WEBVTT - UL NO. 432: Can You Summarize Your Work in a Sentence?

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<v S1>get $1,000 off Vanta at Vanta comm slash unsupervised. That's vanta.com/unsupervised.

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<v S1>Welcome to Unsupervised Learning, a security, AI, and meaning focused

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<v S1>podcast that looks at how best to thrive as humans.

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<v S1>In a post AI world. It combines original ideas, analysis,

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<v S1>and mental models to bring not just the news, but

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<v S1>why it matters and how to respond. All right. Welcome

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<v S1>to unsupervised Learning. This is Daniel, episode 432. Can you

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<v S1>summarize your work in a sentence? All right. Lots of

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<v S1>stuff here. Got a new fabric pattern called git wow

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<v S1>per minute. This is basically like an estimation of the

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<v S1>value density of any piece of content. So what you

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<v S1>do is you essentially take the content and you send

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<v S1>it to this fabric pattern, and it'll give you a

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<v S1>score from 0 to 10. And if it's anything above

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<v S1>like a five, it's got really it's got decent value. Okay.

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<v S1>So 5 to 7 is like decent value and then

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<v S1>like eight, 9 or 10, 8 or 9 even is

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<v S1>like top. I've not seen a ten yet. So just

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<v S1>consider nine to be like the top. So it's like

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<v S1>how much value am I going to get for this thing?

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<v S1>And basically what it's doing is it's looking at novelty,

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<v S1>it's looking at insights, ideas, novelty, surprise and wisdom and

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<v S1>basically collecting all those together and saying those are all

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<v S1>instances of value. And then it's kind of putting all

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<v S1>those together into a score between 0 and 10, and

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<v S1>it is really working well. I put it through some

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<v S1>stuff that I knew was going to be weak sauce,

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<v S1>and it scored like a two or a three, and

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<v S1>I put it through a couple things that I knew

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<v S1>were super high value, and they scored eights and nines.

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<v S1>So highly recommend this if you want to like, test

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<v S1>your gut or use it programmatically for something to rate value.

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<v S1>And importantly, it's doing it value per time, right? So

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<v S1>that was key to me. So OpenAI did some cool

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<v S1>stuff on Monday. So new model the O stands for

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<v S1>Omni GPT four O. It's not a zero. It's not

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<v S1>GPT 40. And it's about as smart as four, but

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<v S1>four times faster and twice as cheap. So half the cost.

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<v S1>And the big thing is that it has vision capabilities

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<v S1>and better audio. And this is not fully released yet,

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<v S1>but what it's going to allow you to do is

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<v S1>basically just talk with it like a normal person. And

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<v S1>even better, they released a desktop app which will soon

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<v S1>have the capability of monitoring your screen. So I could

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<v S1>be like scrolling through this right now and just like

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<v S1>looking at stuff and it'll be like, oh yeah, so

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<v S1>here's this. Don't forget to mention this. I could say,

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<v S1>give me a summary of what's on the screen right now,

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<v S1>and it'll just talk to me. And even cooler is like,

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<v S1>if I'm looking at a data visualization or some math

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<v S1>or something, it could, like, walk me through that math.

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<v S1>It's just unbelievable. I've seen a couple of demos of this.

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<v S1>I'm not sure if they were internally built or if

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<v S1>they were third parties. Actually, I saw one by Khan

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<v S1>from the Khan Academy and he was walking his son

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<v S1>through like teaching him geometry. It's literally you're just talking

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<v S1>to this thing. And what's really crazy about this release

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<v S1>is that this is going to be for free users

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<v S1>as well. So they opened GPT four to free users,

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<v S1>which is absolutely incredible. And I'm just super excited about

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<v S1>this whole thing. It's it's really, really exciting. Again, one

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<v S1>of the things I've been talking about here with AI

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<v S1>stuff is that it's extraordinary when AI is used to

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<v S1>do things that everybody needs, but very few people have

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<v S1>access to, so that's creating movies, that's creating ideas, writing books,

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<v S1>but it's also things like getting a mole looked at,

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<v S1>most importantly, education. I mean, the education use case for

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<v S1>AI currently is insane. And it's really, really incredible when

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<v S1>you start doing this for Zero Vibe, where one they

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<v S1>made the whole model free. I'm not sure what the

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<v S1>usage is going to be for that. Hopefully it'll be decent,

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<v S1>but not only do they make it free, but it's interactive.

