WEBVTT - Should You Learn Poker from ChatGPT? And Other AI Questions

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<v Speaker 1>Pushkin. Welcome back to Risky Business, our show about making

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<v Speaker 1>better decisions. I'm Maria Kanikova.

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<v Speaker 2>And I'm Nate Silver.

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<v Speaker 1>Today on the show, we're going to be getting into

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<v Speaker 1>it on AI. There has been a lot of news

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<v Speaker 1>on the AI front in the last few weeks, some

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<v Speaker 1>of it coming from the Trump administration and some coming

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<v Speaker 1>from overseas with China and Deep Seek.

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<v Speaker 2>Maria thinks AI is overrated. I think AI is properly rated,

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<v Speaker 2>as you'll see.

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<v Speaker 1>And then we're going to get into a listener question

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<v Speaker 1>about poker and how to beat your local cash can.

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<v Speaker 2>Let's start with our friend artificial intelligence.

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<v Speaker 1>Yeah, so I think we're talking about a few different things, right,

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<v Speaker 1>So we have the Trump initiative on AI. So we

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<v Speaker 1>have a few things that he did, including things that

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<v Speaker 1>he took away, right the executive Order that took away

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<v Speaker 1>certain restrictions on AI that had been put in place

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<v Speaker 1>by Biden. But then also we have you know, this

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<v Speaker 1>big funding initiative into AA by the US government, Stargate,

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<v Speaker 1>and then we also have AI coming out of China

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<v Speaker 1>Deep Seek, which has freaked everyone the fuck out. I

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<v Speaker 1>think that's the scientific way of putting it and has

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<v Speaker 1>made markets, crash video stocks, a lot of other stocks Nasdaq.

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<v Speaker 1>You know, people have not been happy to see the

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<v Speaker 1>success of deep Seek, So there's a lot to talk

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<v Speaker 1>about today.

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<v Speaker 2>Where do you want to start, Maria.

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<v Speaker 1>Well, do we want to start with? I think if

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<v Speaker 1>it makes sense to start with deep seek because it actually,

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<v Speaker 1>you know, I think that the two are very related,

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<v Speaker 1>right because we have what the US government is and

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<v Speaker 1>is not doing, and one of the reasons that right

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<v Speaker 1>now things are freaking out is because of deep Seek.

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<v Speaker 1>So I think we can start with that, see what

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<v Speaker 1>the implications are, what the responses can be, and then

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<v Speaker 1>kind of see what the US has done so far

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<v Speaker 1>to see if it's in line with what we think

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<v Speaker 1>the correct strategy should be. Yeah.

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<v Speaker 2>Look, until about a week and a half ago, when

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<v Speaker 2>people started to notice Deep Seek their model are one.

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<v Speaker 2>In particular, the conventional wisdom was that, like America is

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<v Speaker 2>way ahead in the AI race. I should say with

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<v Speaker 2>respect to large language models, machine learning transformers, right, you know,

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<v Speaker 2>driverless cars is a different enterprise, and drones and things

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<v Speaker 2>like that. But in terms some LM's large language models

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<v Speaker 2>chatcypt like things. Then you know, us probably one, two, three,

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<v Speaker 2>four in the rankings and so this, Yeah, this has

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<v Speaker 2>interesting geopolitical implications. Yeah.

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<v Speaker 1>And the one of the reasons, just to step back,

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<v Speaker 1>that the US was assumed to be ahead was because

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<v Speaker 1>the United States had made it more difficult for foreign

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<v Speaker 1>governments to acquire like China, especially to acquire the chips

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<v Speaker 1>that are necessary to build these large AI models, the resources,

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<v Speaker 1>et cetera, et cetera. And so one of the disconcerting

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<v Speaker 1>things to the United States was that when Deepseak announced

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<v Speaker 1>as results, it also announced that it basically was able

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<v Speaker 1>to do this at one tenth of the cost and

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<v Speaker 1>resources that other models had used. So this was like

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<v Speaker 1>an oh shit, you know, even if we restrict access

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<v Speaker 1>to all of these other things, they're still able to

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<v Speaker 1>do this. Now, I will say, and other people have

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<v Speaker 1>pointed this out, I don't actually know how much we

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<v Speaker 1>can trust the numbers and figures, right, this is just

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<v Speaker 1>a claim. We don't know what the training materials were,

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<v Speaker 1>we don't know what the development costs actually were. We

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<v Speaker 1>just know what they claim that they were. So I

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<v Speaker 1>think that this is something that we should put an

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<v Speaker 1>asterisks next to because it is important to realize, right

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<v Speaker 1>that if you can't if you can't actually brace the

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<v Speaker 1>information and verify it, and you have to take it

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<v Speaker 1>on faith. That's never a good way to take information. Right,

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<v Speaker 1>That's one of the things we say over and over

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<v Speaker 1>on risky business when you make decisions, try not to

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<v Speaker 1>take things on faith. Try to verify, right, That's that's

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<v Speaker 1>much better. Yeah.

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<v Speaker 2>So this is basically built by a Chinese hedge fund, right,

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<v Speaker 2>which is well which is well capitalized. And you know,

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<v Speaker 2>there are a lot of smart computer engineers in China,

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<v Speaker 2>and I think they were all working on this project.

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<v Speaker 2>So so kind of the last step of training. I mean,

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<v Speaker 2>it's it's a little bit like you know Rosie who

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<v Speaker 2>Rosie Ruiz?

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<v Speaker 3>I do know who Rosie is is?

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<v Speaker 2>Yeah, if you've covered like fraudsters, right, And I don't

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<v Speaker 2>mean to say it's a fraud, but it's like, so

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<v Speaker 2>she runs what was the New York Marathon? Right, who?

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<v Speaker 2>Like it was a fraud.

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<v Speaker 1>By the way, So Rosie Ruiz actually figures in my

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<v Speaker 1>next book on cheating. So Rosie Ruiz one quote unquote

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<v Speaker 1>I'm putting this in quotes. The Boston Marathon women's time

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<v Speaker 1>with this incredible story was amazing, wonderful. You know, people

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<v Speaker 1>loved it, and then it turned out that she took

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<v Speaker 1>the subway for a huge portion of the race, and

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<v Speaker 1>but she almost got away with it, which is the

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<v Speaker 1>really fucked up thing. The reason she got caught was

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<v Speaker 1>because the subway car that she happened to get on

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<v Speaker 1>had a reporter who was a photographer who had been

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<v Speaker 1>covering the marat on and was like, wait, what's going on.

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<v Speaker 1>So it actually took them multiple days to figure out

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<v Speaker 1>that Rosy Ruiz did not actually win, did not actually

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<v Speaker 1>run the time that she shran. By the way, this

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<v Speaker 1>was back in nineteen eighty so right the technology was different.

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<v Speaker 1>People were not getting tracked as closely as they are

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<v Speaker 1>right now.

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<v Speaker 3>But spoiler alert for.

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<v Speaker 1>You know, or big fun thing that I get into

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<v Speaker 1>in my book, it's possible even today to pull a

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<v Speaker 1>Rosie release.

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<v Speaker 3>So that's for later. But Nate, why are we talking

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<v Speaker 3>about Rosie.

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<v Speaker 2>Because it's a little bit like if I don't say

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<v Speaker 2>there's any actual fraud, I really don't trust anything coming

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<v Speaker 2>out of mainland China. Yeah, but like but yeah, so

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<v Speaker 2>it's a little bit like if you run and around

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<v Speaker 2>the twenty fourth mile and then run two really good

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<v Speaker 2>closing miles, it's still not the same, and it's like

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<v Speaker 2>not like an accurate representation to say that just the

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<v Speaker 2>cost of this training run when you have all these

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<v Speaker 2>resources behind it, and it's kind of like the last step.

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<v Speaker 2>But clearly it's more efficient in terms of you know,

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<v Speaker 2>when you run a request, put in a query, how

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<v Speaker 2>many computer cycles is a burning through? I'm using very

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<v Speaker 2>nigh technical language here, right, You can actually host deep seek.

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<v Speaker 2>You keep going to call deep stack. There are a

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<v Speaker 2>lot of deep stack poker terms. You can host deep

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<v Speaker 2>seek at on a desktop. Right. If you want to

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<v Speaker 2>actually have it say things about Tanaman Square, for example,

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<v Speaker 2>then you need to run your native instance because the

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<v Speaker 2>official Chinese hosted web version doesn't like to you know,

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<v Speaker 2>doesn't like to talk about certain things.

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<v Speaker 1>I would say, Maria, you don't say that, you don't

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<v Speaker 1>say so.

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<v Speaker 2>Then there are a lot of debates though about what's

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<v Speaker 2>it mean if it turns out that I mean so.

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<v Speaker 2>One category to bat is like does the US lead

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<v Speaker 2>lose its lead versus China. That's one kind of whole bucket, right.

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<v Speaker 2>Another bucket is like, what's it mean if you now,

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<v Speaker 2>like run an AI lab on a desktop and they're

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<v Speaker 2>only going to get faster how do we regulate this?

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<v Speaker 2>And then there's a whole bunch of economic stuff about,

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<v Speaker 2>like you know, what's this mean for the price of

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<v Speaker 2>different assets?

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<v Speaker 1>Right?

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<v Speaker 2>So Nvidiah, for example, is the largest manufacturer of semiconductor,

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<v Speaker 2>is a Taiwanese company, you know, so if compute is cheaper,

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<v Speaker 2>is that good for them or bad for them? It's

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<v Speaker 2>not necessarily straightforward.

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<v Speaker 1>Right, Yeah, it's absolutely not straightforward. And also, you know,

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<v Speaker 1>one of the one of the other potential things that

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<v Speaker 1>happened with deep seek we don't know is a process

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<v Speaker 1>of training known as distillations. So that's a slightly more

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<v Speaker 1>technical term, but what it actually means is that you

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<v Speaker 1>are training your model on the outputs of other models, right,

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<v Speaker 1>so you can actually pass the benchmarks and be able

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<v Speaker 1>to trade up more quickly because you are using Okay, so.

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<v Speaker 2>Maybe now we are having more of a Rosie Ruize situation.

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<v Speaker 1>And if that happens, then then it is more of

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<v Speaker 1>a Rosie Rueze situation and just as a like as

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<v Speaker 1>a flag, that's not legal, right, Technically, you're not supposed

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<v Speaker 1>to do that. But if you do do it and

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<v Speaker 1>you're able to then cover.

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<v Speaker 2>These outputs, the respect for intellectual property varies by countries.

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<v Speaker 2>I don't want to be I don't want to bad

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<v Speaker 2>mouth the culture for not respecting electric property rights. But yeah,

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<v Speaker 2>if you're if you're you know, if you can just

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<v Speaker 2>copy off chat, GPT or in for what its weights are,

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<v Speaker 2>then that you know, I mean, that's that's a that's

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<v Speaker 2>an issue.

