WEBVTT - America’s New AI Strategy

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<v Speaker 1>Pushkin. Welcome back to Risky Business, a show about making

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<v Speaker 1>better decisions. I'm Maria Kanakova.

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<v Speaker 2>And I'm Nate Silver. Time for an AI episode, I think, Aria, Yeah, it's.

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<v Speaker 1>It's been a minute since we had AI related conversations

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<v Speaker 1>on the show. But it's obviously a hugely important topic

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<v Speaker 1>and one that should have been more in the news

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<v Speaker 1>last week it got you know, got sidelined by other news.

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<v Speaker 1>But who's that a guy don't don't know, don't know

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<v Speaker 1>Nate but never never met him. That's true, never met him.

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<v Speaker 1>But yeah, well, we'll talk a little bit about the

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<v Speaker 1>AI action plan that was released by the US government

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<v Speaker 1>last week. We have lots to talk about before we do. Nate,

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<v Speaker 1>we're both back in New York, but I'm actually flying

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<v Speaker 1>back to Vegas in twenty four hours to play in

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<v Speaker 1>the twenty five k NBC Heads Up Championship.

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<v Speaker 2>Yeah are you? Are you excited? Have you been coaching?

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<v Speaker 3>I have?

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<v Speaker 1>I have so For people who don't know, this was

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<v Speaker 1>a big show back in the day. It was before

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<v Speaker 1>my time, so I never watched it. Nate, did you

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<v Speaker 1>ever watch it?

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<v Speaker 2>Sure? Yeah, yeah, so time, you're not that much younger.

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<v Speaker 1>I didn't know anything about poker. It was before my time,

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<v Speaker 1>like actually knowing anything about poker, So I didn't watch

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<v Speaker 1>any poker, know about the existence of any poker shows

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<v Speaker 1>before I started researching Biggest Bluff. So that's what I mean,

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<v Speaker 1>before my time, before my time in the poker world.

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<v Speaker 2>Had you heard of poker only because of rounders?

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<v Speaker 1>I knew that technically it was a game that existed,

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<v Speaker 1>but it's not something that was ever really on my radar.

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<v Speaker 1>But yeah, this was a huge show on NBC back

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<v Speaker 1>in the day. Heads Up poker is one on one poker,

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<v Speaker 1>which is kind of the most competitive in some ways

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<v Speaker 1>form of poker because you're forced to play all hands.

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<v Speaker 1>Basically your ranges are one hundred percent, so it forces

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<v Speaker 1>a very different kind of thinking. And it's being rebooted

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<v Speaker 1>in conjunction with Peacock and Poker Stars and Poker Goes

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<v Speaker 1>kind of is helping sponsor all of this. So I

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<v Speaker 1>am yeah, I'll be in the Poker Ghost Studios taping

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<v Speaker 1>and I hope it goes well. I've been getting coaching

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<v Speaker 1>from Kevin Rabichow, who's considered Yeah, he's considered one of

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<v Speaker 1>the best heads up players in the world. He has

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<v Speaker 1>a new heads up coaching course that just came out.

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<v Speaker 1>But yeah, so I've been I've been really trying. You know,

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<v Speaker 1>usually after the World Series, I'm like, okay, no poker

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<v Speaker 1>for a while. Right, it's not gonna just gonna clear

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<v Speaker 1>my my clear my brain.

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<v Speaker 3>I'm in the no poker zone for a period of time.

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<v Speaker 3>We're also bad heads up to be frank, which was

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<v Speaker 3>some coaching might have been good, but like, yeah, I

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<v Speaker 3>can't can't make the time commitment this summer in.

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<v Speaker 1>Yeah, so instead of taking my usual break from from

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<v Speaker 1>poker that I do, I've been instead like going hard

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<v Speaker 1>and trying to prepare myself for this heads up Championship.

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<v Speaker 1>And you know it, heads up, the variants so much higher,

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<v Speaker 1>and the card distribution matters so much, right, So, like no,

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<v Speaker 1>and if someone is just getting hands, that's kind of

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<v Speaker 1>you know, that's it, Like they're they're potentially going to win.

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<v Speaker 1>And there have been lots of times where really great

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<v Speaker 1>players have been just completely obliterated by someone who doesn't

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<v Speaker 1>know how to play. Yeah, so card distribution can be

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<v Speaker 1>a bitch heads up, or it can be amazing.

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<v Speaker 2>Are those exclusive? Uh No, Okay, I'm not going to

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<v Speaker 2>get into it.

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<v Speaker 1>Yeah, no, bitchin amazing can be can be within the

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<v Speaker 1>same match, but it does matter much more so than

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<v Speaker 1>in full ring poker. I saw some of the names

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<v Speaker 1>that we'll be playing, and there's gonna be no spoilers obviously. Well,

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<v Speaker 1>I haven't played yet, but I'm not going to be

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<v Speaker 1>able to tell you how I did until the show

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<v Speaker 1>airs in the fall. Yeah, since it's not it's not

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<v Speaker 1>airing in real time, but you will. People do know

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<v Speaker 1>who's playing. And if I'm paired with someone like Jason

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<v Speaker 1>Kuhn on my first match, yeah, that's that's not going

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<v Speaker 1>to be fun. And if I'm paired with Don Cheetle,

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<v Speaker 1>who's also playing, I think I'm gonna be much happier.

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<v Speaker 2>Yeah.

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<v Speaker 3>I didn't realize there that many not Fish but celebrities

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<v Speaker 3>that maybe Fish adjacent potentially, although he plays a little

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<v Speaker 3>bit right he does.

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<v Speaker 1>Yeah, so so we'll We'll just see and I'm excited

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<v Speaker 1>for it no matter how it goes. And Kevin has

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<v Speaker 1>been very good at preparing me for both heads up

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<v Speaker 1>and also for the eventuality that he as one of

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<v Speaker 1>the best and at times probably the best in the world,

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<v Speaker 1>has sometimes busted in the first round right in the

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<v Speaker 1>matchups like this, because he plays a twenty five K

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<v Speaker 1>heads up at the World Series every year.

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<v Speaker 3>Are you worried about like physical reads and things like that,

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<v Speaker 3>because like that can be more of a factor too.

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<v Speaker 1>Yeah, you know, so I tend to be you know,

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<v Speaker 1>I hope that people can't get a lot of reads

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<v Speaker 1>off of me, but you just never know. And this

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<v Speaker 1>is actually hilarious night the rules of this. When I

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<v Speaker 1>started reading it, I just burst out laughing because they

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<v Speaker 1>said that you are allowed So people who don't play poker,

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<v Speaker 1>this is not normal. You're allowed to expose one or

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<v Speaker 1>both of your cards at any point during a hand.

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<v Speaker 2>You can cash usually but not in turn.

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<v Speaker 1>But this, yeah, this is a tournament. Yeah, so you

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<v Speaker 1>can expose your cards one or both of them. And

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<v Speaker 1>they said they encourage speech play. You can talk about

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<v Speaker 1>the contents of your hands. So basically everything are not

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<v Speaker 1>allowed to do in tournaments normally you're being encouraged to

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<v Speaker 1>do to make good television. I'm not going to be

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<v Speaker 1>showing my cards day.

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<v Speaker 3>Okay, I've become more of a speech play guy over time.

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<v Speaker 1>No really, yeah, okay, okay, give me an example.

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<v Speaker 3>You know, like the Europeans, I'll like try to get

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<v Speaker 3>info out of them. Were so quiet all the time

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<v Speaker 3>that like I want, like, I just want to like

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<v Speaker 3>any vibe I can get pretty much, or with like

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<v Speaker 3>really bad players who like often will reveal information just

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<v Speaker 3>to gauge their comfort level. It's kind of been a

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<v Speaker 3>proto trial and error Zoka. For right now, I'm trying

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<v Speaker 3>to like kind of like collect mental database of like

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<v Speaker 3>how people react to different things.

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<v Speaker 2>I don't know, it's kind of I mean, because so.

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<v Speaker 3>Many decisions are so close, yeah, equilibrium that like any

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<v Speaker 3>vibe you can get, And I like recently cash games

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<v Speaker 3>more than tournaments and they're kind of looser in various

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<v Speaker 3>senses of the term, right, people like you reveal more

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<v Speaker 3>info voluntarily or involuntarily.

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<v Speaker 2>I like cultivating that environment. I think.

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<v Speaker 1>Yeah, no, I'm someone who definitely is chatty and tends

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<v Speaker 1>to be like very friendly at poker tables. But you know,

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<v Speaker 1>I'm not someone who's going to be like, oh, you know,

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<v Speaker 1>do you have aces, like do you do things like

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<v Speaker 1>that or is it because you know there are players

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<v Speaker 1>who do or is it something a little bit different

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<v Speaker 1>just to try to engage.