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<v S1>So you could literally just say teach me calculus, teach

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<v S1>me this infinite patience. It doesn't get mad at you.

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<v S1>In fact, it now detects emotions, so if it hears

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<v S1>you getting frustrated, it's going to be like, hey, let's

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<v S1>slow down. Let me explain it in a different way.

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<v S1>Let me use an analogy that is unbelievable. We're talking

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<v S1>about massively multiplying the percentage of people on this planet

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<v S1>who are educated because they have access to an extremely

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<v S1>high quality superhuman intelligence, superhuman patience, tutor everyone in the

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<v S1>world having access to this. And I'm not sure everyone

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<v S1>in the world has access to GPT yet. And of course,

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<v S1>you need a computer and you need internet. So that's

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<v S1>not exactly true, but the barrier is massively lower as

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<v S1>a result of this. It's just unbelievably positive and awesome.

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<v S1>And obviously that doesn't take away any of the negatives

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<v S1>or the dangers or the alignment problem or superintelligence. Like

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<v S1>we've got issues coming up, no question. But the positives

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<v S1>are just undeniable. And this model becoming. Free. I mean,

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<v S1>and having these interactive conversation capabilities and emotion detection. Just unbelievable.

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<v S1>I predicted there would be more agent stuff, which I

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<v S1>think that will be coming soon. I still believe in

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<v S1>these predictions, not so much about like what OpenAI specifically

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<v S1>is going to do. I'm making broader predictions about what

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<v S1>OpenAI and anthropic and probably Google and all other people

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<v S1>will do, which is essentially moving prompts into or no

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<v S1>moving agents into prompts. So basically, prompting is the most

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<v S1>natural way to interact with an AI, and I believe

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<v S1>that it's the most natural place to build agents as well.

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<v S1>In fact, you'll just describe what you want. Like I

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<v S1>want a team of 100 people creating ideas. I want

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<v S1>a team of ten people filtering through those ideas to

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<v S1>figure out the best ones. In fact, you won't even

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<v S1>have to say 100 or 10. It'll just figure out

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<v S1>based on how much money you have to spend, based

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<v S1>on how much time you have and the time constraints

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<v S1>and your deadline or whatever. It'll spin up more, spin

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<v S1>up more or fewer based on all those constraints, right?

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<v S1>So when you say, I need a team of people

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<v S1>to do this, a team of people to do that,

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<v S1>team of people to do this, then I need the

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<v S1>final result to be rated and tested and validated. It'll

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<v S1>just go and build all those pieces, which are actually

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<v S1>teams of agents all collaborating together. And all you had

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<v S1>to do was put that in the prompt. And that's

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<v S1>why I think prompting is everything. It's an article I

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<v S1>wrote earlier called prompting. Most of AI is prompting or

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<v S1>something like that a couple of weeks ago or a

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<v S1>week ago. So I would check that one out. And yeah,

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<v S1>they got a desktop app. And yeah, they basically created

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<v S1>digital assistants, which I've got a book out from 2016

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<v S1>that was basically talking about this. And it's also in

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<v S1>the Predictable Path video, which you might have seen, which

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<v S1>is kind of like an updated visual version of that book,

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<v S1>but with lots of new stuff, because I didn't know

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<v S1>about Gen AI back in 2016, obviously, but they basically

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<v S1>built her. Not only did they built her from the movie,

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<v S1>but they're also using for the demos the voice that

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<v S1>I use for my personal AI with OpenAI, which is Skylar,

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<v S1>which is the voice of Scarlett Johansson, essentially. I doubt

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<v S1>that it actually is, but maybe it is. Maybe she

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<v S1>got paid for this. RSA was fantastic. Really good. Caught

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<v S1>up with a lot of people, did a couple of

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<v S1>talks and panels. Probably should have brought something to sell.