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<v Speaker 1>Yeah, it absolutely is. But let's let's flip that actually

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<v Speaker 1>around a little bit to talk about some of the

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<v Speaker 1>potential positives of this, which you know there we're obviously

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<v Speaker 1>seeing you know, potential uh red flags and negatives.

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<v Speaker 3>But what about I mean.

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<v Speaker 1>I actually think that it's not a bad thing that

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<v Speaker 1>deep seek is open source, right, so people can try

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<v Speaker 1>to figure out, Okay, what is it actually doing, how

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<v Speaker 1>is it actually doing?

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<v Speaker 3>It? Isn't that? Isn't that good?

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<v Speaker 1>And I know that, and I know that one of

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<v Speaker 1>the things that you know that people don't often like

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<v Speaker 1>is open source. But there's like open source can go

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<v Speaker 1>either way, right, open source bad if it's US and

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<v Speaker 1>China's getting its secrets, but you know, open source good

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<v Speaker 1>in other respects. And I think open source is one

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<v Speaker 1>of the few ways that we can actually peek inside

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<v Speaker 1>the black box. And I would be much more concerned

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<v Speaker 1>if it wasn't even open source, right, if we had

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<v Speaker 1>no idea how it was trained, if we didn't know

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<v Speaker 1>about the funding, if we didn't know it of this

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<v Speaker 1>and it was an open source right, if all of

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<v Speaker 1>those things were compelled, I'd be more worried. Since it

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<v Speaker 1>is open source, I actually think that could potentially be

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<v Speaker 1>a good thing in terms of knowledge sharing and trying

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<v Speaker 1>to figure out how do we make these processes more efficient?

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<v Speaker 1>And Meta has actually created a workforce that is studying

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<v Speaker 1>the deep sea processes and figuring out, okay, how can

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<v Speaker 1>we use these and do we want to change the

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<v Speaker 1>way that we're developing some of our llms, some of

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<v Speaker 1>our chat you know, models to mimic their processes so

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<v Speaker 1>that we become more efficient. And if this process actually

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<v Speaker 1>means that we use fewer resources, that's obviously a net

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<v Speaker 1>positive for the environment. However, if it means proliferation of

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<v Speaker 1>ais everywhere and it's cheaper than could actually be a

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<v Speaker 1>net negative. Which is all to say that this is

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<v Speaker 1>really complicated. This is not black and white, and when

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<v Speaker 1>you're making these sources of decisions, you have to assign

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<v Speaker 1>weights to all of these different outcomes, all of these

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<v Speaker 1>different probabilities, and frankly, I don't have the I don't

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<v Speaker 1>think anyone has the expertise to do that because it's

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<v Speaker 1>such a new world. I certainly don't have the expertise,

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<v Speaker 1>but I don't think anyone can see the future clearly

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<v Speaker 1>enough to figure out, you know, how do we wait this?

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<v Speaker 1>Because there's a lot of uncertainty around this.

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<v Speaker 2>So the hardcore AI concern people, the doomers, tend to

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<v Speaker 2>be anti open source. Open AI was founded as open AI,

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<v Speaker 2>but no longer kind of abides by that mission, and

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<v Speaker 2>I think so I think their view. Let me try

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<v Speaker 2>to give you the summary slash kind of Steelman version

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<v Speaker 2>of it. Right, these think, okay, this period where AI

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<v Speaker 2>is being birth, where artificial general intelligence ranging up to

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<v Speaker 2>artificial superintelligence. The first means it can do most things

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<v Speaker 2>at a human level or human life well plus right,

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<v Speaker 2>and super intelligence means it achieves breakthroughs that no human

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<v Speaker 2>can across the broad range of fields. Basically, right, it

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<v Speaker 2>thinks this process of giving birth to these models is

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<v Speaker 2>going to be very dangerous, and therefore you want to

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<v Speaker 2>have it in the hands of as few people as

0:12:26.324 --> 0:12:29.644
<v Speaker 2>possible and trusted people as possible. I think at one

0:12:29.644 --> 0:12:32.724
<v Speaker 2>point Sam Malton was trusted by this community. You know,

0:12:32.804 --> 0:12:36.324
<v Speaker 2>Anthropic is a bunch of people who left open AI

0:12:36.444 --> 0:12:38.364
<v Speaker 2>because they thought open a I was moving too fast.

0:12:38.444 --> 0:12:42.844
<v Speaker 2>Right and then and then Google Gemini. You know, Google

0:12:42.844 --> 0:12:47.084
<v Speaker 2>again had been fairly conservative about how it moved on AI.

0:12:47.284 --> 0:12:49.444
<v Speaker 2>Didn't want to you know, it's a huge enterprise, doesn't

0:12:49.444 --> 0:12:51.244
<v Speaker 2>want to risk that and other things and kind of

0:12:51.444 --> 0:12:56.164
<v Speaker 2>a different culture I would say at Google, then Facebook

0:12:56.204 --> 0:13:00.684
<v Speaker 2>or Meta, the reason why their models were open source

0:13:00.844 --> 0:13:04.324
<v Speaker 2>is because, like they weren't competitive. This is what people

0:13:04.364 --> 0:13:07.004
<v Speaker 2>would say in the AIXPEC community, right, is because they

0:13:07.044 --> 0:13:11.124
<v Speaker 2>weren't as good as these, you know, clearly as Anthropic

0:13:11.124 --> 0:13:13.484
<v Speaker 2>which has clawed, or open ai or clearly the two

0:13:13.524 --> 0:13:16.964
<v Speaker 2>leading ones. And then and then you know, Google Gemini

0:13:17.084 --> 0:13:20.404
<v Speaker 2>had some problem with like drawing like woke Nazis and

0:13:20.404 --> 0:13:23.364
<v Speaker 2>stuff like that, which I you know, I think it's

0:13:23.404 --> 0:13:25.804
<v Speaker 2>not as good as the other two by a fair bit.

0:13:25.844 --> 0:13:27.524
<v Speaker 2>But like, but that was that was considered in the

0:13:27.524 --> 0:13:31.484
<v Speaker 2>pecking order, right that Microsoft was excuse me, that Meta

0:13:31.844 --> 0:13:35.244
<v Speaker 2>too many m's was fourth, and therefore they open source

0:13:35.284 --> 0:13:37.124
<v Speaker 2>it to kind of say, okay, well we're gonna like

0:13:37.444 --> 0:13:41.684
<v Speaker 2>in some sense it's it's uh, not quite like sabotage.

0:13:42.124 --> 0:13:43.564
<v Speaker 2>You're like, well, fuck you, You're not going to get

0:13:43.564 --> 0:13:46.484
<v Speaker 2>these same returns to us, and will have applications people

0:13:46.484 --> 0:13:48.404
<v Speaker 2>who want to pay for it for free or whatever. Right,

0:13:49.364 --> 0:13:52.524
<v Speaker 2>So the fact that it's open source is interesting. I mean,

0:13:52.524 --> 0:13:58.324
<v Speaker 2>you know, China clearly is willing to do things, uh

0:13:58.724 --> 0:14:05.004
<v Speaker 2>to undermine the American even if so. I mean, the

0:14:05.004 --> 0:14:07.764
<v Speaker 2>other big one in the news is of course TikTok,

0:14:07.764 --> 0:14:10.444
<v Speaker 2>which is owned by bike Dance. Right, the US Congress

0:14:10.444 --> 0:14:13.004
<v Speaker 2>passes a law upheld by the courts. It says you

0:14:13.084 --> 0:14:17.564
<v Speaker 2>have to sell to an American company or at least

0:14:17.644 --> 0:14:19.404
<v Speaker 2>a country not listed on like the in there's like

0:14:19.404 --> 0:14:22.204
<v Speaker 2>literally like an enemy's list of countries, and China is

0:14:22.284 --> 0:14:27.644
<v Speaker 2>on it, right, And bike Dan says, we have this

0:14:27.684 --> 0:14:29.604
<v Speaker 2>really valuable enterprise, but we'll just turn it off, right,

0:14:29.684 --> 0:14:32.284
<v Speaker 2>If you make us sell it, then we'll just turn off. Well, clearly,

0:14:32.324 --> 0:14:34.284
<v Speaker 2>I mean obviously it would be a forced sale and

0:14:34.324 --> 0:14:36.644
<v Speaker 2>you wouldn't have quite the market clearing price, but like

0:14:36.924 --> 0:14:39.124
<v Speaker 2>you know, the value is a lot more than zero,

0:14:39.284 --> 0:14:41.004
<v Speaker 2>and they're willing to So you know, there's a little

0:14:41.004 --> 0:14:43.524
<v Speaker 2>bit of suspicion that like this is just meant to

0:14:43.724 --> 0:14:47.964
<v Speaker 2>like undermine America's lead in AI and not make a

0:14:47.964 --> 0:14:50.124
<v Speaker 2>whole lot of profit for China. That's kind of like

0:14:50.164 --> 0:14:53.204
<v Speaker 2>addition by subtraction, right, you know, And people say, hey,

0:14:53.204 --> 0:14:56.364
<v Speaker 2>these people are idealistic. It's not the same capitalist system there.

0:14:56.404 --> 0:15:00.564
<v Speaker 2>And even in the US sometimes the founder aren't that greedy.

0:15:00.564 --> 0:15:02.204
<v Speaker 2>They just want to make a really cool product. So

0:15:02.644 --> 0:15:04.444
<v Speaker 2>there might be some of that too, But it's in

0:15:04.484 --> 0:15:07.724
<v Speaker 2>line with previous Chinese strategy, I suppose.

0:15:08.484 --> 0:15:11.404
<v Speaker 1>Yeah, it's actually interesting that you that you mentioned TikTok

0:15:11.444 --> 0:15:14.804
<v Speaker 1>because this is another kind of strategic element of this

0:15:15.084 --> 0:15:19.964
<v Speaker 1>that you know, we're we being the US has moved

0:15:20.004 --> 0:15:21.204
<v Speaker 1>to band TikTok right now?

0:15:23.044 --> 0:15:26.764
<v Speaker 2>Sorry, what USA?

0:15:27.204 --> 0:15:33.644
<v Speaker 3>You are mooting for the US? Nice and nice? All right?

0:15:33.764 --> 0:15:38.804
<v Speaker 1>Tem U s I is uh was moving to band TikTok.

0:15:38.844 --> 0:15:40.404
<v Speaker 1>We have no idea what's going to happen with that now.

0:15:40.604 --> 0:15:43.444
<v Speaker 1>But in some ways, you know, and deep seek is

0:15:43.564 --> 0:15:46.724
<v Speaker 1>just like la la la la la. Right, There's there's

0:15:46.764 --> 0:15:49.844
<v Speaker 1>no movement in that direction, and instead Trump is talking

0:15:49.884 --> 0:15:53.644
<v Speaker 1>about tariffs and other things and and trying to kind

0:15:53.644 --> 0:15:55.364
<v Speaker 1>of get at it that way. And I think that

0:15:55.444 --> 0:15:58.084
<v Speaker 1>it's a very interesting dichotomy where like, if you're worried

0:15:58.084 --> 0:16:01.044
<v Speaker 1>about TikTok, like, shouldn't you be worried about the strategic

0:16:01.404 --> 0:16:05.044
<v Speaker 1>and security risks of you know, of a company that

0:16:06.084 --> 0:16:08.844
<v Speaker 1>runs you know that all of the idol Ai models

0:16:08.884 --> 0:16:12.044
<v Speaker 1>are run into right, Like that's Chinese owned, Chinese developed,

0:16:12.324 --> 0:16:15.524
<v Speaker 1>Like do you if you're going to be consistent like that?

