on.

894
00:42:39.280 --> 00:42:42.280
<v Speaker 3>They're organizing and they are winning battles all across the country.

895
00:42:42.440 --> 00:42:45.119
<v Speaker 2>Yeah, it was clearly a big component in the messaging

896
00:42:45.199 --> 00:42:48.360
<v Speaker 2>in Michigan in the recent primary and also in Wisconsin.

897
00:42:56.519 --> 00:43:00.440
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921
00:43:51.119 --> 00:43:52.119
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<v Speaker 1>Two more AI industry questions.

947
00:44:57.519 --> 00:44:58.679
<v Speaker 2>I don't want to get your sense of help, like

948
00:44:58.719 --> 00:45:00.639
<v Speaker 2>gus some advice for folks on how to this stuff.

949
00:45:00.880 --> 00:45:04.679
<v Speaker 2>There are huge long term concerns about the impact of

950
00:45:04.800 --> 00:45:09.039
<v Speaker 2>AI on jobs and employment. What are you seeing so

951
00:45:09.239 --> 00:45:11.679
<v Speaker 2>far when it comes to the impact of AI on

952
00:45:12.199 --> 00:45:13.079
<v Speaker 2>the employment picture?

953
00:45:13.440 --> 00:45:17.039
<v Speaker 3>Yeah, So Stanford has this Canaries in the coal Mine

954
00:45:17.079 --> 00:45:21.159
<v Speaker 3>project they call it, which is this project that they're doing.

955
00:45:21.280 --> 00:45:23.960
<v Speaker 3>They have access to data from one of the big

956
00:45:24.920 --> 00:45:28.400
<v Speaker 3>payment processors, like so, like you probably get your paycheck

957
00:45:28.559 --> 00:45:30.760
<v Speaker 3>if you're a W two from one of these companies,

958
00:45:31.039 --> 00:45:33.239
<v Speaker 3>and they take all of that data and it lets

959
00:45:33.280 --> 00:45:36.639
<v Speaker 3>them track what is happening with jobs on a really

960
00:45:36.679 --> 00:45:41.039
<v Speaker 3>granular level. And the good news for right now is

961
00:45:41.079 --> 00:45:45.119
<v Speaker 3>that we are not seeing massive disruptions, but at least

962
00:45:45.159 --> 00:45:50.239
<v Speaker 3>according to that group, they are seeing enough happening that

963
00:45:50.320 --> 00:45:54.320
<v Speaker 3>they believe that the risks to jobs are real. It

964
00:45:54.320 --> 00:45:58.639
<v Speaker 3>seems to be happening right now. At the more junior level,

965
00:45:59.239 --> 00:46:01.800
<v Speaker 3>companies are a little bit less likely to hire a

966
00:46:01.880 --> 00:46:05.199
<v Speaker 3>junior employee than they were. You know, maybe three or

967
00:46:05.239 --> 00:46:08.599
<v Speaker 3>four years ago. So this is just something where you know,

968
00:46:08.639 --> 00:46:10.800
<v Speaker 3>we're all going to have to keep our eye.

969
00:46:10.599 --> 00:46:13.039
<v Speaker 2>On it, and it doesn't I've never heard anyone talk

970
00:46:13.039 --> 00:46:16.000
<v Speaker 2>about like an AI proof job really, right. I mean, like,

971
00:46:16.039 --> 00:46:18.360
<v Speaker 2>if you're hearing a parent with a kid who's a

972
00:46:18.360 --> 00:46:20.880
<v Speaker 2>freshman in college right now, is there a path that

973
00:46:21.320 --> 00:46:24.119
<v Speaker 2>they're getting steered that is more AI proof.

974
00:46:24.599 --> 00:46:28.719
<v Speaker 3>I'm deeply uncertain about this question. What people who are

975
00:46:28.760 --> 00:46:32.400
<v Speaker 3>optimistic about the future will say is it's easy to

976
00:46:32.440 --> 00:46:36.079
<v Speaker 3>automate a task, but it's hard to automate a job. Right,

977
00:46:36.280 --> 00:46:39.480
<v Speaker 3>Like your AI might be able to, you know, generate

978
00:46:39.519 --> 00:46:42.840
<v Speaker 3>that meeting briefing for you and create that slide deck

979
00:46:42.920 --> 00:46:46.159
<v Speaker 3>for you, but you're the only person who knows how

980
00:46:46.159 --> 00:46:49.199
<v Speaker 3>to actually maneuver through your organization and get buy in

981
00:46:49.280 --> 00:46:51.440
<v Speaker 3>from all of the right people and use your you know,

982
00:46:51.480 --> 00:46:54.719
<v Speaker 3>critical thinking skills. And so that's why you're always going