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<v Speaker 3>Yeah, maybe it's like you're would have decided to fold

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<v Speaker 3>already if they want to like reveal something that they

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<v Speaker 3>might not reveal otherwise, or to send a bassline for

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<v Speaker 3>the next time we play a hand, things like that.

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<v Speaker 1>Yeah, that's that's actually smart.

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<v Speaker 2>So how can you reveal afterward? Right?

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<v Speaker 3>If you're friendly in the right way, they might reveal

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<v Speaker 3>information later on.

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<v Speaker 2>Right for sure.

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<v Speaker 1>Yeah, that's actually something that I have capitalized on because

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<v Speaker 1>I am a friendly player. Like I'll sometimes when it's obvious,

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<v Speaker 1>like I've made a big fold or something like that,

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<v Speaker 1>and I like make it obvious, they'll show me. And

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<v Speaker 1>that's that's very nice because it's good information. But I'm

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<v Speaker 1>always I do try to be careful, and I tell

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<v Speaker 1>people this, you know, with with poker and with just

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<v Speaker 1>like reads and our ability to spot deception in general,

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<v Speaker 1>that we do tend to be not great at it

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<v Speaker 1>as human beings. And the other kind of the other

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<v Speaker 1>element of that is that we think we're better than

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<v Speaker 1>we are. And we also often reveal information when we're

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<v Speaker 1>engaging in speech play without realizing it because of how

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<v Speaker 1>we're talking, what we're doing. And so it's something that

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<v Speaker 1>I think just in general, with the psychology of the thing,

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<v Speaker 1>you have to be careful.

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<v Speaker 2>It's all contextual.

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<v Speaker 3>Any poker tell speech play, it's all about semantic context,

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<v Speaker 3>so to speak for sure.

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<v Speaker 1>For sure. On that note, Nate, shall we switch gears

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<v Speaker 1>and talk about AI and the news from last week

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<v Speaker 1>which got buried because there's a lot of news in

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<v Speaker 1>the news. There's a lot of news in the news

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<v Speaker 1>these days, Nate, that's a very deep insight. So last

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<v Speaker 1>week President released the AI Action Plan that talks about

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<v Speaker 1>what the administration wants to kind of see going forward

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<v Speaker 1>in the AI space. And I think the name of

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<v Speaker 1>this action plan is actually quite telling about the contents.

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<v Speaker 1>It says, winning the Race America's AI Action Plan. So

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<v Speaker 1>it's titled winning the Race. And that's how it's framed, right,

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<v Speaker 1>It's framed as a race between the US and everyone else,

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<v Speaker 1>especially China, but really everyone else, mostly China, but mostly no,

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<v Speaker 1>there isn't. And the overall point of all of the

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<v Speaker 1>different sections is how can we make the US the

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<v Speaker 1>leader in AI the most competitive and how can we

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<v Speaker 1>do that by also kind of screwing over China in

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<v Speaker 1>some respects by not allowing it access to the types

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<v Speaker 1>of things that will allow our allies to access and

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<v Speaker 1>some of the things in it are contradictory, but that's

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<v Speaker 1>kind of the overall message. Did you read the report night,

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<v Speaker 1>Do you have any initial thoughts?

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<v Speaker 2>So?

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<v Speaker 3>V Maschwitz is one of the most prominent and best

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<v Speaker 3>AI bloggers. He writes the substack, don't worry about the vase,

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<v Speaker 3>and he calls it as he sees that he's more

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<v Speaker 3>concerned about ped doom than a lot of people. P

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<v Speaker 3>doom is the possibility if things going really badly, extinction,

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<v Speaker 3>loss of control, et cetera. And he said he thought

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<v Speaker 3>the plan was actually his term pretty good. I don't

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<v Speaker 3>know his politics in detail, but he really dives down

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<v Speaker 3>into like every last word you can read that. So

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<v Speaker 3>I'm kind of relying on that for like general vibes, right.

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<v Speaker 3>I mean, it is interesting that like, even like even

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<v Speaker 3>people who are concerned like V about AI safety, deeply

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<v Speaker 3>concerned in his case, have this ambiguous relationship with China,

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<v Speaker 3>right where if we were the only country developing AI

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<v Speaker 3>and we had like centralized control, then it would be

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<v Speaker 3>easier to argue that Okay, let's speak appropriately cautious here,

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<v Speaker 3>take it slow right with China. You know a lot

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<v Speaker 3>of people I don't want it to be of you

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<v Speaker 3>to him I do think that, well, we have no

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<v Speaker 3>choice but to race, and maybe we can race in

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<v Speaker 3>ways that involves some degree of coordination or cooperation. It's

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<v Speaker 3>hard to run races like that. But you know, I

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<v Speaker 3>mean the notion of like securing American leadership instead of

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<v Speaker 3>seeding it to China, I don't think is terribly controversial.

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<v Speaker 3>I mean there's a lot in the in the in

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<v Speaker 3>the in the plan though, right, there are some Trumpian

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<v Speaker 3>elements around factors like the political orientation of AI models,

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<v Speaker 3>right where they don't want them to be too woke,

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<v Speaker 3>They don't want them to be too political quote unquote right.

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<v Speaker 1>Yeah, which is one of the things which is hard,

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<v Speaker 1>Which is hard, and which is one of the things

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<v Speaker 1>that ZV does point out because I read this as well,

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<v Speaker 1>it's one of the one of the things that he

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<v Speaker 1>points out is actually probably not possible given the type

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<v Speaker 1>of language that that Trump employs, and that as a psychologist,

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<v Speaker 1>I would say is not possible given how AI is developed,

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<v Speaker 1>because there's just there's bias everywhere, and there's no such

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<v Speaker 1>thing as like this is the objective thing, and if

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<v Speaker 1>you're constantly policing quote unquote anti woke, even if that's

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<v Speaker 1>kind of the unbiased position. But you're like, oh no,

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<v Speaker 1>that's you know that, then you're going to it's problematic.

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<v Speaker 1>It's problematic in terms of how your how you go

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<v Speaker 1>about it.

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<v Speaker 3>Yeah, with with Groc or more technically, the Twitter bought Groc,

0:12:53.204 --> 0:12:57.444
<v Speaker 3>which is an instance of Elon Elon's overall modeled rock. Right,

0:12:58.844 --> 0:13:01.924
<v Speaker 3>Elon just did a couple of like subtle things. It

0:13:01.964 --> 0:13:05.124
<v Speaker 3>was like, oh, don't be too woke here, don't trust

0:13:05.164 --> 0:13:08.644
<v Speaker 3>the media too much. Right, if you read the actual

0:13:08.724 --> 0:13:11.084
<v Speaker 3>changes to the archae texture, they weren't that profound, And

0:13:11.164 --> 0:13:14.884
<v Speaker 3>yet Kroc was calling itself. I believe the term is

0:13:14.924 --> 0:13:18.844
<v Speaker 3>Mecha Hitler after some period of time engaging in elaborate

0:13:19.804 --> 0:13:23.724
<v Speaker 3>rape fantasies. I wish this were a joke, but it's not.

0:13:24.004 --> 0:13:28.004
<v Speaker 3>And like so yeah, I mean if you kind of

0:13:28.124 --> 0:13:32.444
<v Speaker 3>nudge a model to override its inputs, it's hard to

0:13:32.444 --> 0:13:35.444
<v Speaker 3>do so in a way that like has any type

0:13:35.484 --> 0:13:37.404
<v Speaker 3>of dexterity. I mean Google had this problem too, right

0:13:37.444 --> 0:13:39.844
<v Speaker 3>when they got to Gemini two years ago, a year

0:13:39.844 --> 0:13:42.844
<v Speaker 3>and a half ago, right, they were like, oh my gosh, yeah,

0:13:43.044 --> 0:13:45.164
<v Speaker 3>people are there's too many like white people, white men

0:13:45.164 --> 0:13:48.244
<v Speaker 3>in these photos, So like literally it was forced to

0:13:48.324 --> 0:13:51.284
<v Speaker 3>draw like multi racial Nazis.

0:13:51.524 --> 0:13:52.804
<v Speaker 2>It always comes down to Nazis.

0:13:52.804 --> 0:13:56.764
<v Speaker 3>And by the way, why well, in part because like

0:13:56.764 --> 0:14:00.044
<v Speaker 3>if you're kind of mining text of arguments on the

0:14:00.044 --> 0:14:06.644
<v Speaker 3>Internet and on Twitter, people invoke Nazi comparisons all the time.

0:14:06.724 --> 0:14:08.244
<v Speaker 2>Right, Who's hot Sydney Sweeney?