0:16:15.524 --> 0:16:17.724
<v Speaker 1>That seems to be a much greater risk than TikTok

0:16:17.804 --> 0:16:18.764
<v Speaker 1>to be perfectly honest.

0:16:21.644 --> 0:16:23.524
<v Speaker 2>And we'll be right back after this break.

0:16:33.204 --> 0:16:36.844
<v Speaker 1>So what do we, like, what can we take from

0:16:36.884 --> 0:16:39.644
<v Speaker 1>this and from what's happened in the last week. How

0:16:39.684 --> 0:16:45.364
<v Speaker 1>does that mesh with the types of endeavors that that

0:16:46.284 --> 0:16:50.004
<v Speaker 1>Trump and team have already put forward. Now, one of

0:16:50.044 --> 0:16:52.404
<v Speaker 1>the things, so I started off by saying that they've

0:16:52.444 --> 0:16:56.844
<v Speaker 1>rescented the executive order. The executive order that Biden had

0:16:57.284 --> 0:16:59.884
<v Speaker 1>on Ai did have to do with open source, right,

0:17:00.164 --> 0:17:03.124
<v Speaker 1>and it did have to say it was actually very

0:17:03.124 --> 0:17:06.724
<v Speaker 1>skeptical of open source as well, because it wanted, you know,

0:17:07.444 --> 0:17:10.564
<v Speaker 1>full reporting, knowing everything that was going on, but let's

0:17:10.644 --> 0:17:15.444
<v Speaker 1>keep that information from foreign governments. Now that's out right,

0:17:15.844 --> 0:17:19.204
<v Speaker 1>So that's been rescinded. So what's and that's one of

0:17:19.204 --> 0:17:21.524
<v Speaker 1>the main issues that we're seeing with deep seek. So

0:17:21.844 --> 0:17:23.404
<v Speaker 1>so what do we think about that? What do we

0:17:23.404 --> 0:17:27.404
<v Speaker 1>think about the government approach? Is it misguided or is

0:17:27.444 --> 0:17:29.684
<v Speaker 1>it on the right track? And if we want to

0:17:29.844 --> 0:17:33.844
<v Speaker 1>I think all of us, no matter if you're AAAI ORNAI,

0:17:34.204 --> 0:17:36.564
<v Speaker 1>I think everyone wants to minimize pe doom, like I

0:17:36.564 --> 0:17:39.724
<v Speaker 1>would hope that no one wants the world to be destroyed.

0:17:40.804 --> 0:17:44.244
<v Speaker 2>So I don't think anybody thought that like this Biden

0:17:44.324 --> 0:17:48.684
<v Speaker 2>executive order is going to stop pe doom by itself.

0:17:48.804 --> 0:17:51.764
<v Speaker 2>The California law that was vetoed by Gavin Newsom probably

0:17:52.124 --> 0:17:54.324
<v Speaker 2>was considered a bigger deal. It was a state law,

0:17:54.364 --> 0:17:56.364
<v Speaker 2>but they're all based. If they want to operate in California,

0:17:56.364 --> 0:17:58.484
<v Speaker 2>then they were subject to it, right, Like that might

0:17:58.524 --> 0:18:00.684
<v Speaker 2>have been a bigger deal. But like the general pattern

0:18:00.724 --> 0:18:03.004
<v Speaker 2>here with the California law failing, with this thing being rescinded,

0:18:05.044 --> 0:18:10.724
<v Speaker 2>with Sam Altman being lesson less shall we say, concerned

0:18:11.564 --> 0:18:14.284
<v Speaker 2>about safety, right, we're going to get this AI raise

0:18:14.404 --> 0:18:18.444
<v Speaker 2>and this idea that you could stop it by having

0:18:19.604 --> 0:18:21.884
<v Speaker 2>only you know, three operators until you reach some point

0:18:21.884 --> 0:18:26.964
<v Speaker 2>where safety was achieved is not going to happen clearly, right,

0:18:28.244 --> 0:18:30.924
<v Speaker 2>you know, Like, if you read any other technology, you

0:18:30.924 --> 0:18:33.084
<v Speaker 2>would say, because one concern I have about AI or

0:18:33.204 --> 0:18:36.564
<v Speaker 2>about this at the newsletter this week. You know, when

0:18:36.564 --> 0:18:39.004
<v Speaker 2>you have these very big, powerful companies that have this

0:18:39.164 --> 0:18:42.604
<v Speaker 2>lead in computing power and engineering talent, right, usually that's

0:18:42.604 --> 0:18:44.244
<v Speaker 2>not how it works, Right, you have the next big thing,

0:18:44.284 --> 0:18:46.764
<v Speaker 2>and the next big thing is created by new companies

0:18:46.804 --> 0:18:50.364
<v Speaker 2>because the old companies are nostodgy and bloated and it's

0:18:50.364 --> 0:18:52.844
<v Speaker 2>not their mission in the first place, and they're not cool,

0:18:52.884 --> 0:18:55.764
<v Speaker 2>so don't attract young talent. Right, So to some accept

0:18:55.764 --> 0:18:59.204
<v Speaker 2>the fact that, like, you know, it can be disrupted

0:18:59.284 --> 0:19:04.284
<v Speaker 2>might lesson the worry about hegemonic concerns over AI and

0:19:04.324 --> 0:19:07.044
<v Speaker 2>the kind of paternalistic slash people get very rich off

0:19:07.044 --> 0:19:09.684
<v Speaker 2>it concerns about AI. But like, but yeah, I mean, look,

0:19:10.324 --> 0:19:15.004
<v Speaker 2>I think we're a long way from achieving artificial superintelligence,

0:19:15.044 --> 0:19:17.844
<v Speaker 2>which is the super human capabilities, right, But there are

0:19:17.884 --> 0:19:21.084
<v Speaker 2>ways that AIS can be dangerous far short of this.

0:19:21.364 --> 0:19:21.564
<v Speaker 1>Right.

0:19:21.684 --> 0:19:25.684
<v Speaker 2>Take ching you how to like mix chemical compounds or

0:19:25.804 --> 0:19:28.684
<v Speaker 2>build a pipe bomb or things like that, right, or

0:19:28.844 --> 0:19:31.724
<v Speaker 2>can aid in a bit like sue with cidal thoughts

0:19:31.764 --> 0:19:33.524
<v Speaker 2>and like in those use cases are going to be.

0:19:33.524 --> 0:19:35.404
<v Speaker 3>Like they're already happening.

0:19:35.604 --> 0:19:39.404
<v Speaker 1>They're already happening. We know that the guy who blew

0:19:39.484 --> 0:19:41.364
<v Speaker 1>up the cyber truck in front of the Trump Hotel

0:19:42.444 --> 0:19:45.364
<v Speaker 1>used chat GPT to figure out how to do it,

0:19:45.604 --> 0:19:47.924
<v Speaker 1>which was actually probably one of the reasons it wasn't

0:19:47.964 --> 0:19:51.724
<v Speaker 1>more destructive because the instructions were not very good. So

0:19:51.764 --> 0:19:53.844
<v Speaker 1>I think I think we should be we should be

0:19:53.844 --> 0:19:58.404
<v Speaker 1>grateful for the limitations of AI models for now. But yeah, no,

0:19:58.524 --> 0:20:01.684
<v Speaker 1>there are I think I think that they're to me.

0:20:02.684 --> 0:20:04.884
<v Speaker 1>That's actually one of the one of the more interesting

0:20:04.924 --> 0:20:07.404
<v Speaker 1>points is that you know, we're worried about p doo,

0:20:07.604 --> 0:20:10.524
<v Speaker 1>about you know, super intelligence, all these things, but I

0:20:10.564 --> 0:20:12.964
<v Speaker 1>think that in the shorter term and potentially in the

0:20:13.004 --> 0:20:15.364
<v Speaker 1>longer term, we need to be more worried about stupidity,

0:20:15.844 --> 0:20:20.044
<v Speaker 1>right about the fact that uh that, like, they aren't

0:20:20.084 --> 0:20:25.524
<v Speaker 1>super intelligent, right, and and people can misuse them, and

0:20:25.564 --> 0:20:29.564
<v Speaker 1>they can give flawed outputs. And as they become more

0:20:29.644 --> 0:20:34.604
<v Speaker 1>and more dominant mainstream used in searches, you know, used

0:20:34.644 --> 0:20:38.044
<v Speaker 1>in used in day to day stuff, but also used

0:20:38.084 --> 0:20:41.644
<v Speaker 1>higher up for people who you know, want something to

0:20:41.644 --> 0:20:44.764
<v Speaker 1>summarize research for them, et cetera, et cetera, that the

0:20:45.364 --> 0:20:48.804
<v Speaker 1>problem is going to be kind of much more mundane,

0:20:49.044 --> 0:20:51.124
<v Speaker 1>right that it gives you that, it gives you bad information,

0:20:51.164 --> 0:20:55.844
<v Speaker 1>it gives you bad instructions, It allides over something. It

0:20:55.844 --> 0:20:59.484
<v Speaker 1>doesn't It doesn't quite synthesize something correctly. I think that

0:20:59.484 --> 0:21:04.004
<v Speaker 1>that is actually the more pressing problem and is not

0:21:04.164 --> 0:21:06.444
<v Speaker 1>P doom boom We're going to blow up, but is

0:21:06.484 --> 0:21:10.644
<v Speaker 1>a kind of a smaller P dooms. It's already lowercase,

0:21:10.684 --> 0:21:15.004
<v Speaker 1>but like subscript fe doom on a day to day basis,

0:21:16.004 --> 0:21:17.244
<v Speaker 1>depending on who uses.

0:21:17.044 --> 0:21:19.764
<v Speaker 2>It n for what. I've kind of flipped on this

0:21:19.804 --> 0:21:22.564
<v Speaker 2>a little bit where I I think the hallucinations are

0:21:22.604 --> 0:21:25.204
<v Speaker 2>an overrated problem. I think what the models are doing

0:21:25.284 --> 0:21:30.764
<v Speaker 2>is is very impressive. They have fewer hallucinations than before.