983
00:46:54.760 --> 00:46:59.199
<v Speaker 3>to have a job. The pessimists say, well, a job

984
00:46:59.280 --> 00:47:01.840
<v Speaker 3>is just a collection of tasks, and if you believe

985
00:47:01.880 --> 00:47:04.679
<v Speaker 3>that the capabilities of these models are going up over time,

986
00:47:05.039 --> 00:47:06.920
<v Speaker 3>eventually they might actually be able to do all of

987
00:47:06.960 --> 00:47:10.400
<v Speaker 3>the tasks that comprise your job. So this is one

988
00:47:10.400 --> 00:47:14.800
<v Speaker 3>where I just have deep uncertainty. But when I sit

989
00:47:14.920 --> 00:47:17.480
<v Speaker 3>with the increase and model capabilities just over the past

990
00:47:17.519 --> 00:47:20.639
<v Speaker 3>three years, it is hard for me to imagine that

991
00:47:20.800 --> 00:47:22.880
<v Speaker 3>they just sort of like top out in the next

992
00:47:22.920 --> 00:47:24.599
<v Speaker 3>six months and we can all relax Like that just

993
00:47:24.599 --> 00:47:25.679
<v Speaker 3>seems very unlikely to me.

994
00:47:26.199 --> 00:47:28.840
<v Speaker 1>We're fucked podcasters, We're done, bro, I know.

995
00:47:30.280 --> 00:47:32.039
<v Speaker 3>I mean, I'm sure you've seen the stories about the

996
00:47:32.039 --> 00:47:34.559
<v Speaker 3>networks of like automated podcasts that just sort of like,

997
00:47:34.599 --> 00:47:35.639
<v Speaker 3>you know, oh my god.

998
00:47:36.079 --> 00:47:38.079
<v Speaker 1>It does feel like the what do you think about

999
00:47:38.079 --> 00:47:39.159
<v Speaker 1>the AI newsrooms?

1000
00:47:39.159 --> 00:47:41.880
<v Speaker 2>Because I feel like they're good at aggregating, but the

1001
00:47:41.880 --> 00:47:44.760
<v Speaker 2>idea of an AI agent like going out and collecting

1002
00:47:44.840 --> 00:47:47.239
<v Speaker 2>new information and interviewing people and buildings, like it feels

1003
00:47:47.280 --> 00:47:48.119
<v Speaker 2>a little more challenging.

1004
00:47:48.199 --> 00:47:48.360
<v Speaker 4>Now.

1005
00:47:48.800 --> 00:47:52.079
<v Speaker 3>I went like four email rounds back and forth with

1006
00:47:52.159 --> 00:47:55.679
<v Speaker 3>some jerk who is like, hey, I put together an

1007
00:47:55.679 --> 00:47:58.559
<v Speaker 3>AI newsroom and over the past three months we publish

1008
00:47:58.639 --> 00:48:01.239
<v Speaker 3>over forty thousand story And I was like, Okay, so

1009
00:48:01.280 --> 00:48:02.960
<v Speaker 3>what we're telling me is you stole a bunch of

1010
00:48:02.960 --> 00:48:04.639
<v Speaker 3>work from a bunch of hard working people and you're

1011
00:48:04.639 --> 00:48:06.239
<v Speaker 3>now passing it off as your own, Like you want

1012
00:48:06.239 --> 00:48:08.519
<v Speaker 3>me to get excited about this, so I basically blew

1013
00:48:08.559 --> 00:48:10.920
<v Speaker 3>him off. A week later he got profiled and wired.

1014
00:48:11.880 --> 00:48:13.960
<v Speaker 3>So I don't know, Tommy, he might have a better

1015
00:48:14.000 --> 00:48:14.760
<v Speaker 3>strategy than I do.

1016
00:48:15.599 --> 00:48:19.920
<v Speaker 2>Oh well, listen, I admire your your gumption and having

1017
00:48:19.960 --> 00:48:22.800
<v Speaker 2>that fight. Okay, So if AI takes all the jobs,

1018
00:48:22.800 --> 00:48:26.599
<v Speaker 2>that is obviously bad, But there's also I think a

1019
00:48:26.679 --> 00:48:30.920
<v Speaker 2>less obvious risk to the economy if AI is all

1020
00:48:30.960 --> 00:48:33.719
<v Speaker 2>actually just bullshit and hype, because that means there's a

1021
00:48:33.719 --> 00:48:36.880
<v Speaker 2>massive stock market bubble built around AI that's gonna pop.