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<v S1>I didn't really like go in there trying to sell anything,

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<v S1>which I guess I should have. But I did talk

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<v S1>a little bit about threshold, so that was cool. The

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<v S1>energy and optimism around RSA was extraordinary. I think this

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<v S1>is largely in part to AI, and there were tons

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<v S1>of products talking about how much they're using AI and

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<v S1>everything like that. So we've all made those jokes already.

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<v S1>But speaking of threshold, holy crap, I am absolutely in

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<v S1>love with this product. Okay, I am in love with

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<v S1>this product. And yes, it is a paid product and

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<v S1>it is my product. But look at this. This is

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<v S1>my current feed right now. I didn't plan on showing this,

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<v S1>but whatever. So how do I blow this up? Yeah.

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<v S1>So how to cope with the fear of aging? I

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<v S1>haven't looked at that one yet. 2025 models will be

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<v S1>more like coworkers than than search engines. Again, this I

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<v S1>did not explicitly go follow this person. What is this?

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<v S1>This is. Uh dwarkesh.

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<v S2>I think in 1 or 2 years we'll find that

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<v S2>you can use.

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<v S1>So this is Dwarkesh Patel, who's doing these interviews, and

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<v S1>he's talking to really smart people about AI or whatever.

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<v S1>He's talking about lots of different things. But this particular

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<v S1>conversation is about coworkers and search engines and AGI and

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<v S1>like all this super interesting topics. But here's the thing, okay?

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<v S1>In order to show this to me, it came into

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<v S1>the top of threshold and all my different AI stuff

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<v S1>ran against it to assess it and determine what the

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<v S1>content was and how high quality the content was, and

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<v S1>it had to be above a certain threshold in order

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<v S1>for it to even show up. Now I have it

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<v S1>set to 50, which is the minimum because I want

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<v S1>to see a lot of content, but I can move

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<v S1>this up and I could turn off a lot of

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<v S1>these things here. This is the first time I've actually

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<v S1>showing threshold kind of interesting. So I can move those

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<v S1>and I can say save and then look at this

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<v S1>completely change the feed. But now it has to be

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<v S1>above an 80 and it has to be in these

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<v S1>categories or these categories have to apply. So just I

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<v S1>mean every single thing listen to me, every single thing

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<v S1>I click on here, I love I absolutely love it.

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<v S1>And I don't have to stress about oh did I

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<v S1>watch all the. Tests, from leks and from Huberman and

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<v S1>all these different people and all these different I people. No,

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<v S1>I just put them into the top of the funnel.

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<v S1>I put them into the top of the funnel for threshold,

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<v S1>and the whole I pipeline runs against it and I

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<v S1>get the analysis. Oh, and I forgot to mention watch this. Okay,

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<v S1>this is the sickest video. I want to talk about

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<v S1>this anyway. So this is the sickest business video that

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<v S1>I've ever seen and I forget how long it is.

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<v S1>Soon we're going to have duration things in here. But

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<v S1>watch this. If I go click on the video, obviously

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<v S1>it's going to open up.

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<v S3>In the engineering room and said these.

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<v S1>Basically this guy Alex talking about stuff for an hour

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<v S1>and 29 minutes okay. It is fantastic. But watch this.

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<v S1>I could go like this. This is a major feature

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<v S1>of threshold that no other platform has. You click on

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<v S1>it and it tells you a summary of it, the

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<v S1>ideas and a recommendation, and it gives you a review

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<v S1>of it so you don't even have to go watch

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<v S1>it if you don't want. But watch this. That was

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<v S1>surface level. Watch this. If I go to middle level,

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<v S1>gives me a deeper summary. It breaks out more ideas

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<v S1>and more recommendations. And if I go to deep level

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<v S1>auto updates, summary, core ideas, core recommendations. Unbelievable. I mean,

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<v S1>I've always wanted this and that's why we actually created it.