0:21:32.324 --> 0:21:34.764
<v Speaker 2>And you know, I use them a lot just for

0:21:34.884 --> 0:21:37.964
<v Speaker 2>like research and problem solving a little bit of programming

0:21:38.004 --> 0:21:40.364
<v Speaker 2>and things like that. And I think, you know, the

0:21:40.404 --> 0:21:42.124
<v Speaker 2>one I've used the most is O one, which is

0:21:42.124 --> 0:21:47.724
<v Speaker 2>the latest public build of chatgypt or open AI. It

0:21:47.804 --> 0:21:51.164
<v Speaker 2>just can do higher level shit pretty well. You know,

0:21:51.964 --> 0:21:55.684
<v Speaker 2>it also can catch itself in midstream. They put some

0:21:55.764 --> 0:21:59.444
<v Speaker 2>routine in where it like well, typically a large language model.

0:21:59.684 --> 0:22:01.404
<v Speaker 2>The reason why it seems like it's printing one word

0:22:01.404 --> 0:22:03.244
<v Speaker 2>at a time. Is because like that's actually kind of

0:22:03.324 --> 0:22:08.644
<v Speaker 2>like how it works, right. It literally it literally kind

0:22:08.644 --> 0:22:10.844
<v Speaker 2>of goes to quench, It compresses its whole tex string,

0:22:10.844 --> 0:22:13.484
<v Speaker 2>puts it through transformer. Right. But then you know then

0:22:13.564 --> 0:22:15.844
<v Speaker 2>kind of it is recurs on how it puts it out.

0:22:16.004 --> 0:22:18.004
<v Speaker 2>It doesn't think of it all at once, right. But

0:22:18.084 --> 0:22:20.844
<v Speaker 2>now they've trained it to actually go back and check

0:22:20.884 --> 0:22:26.604
<v Speaker 2>its output to check for hallucinations, and it catches them

0:22:26.884 --> 0:22:29.924
<v Speaker 2>a lot of the time, but not a lot of

0:22:29.964 --> 0:22:30.284
<v Speaker 2>the time.

0:22:30.364 --> 0:22:30.524
<v Speaker 3>Right.

0:22:30.564 --> 0:22:34.084
<v Speaker 1>So I actually just did some test runs prior to

0:22:34.364 --> 0:22:36.684
<v Speaker 1>taping this so that I could see what was going

0:22:36.724 --> 0:22:40.084
<v Speaker 1>on right now. And when it's in my area of expertise,

0:22:40.284 --> 0:22:44.324
<v Speaker 1>I catch a lot of inaccuracies, not just hallucinations, but

0:22:44.404 --> 0:22:48.124
<v Speaker 1>things that are almost right but kind of misunderstood the point, right,

0:22:48.164 --> 0:22:51.644
<v Speaker 1>which which is actually which could be even more problematic.

0:22:51.724 --> 0:22:54.044
<v Speaker 1>So I had to do some test runs in psychology

0:22:54.084 --> 0:22:55.124
<v Speaker 1>where first of all.

0:22:55.004 --> 0:22:55.804
<v Speaker 3>It did hallucinate.

0:22:55.844 --> 0:22:59.124
<v Speaker 1>It still is making up studies, making up data that

0:22:59.164 --> 0:23:01.284
<v Speaker 1>does not actually exist. When I try to, I'm like, oh,

0:23:01.284 --> 0:23:03.484
<v Speaker 1>this is really cool. I want to look it up. No,

0:23:03.604 --> 0:23:07.284
<v Speaker 1>it doesn't exist. But it also miss like it actually

0:23:07.284 --> 0:23:10.564
<v Speaker 1>misinterprets findings and doesn't all always get it right. This

0:23:10.724 --> 0:23:12.884
<v Speaker 1>is my expertise, right, I have a PhD at it,

0:23:13.004 --> 0:23:15.324
<v Speaker 1>so I can figure this out and be like, you

0:23:15.324 --> 0:23:16.244
<v Speaker 1>know what this is.

0:23:16.404 --> 0:23:17.964
<v Speaker 3>It's pretty good, but not.

0:23:18.084 --> 0:23:21.244
<v Speaker 1>Actually like you don't want to rely on this and

0:23:21.284 --> 0:23:25.404
<v Speaker 1>this is just outright wrong. But because it's overall it

0:23:25.444 --> 0:23:27.884
<v Speaker 1>seems pretty good, I don't catch it when it's not

0:23:27.964 --> 0:23:30.084
<v Speaker 1>my area of expertise, and I just assume that it's

0:23:30.124 --> 0:23:32.684
<v Speaker 1>pretty good and that pretty is doing a lot of

0:23:32.684 --> 0:23:33.364
<v Speaker 1>heavy lifting.

0:23:33.884 --> 0:23:35.924
<v Speaker 2>What about if you read a New York Times or

0:23:35.964 --> 0:23:40.284
<v Speaker 2>Washington Post article on poker or sports betting, right or

0:23:40.404 --> 0:23:42.164
<v Speaker 2>some feel bad, but.

0:23:42.124 --> 0:23:45.124
<v Speaker 1>It doesn't actually hallucinate. It's not going to really it's

0:23:45.124 --> 0:23:47.404
<v Speaker 1>not going to tell me about findings that don't exist

0:23:47.524 --> 0:23:48.284
<v Speaker 1>to prove its point.

0:23:48.684 --> 0:23:50.324
<v Speaker 2>It can tell a lot of white lies though, and

0:23:50.404 --> 0:23:52.484
<v Speaker 2>misrepresent and be fundamentally dishonest.

0:23:53.044 --> 0:23:56.084
<v Speaker 1>Right, Well, sure you have. You have a problem of

0:23:56.404 --> 0:23:59.644
<v Speaker 1>reporting bias always, But there's a problem when you think

0:23:59.684 --> 0:24:02.684
<v Speaker 1>something is factual information and it's not right. When I'm

0:24:02.684 --> 0:24:04.444
<v Speaker 1>reading an op ed, I know it's an op ed

0:24:04.484 --> 0:24:07.404
<v Speaker 1>when I'm reading an article, but when i'm when I

0:24:07.444 --> 0:24:09.164
<v Speaker 1>want this for facts.

0:24:09.444 --> 0:24:11.524
<v Speaker 2>But I want I want to know, not the use case.

0:24:11.564 --> 0:24:13.484
<v Speaker 2>Though you can't put everything in the microwave oven.

0:24:13.764 --> 0:24:16.084
<v Speaker 1>Of course I want to put one of the things

0:24:16.724 --> 0:24:18.844
<v Speaker 1>if I want to learn about a field. So let

0:24:18.884 --> 0:24:21.044
<v Speaker 1>me give you another example. I didn't just use psychology.

0:24:21.364 --> 0:24:25.564
<v Speaker 1>I asked about I wanted to know about a specific

0:24:25.604 --> 0:24:27.164
<v Speaker 1>type of company. I'm not going to give you kind

0:24:27.164 --> 0:24:30.964
<v Speaker 1>of the search that was making a specific type of

0:24:30.964 --> 0:24:33.964
<v Speaker 1>crypto investment. So I asked, like, what's a list of

0:24:33.964 --> 0:24:35.604
<v Speaker 1>companies that's done it? And gave me a list. I

0:24:35.604 --> 0:24:38.084
<v Speaker 1>was like, great, now will you tell me what the

0:24:38.084 --> 0:24:40.924
<v Speaker 1>specific investments are? And it's like, oh, sorry, we don't

0:24:40.924 --> 0:24:42.884
<v Speaker 1>actually know, Like we don't know that these companies have

0:24:42.924 --> 0:24:45.884
<v Speaker 1>made any investments. We just gave you a list, And

0:24:46.284 --> 0:24:47.244
<v Speaker 1>I was like, okay.

0:24:47.124 --> 0:24:52.484
<v Speaker 2>You're using it wrong. You there are a lot of

0:24:52.484 --> 0:25:00.364
<v Speaker 2>situations in life where precision isn't that important, right, you know?

0:25:00.564 --> 0:25:04.284
<v Speaker 2>I mean, for example, I was as you made no listeners.

0:25:04.324 --> 0:25:06.604
<v Speaker 2>I was in Korea and Japan recently, and like something

0:25:06.604 --> 0:25:09.364
<v Speaker 2>I've been lazy about. I never taught myself how to

0:25:09.564 --> 0:25:14.164
<v Speaker 2>distinguished Japanese, Chinese and Korean characters, and so I like

0:25:14.244 --> 0:25:17.924
<v Speaker 2>told to bet I'm on the flight to Tokyo. I'm like, hey,

0:25:17.924 --> 0:25:20.804
<v Speaker 2>give me a little very quick summary and give me

0:25:20.804 --> 0:25:22.084
<v Speaker 2>a pop quiz and like you learn it in like

0:25:22.084 --> 0:25:24.044
<v Speaker 2>ten or fifteen minutes, right, And they're like, you know,

0:25:24.044 --> 0:25:27.124
<v Speaker 2>I don't have to like distinguish those characters one hundred accuracy.

0:25:27.164 --> 0:25:30.444
<v Speaker 2>But it's like basically pretty good, and like I can

0:25:30.484 --> 0:25:34.844
<v Speaker 2>tailor exactly how how that resources geared toward me.

0:25:36.124 --> 0:25:38.204
<v Speaker 1>I'm not saying this is useless. I'm just saying that

0:25:38.244 --> 0:25:41.004
<v Speaker 1>it's right now. It is being used for the cases

0:25:41.044 --> 0:25:42.844
<v Speaker 1>that I've told you about because it's at the top

0:25:42.884 --> 0:25:46.964
<v Speaker 1>of your such when you do a Google search, like

0:25:47.644 --> 0:25:49.604
<v Speaker 1>that's the first thing that comes up as the.

0:25:49.724 --> 0:25:54.524
<v Speaker 2>I think it's very bad branding decision by by Google, right.

0:25:54.564 --> 0:25:56.644
<v Speaker 2>I do think it's a bad because like and Google's

0:25:56.764 --> 0:26:00.044
<v Speaker 2>I'm sorry, it's not as good as opening Eye show anthropic.

0:26:00.084 --> 0:26:03.964
<v Speaker 2>It's not it's not sorry Google, and like it undermines

0:26:04.044 --> 0:26:06.204
<v Speaker 2>Google's kind of lead in search. And I think Google

0:26:06.204 --> 0:26:08.244
<v Speaker 2>has handled this a lot of things in this space

0:26:08.364 --> 0:26:10.764
<v Speaker 2>very badly. Although I mean, you know, it was Google

0:26:10.804 --> 0:26:13.164
<v Speaker 2>engineers who came up with transformer paper and they and

0:26:13.204 --> 0:26:17.244
<v Speaker 2>they and they, like you know, still hire lots of

0:26:17.244 --> 0:26:18.724
<v Speaker 2>great pale up but they've kind of become like this

0:26:18.804 --> 0:26:23.124
<v Speaker 2>feeder system to like the hip or cooler AI companies,

0:26:23.444 --> 0:26:26.124
<v Speaker 2>I think, But like anyway I think people are I

0:26:26.164 --> 0:26:30.044
<v Speaker 2>think people are way too hipster about this, Like this

0:26:30.084 --> 0:26:33.444
<v Speaker 2>is the most quickly adopted technology in the history of

0:26:33.444 --> 0:26:34.844
<v Speaker 2>the world by some mess.