1022
00:48:36.920 --> 00:48:38.360
<v Speaker 2>So there's a bunch of different ways you could try

1023
00:48:38.360 --> 00:48:41.400
<v Speaker 2>to quantify the size of the AI bubble right now,

1024
00:48:41.480 --> 00:48:44.480
<v Speaker 2>but one easy one to think about is there's about

1025
00:48:44.480 --> 00:48:48.960
<v Speaker 2>seven companies Alphabet, Apple, Amazon, Meta, Microsoft, Nvidia, and Tesla

1026
00:48:49.320 --> 00:48:52.119
<v Speaker 2>that make up something like thirty to five thirty five

1027
00:48:52.159 --> 00:48:54.159
<v Speaker 2>percent of the S and P five hundred market cap.

1028
00:48:54.519 --> 00:48:57.719
<v Speaker 2>If their AI businesses creater, that would lead to a

1029
00:48:57.719 --> 00:48:59.440
<v Speaker 2>stock market crash.

1030
00:48:59.599 --> 00:49:00.360
<v Speaker 1>There's all so like.

1031
00:49:00.280 --> 00:49:02.199
<v Speaker 2>AI is driving a huge amount of corporate investment.

1032
00:49:02.239 --> 00:49:02.440
<v Speaker 1>I think.

1033
00:49:02.440 --> 00:49:05.159
<v Speaker 2>I just saw Golden Sacks release for report earlier this

1034
00:49:05.199 --> 00:49:08.320
<v Speaker 2>month where they estimated that there will be one trillion

1035
00:49:08.400 --> 00:49:12.400
<v Speaker 2>dollars of AI related investment in twenty twenty six, more

1036
00:49:12.440 --> 00:49:15.119
<v Speaker 2>than half of that in the US, and if that

1037
00:49:15.199 --> 00:49:18.320
<v Speaker 2>investment is worthless, obviously it dries up. So Casey, how

1038
00:49:18.480 --> 00:49:21.519
<v Speaker 2>concerned are people you talk to about the risk of

1039
00:49:21.519 --> 00:49:22.920
<v Speaker 2>an AI bubble bursting?

1040
00:49:23.840 --> 00:49:28.119
<v Speaker 3>So people are very concerned about this. I have to

1041
00:49:28.159 --> 00:49:31.559
<v Speaker 3>say this is a place where I have a strong take,

1042
00:49:31.840 --> 00:49:34.800
<v Speaker 3>which is that I do not think that this is

1043
00:49:34.840 --> 00:49:38.400
<v Speaker 3>going to lead to some sort of massive wipeout. Here

1044
00:49:38.440 --> 00:49:41.239
<v Speaker 3>is where I should say. My fiance works at Anthropic.

1045
00:49:41.280 --> 00:49:42.800
<v Speaker 3>That is something that you should know about me. I

1046
00:49:42.800 --> 00:49:44.920
<v Speaker 3>strive to maintain my independence, but like it is just

1047
00:49:45.039 --> 00:49:47.519
<v Speaker 3>a fact on my life. But here's the reason why

1048
00:49:47.519 --> 00:49:50.320
<v Speaker 3>I don't think that we're about to see a big wipeout.

1049
00:49:50.760 --> 00:49:55.079
<v Speaker 3>Because you personally might not care about AI, you don't

1050
00:49:55.079 --> 00:49:57.760
<v Speaker 3>want to use it, But my guess is your boss does.

1051
00:49:58.000 --> 00:50:01.400
<v Speaker 3>And this is the entire thing. Business are buying AI.

1052
00:50:01.679 --> 00:50:05.440
<v Speaker 3>They are buying as much AI as the labs can make.

1053
00:50:05.559 --> 00:50:08.159
<v Speaker 3>Almost all of these companies, well, you know, maybe not

1054
00:50:08.280 --> 00:50:12.559
<v Speaker 3>a groc because it sucks, but you know the frontier labs, right,

1055
00:50:12.599 --> 00:50:16.000
<v Speaker 3>So like the Entropic, Open AI, Google, Gemini, for the

1056
00:50:16.000 --> 00:50:20.400
<v Speaker 3>most part, they have been in this kind of capacity

1057
00:50:20.440 --> 00:50:24.480
<v Speaker 3>crunch for like a year now. Because people cannot get

1058
00:50:24.639 --> 00:50:27.760
<v Speaker 3>enough of this stuff, they are bringing it into their businesses.

1059
00:50:28.039 --> 00:50:31.039
<v Speaker 3>That is why these companies, you know, Open and Anthropic

1060
00:50:31.199 --> 00:50:34.480
<v Speaker 3>are on pace to have two of the biggest IPOs

1061
00:50:34.519 --> 00:50:37.440
<v Speaker 3>in history. So in order for you to believe that

1062
00:50:37.519 --> 00:50:40.559
<v Speaker 3>there is going to be this big wipeout, you have

1063
00:50:40.599 --> 00:50:44.440
<v Speaker 3>to believe that businesses are going to stop buying the technology.