0:14:08.324 --> 0:14:11.804
<v Speaker 3>Right, there was some new American ego or commercial where

0:14:11.884 --> 0:14:14.964
<v Speaker 3>like she's inn am pair of gens and she talks

0:14:14.964 --> 0:14:18.164
<v Speaker 3>about how she is good genes. A little weird, right,

0:14:18.204 --> 0:14:21.924
<v Speaker 3>but like it was kind of Nazi. It was a

0:14:21.924 --> 0:14:25.364
<v Speaker 3>little weird. However, idiots on the internet were like, this

0:14:25.644 --> 0:14:29.124
<v Speaker 3>has Nazi symbolism in it, you know, not just alluding

0:14:29.124 --> 0:14:31.724
<v Speaker 3>to that saying the word Nazi. So if you're like groc,

0:14:32.284 --> 0:14:33.924
<v Speaker 3>you're like, okay, well you want like kind of the

0:14:33.964 --> 0:14:39.004
<v Speaker 3>garden variety political epitaph and calling people Nazi or Hitler,

0:14:39.484 --> 0:14:41.724
<v Speaker 3>which should be more forbidden, you would think, But that

0:14:41.804 --> 0:14:45.084
<v Speaker 3>taboo is a violated all the time. And so an

0:14:45.084 --> 0:14:48.644
<v Speaker 3>AI trained on political speech, if you go and say, yeah,

0:14:48.764 --> 0:14:51.804
<v Speaker 3>don't be so woke here, right, Well, can kind of

0:14:51.844 --> 0:14:53.804
<v Speaker 3>go into like a downward spiral election people do where

0:14:53.844 --> 0:14:56.964
<v Speaker 3>before long it's calling everybody or itself hitler.

0:14:57.764 --> 0:15:01.004
<v Speaker 1>Yeah, no, I think that that's absolutely true, and you

0:15:01.044 --> 0:15:06.284
<v Speaker 1>know it also your your point actually makes a broader

0:15:06.404 --> 0:15:10.524
<v Speaker 1>point about this AI action play, and where a lot

0:15:10.564 --> 0:15:12.604
<v Speaker 1>of the things and I did skim through it. I

0:15:12.644 --> 0:15:15.324
<v Speaker 1>didn't read the whole thing word for word. It is

0:15:15.524 --> 0:15:19.044
<v Speaker 1>small print on twenty eight pages, and I had other

0:15:19.164 --> 0:15:20.964
<v Speaker 1>things to do this week, so I just prepare for

0:15:20.964 --> 0:15:22.884
<v Speaker 1>the Heads Up Championship. So I didn't read the whole thing,

0:15:23.084 --> 0:15:25.324
<v Speaker 1>but a lot of it actually, like there are things

0:15:25.364 --> 0:15:29.044
<v Speaker 1>that sound reasonable in theory, but there's no practical way

0:15:29.124 --> 0:15:31.964
<v Speaker 1>of like how is this actually going to happen? How

0:15:31.964 --> 0:15:34.084
<v Speaker 1>do we make this happen? And so you know, I

0:15:34.084 --> 0:15:36.404
<v Speaker 1>think that this is a very concrete this like anti

0:15:36.484 --> 0:15:39.644
<v Speaker 1>woke is a very concrete example where like, okay, well,

0:15:39.724 --> 0:15:42.324
<v Speaker 1>even if in theory we're saying we want everything to

0:15:42.364 --> 0:15:45.444
<v Speaker 1>just be unbiased, let's like, let's just remove anti woke, right,

0:15:45.764 --> 0:15:49.164
<v Speaker 1>we want everything to be like as unbiased as possible.

0:15:49.324 --> 0:15:51.764
<v Speaker 1>Let's pretend that that's actually what it said, even though

0:15:51.764 --> 0:15:54.844
<v Speaker 1>it didn't. It did use the terminology anti woke, and

0:15:54.844 --> 0:15:57.604
<v Speaker 1>then there's even an anti woke executive order after it.

0:15:57.764 --> 0:16:00.284
<v Speaker 1>Let's pretend it didn't, Like, let's just pretend it was

0:16:00.524 --> 0:16:04.004
<v Speaker 1>we do not want bias. Great, I agree with that.

0:16:04.604 --> 0:16:07.004
<v Speaker 1>How do you implement it? Like, how do you actually

0:16:07.044 --> 0:16:09.324
<v Speaker 1>like do those weights? How do you It's it's base

0:16:09.484 --> 0:16:13.724
<v Speaker 1>sickly impossible. If not, like, it's a ridiculously thorny problem.

0:16:14.044 --> 0:16:17.444
<v Speaker 1>And that is just a very specific thing that you

0:16:17.484 --> 0:16:19.884
<v Speaker 1>can kind of grab onto it to realize how a

0:16:19.924 --> 0:16:23.244
<v Speaker 1>lot of these statements might sound good and like, Okay,

0:16:23.244 --> 0:16:25.324
<v Speaker 1>well this is a reasonable aim, but if you don't

0:16:25.364 --> 0:16:28.404
<v Speaker 1>actually have the implementation down and have the nitty gritty

0:16:28.404 --> 0:16:30.724
<v Speaker 1>of how to do it, it's pointless. It's just words,

0:16:30.764 --> 0:16:35.844
<v Speaker 1>it's just rhetoric. And we'll be back right after this.

0:16:48.964 --> 0:16:52.764
<v Speaker 1>There's another really interesting part of this action plan that

0:16:52.844 --> 0:16:55.644
<v Speaker 1>I think we should talk about because it was something

0:16:55.684 --> 0:16:58.564
<v Speaker 1>that the Biden and administration also struggled with, which is

0:16:59.124 --> 0:17:02.284
<v Speaker 1>what do we do in terms of proprietary versus open

0:17:02.324 --> 0:17:03.284
<v Speaker 1>source models?

0:17:03.364 --> 0:17:03.524
<v Speaker 2>Right?

0:17:03.964 --> 0:17:07.844
<v Speaker 1>Do we encourage people to kind of share all the

0:17:07.844 --> 0:17:11.004
<v Speaker 1>code so that anyone can use it and anyone can

0:17:11.044 --> 0:17:13.524
<v Speaker 1>kind of build on top of it, or is this

0:17:13.604 --> 0:17:17.444
<v Speaker 1>something that we want to kind of keep inside, kind

0:17:17.444 --> 0:17:21.444
<v Speaker 1>of keep internal. China went open source right almost immediately

0:17:21.524 --> 0:17:23.444
<v Speaker 1>with kind of deep seak all of that those are

0:17:23.524 --> 0:17:27.564
<v Speaker 1>open source models, and in the US, the Biden administration

0:17:27.604 --> 0:17:30.084
<v Speaker 1>didn't really like they just like punted on it. They

0:17:30.164 --> 0:17:33.564
<v Speaker 1>didn't they didn't have a position. And we do have both, right,

0:17:33.724 --> 0:17:36.444
<v Speaker 1>we have proprietary models, we have some open source stuff,

0:17:36.844 --> 0:17:39.804
<v Speaker 1>and there are arguments on both sides. But you had

0:17:39.844 --> 0:17:41.964
<v Speaker 1>started off by talking about p doom, which is not

0:17:42.004 --> 0:17:44.684
<v Speaker 1>something this report mentions at all, and one of the

0:17:44.804 --> 0:17:50.444
<v Speaker 1>arguments against having everything be open sources. Well, okay, great,

0:17:50.564 --> 0:17:54.924
<v Speaker 1>but then you know, rogue actors, people who don't have

0:17:54.964 --> 0:17:58.084
<v Speaker 1>the best interests of the United States in mind will

0:17:58.124 --> 0:18:00.804
<v Speaker 1>have this code as well. It's kind of the same

0:18:00.924 --> 0:18:03.924
<v Speaker 1>arguments that have been made in the past with like

0:18:03.964 --> 0:18:07.804
<v Speaker 1>when people provide the full genomic sequence of like deadly viruses,

0:18:07.884 --> 0:18:11.124
<v Speaker 1>right or things like that, are you know, instructions for

0:18:11.164 --> 0:18:14.244
<v Speaker 1>how to build kind of a bomb was step by step?

0:18:14.484 --> 0:18:18.084
<v Speaker 1>Like hey, guys, like, why are we actually making all

0:18:18.124 --> 0:18:20.524
<v Speaker 1>of this information publicly available? So that's kind of I

0:18:20.524 --> 0:18:23.524
<v Speaker 1>think the strongest case against open source. There's a lot

0:18:23.564 --> 0:18:25.324
<v Speaker 1>of pro let's let's talk about con first.