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<v S1>I've always wanted this as a tool and the stuff

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<v S1>that we're about to be adding to this, the I'm

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<v S1>not even going to talk about that yet, but insane

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<v S1>stuff along the lines of everything I've been talking about

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<v S1>for this last year and a half with with AI

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<v S1>content rating, all that stuff like the new features that

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<v S1>are coming are just going to be insane. And again,

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<v S1>the guiding light that I'm using here, like I haven't

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<v S1>raised any VC money. I'm not worried about investors. I'm

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<v S1>worried about making the best possible tool for me. And

0:12:54.950 --> 0:12:58.100
<v S1>this is the tool that I've always needed, and that's

0:12:58.100 --> 0:13:00.620
<v S1>why it exists. And of course, when people are like, hey,

0:13:00.620 --> 0:13:02.960
<v S1>I wish I had this. Well, if it's something that

0:13:02.960 --> 0:13:05.870
<v S1>really resonates with me and I think everyone's going to love,

0:13:05.870 --> 0:13:07.790
<v S1>then yeah, we put that into the pipeline and we

0:13:07.790 --> 0:13:11.090
<v S1>actually build that. But ultimately it's it's a thing that

0:13:11.090 --> 0:13:14.390
<v S1>solves a problem that I've had of collecting as much

0:13:14.390 --> 0:13:18.229
<v S1>information as possible, as high quality as possible, but at

0:13:18.230 --> 0:13:21.380
<v S1>a threshold level that I could control the flow. So

0:13:21.380 --> 0:13:23.120
<v S1>I could basically go in here and say, you know what,

0:13:23.120 --> 0:13:25.309
<v S1>I need it to be a 90 or a higher,

0:13:25.309 --> 0:13:28.309
<v S1>and I want it to be only about AI. So

0:13:28.309 --> 0:13:32.120
<v S1>watch this. And that pulls it down even further. It's

0:13:32.120 --> 0:13:36.410
<v S1>just it's just unbelievably useful. So that's my pitch for that.

0:13:36.410 --> 0:13:40.280
<v S1>It is a paid thing. So yeah. Whatever. Is that

0:13:40.280 --> 0:13:42.500
<v S1>even called a sponsor post. Is it a sponsor if

0:13:42.500 --> 0:13:44.990
<v S1>it's your own product? I have no idea. But anyway,

0:13:44.990 --> 0:13:47.780
<v S1>highly worth it. I would pay thousands of dollars per

0:13:47.780 --> 0:13:51.920
<v S1>year to buy this product. No joke, I absolutely would.

0:13:51.920 --> 0:13:54.470
<v S1>Oh yeah, and this is the email. So I have

0:13:54.470 --> 0:13:56.780
<v S1>it set to a daily email. So you get this

0:13:56.809 --> 0:13:59.720
<v S1>email that basically shows you the stuff. Because sometimes like

0:13:59.720 --> 0:14:01.610
<v S1>I'll forget to check, I'll just be super busy in

0:14:01.610 --> 0:14:04.190
<v S1>meetings or whatever, and I'll be super busy. And then

0:14:04.190 --> 0:14:06.410
<v S1>at the end of the day I get this, look

0:14:06.410 --> 0:14:08.990
<v S1>at these. How strong is AI as a tool, as

0:14:08.990 --> 0:14:12.800
<v S1>a successor? Deferred happiness syndrome? This thing is unbelievable. And

0:14:12.800 --> 0:14:15.050
<v S1>then I click on view right here and it goes

0:14:15.050 --> 0:14:17.179
<v S1>yeah this is the business truth one. That's how I

0:14:17.179 --> 0:14:19.940
<v S1>found that video. Also from what's it called. This is

0:14:19.940 --> 0:14:23.060
<v S1>from Peter Attia on VO2 max and muscle mass. Anyway

0:14:23.060 --> 0:14:26.690
<v S1>it's it's fantastic. I just love it. I got a

0:14:26.690 --> 0:14:32.180
<v S1>sponsored conversation had with BlackBerry and Cary Ransom about maritime security.