1064
00:50:44.440 --> 00:50:46.159
<v Speaker 3>And if that is the case that you're going to make,

1065
00:50:46.320 --> 00:50:48.559
<v Speaker 3>you have to give me a really good reason for

1066
00:50:48.800 --> 00:50:50.760
<v Speaker 3>why they're going to stop buying it. And I just

1067
00:50:50.840 --> 00:50:52.119
<v Speaker 3>have not myself heard that reason.

1068
00:50:52.400 --> 00:50:53.840
<v Speaker 1>I can't believe you said that about rock.

1069
00:50:54.920 --> 00:50:56.639
<v Speaker 2>If you want to create an image of a teenage

1070
00:50:56.679 --> 00:51:00.400
<v Speaker 2>classmate in a see through bikini, where else are you turn?

1071
00:51:00.760 --> 00:51:02.119
<v Speaker 3>That's a good point. That's a good point.

1072
00:51:02.199 --> 00:51:04.639
<v Speaker 1>Yeah, thank you. I do think there is like there.

1073
00:51:04.679 --> 00:51:07.199
<v Speaker 2>I think you're right there, Like groc is, groc is

1074
00:51:07.239 --> 00:51:10.000
<v Speaker 2>a shitty lollm. There is a question of whether Tesla

1075
00:51:10.199 --> 00:51:12.400
<v Speaker 2>and SpaceX and all those various companies are going to

1076
00:51:12.400 --> 00:51:16.000
<v Speaker 2>do something interesting in robotics that could be revolutionary in

1077
00:51:16.000 --> 00:51:17.679
<v Speaker 2>some way. Do you are you more of an optivist

1078
00:51:17.679 --> 00:51:18.599
<v Speaker 2>in that use case?

1079
00:51:19.760 --> 00:51:23.639
<v Speaker 3>I'm like pretty scared of robots actually. But you know,

1080
00:51:23.679 --> 00:51:25.719
<v Speaker 3>I but I wouldn't make another point about GROK because

1081
00:51:25.719 --> 00:51:28.480
<v Speaker 3>it's relevant to the bubble discussion, which is that groc

1082
00:51:28.760 --> 00:51:31.800
<v Speaker 3>was not able to like use all of its capacity

1083
00:51:31.880 --> 00:51:34.679
<v Speaker 3>to you know, make c SAM and so what they

1084
00:51:34.679 --> 00:51:37.400
<v Speaker 3>did instead, because there was no real consumer demand, was

1085
00:51:37.440 --> 00:51:39.840
<v Speaker 3>that they just sold it to Anthropic. And so I

1086
00:51:39.880 --> 00:51:41.559
<v Speaker 3>think you're going to see this dynamic because you know,

1087
00:51:41.599 --> 00:51:44.159
<v Speaker 3>some people are like, well, what if we massively overbuild

1088
00:51:44.199 --> 00:51:45.920
<v Speaker 3>and we have a bunch of data centers lying around

1089
00:51:45.920 --> 00:51:48.119
<v Speaker 3>that nobody needs, like you know, that's when the bubble

1090
00:51:48.159 --> 00:51:50.719
<v Speaker 3>will burst. My view is no, like, whoever happens to

1091
00:51:50.719 --> 00:51:52.599
<v Speaker 3>be winning at the time, they're just going to buy

1092
00:51:52.639 --> 00:51:54.679
<v Speaker 3>the excess compute because it takes a long time and

1093
00:51:54.719 --> 00:51:56.159
<v Speaker 3>you have to find a lot of political battles to

1094
00:51:56.159 --> 00:51:57.199
<v Speaker 3>get one of those things built.

1095
00:51:57.400 --> 00:51:59.599
<v Speaker 2>Yeah, uh, okay, let's end this upthing a little more

1096
00:51:59.639 --> 00:52:03.760
<v Speaker 2>fun that's hopefully also educational. First of all, people need

1097
00:52:03.800 --> 00:52:07.920
<v Speaker 2>recommendations like I use I switch to claud. I use

1098
00:52:07.960 --> 00:52:11.920
<v Speaker 2>it as mostly a souped up Google. I don't really

1099
00:52:11.960 --> 00:52:13.920
<v Speaker 2>let it write for me because I don't trust that

1100
00:52:13.960 --> 00:52:15.079
<v Speaker 2>it's not hallucinating.

1101
00:52:15.760 --> 00:52:17.039
<v Speaker 1>But I find it very.