0:26:34.684 --> 0:26:37.644
<v Speaker 1>Absolutely, and I'm not like I actually like, I think

0:26:37.684 --> 0:26:40.284
<v Speaker 1>that it has a lot of potential. I want it

0:26:40.324 --> 0:26:43.444
<v Speaker 1>to do better, right, Like I like I want them

0:26:43.444 --> 0:26:44.284
<v Speaker 1>to fix this shit.

0:26:44.764 --> 0:26:44.964
<v Speaker 3>Right.

0:26:45.044 --> 0:26:47.404
<v Speaker 2>Look, we are poker players, Maria. We should be used

0:26:47.444 --> 0:26:51.724
<v Speaker 2>to being able to accept information as shifting your prior

0:26:51.804 --> 0:26:54.684
<v Speaker 2>or shifting your view, but like not being definitive, right,

0:26:54.724 --> 0:26:57.124
<v Speaker 2>And that's a journalist. We're both journalists too, Like you know,

0:26:57.244 --> 0:26:59.004
<v Speaker 2>when a source tells you something, you've vet.

0:26:59.004 --> 0:27:03.004
<v Speaker 1>It absolutely, But it actually adds more work for me

0:27:03.444 --> 0:27:05.444
<v Speaker 1>because I have to go through it and try to

0:27:05.484 --> 0:27:07.644
<v Speaker 1>figure out what can I rely on, what can't I

0:27:07.724 --> 0:27:11.844
<v Speaker 1>rely on. Now, one listener who who has shared his

0:27:11.924 --> 0:27:15.524
<v Speaker 1>experience on UH on social media as well, and I

0:27:15.564 --> 0:27:18.884
<v Speaker 1>know you wrote you kind of referenced it in your

0:27:18.884 --> 0:27:22.524
<v Speaker 1>newsletter this week, Kevin Ruse had emailed me about poker

0:27:22.564 --> 0:27:26.364
<v Speaker 1>training and said that he was using chat GPT and

0:27:26.444 --> 0:27:28.764
<v Speaker 1>AIS to help him with poker. And I said, don't

0:27:28.764 --> 0:27:31.324
<v Speaker 1>do that because it's going to tell you the wrong thing.

0:27:32.284 --> 0:27:36.364
<v Speaker 1>And he did it. He still did it and he said, oh,

0:27:36.364 --> 0:27:38.484
<v Speaker 1>I want to tournament. It was it was good, it

0:27:38.564 --> 0:27:41.524
<v Speaker 1>was helpful. So I actually had chat GPT do some

0:27:41.604 --> 0:27:42.564
<v Speaker 1>poker training for me.

0:27:42.884 --> 0:27:43.964
<v Speaker 3>It's not good.

0:27:44.404 --> 0:27:46.844
<v Speaker 1>It gives you incorrect advice if you don't know, if

0:27:46.844 --> 0:27:49.164
<v Speaker 1>you're a novice, and if you're using this, you might

0:27:49.204 --> 0:27:52.284
<v Speaker 1>get lucky, right, and it were all works out, but

0:27:52.404 --> 0:27:55.644
<v Speaker 1>let's go to poker, like, try to use chat GPT

0:27:55.684 --> 0:27:58.404
<v Speaker 1>to teach you poker strategy. It is not going to

0:27:58.404 --> 0:28:01.604
<v Speaker 1>teach you strategy. Did you did you and the better

0:28:01.644 --> 0:28:01.924
<v Speaker 1>you are?

0:28:03.804 --> 0:28:04.004
<v Speaker 3>Yeah?

0:28:04.444 --> 0:28:06.564
<v Speaker 2>Yeah, I just I did the same and I thought

0:28:06.564 --> 0:28:09.724
<v Speaker 2>it was pretty good. It was it misses things that

0:28:09.804 --> 0:28:12.124
<v Speaker 2>like so I actually did this last night. I mean

0:28:12.164 --> 0:28:14.444
<v Speaker 2>it gets you know, I so what do you? What

0:28:14.444 --> 0:28:14.844
<v Speaker 2>do you actually?

0:28:15.244 --> 0:28:19.284
<v Speaker 3>But here's the thing, though, are you yellous? You're you're able.

0:28:19.044 --> 0:28:22.124
<v Speaker 1>To distinguish what it's missing and what is getting pretty well.

0:28:22.364 --> 0:28:25.724
<v Speaker 1>If you're using this as the tool to train yourself

0:28:26.244 --> 0:28:30.684
<v Speaker 1>and you don't have any background knowledge, that is the problem, right,

0:28:30.724 --> 0:28:33.244
<v Speaker 1>you need it to be you need it to teach

0:28:33.244 --> 0:28:36.644
<v Speaker 1>you correctly. It's much more difficult as someone who started

0:28:36.684 --> 0:28:40.804
<v Speaker 1>poker from zero as an adult. Right, let me tell you, Like,

0:28:40.924 --> 0:28:42.804
<v Speaker 1>one of the most important things I learned was that

0:28:42.844 --> 0:28:46.004
<v Speaker 1>it's much easier to teach someone from zero because I

0:28:46.004 --> 0:28:47.204
<v Speaker 1>didn't have any bad habits.

0:28:47.284 --> 0:28:47.444
<v Speaker 3>Right.

0:28:47.484 --> 0:28:51.004
<v Speaker 1>If I had instead learned from chat GPT and those

0:28:51.084 --> 0:28:53.844
<v Speaker 1>were kind of the habits and the thought processes that

0:28:53.884 --> 0:28:56.564
<v Speaker 1>I acquired, and some of them were just wrong or

0:28:56.604 --> 0:28:59.484
<v Speaker 1>didn't teach me how to think correctly through things, I'd

0:28:59.484 --> 0:29:01.084
<v Speaker 1>be a really shitty poker player.

0:29:01.684 --> 0:29:03.604
<v Speaker 2>Yeah, so let me give you some example of how

0:29:03.644 --> 0:29:05.444
<v Speaker 2>I use chat GPT.

0:29:05.804 --> 0:29:05.964
<v Speaker 1>Right.

0:29:07.244 --> 0:29:11.924
<v Speaker 2>You know, one is kind of as a research assistant,

0:29:12.004 --> 0:29:14.324
<v Speaker 2>but like once you already know something about a topic, right,

0:29:14.324 --> 0:29:15.964
<v Speaker 2>Like I'm not getting a first brief, but I'm like

0:29:16.044 --> 0:29:18.804
<v Speaker 2>quarrying it where I'm saying, Okay, I talked to this person.

0:29:19.924 --> 0:29:24.044
<v Speaker 2>Here's a description of how an AI thing works, or

0:29:24.084 --> 0:29:26.644
<v Speaker 2>a crypto thing works, or concept and finance works. Right,

0:29:27.004 --> 0:29:30.684
<v Speaker 2>will you vet this for me? What critiques might you have? Right?

0:29:31.604 --> 0:29:33.524
<v Speaker 2>It's maybe not quite as good as talking to like

0:29:33.564 --> 0:29:35.684
<v Speaker 2>an expert, but I find like you often get a

0:29:35.724 --> 0:29:37.404
<v Speaker 2>lot of value from that, and again it's not the

0:29:37.444 --> 0:29:38.924
<v Speaker 2>last step in the process.

0:29:39.004 --> 0:29:39.124
<v Speaker 1>Right.

0:29:39.124 --> 0:29:41.804
<v Speaker 2>You can also use it for creative inspiration. Give me

0:29:41.924 --> 0:29:44.444
<v Speaker 2>ten potential headlines from this. You can use to fill

0:29:44.484 --> 0:29:46.004
<v Speaker 2>in missing words, because it thinks in terms of a

0:29:46.004 --> 0:29:48.724
<v Speaker 2>big matrix, right, so like what's an analogy that I

0:29:48.764 --> 0:29:51.844
<v Speaker 2>can think of? What's this word or concept that I'm missing?

0:29:51.884 --> 0:29:55.044
<v Speaker 2>Invent the name for this thing or that thing. You

0:29:55.044 --> 0:29:57.364
<v Speaker 2>can use it to kind of squeeze quantitative data out

0:29:57.364 --> 0:29:59.764
<v Speaker 2>of qualitative information, like I asked it, for example, to

0:30:00.564 --> 0:30:02.604
<v Speaker 2>an identify straft to this again, right, but to like

0:30:03.524 --> 0:30:07.564
<v Speaker 2>vet my estimate of how liberal or conservative different eras

0:30:07.564 --> 0:30:10.204
<v Speaker 2>in American history we're on a negative to to positive

0:30:10.244 --> 0:30:13.324
<v Speaker 2>ten scale. It can make ranking lists of different kinds.

0:30:13.324 --> 0:30:15.324
<v Speaker 2>I mean, it's just like there are so many use

0:30:15.324 --> 0:30:19.964
<v Speaker 2>cases for it, and like people just want us to

0:30:19.964 --> 0:30:23.084
<v Speaker 2>like cheat on papers or use it as a substitute

0:30:23.084 --> 0:30:24.804
<v Speaker 2>for like Wikipedia or something, which you're not the best

0:30:24.924 --> 0:30:26.964
<v Speaker 2>use cases for it. And if you ask chet ChiPT,

0:30:27.124 --> 0:30:28.724
<v Speaker 2>it will tell you that those are not the best

0:30:29.164 --> 0:30:30.044
<v Speaker 2>use cases for it.

0:30:30.164 --> 0:30:30.324
<v Speaker 1>Right.

0:30:30.404 --> 0:30:32.964
<v Speaker 2>The queriable nature of it and the fact that it

0:30:33.044 --> 0:30:35.564
<v Speaker 2>reorganizes this information in a way that for many purposes

0:30:35.564 --> 0:30:38.684
<v Speaker 2>but not all purposes, is much more approachable accessible, is

0:30:38.804 --> 0:30:41.204
<v Speaker 2>it's I don't know, it's I think it's a miraculous technology.

0:30:41.444 --> 0:30:44.684
<v Speaker 2>I mean, you know you had woken up. If I

0:30:44.724 --> 0:30:50.004
<v Speaker 2>had fallen to a coma years in twenty fifteen and

0:30:50.284 --> 0:30:55.604
<v Speaker 2>woken up, I missed the whole first Trump administration, I'm like, oh,

0:30:55.604 --> 0:31:00.284
<v Speaker 2>Trump's prison, Oh he was already President's surprise then, like

0:31:00.644 --> 0:31:02.844
<v Speaker 2>you would be fucking blown away by this shit, right,

0:31:02.844 --> 0:31:04.964
<v Speaker 2>and be like, oh my fucking god. Right, just like

0:31:05.004 --> 0:31:07.764
<v Speaker 2>passing the Turing test. I mean, there are definitions to

0:31:07.764 --> 0:31:08.924
<v Speaker 2>meet it's but whether it's a good test, whether it

0:31:09.004 --> 0:31:13.324
<v Speaker 2>actually is, But like it basically is like human esque

0:31:13.444 --> 0:31:18.564
<v Speaker 2>intelligence in some ways, inferior in some cases superior over

0:31:18.644 --> 0:31:20.844
<v Speaker 2>a large domain of fields. Just the way it can

0:31:21.004 --> 0:31:26.164
<v Speaker 2>like parse this very open ended, fuzzy logic of techt strings.