0:18:25.364 --> 0:18:27.524
<v Speaker 3>Yeah, well, look, I think part of it was there's

0:18:27.564 --> 0:18:29.404
<v Speaker 3>a period of time where I think the AI safety

0:18:29.404 --> 0:18:31.284
<v Speaker 3>folks thought that hey, maybe we could just kind of

0:18:32.364 --> 0:18:37.284
<v Speaker 3>contain it to open AI, Anthropic and Google or like

0:18:37.404 --> 0:18:39.964
<v Speaker 3>or have been like the Big three, right, and maybe

0:18:39.964 --> 0:18:42.004
<v Speaker 3>that we can avoid like a race dynamic if there's

0:18:42.004 --> 0:18:43.884
<v Speaker 3>a finite number of players and they all believe in

0:18:43.924 --> 0:18:47.484
<v Speaker 3>AI safety, right, and I think now a there's like

0:18:47.644 --> 0:18:51.804
<v Speaker 3>less belief that like open AI in particular, is that

0:18:51.884 --> 0:18:56.444
<v Speaker 3>concerned about AI safety. It's a legitmission, right, you know.

0:18:56.644 --> 0:18:59.484
<v Speaker 3>B we've seen with deep Seek the Chinese model that

0:18:59.644 --> 0:19:02.844
<v Speaker 3>like with some clever engineers, you can probably have a

0:19:02.884 --> 0:19:06.244
<v Speaker 3>model it's like only six months to a year behind

0:19:06.284 --> 0:19:10.284
<v Speaker 3>the frontier, probably not on the frontier. Sottitudes have changed

0:19:10.324 --> 0:19:13.244
<v Speaker 3>again kind of as a resignation to the inotability, I

0:19:13.244 --> 0:19:16.084
<v Speaker 3>think in part and also there is some protectionism, right,

0:19:16.164 --> 0:19:20.604
<v Speaker 3>Like Meta has championed open models. Why well, partly because

0:19:20.644 --> 0:19:24.924
<v Speaker 3>Meta's models don't suck, but they've been considered behind to

0:19:24.964 --> 0:19:28.604
<v Speaker 3>the point where they're literally offering people AI engineers, in

0:19:28.644 --> 0:19:31.324
<v Speaker 3>one case, allegedly, according to a Wired as much as

0:19:31.324 --> 0:19:33.964
<v Speaker 3>a billion dollars to join Meta so they can catch.

0:19:33.804 --> 0:19:36.044
<v Speaker 2>Up and become like a fourth part of the Big four.

0:19:36.444 --> 0:19:37.604
<v Speaker 2>I guess it would be, right.

0:19:38.204 --> 0:19:41.164
<v Speaker 3>So yeah, I mean, when it comes to election analysis

0:19:41.964 --> 0:19:44.444
<v Speaker 3>and other models. Oftentimes, I found the people in that

0:19:44.524 --> 0:19:47.204
<v Speaker 3>space who are advocating for total open source everything are

0:19:47.244 --> 0:19:50.884
<v Speaker 3>people that like A don't need the income or be their.

0:19:50.724 --> 0:19:52.484
<v Speaker 2>Models kind of suck, right. They're like, we're doing this

0:19:52.524 --> 0:19:53.164
<v Speaker 2>really good the community.

0:19:53.164 --> 0:19:54.644
<v Speaker 3>It's like, well, you're doing that because you're not gonna

0:19:54.724 --> 0:19:57.244
<v Speaker 3>it's not really good enough to sell that product for

0:19:57.324 --> 0:20:00.564
<v Speaker 3>a premium price, whereas I think mine is for example. Right, So,

0:20:00.604 --> 0:20:04.084
<v Speaker 3>like there are all types of ulterior motives. There's regulatory capture,

0:20:04.164 --> 0:20:07.284
<v Speaker 3>right of course Sam Milton might say, well, yeah, we

0:20:07.364 --> 0:20:10.004
<v Speaker 3>have to be regulated. We can't have any and pop

0:20:10.364 --> 0:20:14.764
<v Speaker 3>Shop burning an AI model, so therefore just just us three, right,

0:20:14.884 --> 0:20:18.244
<v Speaker 3>just as Google and a thropic, and therefore we capture

0:20:18.324 --> 0:20:19.924
<v Speaker 3>all the market share in perpetuity.

0:20:20.444 --> 0:20:24.444
<v Speaker 1>Yeah. So so the the incentives here are definitely not

0:20:24.724 --> 0:20:27.404
<v Speaker 1>as aligned as as one might think. And I think

0:20:27.444 --> 0:20:31.164
<v Speaker 1>you you're also kind of subtly raising another point here,

0:20:31.564 --> 0:20:35.764
<v Speaker 1>which is that in general, and stop me if you disagree,

0:20:35.804 --> 0:20:38.924
<v Speaker 1>But it seems like over the last year, I sure

0:20:38.964 --> 0:20:41.884
<v Speaker 1>like people are you know, worried about AI and like

0:20:41.924 --> 0:20:43.444
<v Speaker 1>p doom and all this, but it seems like that

0:20:43.564 --> 0:20:47.684
<v Speaker 1>discourse has actually quieted down and instead people are like, yeah,

0:20:47.724 --> 0:20:50.844
<v Speaker 1>let's let's be more competitive with China. Okay, fuck it, Like,

0:20:50.964 --> 0:20:53.524
<v Speaker 1>let's let's let's try to push to like do what

0:20:53.604 --> 0:20:56.764
<v Speaker 1>we can to like to make it really good. And

0:20:56.844 --> 0:21:00.204
<v Speaker 1>I think that people have actually just maybe it's because

0:21:00.204 --> 0:21:03.244
<v Speaker 1>they've become, you know, just more used to having AI

0:21:03.364 --> 0:21:07.124
<v Speaker 1>whatever it is. It feels like the safety concerns have

0:21:07.284 --> 0:21:14.484
<v Speaker 1>taken kind of a secondary role to capitalistic and competitive instincts.

0:21:14.764 --> 0:21:18.404
<v Speaker 3>I think there is maybe some view that, like this

0:21:18.524 --> 0:21:21.804
<v Speaker 3>year has not seen as much progress in AI timelines

0:21:21.924 --> 0:21:24.924
<v Speaker 3>as people would have thought back in January, that might

0:21:24.964 --> 0:21:27.004
<v Speaker 3>be debated. I mean, I think people are also like

0:21:28.564 --> 0:21:30.724
<v Speaker 3>a little reluctant to talk about this in the AI

0:21:30.724 --> 0:21:32.444
<v Speaker 3>safety community because they don't want to make it seem

0:21:32.564 --> 0:21:36.364
<v Speaker 3>like their guards are down right, But that's my sense,

0:21:36.444 --> 0:21:40.044
<v Speaker 3>right almost more about what's being kind of on said now. Also,

0:21:40.084 --> 0:21:41.844
<v Speaker 3>people can get bored of saying the same thing over

0:21:41.884 --> 0:21:44.284
<v Speaker 3>and over. There's a new book out very soon about

0:21:44.284 --> 0:21:46.484
<v Speaker 3>how AI is going to kill everybody if we don't

0:21:46.524 --> 0:21:49.044
<v Speaker 3>learn how to control it quickly, right from people Olosio

0:21:49.084 --> 0:21:52.844
<v Speaker 3>Yukowski and need Sours who are doomers, but very smart

0:21:52.884 --> 0:21:55.484
<v Speaker 3>people widely respect to me, we'll have one of them

0:21:55.484 --> 0:21:58.284
<v Speaker 3>on at some point. I don't know, right, but yeah,

0:21:58.364 --> 0:22:00.524
<v Speaker 3>and I think it's kind of like also maybe a

0:22:00.604 --> 0:22:04.724
<v Speaker 3>view that like, Okay, this technology is interesting and economically

0:22:05.364 --> 0:22:07.804
<v Speaker 3>powerful and kind of fun, right, so we can't talk

0:22:07.844 --> 0:22:08.764
<v Speaker 3>about the same thing all the time.

0:22:08.764 --> 0:22:10.284
<v Speaker 2>I don't know, it's my that's my impression.

0:22:10.844 --> 0:22:14.284
<v Speaker 1>Yeah, whatever, whatever the cases, whatever's going on behind the scenes.

0:22:14.524 --> 0:22:17.524
<v Speaker 1>I do feel like, well, this report, the AI report,

0:22:17.564 --> 0:22:19.924
<v Speaker 1>didn't really mention it at all, right, Like there there

0:22:20.004 --> 0:22:24.284
<v Speaker 1>was very little talk about safety or concerns, and there

0:22:24.324 --> 0:22:27.124
<v Speaker 1>was some hand waving too, like oh, you know, if

0:22:27.164 --> 0:22:31.684
<v Speaker 1>anything seems like it's you know, getting bad, we'll fix it.