1102
00:52:16.920 --> 00:52:20.280
<v Speaker 2>Useful as a research tool. What AI products do you use,

1103
00:52:20.519 --> 00:52:23.519
<v Speaker 2>what has helped you at life and work? And is

1104
00:52:23.519 --> 00:52:26.760
<v Speaker 2>there anything you've tried that was just comically shitty that

1105
00:52:26.800 --> 00:52:27.639
<v Speaker 2>you can tell us about.

1106
00:52:30.119 --> 00:52:33.079
<v Speaker 3>Sure, let's see. I mean some things that I've done.

1107
00:52:33.159 --> 00:52:36.559
<v Speaker 3>Like something that I encourage everyone to do is use

1108
00:52:36.599 --> 00:52:39.199
<v Speaker 3>one of these tools to build a personal website. You

1109
00:52:39.239 --> 00:52:40.679
<v Speaker 3>don't have to put it on the internet, Like you

1110
00:52:40.719 --> 00:52:42.840
<v Speaker 3>can build a website that just lives in your browser,

1111
00:52:43.079 --> 00:52:45.960
<v Speaker 3>but use a tool like chat, JPT, code AX or

1112
00:52:46.079 --> 00:52:48.719
<v Speaker 3>claude and just say, hey, make a website about me.

1113
00:52:49.159 --> 00:52:51.400
<v Speaker 3>The reason I suggest people do this is because it's

1114
00:52:51.480 --> 00:52:54.079
<v Speaker 3>kind of fun to make a website. And two, if

1115
00:52:54.119 --> 00:52:56.960
<v Speaker 3>you haven't yet like watched this thing work, I think

1116
00:52:57.000 --> 00:52:59.480
<v Speaker 3>you will learn a lot from that process. Right when

1117
00:52:59.480 --> 00:53:01.760
<v Speaker 3>you see that, you're like, could you, like, you know,

1118
00:53:01.840 --> 00:53:03.840
<v Speaker 3>make it purple and add in a little widget that

1119
00:53:03.880 --> 00:53:06.239
<v Speaker 3>pulls on the weather and like maybe my Spotify history

1120
00:53:06.400 --> 00:53:08.559
<v Speaker 3>and it just kind of does it. That may help

1121
00:53:08.599 --> 00:53:11.239
<v Speaker 3>you understand like, wow, it's pretty weird to just be

1122
00:53:11.280 --> 00:53:13.320
<v Speaker 3>able to like types some words into a box and

1123
00:53:13.360 --> 00:53:15.880
<v Speaker 3>like make an entire website. So like that's usually where

1124
00:53:15.880 --> 00:53:21.280
<v Speaker 3>I suggest that people start. In terms of other tools

1125
00:53:21.320 --> 00:53:24.480
<v Speaker 3>that I'm using. I really like this tool called Granola.

1126
00:53:25.280 --> 00:53:26.920
<v Speaker 3>It seemed a lot more interesting when it came out

1127
00:53:26.920 --> 00:53:29.199
<v Speaker 3>because everyone has copied it now. But basically, it just

1128
00:53:29.280 --> 00:53:32.400
<v Speaker 3>like listens in on my meetings. It takes really good notes.

1129
00:53:32.639 --> 00:53:35.199
<v Speaker 3>But then importantly, it's just like kind of a knowledge base,

1130
00:53:35.280 --> 00:53:37.599
<v Speaker 3>so that you know, I'm planning this new company with Kevin,

1131
00:53:37.639 --> 00:53:39.719
<v Speaker 3>I'm trying to remember what we decided about this one

1132
00:53:39.760 --> 00:53:43.440
<v Speaker 3>particular thing. I could text him, but you know, he's,

1133
00:53:43.719 --> 00:53:45.280
<v Speaker 3>you know, a diva who knows where he.

1134
00:53:45.320 --> 00:53:49.320
<v Speaker 1>Is for you of equity is what I tol.

1135
00:53:49.840 --> 00:53:51.880
<v Speaker 3>Yeah, that's what I think. That's that's what I remember too,

1136
00:53:52.159 --> 00:53:53.559
<v Speaker 3>But now I can just sort of like get it

1137
00:53:53.599 --> 00:53:55.960
<v Speaker 3>from there. So that's another one that I like that's

1138
00:53:56.000 --> 00:53:59.519
<v Speaker 3>really useful. And then I've been trying this thing town

1139
00:53:59.639 --> 00:54:01.280
<v Speaker 3>that I just mentioned, and this thing is like only

1140
00:54:01.280 --> 00:54:03.079
<v Speaker 3>been around since June. You know, I don't know if

1141
00:54:03.079 --> 00:54:05.159
<v Speaker 3>this thing has legs, but I like the fact that