0:31:26.204 --> 0:31:27.804
<v Speaker 2>I mean, I just think it's kind of an amazing

0:31:28.644 --> 0:31:32.404
<v Speaker 2>It's amazically a robust in some ways, right, sure that

0:31:32.444 --> 0:31:35.204
<v Speaker 2>you can misspell things you get, I mean, it's amazingly

0:31:35.284 --> 0:31:37.684
<v Speaker 2>robust in a way that like it's hard to think

0:31:37.684 --> 0:31:43.564
<v Speaker 2>of other technologies that compare to it exactly, and you know,

0:31:43.804 --> 0:31:49.004
<v Speaker 2>and solved using very simple underlying math, right, I mean,

0:31:49.044 --> 0:31:51.124
<v Speaker 2>the code for deep seek is something like a few

0:31:51.204 --> 0:31:54.444
<v Speaker 2>hundred lines of code long. My fucking election model is

0:31:54.524 --> 0:31:58.084
<v Speaker 2>longer than that. Right, It's like it's like it's kind

0:31:58.084 --> 0:31:58.724
<v Speaker 2>of a miracle.

0:31:59.084 --> 0:32:04.924
<v Speaker 1>Absolutely absolutely I agree with all of that. Where but

0:32:05.244 --> 0:32:08.324
<v Speaker 1>now I think to push it a little bit further. Obviously,

0:32:08.364 --> 0:32:12.564
<v Speaker 1>this miracle, as we know, it's coming at a big cost, right,

0:32:12.924 --> 0:32:17.444
<v Speaker 1>environmental cost. It also P doom. Right, we've talked about

0:32:17.524 --> 0:32:21.164
<v Speaker 1>that potential risk is the miracle of you know, giving

0:32:21.164 --> 0:32:25.164
<v Speaker 1>you a good analogy worth it at this cost. That's

0:32:25.204 --> 0:32:26.164
<v Speaker 1>I think those are kind.

0:32:26.084 --> 0:32:28.524
<v Speaker 2>Of don't give me this environmental.

0:32:28.324 --> 0:32:31.284
<v Speaker 1>I'm not talking I'm talking about P doom and environmental.

0:32:31.284 --> 0:32:34.164
<v Speaker 1>It's not crap, Nate. We talked about this before, like

0:32:34.604 --> 0:32:35.444
<v Speaker 1>a lot of energy.

0:32:35.524 --> 0:32:37.324
<v Speaker 2>Okay, look at this. This is something that's supposed to scare me.

0:32:37.524 --> 0:32:41.564
<v Speaker 2>Four impress dot org. The energy consumption for training chat

0:32:41.604 --> 0:32:45.244
<v Speaker 2>EPT leading model is even more staggering, equated to that

0:32:45.284 --> 0:32:47.724
<v Speaker 2>of an American hassole for more than seven hundred years.

0:32:47.764 --> 0:32:51.324
<v Speaker 2>So basically, to train this leading model only took seven

0:32:51.404 --> 0:32:56.244
<v Speaker 2>hundred households worth like one subdivision of some fucking neighborhood

0:32:56.284 --> 0:33:00.044
<v Speaker 2>in Tulsa. Right, it's not very much like don't you

0:33:00.084 --> 0:33:02.444
<v Speaker 2>know you undermind the argument for ped doom. We all

0:33:02.484 --> 0:33:05.084
<v Speaker 2>die if like I mean this, you know, obviously if

0:33:05.764 --> 0:33:07.804
<v Speaker 2>the models get hungrier and hungrier. But by the way,

0:33:07.804 --> 0:33:11.844
<v Speaker 2>the deep seek thing should be good news for the environment.

0:33:11.964 --> 0:33:14.124
<v Speaker 1>Well that's why I said, we don't know, because on

0:33:14.164 --> 0:33:17.644
<v Speaker 1>the one hand, maybe depending on what the actual resources are.

0:33:17.844 --> 0:33:19.764
<v Speaker 1>On the other hand, if it means that every single

0:33:19.764 --> 0:33:22.164
<v Speaker 1>person is now running these smaller things, or not every

0:33:22.164 --> 0:33:25.364
<v Speaker 1>single person, but if it makes it more likely that

0:33:25.484 --> 0:33:28.204
<v Speaker 1>more of these are what's the net impact, right, If

0:33:28.244 --> 0:33:30.964
<v Speaker 1>it's one tenth but you actually have one hundred times

0:33:31.204 --> 0:33:33.724
<v Speaker 1>more people using it as a result, then it's a

0:33:33.764 --> 0:33:37.324
<v Speaker 1>net obviously negative impact instead of net positive. These are

0:33:37.364 --> 0:33:39.764
<v Speaker 1>all open questions, right, And like I said, I am

0:33:39.844 --> 0:33:42.524
<v Speaker 1>not an AI skeptic. I think it's really cool. I

0:33:42.564 --> 0:33:45.044
<v Speaker 1>think there are lots of really interesting things here. I

0:33:45.124 --> 0:33:47.044
<v Speaker 1>just think that there are other you know, you can't

0:33:47.084 --> 0:33:49.364
<v Speaker 1>also be like a raw raw cheer later none of

0:33:49.364 --> 0:33:52.004
<v Speaker 1>this matters. Of course, it does matter. I think all

0:33:52.044 --> 0:33:52.844
<v Speaker 1>of these things matter.

0:33:53.204 --> 0:33:56.884
<v Speaker 2>I just think people are over indexing to like I

0:33:56.884 --> 0:33:59.724
<v Speaker 2>don't know. I mean, have you taken wes Wimo Maria

0:33:59.724 --> 0:34:01.284
<v Speaker 2>and by the way if you're not aware, this is

0:34:01.324 --> 0:34:06.604
<v Speaker 2>a self driving car company which is available in San Francisco, Phoenix,

0:34:06.644 --> 0:34:08.044
<v Speaker 2>and maybe one or two other places.

0:34:08.124 --> 0:34:08.284
<v Speaker 1>La.

0:34:08.364 --> 0:34:10.204
<v Speaker 2>I think have you taken a Weimo in any.

0:34:10.044 --> 0:34:12.324
<v Speaker 3>Of those places, Maria, I have not name.

0:34:12.764 --> 0:34:15.244
<v Speaker 2>It's fucking blade wrinner. I'm telling you, it's a very

0:34:15.284 --> 0:34:17.724
<v Speaker 2>good experience. It's a much smoother ride than i'd say

0:34:17.764 --> 0:34:21.364
<v Speaker 2>ninety five percent of ubers. They have like space sage music,

0:34:21.404 --> 0:34:24.124
<v Speaker 2>and you feel like you're in the fucking future. And

0:34:24.324 --> 0:34:29.324
<v Speaker 2>I would almost guarantee you that driver less cars are

0:34:29.324 --> 0:34:32.204
<v Speaker 2>going to be a very popular technology.

0:34:32.324 --> 0:34:33.164
<v Speaker 3>I don't know. I don't know.

0:34:33.804 --> 0:34:36.364
<v Speaker 1>I watched I watched that. I watched that episode of

0:34:36.404 --> 0:34:39.044
<v Speaker 1>Silicon Valley where he's in the driver less car and

0:34:39.164 --> 0:34:42.044
<v Speaker 1>en step on a on a boat somewhere in the

0:34:42.084 --> 0:34:47.404
<v Speaker 1>middle of the ocean. So I'm a little obviously TV

0:34:47.484 --> 0:34:48.364
<v Speaker 1>show comedy.

0:34:48.444 --> 0:34:51.364
<v Speaker 3>But but you know, you never you never know how

0:34:51.364 --> 0:34:53.164
<v Speaker 3>the experience will will end up.

0:34:53.284 --> 0:34:55.404
<v Speaker 1>But I'm going to San Francisco next week, Nate, so

0:34:55.604 --> 0:34:57.644
<v Speaker 1>you know, maybe I'll take my first Weimo.

0:34:57.644 --> 0:35:00.164
<v Speaker 2>Take a Wimo. It's it's it's like a ninety fifth

0:35:00.244 --> 0:35:02.764
<v Speaker 2>percentile Uber driver.

0:35:03.324 --> 0:35:06.324
<v Speaker 1>All right, Well, well, on that positive note, Shall we

0:35:06.444 --> 0:35:08.484
<v Speaker 1>talk a little bit more poker and switch to a

0:35:08.524 --> 0:35:16.844
<v Speaker 1>listener question? Okay, fine, we'll be back right after this.

0:35:27.604 --> 0:35:32.684
<v Speaker 1>All right, So we had a poker related listener question

0:35:33.004 --> 0:35:38.364
<v Speaker 1>that I think, Nate, you are probably more equipped to

0:35:38.404 --> 0:35:41.404
<v Speaker 1>answer in the sense that you play cash home games

0:35:41.444 --> 0:35:43.964
<v Speaker 1>and I don't. By the way, I'm really sorry if

0:35:44.004 --> 0:35:47.964
<v Speaker 1>you can hear some knock knock noises in the background.

0:35:48.724 --> 0:35:52.804
<v Speaker 1>Apparently the apartment above mine has just started construction. It

0:35:52.884 --> 0:35:56.444
<v Speaker 1>actually just happened as we started taping this podcast. This

0:35:56.604 --> 0:35:59.404
<v Speaker 1>is the first hammering I have heard. But of course

0:35:59.484 --> 0:36:02.724
<v Speaker 1>you get to experience it alongside me, because I love

0:36:02.724 --> 0:36:04.804
<v Speaker 1>our listeners and I want to share all of my

0:36:04.924 --> 0:36:09.204
<v Speaker 1>experiences with them. So Nate, here's the listener question. I

0:36:09.284 --> 0:36:12.204
<v Speaker 1>have a neighborhood poker night with my friends. Everyone plays

0:36:12.204 --> 0:36:14.924
<v Speaker 1>really loose and passive, lots of calling, not much raising.

0:36:15.364 --> 0:36:18.004
<v Speaker 1>How do I win against real amateurs like that? What

0:36:18.084 --> 0:36:20.404
<v Speaker 1>are the most common and easy to detect tells by

0:36:20.444 --> 0:36:23.644
<v Speaker 1>amateurs like this? So part of this I can answer too, right,

0:36:23.644 --> 0:36:26.164
<v Speaker 1>because this happens in tournaments as well. But let's start

0:36:26.164 --> 0:36:29.844
<v Speaker 1>with what you think. Since you play in home games,

0:36:29.924 --> 0:36:32.964
<v Speaker 1>you know this is something that you find fun and

0:36:33.564 --> 0:36:35.764
<v Speaker 1>not an experience that I often have.