0:22:32.084 --> 0:22:35.644
<v Speaker 3>But even Gavin knwso veto to bill last year called

0:22:35.764 --> 0:22:37.684
<v Speaker 3>SS Yeah, I don't know which number it was, right

0:22:38.364 --> 0:22:40.804
<v Speaker 3>that would have regulated all the AI labs in California,

0:22:40.844 --> 0:22:44.244
<v Speaker 3>since they're all currently have substantial economic nexus in California,

0:22:44.284 --> 0:22:46.084
<v Speaker 3>they would have all have been affected by it. So

0:22:46.564 --> 0:22:48.524
<v Speaker 3>I don't know, right, Maybe it's like a lot of

0:22:48.524 --> 0:22:51.444
<v Speaker 3>things where something really bad has to happen, and what

0:22:51.484 --> 0:22:53.564
<v Speaker 3>people like Aliozier are concerned about that by the time

0:22:53.644 --> 0:22:57.564
<v Speaker 3>the bad things happen, it's it's too late. Right again,

0:22:57.644 --> 0:23:02.444
<v Speaker 3>I'm I'm skeptical of the idea of like a super

0:23:02.444 --> 0:23:06.404
<v Speaker 3>intelligence explosion quote unquote. We talked in the Poker episode

0:23:06.404 --> 0:23:09.124
<v Speaker 3>a month or so ago about how like AI progress

0:23:09.124 --> 0:23:12.684
<v Speaker 3>has been patchier. It's already superhuman in some areas, it's

0:23:12.764 --> 0:23:17.604
<v Speaker 3>kind of deficient in others. Right, and as a near

0:23:17.684 --> 0:23:20.524
<v Speaker 3>daily user of these products, right, I mean, there are

0:23:20.564 --> 0:23:22.284
<v Speaker 3>times where I think it's thinking and being very smart,

0:23:22.284 --> 0:23:24.484
<v Speaker 3>in times when it can't fucking add numbers together, right,

0:23:24.724 --> 0:23:28.644
<v Speaker 3>So and so like, in some ways, the Groc thing

0:23:29.844 --> 0:23:31.844
<v Speaker 3>was scarier than like the Google thing, because like Elon

0:23:31.924 --> 0:23:36.684
<v Speaker 3>had like very restively gentle changes for the architecture produced

0:23:36.684 --> 0:23:39.684
<v Speaker 3>these profound changes where it was literally calling itself Mecha

0:23:39.724 --> 0:23:40.724
<v Speaker 3>Hitler in outputs.

0:23:40.804 --> 0:23:40.964
<v Speaker 1>Right.

0:23:41.884 --> 0:23:45.004
<v Speaker 3>At the same time that gets to the race dynamic, right,

0:23:45.044 --> 0:23:47.284
<v Speaker 3>that model had not been because you know what happens.

0:23:48.244 --> 0:23:50.284
<v Speaker 3>You program an AI, right, you train it, you give

0:23:50.324 --> 0:23:53.044
<v Speaker 3>it a system prompt, and then you test test test it, right,

0:23:54.204 --> 0:23:57.644
<v Speaker 3>and whenever it says Hitler, you say no, you're being

0:23:57.644 --> 0:23:58.204
<v Speaker 3>a bad boy.

0:23:58.284 --> 0:23:59.404
<v Speaker 2>If this is not in the context of.

0:23:59.444 --> 0:24:02.604
<v Speaker 3>World War two or something, then please don't mention Hitler

0:24:02.684 --> 0:24:05.284
<v Speaker 3>so much. Right, And you know, if you spank it

0:24:05.324 --> 0:24:07.844
<v Speaker 3>really hard. It learns to avoid that, right, But if

0:24:07.884 --> 0:24:10.244
<v Speaker 3>you're if you're just kind of I'm getting the prompt,

0:24:10.804 --> 0:24:12.924
<v Speaker 3>testing it with two of your buddies and then releasing it,

0:24:12.964 --> 0:24:15.284
<v Speaker 3>you might you might miss those. So there is fundamentally

0:24:15.324 --> 0:24:19.284
<v Speaker 3>a speed off or a trade off, speed off, a

0:24:19.324 --> 0:24:24.124
<v Speaker 3>trade off between speed and safety. Right, it's maybe not

0:24:24.164 --> 0:24:26.644
<v Speaker 3>a one for one trade off that it's probably pretty

0:24:26.884 --> 0:24:27.964
<v Speaker 3>inversely correlated.

0:24:28.364 --> 0:24:29.844
<v Speaker 1>It is it is, And by the way, in the

0:24:29.844 --> 0:24:34.444
<v Speaker 1>Grock example, I think it's also interesting that some of

0:24:34.484 --> 0:24:37.524
<v Speaker 1>the coding that was revealed said also to check what

0:24:37.524 --> 0:24:40.884
<v Speaker 1>Elon Musk thinks about this right before giving your answer.

0:24:40.964 --> 0:24:44.324
<v Speaker 1>And this was not this was not a blip, Like

0:24:44.404 --> 0:24:48.604
<v Speaker 1>multiple people replicated that this was actually in the coding.

0:24:49.004 --> 0:24:52.364
<v Speaker 1>And as you've already said, like open AI said before

0:24:52.404 --> 0:24:55.364
<v Speaker 1>that it was you know, safety first, and that's clearly

0:24:55.404 --> 0:24:57.604
<v Speaker 1>not the case, and they've shown that to not be

0:24:57.644 --> 0:24:59.724
<v Speaker 1>the case. So I think we do need to keep

0:24:59.764 --> 0:25:05.164
<v Speaker 1>asking questions about incentives, about alignment, and about kind of

0:25:05.444 --> 0:25:10.764
<v Speaker 1>who's benefiting from what type of advances in the AI community.

0:25:11.084 --> 0:25:12.684
<v Speaker 3>Yeah, I mean the as kid, I mean, it felt

0:25:12.684 --> 0:25:14.244
<v Speaker 3>to me like Grock kind of almost took on like

0:25:14.284 --> 0:25:16.724
<v Speaker 3>a personality or became like kind of a self caricature,

0:25:16.804 --> 0:25:20.004
<v Speaker 3>right where it can be recursive, right if it's like

0:25:20.524 --> 0:25:24.884
<v Speaker 3>searching output on X, including its own output. Right, I

0:25:24.964 --> 0:25:27.924
<v Speaker 3>might say, Okay, this is how Groc behaves, and like,

0:25:29.124 --> 0:25:31.004
<v Speaker 3>let me be careful about this. I mean, Groc can

0:25:31.124 --> 0:25:35.124
<v Speaker 3>kind of be in a dark way, kind of funny,

0:25:36.084 --> 0:25:40.604
<v Speaker 3>whereas the other A models are are are not right,

0:25:40.644 --> 0:25:43.884
<v Speaker 3>they're kind of goody two shoes aiming to please. Oh,

0:25:43.964 --> 0:25:46.204
<v Speaker 3>that's the most brilliant article I've ever seen, Nate. You know,

0:25:46.244 --> 0:25:48.244
<v Speaker 3>here are twenty seven typos if I give it a

0:25:48.244 --> 0:25:52.804
<v Speaker 3>copyated task, right, And this is a counter to that.

0:25:52.844 --> 0:25:54.444
<v Speaker 3>But like, all these things are tied together, right, Like

0:25:55.804 --> 0:26:00.164
<v Speaker 3>wokeness is also tied to kind of a certain type

0:26:00.204 --> 0:26:04.404
<v Speaker 3>of academic expertise, you know what I mean, which I

0:26:04.444 --> 0:26:06.724
<v Speaker 3>call the indigo blob. How Like, Yeah, the liberal media

0:26:06.804 --> 0:26:10.764
<v Speaker 3>is biased and liberal, but also it's generally more accurate

0:26:10.804 --> 0:26:13.124
<v Speaker 3>and has more expertise in the conservative media. Both those

0:26:13.164 --> 0:26:15.724
<v Speaker 3>things are true. If you crunch a bunch of data

0:26:16.484 --> 0:26:20.404
<v Speaker 3>from the Internet into vectors, then that gets hard, right,

0:26:20.484 --> 0:26:22.244
<v Speaker 3>It gets hard because you might throw the baby out

0:26:22.284 --> 0:26:23.924
<v Speaker 3>with the bath water, right that you want to like

0:26:24.724 --> 0:26:28.924
<v Speaker 3>have it reflect the expert consensus. Well, the experts have

0:26:29.124 --> 0:26:32.604
<v Speaker 3>biased it sometimes sometimes creeps into that consensus, right, And

0:26:32.684 --> 0:26:35.284
<v Speaker 3>it's very hard for again for newsrooms and journals and

0:26:35.284 --> 0:26:37.484
<v Speaker 3>constitutions to do it, but just as hard for AI models.

0:26:38.124 --> 0:26:42.564
<v Speaker 1>Yeah, And as AI models become more integrated and become

0:26:42.644 --> 0:26:44.764
<v Speaker 1>kind of more a part of the way that people

0:26:44.804 --> 0:26:48.404
<v Speaker 1>do work, and we see more outputs from AI models

0:26:48.444 --> 0:26:51.684
<v Speaker 1>and their training materials shift, like these are things that

0:26:51.724 --> 0:26:54.484
<v Speaker 1>can become even worse kind of in the future. It

0:26:54.564 --> 0:26:57.644
<v Speaker 1>is kind of this cycle that can self reinforce.