1142
00:54:05.199 --> 00:54:08.280
<v Speaker 3>it's briefing me on all of my meetings. It also

1143
00:54:08.400 --> 00:54:10.480
<v Speaker 3>like creates this wiki, so it's like kind of like

1144
00:54:10.519 --> 00:54:13.400
<v Speaker 3>a wiki of my life. Think about like how much

1145
00:54:13.519 --> 00:54:16.400
<v Speaker 3>like useful information is hidden in your email. This just

1146
00:54:16.480 --> 00:54:19.400
<v Speaker 3>kind of like organizes it. It sort of pulls out important documents,

1147
00:54:19.400 --> 00:54:21.000
<v Speaker 3>it puts them in a place that you can find.

1148
00:54:21.280 --> 00:54:24.039
<v Speaker 3>So just that kind of basic personal assistance stuff that

1149
00:54:24.079 --> 00:54:25.639
<v Speaker 3>I find really useful.

1150
00:54:25.880 --> 00:54:26.639
<v Speaker 1>That's really interesting.

1151
00:54:26.639 --> 00:54:28.239
<v Speaker 2>I mean I think people are always like, oh, you

1152
00:54:28.280 --> 00:54:31.360
<v Speaker 2>should try claud code and build something. And I was like, hey, man,

1153
00:54:31.519 --> 00:54:33.360
<v Speaker 2>if I had a fucking idea for an app, I

1154
00:54:33.400 --> 00:54:35.440
<v Speaker 2>would have been like rich in twenty twelve.

1155
00:54:35.480 --> 00:54:36.239
<v Speaker 1>Okay, but I'm not.

1156
00:54:36.840 --> 00:54:38.960
<v Speaker 2>So That's why I'm here talking to you people.

1157
00:54:39.360 --> 00:54:41.719
<v Speaker 3>But I mean, have you guys thought about doing like

1158
00:54:41.800 --> 00:54:43.559
<v Speaker 3>cause you could make a pod save app. Maybe you

1159
00:54:43.559 --> 00:54:45.079
<v Speaker 3>have something like that. It's already you could just beat

1160
00:54:45.119 --> 00:54:48.320
<v Speaker 3>every transcript of every episode and like, you know, everyone

1161
00:54:48.360 --> 00:54:50.000
<v Speaker 3>on your team, because I'm sure you must all the

1162
00:54:50.039 --> 00:54:52.119
<v Speaker 3>time be like what episode did that happen on? When

1163
00:54:52.159 --> 00:54:53.639
<v Speaker 3>is the last time we talked about that? When is

1164
00:54:53.679 --> 00:54:55.480
<v Speaker 3>the last time that guest came on the show? That

1165
00:54:55.559 --> 00:54:57.679
<v Speaker 3>is something that you personally could make with AIO would

1166
00:54:57.679 --> 00:54:58.360
<v Speaker 3>not even be that hard.

1167
00:54:58.519 --> 00:54:59.920
<v Speaker 1>Oh that's really interesting, what about it?

1168
00:55:00.079 --> 00:55:02.079
<v Speaker 2>I wanted to make somethings like, Okay, I have like

1169
00:55:02.159 --> 00:55:06.119
<v Speaker 2>some nerdy niche interests, like I really care about American politics.

1170
00:55:06.159 --> 00:55:08.440
<v Speaker 2>I think foreign policies super interesting. I do shows on

1171
00:55:08.480 --> 00:55:11.239
<v Speaker 2>each Could I build an app that is able to

1172
00:55:11.320 --> 00:55:14.000
<v Speaker 2>brief me every morning on those things? And the thing

1173
00:55:14.079 --> 00:55:16.320
<v Speaker 2>I worry about how to get around is like whenever

1174
00:55:16.400 --> 00:55:19.000
<v Speaker 2>I ask Claude to research something for me, the websites

1175
00:55:19.239 --> 00:55:21.800
<v Speaker 2>that come back as sources are not the most reputable.

1176
00:55:21.840 --> 00:55:23.360
<v Speaker 1>Casey, it's none of the stuff I pay for.

1177
00:55:23.400 --> 00:55:25.360
<v Speaker 2>It's some of the great journalism that I pay for.

1178
00:55:25.639 --> 00:55:26.840
<v Speaker 2>Can I get it to pull from that?