0:36:37.564 --> 0:36:39.884
<v Speaker 2>So it depends this comes from listener.

0:36:40.044 --> 0:36:40.204
<v Speaker 1>Hugh.

0:36:40.524 --> 0:36:46.924
<v Speaker 2>H u g h. I guess that's the way you spill, Hugh.

0:36:48.684 --> 0:36:49.764
<v Speaker 3>You does sound British.

0:36:49.844 --> 0:36:52.884
<v Speaker 1>I'm sorry, it's just a name that I automatically associate

0:36:52.924 --> 0:36:53.924
<v Speaker 1>with you with being English.

0:36:54.444 --> 0:36:57.844
<v Speaker 2>We have Okay, So what are basics for loose home?

0:36:57.884 --> 0:37:00.364
<v Speaker 2>I mean depends on if you're talking about like really

0:37:00.404 --> 0:37:02.804
<v Speaker 2>bad players. He seems to be.

0:37:03.044 --> 0:37:05.364
<v Speaker 3>He seems to be, so.

0:37:06.164 --> 0:37:08.764
<v Speaker 2>You know, the basics are you actually don't want to

0:37:08.764 --> 0:37:10.884
<v Speaker 2>play like everyone else beating, you know, don't be so

0:37:11.084 --> 0:37:16.724
<v Speaker 2>loose and passive. Right, you need particularly out of position

0:37:17.044 --> 0:37:21.804
<v Speaker 2>hands that can make the nuts right, so suited hands

0:37:21.844 --> 0:37:26.804
<v Speaker 2>particularly you know asex suited, Broadway suited hands ten nine

0:37:26.844 --> 0:37:29.444
<v Speaker 2>suited kind of an above right. So number one, hand

0:37:29.484 --> 0:37:34.884
<v Speaker 2>selection becomes more more oriented toward strong hands that can

0:37:34.884 --> 0:37:39.404
<v Speaker 2>make big you know, straights and flushes and better. That's

0:37:39.484 --> 0:37:42.404
<v Speaker 2>part one, right, Number two, you're gonna want to like

0:37:42.924 --> 0:37:46.924
<v Speaker 2>increase your bet sizing maybe quite a bit. Theory says

0:37:46.924 --> 0:37:48.524
<v Speaker 2>in a cash game that you're supposed to raise to

0:37:48.564 --> 0:37:50.764
<v Speaker 2>maybe two and a half x a big blind here

0:37:50.804 --> 0:37:53.564
<v Speaker 2>you can go four or five if they're already limpers.

0:37:53.684 --> 0:37:56.444
<v Speaker 2>You can raise even more than that. Right, There are

0:37:56.444 --> 0:37:58.284
<v Speaker 2>some games where the standard open might be to like

0:37:58.644 --> 0:38:00.204
<v Speaker 2>ten x or things like that. But like, let me

0:38:00.244 --> 0:38:02.644
<v Speaker 2>maybe let me even back up a little further, right,

0:38:02.764 --> 0:38:05.684
<v Speaker 2>I actually have dealt poker games to total rank amateurs

0:38:05.764 --> 0:38:07.484
<v Speaker 2>or like literally five to ten people. I have never

0:38:07.524 --> 0:38:08.764
<v Speaker 2>played booker before.

0:38:08.844 --> 0:38:09.044
<v Speaker 1>Right.

0:38:11.404 --> 0:38:14.404
<v Speaker 2>The two things that they most routinely get wrong are

0:38:14.644 --> 0:38:18.724
<v Speaker 2>number one, they call too much, meaning they call and

0:38:18.804 --> 0:38:21.124
<v Speaker 2>play it like a slot machine instead of folding or

0:38:21.164 --> 0:38:25.244
<v Speaker 2>raising more. And number two, they don't understand bet sizing.

0:38:25.764 --> 0:38:27.604
<v Speaker 2>What is the size of your bet relative to the

0:38:27.684 --> 0:38:31.844
<v Speaker 2>size of the pot. Right, If you don't know anything

0:38:31.844 --> 0:38:35.884
<v Speaker 2>about poker, no, nothing at all, then just bet half

0:38:35.924 --> 0:38:38.484
<v Speaker 2>the size of the pot. Keep track of what's in

0:38:38.524 --> 0:38:41.084
<v Speaker 2>the pot and bet half that size. But in general,

0:38:41.404 --> 0:38:42.444
<v Speaker 2>don't do so much calling.

0:38:42.484 --> 0:38:42.604
<v Speaker 1>Right.

0:38:42.644 --> 0:38:44.204
<v Speaker 2>If you have a good hand or a good bluff,

0:38:44.444 --> 0:38:45.684
<v Speaker 2>or even if you just kind of think other people

0:38:45.724 --> 0:38:49.964
<v Speaker 2>are scared, then then do some raising if you think

0:38:50.004 --> 0:38:52.084
<v Speaker 2>there'll be then most amateur players are not going to

0:38:52.164 --> 0:38:53.764
<v Speaker 2>go nuts. I mean it's a little complicate because like

0:38:54.204 --> 0:38:56.404
<v Speaker 2>they might not understand hands strikes, so you might want

0:38:56.404 --> 0:38:58.324
<v Speaker 2>to weig absolute strength a little bit more, but like,

0:38:59.324 --> 0:39:00.884
<v Speaker 2>but don't be afraid to get the money. And when

0:39:00.924 --> 0:39:02.644
<v Speaker 2>you have a good hand, and when other people have

0:39:02.684 --> 0:39:06.404
<v Speaker 2>a good representing a good hand, then it gets a

0:39:06.444 --> 0:39:10.564
<v Speaker 2>little bit complicated. But then you know, you don't have

0:39:10.604 --> 0:39:13.764
<v Speaker 2>to do a whole excess amount of bluff catching. I mean,

0:39:13.764 --> 0:39:17.524
<v Speaker 2>those are the basic And then I'd say, like, in general,

0:39:17.564 --> 0:39:20.404
<v Speaker 2>in these lose cash games, people are very sticky. Now

0:39:20.404 --> 0:39:22.924
<v Speaker 2>we're talking about a slightly higher caliber of players people

0:39:22.964 --> 0:39:25.924
<v Speaker 2>have had played before. Right, people are mostly very sticky

0:39:25.964 --> 0:39:29.644
<v Speaker 2>pre flop and on the flop, and then they will

0:39:29.724 --> 0:39:32.484
<v Speaker 2>start to fold cash can players do like to fold

0:39:32.524 --> 0:39:35.404
<v Speaker 2>on turns and rivers sometimes, Right, So that means that,

0:39:35.484 --> 0:39:37.964
<v Speaker 2>like you know that can affect your whole strategy for

0:39:38.004 --> 0:39:39.484
<v Speaker 2>the whole hand is that you tend not to have

0:39:39.524 --> 0:39:41.644
<v Speaker 2>a lot of full equity preflop in on flops, and

0:39:41.684 --> 0:39:43.924
<v Speaker 2>then it requires multiple barrels sometimes.

0:39:44.364 --> 0:39:45.124
<v Speaker 3>Yeah.

0:39:45.204 --> 0:39:48.604
<v Speaker 1>I think that as someone who is a tournament player,

0:39:49.604 --> 0:39:52.964
<v Speaker 1>there is some advice that I think applies all around,

0:39:53.684 --> 0:39:56.964
<v Speaker 1>which basically goes hand in hand with what you said Nate.

0:39:57.804 --> 0:40:00.484
<v Speaker 1>Number one, You don't want to follow the tendencies of

0:40:00.564 --> 0:40:03.084
<v Speaker 1>the people who are making mistakes, right, So If people

0:40:03.124 --> 0:40:05.564
<v Speaker 1>are too loose, you actually want to tighten up. If

0:40:05.604 --> 0:40:09.564
<v Speaker 1>people are passive, you want to become more aggressive. I

0:40:09.604 --> 0:40:11.924
<v Speaker 1>think that's important. But you should also realize if they're

0:40:11.964 --> 0:40:14.724
<v Speaker 1>going to be sticky, then you should just bet huge, right,

0:40:14.844 --> 0:40:17.404
<v Speaker 1>Like if you are going to if you'd normally bet

0:40:17.404 --> 0:40:20.284
<v Speaker 1>half pot, just bet pot they're going to call anyway, right,

0:40:20.724 --> 0:40:23.964
<v Speaker 1>build massive pots with your good hands. This will also

0:40:24.084 --> 0:40:28.484
<v Speaker 1>enable you to bluff, right, because they will eventually fold. Now,

0:40:28.684 --> 0:40:30.684
<v Speaker 1>something you said, I think this is actually true, not

0:40:30.804 --> 0:40:35.044
<v Speaker 1>just of cash games, but in general in tournaments as well.

0:40:35.604 --> 0:40:41.204
<v Speaker 1>People do tend to overcall flop and overfold turn. So

0:40:41.364 --> 0:40:44.444
<v Speaker 1>that's a great you know, I think building an over

0:40:44.484 --> 0:40:47.644
<v Speaker 1>betting strategy into your game in a game like that

0:40:47.764 --> 0:40:50.884
<v Speaker 1>is really good, right, And sometimes they'll get very sticky

0:40:51.084 --> 0:40:52.924
<v Speaker 1>like I've had. Because the second part of this question

0:40:53.044 --> 0:40:55.404
<v Speaker 1>was tells, which I think is just bad. Do not

0:40:55.564 --> 0:40:58.324
<v Speaker 1>use tells, even though in games like that people probably

0:40:58.364 --> 0:41:00.764
<v Speaker 1>do have tells, especially if you're going to play with

0:41:00.804 --> 0:41:02.564
<v Speaker 1>them over and over. It might be a little different,

0:41:02.804 --> 0:41:04.644
<v Speaker 1>but I just don't think that's great to rely on.

0:41:05.004 --> 0:41:07.884
<v Speaker 1>But when I've relied on tells, I've actually made really

0:41:07.924 --> 0:41:11.724
<v Speaker 1>big mistakes. Because I've had I've had a situations where

0:41:11.724 --> 0:41:13.764
<v Speaker 1>I'm like, oh, this person really likes their hand, they

0:41:13.844 --> 0:41:16.924
<v Speaker 1>must be really strong, and I end up folding. And

0:41:17.044 --> 0:41:19.484
<v Speaker 1>they had like ace deucee off suit, but there was

0:41:19.484 --> 0:41:21.044
<v Speaker 1>an ace on the board, and they thought that it

0:41:21.084 --> 0:41:24.484
<v Speaker 1>was just like the nuts, right, because they completely overvalued

0:41:24.524 --> 0:41:26.924
<v Speaker 1>the fact that they had an ace, and so they

0:41:26.924 --> 0:41:28.564
<v Speaker 1>were playing it like they had the nuts and they

0:41:28.604 --> 0:41:30.884
<v Speaker 1>thought they had the nuts, but they really didn't. So

0:41:30.924 --> 0:41:34.124
<v Speaker 1>if people are bad, don't use tells because the strength

0:41:34.764 --> 0:41:37.524
<v Speaker 1>their perceived strength of their hand may not actually be

0:41:37.604 --> 0:41:39.564
<v Speaker 1>the actual strength of their hands.