0:27:01.684 --> 0:27:03.604
<v Speaker 2>And we'll be right back after this break.

0:27:16.844 --> 0:27:19.164
<v Speaker 3>I don't want people thinking that like an AI is

0:27:19.244 --> 0:27:23.164
<v Speaker 3>like an oracular. It's not perfect entity either, right.

0:27:23.244 --> 0:27:25.524
<v Speaker 2>You know. Paul Krugman had a thing about like.

0:27:26.924 --> 0:27:28.884
<v Speaker 3>GROC a couple of weeks ago where he's like, well,

0:27:28.924 --> 0:27:31.204
<v Speaker 3>if AI has a liberal bias, because reality has a

0:27:31.244 --> 0:27:33.484
<v Speaker 3>liberal bias, right, And I'm like, well, maybe on some things,

0:27:33.564 --> 0:27:36.444
<v Speaker 3>but like you know, and he's actually pretty skeptical of AI,

0:27:36.524 --> 0:27:40.684
<v Speaker 3>Like that's not you know, look at any algorithm, and

0:27:41.724 --> 0:27:43.804
<v Speaker 3>I probably an AIL. I'm probably too complicated to describe

0:27:43.804 --> 0:27:46.284
<v Speaker 3>as an algorithm. It has like some membership behaviors, but

0:27:46.364 --> 0:27:52.524
<v Speaker 3>still directionally speaking, right, any algorithm is imperfect, you know

0:27:52.524 --> 0:27:56.764
<v Speaker 3>what I mean, to make bad predictions can reflect bad data.

0:27:57.284 --> 0:28:01.644
<v Speaker 3>And the AI is especially they're not fine tuned, which

0:28:01.644 --> 0:28:02.484
<v Speaker 3>requires human input.

0:28:02.564 --> 0:28:04.084
<v Speaker 2>Right, that's how they're fine tune. They have like a

0:28:04.084 --> 0:28:05.804
<v Speaker 2>bunch of people being like yes no, yes, no.

0:28:06.804 --> 0:28:09.244
<v Speaker 3>Then I mean I think garbage in, garbage out is

0:28:09.284 --> 0:28:10.484
<v Speaker 3>not quite the right case.

0:28:10.564 --> 0:28:15.524
<v Speaker 1>But yeah, directionally speaking, that actually that points to what

0:28:15.604 --> 0:28:19.124
<v Speaker 1>we're talking about, which is that the inputs really really

0:28:19.164 --> 0:28:21.844
<v Speaker 1>do matter. And I think the other thing is that

0:28:21.884 --> 0:28:26.204
<v Speaker 1>there is this human bias to think that, oh, well,

0:28:26.244 --> 0:28:28.804
<v Speaker 1>this is data. This is a machine, so it's more

0:28:28.924 --> 0:28:32.004
<v Speaker 1>unbiased because it's not human. And that's simply not true,

0:28:33.284 --> 0:28:36.164
<v Speaker 1>you know. And if we have that bias to say, oh, well,

0:28:36.164 --> 0:28:39.044
<v Speaker 1>this is like this is objective truth because it's coming

0:28:39.084 --> 0:28:43.564
<v Speaker 1>from a not like it's coming from a program that's

0:28:43.644 --> 0:28:46.044
<v Speaker 1>that ain't work, that ain't where it's at like that,

0:28:46.044 --> 0:28:48.684
<v Speaker 1>that is actually a highly problematic way of thinking.

0:28:48.764 --> 0:28:51.564
<v Speaker 3>Yeah, and look what it's objectives aren't clear, right, I mean,

0:28:51.604 --> 0:28:55.364
<v Speaker 3>in one sense, large language models are trying to minimize

0:28:55.364 --> 0:28:58.164
<v Speaker 3>the laws function from accurately affecting what's represent the data.

0:28:58.364 --> 0:29:02.804
<v Speaker 3>On the other hand, it's contradicted by the human feedback

0:29:02.844 --> 0:29:04.764
<v Speaker 3>that it gets, right, and so it's kind of trying

0:29:04.844 --> 0:29:09.524
<v Speaker 3>to please its creators to whatever extent it can, and

0:29:09.604 --> 0:29:11.644
<v Speaker 3>to the point of being kind of a sycophant in

0:29:11.684 --> 0:29:15.524
<v Speaker 3>some cases. So like and you know, I think people

0:29:15.644 --> 0:29:18.884
<v Speaker 3>understand more about interpreting AI outputs than they did a

0:29:18.964 --> 0:29:22.284
<v Speaker 3>year or two or three ago. But it can be fragile.

0:29:22.364 --> 0:29:29.044
<v Speaker 3>You know, small things can affect the entire system. Right,

0:29:29.084 --> 0:29:32.044
<v Speaker 3>It's it's complexity. It's a kind of origin of complexity.

0:29:32.084 --> 0:29:35.204
<v Speaker 3>Theory really is well reflected in AI. Where a butterfly

0:29:35.244 --> 0:29:38.484
<v Speaker 3>flaps its wings in Beijing, this tornado in Texas. Right,

0:29:38.804 --> 0:29:42.844
<v Speaker 3>you know, Elon puts one change the system prompt in place.

0:29:42.924 --> 0:29:43.844
<v Speaker 2>It doesn't seem to matter.

0:29:44.124 --> 0:29:46.804
<v Speaker 3>But when you put that change in and then you say, also,

0:29:47.324 --> 0:29:50.244
<v Speaker 3>please make sure you're reading what Elon would write. Right,

0:29:50.764 --> 0:29:53.564
<v Speaker 3>those things combined can have a profound effect.

0:29:53.884 --> 0:29:56.764
<v Speaker 1>And this is just something that's visible. Now, imagine all

0:29:56.804 --> 0:29:59.444
<v Speaker 1>the things that are invisible right behind the scenes, like

0:29:59.524 --> 0:30:02.924
<v Speaker 1>tiny tweaks like that that we don't see because it's

0:30:03.004 --> 0:30:07.924
<v Speaker 1>not actually visible in like your immediate LLLM output unless

0:30:07.964 --> 0:30:10.044
<v Speaker 1>you really try to kind of no, and we.

0:30:10.084 --> 0:30:11.884
<v Speaker 2>Moved away from transparency in general.

0:30:11.964 --> 0:30:14.204
<v Speaker 3>I mean not just in Google's Ai Gemini, but like

0:30:14.244 --> 0:30:17.964
<v Speaker 3>in Google Search, there's a lot of intervention, right that

0:30:18.004 --> 0:30:21.244
<v Speaker 3>if you search for occupations, just in regular Google search

0:30:21.284 --> 0:30:25.844
<v Speaker 3>for photos of like doctors, it will be very conscientious

0:30:25.884 --> 0:30:28.684
<v Speaker 3>to show I mean there might be more women doctors now.

0:30:28.684 --> 0:30:32.244
<v Speaker 3>It's like it will show like doctors of all races

0:30:32.244 --> 0:30:34.284
<v Speaker 3>and women doctors, right if you probably if you search

0:30:34.284 --> 0:30:35.924
<v Speaker 3>for hockey player, it'll make sure. I mean there are

0:30:36.004 --> 0:30:38.324
<v Speaker 3>some great black hockey players, right, but it's a lot

0:30:38.324 --> 0:30:44.444
<v Speaker 3>of white Canadian and European kids, right, And so you know, yeah,

0:30:44.484 --> 0:30:46.364
<v Speaker 3>the notion of oh, the Web's just a search, right

0:30:46.564 --> 0:30:48.124
<v Speaker 3>or large language models are just kind of a new

0:30:48.164 --> 0:30:52.084
<v Speaker 3>to presentation of a clever way to like matricize Internet

0:30:52.204 --> 0:30:53.244
<v Speaker 3>data and writing.

0:30:53.324 --> 0:30:54.564
<v Speaker 2>I mean, it's never been that.

0:30:54.884 --> 0:31:00.404
<v Speaker 3>And the consensus has moved away from transparency if anything

0:31:00.484 --> 0:31:04.724
<v Speaker 3>almost toward like, well, if we're transparent transparent, they'll just

0:31:04.804 --> 0:31:06.604
<v Speaker 3>give you more things to critique or to pick on.

0:31:06.764 --> 0:31:10.164
<v Speaker 3>And so so sorry, you know, if you like the model,

0:31:10.204 --> 0:31:12.164
<v Speaker 3>then use it. If you don't like it, then use

0:31:12.204 --> 0:31:13.044
<v Speaker 3>different model instead.