1179
00:55:27.679 --> 00:55:29.599
<v Speaker 3>It's a great point, you know, this is this is

1180
00:55:29.599 --> 00:55:32.760
<v Speaker 3>an area where the publishers to protect their own interests

1181
00:55:32.760 --> 00:55:35.320
<v Speaker 3>because the AI companies are all incredibly like rapacious and

1182
00:55:35.320 --> 00:55:38.239
<v Speaker 3>would steal absolutely every like pixel on their website if

1183
00:55:38.280 --> 00:55:40.360
<v Speaker 3>the publishers would let them. The publishers have all said

1184
00:55:40.360 --> 00:55:42.280
<v Speaker 3>like whoa, oh no, like you cannot scrape us. So

1185
00:55:42.360 --> 00:55:44.679
<v Speaker 3>like they have not created a way so that you can,

1186
00:55:44.719 --> 00:55:48.519
<v Speaker 3>you know, sign in to chat GPT with your Bloomberg account,

1187
00:55:48.519 --> 00:55:50.199
<v Speaker 3>which is something I would love to do so that

1188
00:55:50.239 --> 00:55:52.320
<v Speaker 3>I could get the kind of briefing that you're talking about.

1189
00:55:52.679 --> 00:55:54.360
<v Speaker 3>So can you get a briefing?

1190
00:55:54.559 --> 00:55:54.800
<v Speaker 8>Yes?

1191
00:55:54.960 --> 00:55:56.639
<v Speaker 3>Will it be high quality sources?

1192
00:55:56.840 --> 00:55:56.920
<v Speaker 7>No?

1193
00:55:57.519 --> 00:55:59.960
<v Speaker 3>Are there a strange number of websites that just see

1194
00:56:00.239 --> 00:56:02.559
<v Speaker 3>to like republish the New York Times, in the Wall

1195
00:56:02.559 --> 00:56:04.960
<v Speaker 3>Street Journal and other credible sources, and so you still

1196
00:56:04.960 --> 00:56:07.679
<v Speaker 3>sort of wind up getting a decent briefing anyway. Yes,

1197
00:56:08.639 --> 00:56:10.599
<v Speaker 3>but yeah, that's it's not a bad place to start.

1198
00:56:10.920 --> 00:56:11.480
<v Speaker 1>Yeah.

1199
00:56:11.519 --> 00:56:14.239
<v Speaker 2>Weren't you building yourself some sort of goofy day planner

1200
00:56:14.280 --> 00:56:15.320
<v Speaker 2>that Kevin made fun of you for.

1201
00:56:15.800 --> 00:56:20.400
<v Speaker 3>Yes, So you know here, one of my core beliefs

1202
00:56:20.440 --> 00:56:23.000
<v Speaker 3>as a technology journalist is that it is fun to

1203
00:56:23.079 --> 00:56:25.159
<v Speaker 3>build and make things, and so I like to just

1204
00:56:25.360 --> 00:56:27.679
<v Speaker 3>have moments in my week where I am building and

1205
00:56:27.719 --> 00:56:30.119
<v Speaker 3>making things. One of the easiest things you can make

1206
00:56:30.159 --> 00:56:33.079
<v Speaker 3>with an AI tool is a to do list, and

1207
00:56:33.159 --> 00:56:36.400
<v Speaker 3>I've used literally all of them, and they're all functionally

1208
00:56:36.440 --> 00:56:38.679
<v Speaker 3>the same. There's no good reason to use one over

1209
00:56:38.719 --> 00:56:41.119
<v Speaker 3>the other. Anyone will will do you. So I had

1210
00:56:41.159 --> 00:56:42.800
<v Speaker 3>the idea to make one that was themed with a

1211
00:56:42.800 --> 00:56:46.000
<v Speaker 3>comic book that I've been reading, which is called Nightwing. Tommy,

1212
00:56:46.039 --> 00:56:48.199
<v Speaker 3>I'm sure you know that night Wing is Dick Grayson,

1213
00:56:48.280 --> 00:56:53.000
<v Speaker 3>the original Robin and so you know, I basically just

1214
00:56:53.039 --> 00:56:55.000
<v Speaker 3>wanted to see what it could do. Could I get

1215
00:56:55.360 --> 00:56:59.239
<v Speaker 3>Gemini and chat GBT to violate DC Comics copyright and

1216
00:56:59.280 --> 00:57:01.599
<v Speaker 3>create for me a night Wing themed to do list

1217
00:57:01.599 --> 00:57:03.480
<v Speaker 3>app and guess what the answer was, Yes, And that's

1218
00:57:03.480 --> 00:57:03.880
<v Speaker 3>the power of.

1219
00:57:03.840 --> 00:57:08.400
<v Speaker 2>AI night Wing who has not wanted a Robin themed

1220
00:57:08.480 --> 00:57:10.159
<v Speaker 2>anything for me when I want to build something, I

1221
00:57:10.239 --> 00:57:13.960
<v Speaker 2>described the magnetiles with my kids and that last.