0:41:39.604 --> 0:41:44.204
<v Speaker 2>I'm more till it's funny because we had like opposite personnelity.

0:41:44.204 --> 0:41:46.404
<v Speaker 2>You're like way more sound theoretically, and I'm kind of

0:41:46.444 --> 0:41:51.364
<v Speaker 2>like psychoanalyzing people a little bit more. And no, look,

0:41:51.404 --> 0:41:55.684
<v Speaker 2>I think the premise are like two categories of tells

0:41:55.724 --> 0:42:00.724
<v Speaker 2>from very inexperienced players that I don't think I're always

0:42:00.724 --> 0:42:03.484
<v Speaker 2>hard to distinguish, but require additional context. Right, what is

0:42:03.524 --> 0:42:08.204
<v Speaker 2>a really bad actor tell right where they just are

0:42:08.244 --> 0:42:10.564
<v Speaker 2>like they watched like poker movies, We're supposed to act

0:42:11.084 --> 0:42:12.604
<v Speaker 2>if you're strong and starting every week and they just

0:42:12.644 --> 0:42:16.044
<v Speaker 2>really over knew it. In like a comical way, right, yeah,

0:42:16.044 --> 0:42:19.524
<v Speaker 2>and then I have seen that, but just sometimes people

0:42:19.564 --> 0:42:22.444
<v Speaker 2>are like extremely There's also there's a.

0:42:22.324 --> 0:42:25.684
<v Speaker 1>Lot of hollywooding actually, and I've seen this in uh

0:42:25.804 --> 0:42:28.524
<v Speaker 1>from amateur where like if you have the nuts right,

0:42:28.564 --> 0:42:32.284
<v Speaker 1>like say you flopped quads right or something like that,

0:42:32.564 --> 0:42:37.724
<v Speaker 1>and then they'll just be like the size and then

0:42:37.764 --> 0:42:41.644
<v Speaker 1>like I guess I call right like that if someone's

0:42:41.724 --> 0:42:43.884
<v Speaker 1>doing that, like holy shit, you're beat.

0:42:44.604 --> 0:42:47.964
<v Speaker 3>Like just there are there are certain situations like.

0:42:47.924 --> 0:42:51.444
<v Speaker 1>That, but I think in general it's it's better to

0:42:51.884 --> 0:42:53.004
<v Speaker 1>we haven't played.

0:42:52.764 --> 0:42:55.324
<v Speaker 3>In Hughes game or Hughes game.

0:42:55.964 --> 0:42:59.764
<v Speaker 1>So I think that just sticking to the advice that

0:42:59.764 --> 0:43:04.564
<v Speaker 1>that we've given, which is, you know, don't be lose passive. Basically,

0:43:04.764 --> 0:43:06.324
<v Speaker 1>you have to tighten up your ranges. You have to

0:43:06.324 --> 0:43:11.364
<v Speaker 1>figure out what those ranges are. And you know, the

0:43:11.364 --> 0:43:14.284
<v Speaker 1>the other thing is you know your bet sizing is

0:43:14.324 --> 0:43:16.004
<v Speaker 1>going to change, because if people are going to be

0:43:16.044 --> 0:43:18.924
<v Speaker 1>calling stations, great, exploit it. If people are going to

0:43:18.924 --> 0:43:22.124
<v Speaker 1>call pre flop anyway, great, make your sizes bigger. Just

0:43:22.604 --> 0:43:25.404
<v Speaker 1>build pots when you have very strong hands.

0:43:25.484 --> 0:43:27.204
<v Speaker 2>I mean the other thing, you know, to close this

0:43:27.284 --> 0:43:30.884
<v Speaker 2>cussing on tells I mean, people can also be very honest, right,

0:43:31.004 --> 0:43:35.764
<v Speaker 2>Like they don't you know, in games where the stakes

0:43:35.804 --> 0:43:38.964
<v Speaker 2>are low relative to people's like net worth, which depends

0:43:39.004 --> 0:43:42.444
<v Speaker 2>on people's net worth, right, then they just don't necessarily

0:43:42.524 --> 0:43:48.004
<v Speaker 2>take a lot of action to like conceal disappointment with

0:43:48.084 --> 0:43:52.404
<v Speaker 2>a bad flop or things like that. You know a

0:43:52.444 --> 0:43:53.924
<v Speaker 2>lot of times all I gotta catch my car like

0:43:53.964 --> 0:43:57.564
<v Speaker 2>that actually often is more than not honest, more in

0:43:57.644 --> 0:44:00.004
<v Speaker 2>cash games and in tournaments. I don't know why, right,

0:44:01.244 --> 0:44:04.644
<v Speaker 2>I think tournaments people like are just like playing their

0:44:04.844 --> 0:44:09.604
<v Speaker 2>A game a bit more Amit's secret of cash right more?

0:44:09.604 --> 0:44:12.604
<v Speaker 2>Playing their A game more often in tournaments at games.

0:44:12.524 --> 0:44:15.004
<v Speaker 1>Yeah, no, I actually I think I think there's something

0:44:15.004 --> 0:44:17.084
<v Speaker 1>too that people do tend to be more honest in

0:44:17.124 --> 0:44:19.964
<v Speaker 1>cash games. I had a hilarious situation at a higher

0:44:19.964 --> 0:44:23.724
<v Speaker 1>stakes cash game where I had raised and I don't

0:44:23.724 --> 0:44:25.804
<v Speaker 1>remember if it was small or big blind had defended

0:44:26.844 --> 0:44:32.244
<v Speaker 1>and anyway, went, you know, check bet on the flop,

0:44:33.404 --> 0:44:38.604
<v Speaker 1>then check and check on the turn and check and no, no,

0:44:38.644 --> 0:44:41.324
<v Speaker 1>not check And I was like looking to see like

0:44:41.444 --> 0:44:43.444
<v Speaker 1>I had nothing what I wanted to bet on the

0:44:43.524 --> 0:44:46.164
<v Speaker 1>river and he just folded. He's like, you definitely have

0:44:46.284 --> 0:44:49.444
<v Speaker 1>me beat, because like I've got nothing and I had nothing, right, Like,

0:44:49.484 --> 0:44:51.244
<v Speaker 1>I don't think I definitely had a beat, and he

0:44:51.364 --> 0:44:53.284
<v Speaker 1>just folded to me, right. I didn't even have to

0:44:53.284 --> 0:44:55.084
<v Speaker 1>think about the sizing or whether I was going to

0:44:55.124 --> 0:44:57.444
<v Speaker 1>bet or any of it. That would never happen in

0:44:57.484 --> 0:45:00.124
<v Speaker 1>a tournament, but it happens in cash games all the time.

0:45:00.164 --> 0:45:01.284
<v Speaker 3>And I still remember this hand.

0:45:01.284 --> 0:45:03.964
<v Speaker 1>I don't play cash very often, so things like that

0:45:04.044 --> 0:45:06.364
<v Speaker 1>stand out, but I've seen people do that and then

0:45:06.364 --> 0:45:07.964
<v Speaker 1>they try to do it in tournaments. Actually, you can

0:45:08.004 --> 0:45:10.724
<v Speaker 1>often spot a cash player a tournament because they will

0:45:10.764 --> 0:45:13.244
<v Speaker 1>sometimes fold out of turn. They'll do things that are

0:45:13.284 --> 0:45:16.484
<v Speaker 1>just like very honestly communicate that they have no more

0:45:16.524 --> 0:45:17.204
<v Speaker 1>interest in.

0:45:17.084 --> 0:45:21.364
<v Speaker 2>This hand and don't be a super knit right, like

0:45:21.444 --> 0:45:25.404
<v Speaker 2>to show people over value, especially in cash games, the

0:45:25.484 --> 0:45:27.604
<v Speaker 2>last thing they saw, right, So like if you have

0:45:27.724 --> 0:45:32.444
<v Speaker 2>like an occasional hand where you get a little out

0:45:32.444 --> 0:45:36.004
<v Speaker 2>of line, right, and again, I think you know usually

0:45:36.164 --> 0:45:38.804
<v Speaker 2>worth picking your spots carefully, and there's some psychology to that.

0:45:38.884 --> 0:45:40.964
<v Speaker 2>And then like if you show, oh, I three bit

0:45:41.084 --> 0:45:44.684
<v Speaker 2>five four suited from the button, which might actually be

0:45:44.724 --> 0:45:48.604
<v Speaker 2>a perfectly fine near gto three bed occasionally right, if

0:45:48.644 --> 0:45:52.164
<v Speaker 2>you turn as straight with that an the other guy folds.

0:45:52.204 --> 0:45:53.764
<v Speaker 2>You definitely want to show that hand right. You want

0:45:53.764 --> 0:45:57.604
<v Speaker 2>to like you're maintaining your reputation because, like a seat

0:45:57.644 --> 0:45:59.484
<v Speaker 2>in a good cash game is a valuable thing and

0:45:59.524 --> 0:46:02.644
<v Speaker 2>people absolutely will notice if you're being a knit. Don't

0:46:02.644 --> 0:46:03.044
<v Speaker 2>be a knit.

0:46:03.364 --> 0:46:03.564
<v Speaker 3>Yep.

0:46:03.604 --> 0:46:06.524
<v Speaker 2>Have fun, play toward the looser end of your GTO range.

0:46:06.844 --> 0:46:09.004
<v Speaker 2>How your GT arrange may actually be pretty tight against

0:46:09.684 --> 0:46:12.964
<v Speaker 2>phishing number fold yep, good luck you, good luck you.

0:46:19.764 --> 0:46:21.924
<v Speaker 2>Let us know what you think of the show. Reach

0:46:22.004 --> 0:46:26.484
<v Speaker 2>out to us at Risky Business at pushkin dot Fm.

0:46:26.644 --> 0:46:30.204
<v Speaker 2>Risky Business is hosted by me Maria Kondikova and byby

0:46:30.484 --> 0:46:31.004
<v Speaker 2>Nate Silver.

0:46:31.844 --> 0:46:35.364
<v Speaker 1>The show is a co production of Pushkin Industries and iHeartMedia.

0:46:35.884 --> 0:46:39.444
<v Speaker 1>This episode was produced by Isabel Carter. Our associate producer

0:46:39.524 --> 0:46:43.044
<v Speaker 1>is Gabriel Hunter Chang. Our executive producer is Jacob Goldstein.

0:46:43.484 --> 0:46:45.604
<v Speaker 2>If you like the show, please rate and review us

0:46:45.604 --> 0:46:47.684
<v Speaker 2>so other people can find us too. And if you

0:46:47.724 --> 0:46:50.084
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0:46:50.084 --> 0:46:52.484
<v Speaker 2>for Pushkin Plus. For We're six, ten and nine a

0:46:52.524 --> 0:46:55.004
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0:46:55.044 --> 0:46:55.444
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