0:31:13.444 --> 0:31:15.324
<v Speaker 1>Yeah, and there is this tension here once again with

0:31:15.644 --> 0:31:17.924
<v Speaker 1>going back to what we were talking about with open source, right, Like,

0:31:17.964 --> 0:31:21.644
<v Speaker 1>there's definitely this tension between open source, and that's actually

0:31:21.684 --> 0:31:24.004
<v Speaker 1>some of the good stuff of transparency, right that you

0:31:24.044 --> 0:31:26.124
<v Speaker 1>can actually look at the inputs and actually try to

0:31:26.124 --> 0:31:28.884
<v Speaker 1>figure out what's going on, are they Like, that's one

0:31:28.884 --> 0:31:32.404
<v Speaker 1>of the benefits of having open source, transparent models that

0:31:32.444 --> 0:31:34.924
<v Speaker 1>people can kind of pick apart and play with. We've

0:31:34.924 --> 0:31:36.724
<v Speaker 1>talked about kind of the risks, you know, p doom,

0:31:36.724 --> 0:31:40.284
<v Speaker 1>et cetera, et cetera, But there are benefits, and transparency

0:31:40.324 --> 0:31:41.564
<v Speaker 1>is certainly one of them.

0:31:41.924 --> 0:31:44.684
<v Speaker 3>Yeah, they been many times when we've had models different

0:31:44.724 --> 0:31:48.044
<v Speaker 3>kinds running, right, and people are like, this seems wrong, right,

0:31:48.164 --> 0:31:50.844
<v Speaker 3>why is this pull away a certain way? And like, yeah,

0:31:51.204 --> 0:31:54.244
<v Speaker 3>eighty percent of time it's part ofsan bs, But twenty

0:31:54.244 --> 0:31:56.764
<v Speaker 3>percent of time that they've caught something for sure, right,

0:31:56.804 --> 0:32:00.844
<v Speaker 3>any for sure? Even for myself, if I have a

0:32:00.924 --> 0:32:04.844
<v Speaker 3>model making sure I output different data at different stages,

0:32:05.164 --> 0:32:09.204
<v Speaker 3>evaluate it. If you don't catch a problem early on

0:32:09.244 --> 0:32:11.244
<v Speaker 3>when you're building a complex, you know, the NFL thing

0:32:11.284 --> 0:32:13.484
<v Speaker 3>I'm working on, right, there are lots of component parts.

0:32:13.484 --> 0:32:14.484
<v Speaker 2>It will eventually be a couple of.

0:32:14.484 --> 0:32:17.844
<v Speaker 3>Thousand lines of code and then which individually are that

0:32:17.844 --> 0:32:21.484
<v Speaker 3>complicated if like, if there's one step that's wrong, it

0:32:21.484 --> 0:32:25.084
<v Speaker 3>can infect the entire system, right, And if you're smart,

0:32:25.084 --> 0:32:27.644
<v Speaker 3>you're building and robust us and redundancy. You know, every

0:32:27.644 --> 0:32:30.124
<v Speaker 3>major computer program has bugs, every model has bugs.

0:32:30.204 --> 0:32:30.364
<v Speaker 2>Right.

0:32:30.404 --> 0:32:32.884
<v Speaker 3>But like, but like outputting that and being like I

0:32:32.884 --> 0:32:34.644
<v Speaker 3>want to visualize this, I want to look at the

0:32:34.764 --> 0:32:37.124
<v Speaker 3>right inputs, right, I want to look at edge cases

0:32:37.124 --> 0:32:37.804
<v Speaker 3>that are important.

0:32:38.044 --> 0:32:39.204
<v Speaker 2>Like that's an important thing to do.

0:32:39.844 --> 0:32:43.404
<v Speaker 1>Yeah, it absolutely is. And you know, to kind of

0:32:43.444 --> 0:32:47.844
<v Speaker 1>defend open source. That's one of the big things about

0:32:48.324 --> 0:32:53.484
<v Speaker 1>data integrity. Just everywhere is open sources good? Right, So

0:32:53.524 --> 0:32:57.244
<v Speaker 1>there was huge crisis in academia with you know, with cheating,

0:32:57.404 --> 0:33:01.244
<v Speaker 1>with fabricating data, you know, with papers that were published

0:33:01.244 --> 0:33:04.964
<v Speaker 1>in important journals with big results that ended up being manipulated.

0:33:05.244 --> 0:33:07.844
<v Speaker 1>And so there's more and more of a movement toward

0:33:08.284 --> 0:33:10.204
<v Speaker 1>you know, not just pre regis during your study, but

0:33:10.204 --> 0:33:12.764
<v Speaker 1>sharing your data, right, like actually sharing the data sets

0:33:12.764 --> 0:33:15.524
<v Speaker 1>so that people can look at what the source material was.

0:33:16.004 --> 0:33:19.084
<v Speaker 1>And you know, like one of the biggest scandals that

0:33:19.124 --> 0:33:23.364
<v Speaker 1>we talked about briefly on the show with Dan Ariellie

0:33:23.764 --> 0:33:29.484
<v Speaker 1>and Francesca Gino, they you know, showed that some of

0:33:29.524 --> 0:33:33.444
<v Speaker 1>those data sets were manipulated, but that was only after

0:33:33.524 --> 0:33:36.604
<v Speaker 1>they were forced to provide the data sets, you know,

0:33:36.724 --> 0:33:40.564
<v Speaker 1>after some good some ego eide researchers were like, hey,

0:33:40.724 --> 0:33:43.804
<v Speaker 1>like these what we're seeing in the paper doesn't make sense,

0:33:44.164 --> 0:33:48.324
<v Speaker 1>and sometimes it's willful manipulation and sometimes it's just a mistake. Right.

0:33:48.364 --> 0:33:50.204
<v Speaker 1>There have been some side like there was one very

0:33:50.204 --> 0:33:54.004
<v Speaker 1>famous scientific study where they fucked up an Excel sheet

0:33:54.084 --> 0:33:57.324
<v Speaker 1>where they buy mistake like moved the rows down by one,

0:33:57.804 --> 0:34:00.444
<v Speaker 1>and that just completely. It was just it was horrific

0:34:00.484 --> 0:34:04.324
<v Speaker 1>because this is a medical study. Right, So actually tiny

0:34:04.364 --> 0:34:08.084
<v Speaker 1>things like that, it's incredibly important to have access to

0:34:08.124 --> 0:34:10.524
<v Speaker 1>the raw data, to be able to to look at this,

0:34:10.684 --> 0:34:14.964
<v Speaker 1>to manipulate it on your own. People can really spot

0:34:15.004 --> 0:34:18.804
<v Speaker 1>both malfeasance and just human error which will happen and

0:34:18.924 --> 0:34:21.924
<v Speaker 1>with AI will have both human error and computer error.

0:34:22.164 --> 0:34:25.684
<v Speaker 1>Right as we're as we're having AIS do coding for us,

0:34:25.724 --> 0:34:28.084
<v Speaker 1>you know, vibe coding all of that, there might be

0:34:28.244 --> 0:34:31.604
<v Speaker 1>errors there. We need people. We need people capable of

0:34:31.604 --> 0:34:34.004
<v Speaker 1>looking at it, debugging and trying to figure out, hey,

0:34:34.244 --> 0:34:36.804
<v Speaker 1>this seems like it's working great, but actually it's not.

0:34:37.684 --> 0:34:40.724
<v Speaker 3>Now a well designed model, including in a large language

0:34:40.724 --> 0:34:43.724
<v Speaker 3>model is kind of like a airplane, right, there are

0:34:43.764 --> 0:34:48.644
<v Speaker 3>like multiple redundant systems, there are different levels of safety

0:34:48.684 --> 0:34:50.564
<v Speaker 3>and safeguards, and like that's hard to do it. That

0:34:50.604 --> 0:34:53.244
<v Speaker 3>requires a lot of work and expensive budget and being

0:34:53.284 --> 0:34:55.084
<v Speaker 3>an actually good programmer YEP.

0:34:55.484 --> 0:34:59.084
<v Speaker 1>One of the other major things that I saw in

0:34:59.124 --> 0:35:02.924
<v Speaker 1>this action plan that I think is actually quite important,

0:35:03.004 --> 0:35:06.084
<v Speaker 1>and again there are arguments on both sides, is like

0:35:06.284 --> 0:35:10.164
<v Speaker 1>one of the big bottlenecks to AI development is energy, right,

0:35:10.204 --> 0:35:14.324
<v Speaker 1>because AI just like takes a lot a huge energy

0:35:14.364 --> 0:35:17.804
<v Speaker 1>cost and access to data centers. Like that's that's actually

0:35:17.804 --> 0:35:21.244
<v Speaker 1>been a big thing where data centers like can't you know,

0:35:21.484 --> 0:35:25.004
<v Speaker 1>they've tried to bypass the power grids. There's been you know, pushback,

0:35:25.044 --> 0:35:27.044
<v Speaker 1>et cetera, et cetera. So one of the things that

0:35:27.124 --> 0:35:30.284
<v Speaker 1>this plan tries to do is say, let's eliminate all

0:35:30.324 --> 0:35:33.244
<v Speaker 1>the barriers and let's try to use all the energy

0:35:33.244 --> 0:35:35.644
<v Speaker 1>we have available for AI. Yeah.