1222
00:57:13.760 --> 00:57:15.719
<v Speaker 1>Question for you. So there's probably a lot of people

1223
00:57:15.960 --> 00:57:16.480
<v Speaker 1>who are.

1224
00:57:16.320 --> 00:57:18.599
<v Speaker 2>Listening, thank you for still listening, by the way we

1225
00:57:18.639 --> 00:57:20.719
<v Speaker 2>get to the end of the show, who feel like

1226
00:57:20.840 --> 00:57:24.559
<v Speaker 2>they are getting totally left behind by this technology and

1227
00:57:24.559 --> 00:57:26.280
<v Speaker 2>they just want a better understanding of these tools. I

1228
00:57:26.280 --> 00:57:28.440
<v Speaker 2>think you gave some great advice there of like use

1229
00:57:28.480 --> 00:57:31.320
<v Speaker 2>them build some things. But are there also organizations you

1230
00:57:31.360 --> 00:57:34.519
<v Speaker 2>look to or like YouTube series or like people that

1231
00:57:34.559 --> 00:57:36.280
<v Speaker 2>are doing kind of like informational stuff.

1232
00:57:36.440 --> 00:57:39.559
<v Speaker 3>Let's see beside reading platform or of course, of course,

1233
00:57:39.639 --> 00:57:41.960
<v Speaker 3>of course and listening to hard work. And we'll have

1234
00:57:42.159 --> 00:57:45.960
<v Speaker 3>a new show for folks to watch pretty soon. What

1235
00:57:46.039 --> 00:57:48.800
<v Speaker 3>I see people doing that is great is that they're

1236
00:57:48.800 --> 00:57:52.599
<v Speaker 3>going to public meetings and they're calling their representatives and

1237
00:57:52.639 --> 00:57:56.480
<v Speaker 3>they're raising concerns, and that is the place where I

1238
00:57:56.559 --> 00:57:59.599
<v Speaker 3>see getting involved really making a difference. Look, if you

1239
00:57:59.639 --> 00:58:01.840
<v Speaker 3>want to and something specific about AI, you can just

1240
00:58:01.880 --> 00:58:04.119
<v Speaker 3>type it into the YouTube search box, and I guarantee

1241
00:58:04.119 --> 00:58:06.519
<v Speaker 3>you there is some hustlebro that has like a fourteen

1242
00:58:06.559 --> 00:58:08.800
<v Speaker 3>minute video about how you should do all of it instantly.

1243
00:58:08.800 --> 00:58:10.000
<v Speaker 1>Well he planks.

1244
00:58:11.639 --> 00:58:16.679
<v Speaker 3>Exactly, but no, just you know, I would try to

1245
00:58:16.719 --> 00:58:20.199
<v Speaker 3>stay curious about it. But like, if you're nervous about

1246
00:58:20.199 --> 00:58:22.920
<v Speaker 3>what you're seeing out there, like just know that I'm

1247
00:58:22.960 --> 00:58:23.960
<v Speaker 3>with you. I'm nervous too.

1248
00:58:24.280 --> 00:58:27.519
<v Speaker 2>Okay, that's good advice. Casey Newton, thank you so much.

1249
00:58:27.559 --> 00:58:30.519
<v Speaker 2>Everyone go to platformer dot news to learn more about

1250
00:58:30.559 --> 00:58:33.239
<v Speaker 2>AI and everything in tech, and I really appreciate it.

1251
00:58:33.559 --> 00:58:34.519
<v Speaker 3>Thanks time. It was fun.

1252
00:58:34.760 --> 00:58:36.719
<v Speaker 2>Thanks again to Casey Newton for joining the show, and

1253
00:58:37.000 --> 00:58:39.000
<v Speaker 2>we will be back in your feeds on Tuesday.

1254
00:58:39.159 --> 00:58:41.480
<v Speaker 9>Positive America is a Crooked media production. Our show is

1255
00:58:41.519 --> 00:58:44.559
<v Speaker 9>produced by Austin Fisher, Saul Ruben, McKenna Roberts, and Faris Safari,

1256
00:58:44.599 --> 00:58:47.079
<v Speaker 9>with re Jerland, Elijah Cone and Adrian Hill. Our team

1257
00:58:47.079 --> 00:58:50.159
<v Speaker 9>includes Matt to Grote, Ben Hefco, Jordan Canter, Charlottelandis Krol

1258
00:58:50.199 --> 00:58:53.079
<v Speaker 9>pel Aviv, David Toles, Mia Kelman, Ryan Young, and Naomi Single.

1259
00:58:53.159 --> 00:58:55.039
<v Speaker 9>Our staff is probably unionized with the Writer's Guild of

1260
00:58:55.079 --> 00:58:58.239
<v Speaker 9>America East