0:35:35.844 --> 0:35:38.364
<v Speaker 3>I mean, look, I think it's just like a little overclaim, right.

0:35:38.404 --> 0:35:42.444
<v Speaker 3>If you look at like the amount of actual wattage

0:35:42.444 --> 0:35:45.364
<v Speaker 3>required to like run a chat reipete response, it's like

0:35:45.404 --> 0:35:48.164
<v Speaker 3>this is kind of like a I don't know, it's

0:35:48.164 --> 0:35:51.284
<v Speaker 3>a fairly bullshitty claim based on the present capabilities of AI.

0:35:52.444 --> 0:35:54.484
<v Speaker 1>So Nate, let me just push back a little bit

0:35:54.604 --> 0:35:57.284
<v Speaker 1>because there's a related issue, which is the availability of

0:35:57.324 --> 0:36:00.764
<v Speaker 1>water to cool these data centers. And we have already

0:36:00.804 --> 0:36:03.404
<v Speaker 1>seen that there has been you know, there have been

0:36:03.484 --> 0:36:07.684
<v Speaker 1>instances of wells town wells running dry. There's been instances

0:36:07.804 --> 0:36:12.204
<v Speaker 1>of construction having to be because the water, because of

0:36:12.204 --> 0:36:14.844
<v Speaker 1>basically water shortage issues. So I think that that's a

0:36:14.884 --> 0:36:17.684
<v Speaker 1>related concern that we should have just dispised.

0:36:17.564 --> 0:36:19.684
<v Speaker 2>Getting from low Ki Maria.

0:36:20.924 --> 0:36:23.604
<v Speaker 1>Maybe maybe Grock, What do you have to say about this?

0:36:23.844 --> 0:36:28.244
<v Speaker 3>Yeah, I would, I would, I would be I'm skeptical.

0:36:27.764 --> 0:36:29.124
<v Speaker 1>Of I think it is a big I think it

0:36:29.204 --> 0:36:29.804
<v Speaker 1>is a big deal.

0:36:30.124 --> 0:36:33.684
<v Speaker 3>It's not relative to other uses of electricity though it's

0:36:33.684 --> 0:36:36.564
<v Speaker 3>a small piece of the pie. And granted Sam Altman

0:36:36.644 --> 0:36:38.084
<v Speaker 3>at all want to be bigger.

0:36:38.004 --> 0:36:39.124
<v Speaker 2>Right.

0:36:40.364 --> 0:36:42.564
<v Speaker 1>Yeah, And I you know, it's hard for me. I

0:36:42.604 --> 0:36:44.964
<v Speaker 1>don't have the numbers in front of me, so I'm

0:36:44.964 --> 0:36:47.644
<v Speaker 1>not going to say something and have it not be true.

0:36:47.684 --> 0:36:50.564
<v Speaker 1>So so I'm just I'm not gonna engage that point

0:36:50.604 --> 0:36:54.564
<v Speaker 1>because I just honestly don't know. However, it is something

0:36:55.084 --> 0:36:58.444
<v Speaker 1>that this bill is trying to address and trying to

0:36:58.444 --> 0:37:02.524
<v Speaker 1>give AI companies whatever resources it needs to access power grids,

0:37:02.564 --> 0:37:06.644
<v Speaker 1>access energy grids, so that data centers can be built

0:37:06.644 --> 0:37:10.964
<v Speaker 1>on federal land and kind of allow innovation to proceed

0:37:11.364 --> 0:37:14.124
<v Speaker 1>without there being an energy bottleneck. I think that that's

0:37:14.244 --> 0:37:17.924
<v Speaker 1>kind of objectively what this bill is trying to accomplish.

0:37:18.164 --> 0:37:21.804
<v Speaker 3>Yeah, look, I mean, by the standards of Trump, it's

0:37:21.804 --> 0:37:26.684
<v Speaker 3>a pretty serious document. The one good thing about their

0:37:26.724 --> 0:37:28.684
<v Speaker 3>alliance may not the only good thing right with the

0:37:28.764 --> 0:37:30.644
<v Speaker 3>kind of tech right is that they do I think

0:37:30.684 --> 0:37:34.484
<v Speaker 3>have like Capetan people in place. You might have different

0:37:34.484 --> 0:37:39.164
<v Speaker 3>position on AI, but like, this isn't an amateurish documents.

0:37:39.284 --> 0:37:42.644
<v Speaker 3>It's thoughtful. It involves politics, but like there was some

0:37:42.684 --> 0:37:45.724
<v Speaker 3>care put into this. Yeah, for sure, for sure, very

0:37:45.764 --> 0:37:47.324
<v Speaker 3>unlike Trump in most ways.

0:37:47.484 --> 0:37:51.084
<v Speaker 1>I agree. I agree reading it, you know, obviously you

0:37:51.084 --> 0:37:52.924
<v Speaker 1>can see the Trump and language and parts of it,

0:37:53.244 --> 0:37:56.644
<v Speaker 1>but there there are nuanced points here where it will

0:37:56.684 --> 0:37:59.644
<v Speaker 1>be interesting to see how, if at all, any of

0:37:59.684 --> 0:38:03.124
<v Speaker 1>this is enforced and kind of what ends up happening.

0:38:03.124 --> 0:38:05.564
<v Speaker 1>I think we'll just have to see over the next

0:38:05.684 --> 0:38:09.204
<v Speaker 1>six months, one year and see how a lot of

0:38:09.244 --> 0:38:11.244
<v Speaker 1>these provisions shakeout. By the way, there are a lot

0:38:11.284 --> 0:38:14.084
<v Speaker 1>more provisions. We're not going to talk about the whole thing. Nate,

0:38:14.124 --> 0:38:17.004
<v Speaker 1>as you said, V has a good substock on this,

0:38:17.164 --> 0:38:19.364
<v Speaker 1>so for people who want to know more, I think

0:38:19.484 --> 0:38:22.764
<v Speaker 1>we'd both encourage you to read that. But yeah, all

0:38:22.764 --> 0:38:26.844
<v Speaker 1>in all, you know some things where you're like, okay, yeah,

0:38:26.924 --> 0:38:29.364
<v Speaker 1>this makes out some things that are a little you know,

0:38:29.884 --> 0:38:36.964
<v Speaker 1>eyebrow raising, not enough care shown to or not care

0:38:37.044 --> 0:38:40.284
<v Speaker 1>that's the wrong word. But I think we're seeing speed

0:38:40.804 --> 0:38:44.084
<v Speaker 1>over safety in a lot of this, and how do

0:38:44.124 --> 0:38:46.684
<v Speaker 1>we facilitate speed instead of safety? So I think that that,

0:38:47.044 --> 0:38:48.724
<v Speaker 1>to me is the big thing to kind of watch

0:38:48.724 --> 0:38:56.324
<v Speaker 1>out for and to keep an eye on. Thanks for listening.

0:38:56.564 --> 0:38:58.804
<v Speaker 1>We're taking next week off and we'll be back in

0:38:58.844 --> 0:39:02.684
<v Speaker 1>your feeds on August fourteenth. As always, we have some

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<v Speaker 1>additional content for premium subscribers who also get ad free

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<v Speaker 1>listening across Pushkin's entire network of shows. This week, we're

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<v Speaker 1>answering a listener question about how to teach poker to kids.

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<v Speaker 1>That's coming up after the credits, So you still have time.

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<v Speaker 1>Subscribe now for just six ninety nine a month. Let

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<v Speaker 1>us know what you think. Of the show reach out

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<v Speaker 1>to Us at Risky Business at Pushkin dot Fm. Risky

0:39:29.444 --> 0:39:32.164
<v Speaker 1>Business is hosted by me Maria Kanikova.

0:39:31.724 --> 0:39:34.084
<v Speaker 3>And by me Nate Silver. The show is a co

0:39:34.164 --> 0:39:38.324
<v Speaker 3>production of Pushkin Industries and iHeartMedia. This episode was produced

0:39:38.324 --> 0:39:42.084
<v Speaker 3>by Isabel Carter. Our associate producer is Sonia Gerwin. Sally

0:39:42.124 --> 0:39:45.164
<v Speaker 3>Helm is our editor, and our executive producer is Jacob Goldstein.

0:39:45.684 --> 0:39:46.844
<v Speaker 2>Mixing by Sarah Bruger.

0:39:47.084 --> 0:39:48.244
<v Speaker 1>Thanks so much for tuning in.