0:14:32.180 --> 0:14:35.720
<v S1>My dad just went on a podcast in, uh, in

0:14:35.720 --> 0:14:38.600
<v S1>a studio in San Francisco. I was actually giving a

0:14:38.600 --> 0:14:41.060
<v S1>talk a couple of blocks away. My dad's in the

0:14:41.060 --> 0:14:45.170
<v S1>studio talking about his music, showing his music, just really,

0:14:45.170 --> 0:14:47.510
<v S1>really cool. And I got a link here to the

0:14:47.510 --> 0:14:50.690
<v S1>full show, which is this one or no, this one.

0:14:50.690 --> 0:14:53.360
<v S1>And then this one is him playing one of my

0:14:53.360 --> 0:14:56.990
<v S1>favorite songs that he's ever written called children of the nights,

0:14:56.990 --> 0:15:00.680
<v S1>and you definitely want to check that one out. It's fantastic.

0:15:00.680 --> 0:15:04.130
<v S1>And security Dell got hacked real bad through an API.

0:15:04.130 --> 0:15:06.620
<v S1>I think if I could invest in any sort of

0:15:06.620 --> 0:15:11.540
<v S1>legacy non-ai tech, which I guess it's quite AI related

0:15:11.540 --> 0:15:13.310
<v S1>at this point. And that's kind of the point, is

0:15:13.310 --> 0:15:17.390
<v S1>that API security is like everything, because everything is becoming

0:15:17.390 --> 0:15:22.550
<v S1>APIs that get wielded by AI, and your company is

0:15:22.550 --> 0:15:26.810
<v S1>essentially about to be mostly your API. So you've got

0:15:26.810 --> 0:15:28.760
<v S1>to lock that down. So I feel like of all

0:15:28.760 --> 0:15:31.430
<v S1>the traditional security spaces that I would want to be

0:15:31.430 --> 0:15:33.260
<v S1>in right now, which I don't want to be in

0:15:33.260 --> 0:15:35.180
<v S1>any of them, but if I did, it would probably

0:15:35.180 --> 0:15:38.630
<v S1>be API security. And speaking of that, my buddy Joseph

0:15:38.630 --> 0:15:41.720
<v S1>Thacker has put out a couple of different pieces about

0:15:41.720 --> 0:15:47.390
<v S1>API security assumptions about AI, and also one about agents

0:15:47.390 --> 0:15:51.830
<v S1>and authentication. So check that out. Both of those and

0:15:51.830 --> 0:15:54.920
<v S1>CSA has a new alert system. They're basically allowing companies

0:15:54.920 --> 0:15:59.210
<v S1>to sign up. And then they send them Kev alerts

0:15:59.210 --> 0:16:02.510
<v S1>if they see something associated with their company. Attackers are

0:16:02.510 --> 0:16:07.220
<v S1>using Microsoft Graphs API for malware comms. I love these

0:16:07.220 --> 0:16:11.270
<v S1>side channel things, I just. Absolutely love them where you could, like,

0:16:11.270 --> 0:16:14.840
<v S1>use something in a way that's not expected. The best

0:16:14.840 --> 0:16:19.100
<v S1>example of this that I remember is Gmail drafts. You actually,

0:16:19.100 --> 0:16:22.400
<v S1>you you have a shared email account. You create a

0:16:22.400 --> 0:16:25.910
<v S1>draft on one side, you don't send the email, and

0:16:25.910 --> 0:16:28.700
<v S1>then someone else has access to that email account and

0:16:28.700 --> 0:16:32.030
<v S1>they just log in and read the draft so the

0:16:32.030 --> 0:16:35.450
<v S1>email never gets sent. So that's another example of just

0:16:35.450 --> 0:16:39.050
<v S1>like using a a platform in a way that's sneaky.

0:16:39.080 --> 0:16:43.430
<v S1>All right. So one password. Thank you for sponsoring. That's

0:16:43.430 --> 0:16:50.240
<v S1>Collidin one password and Russian influence campaign looking at magnifying

0:16:50.240 --> 0:16:55.190
<v S1>and taking advantage of the campus protests. Google's making MFA

0:16:55.190 --> 0:16:59.150
<v S1>setup smoother by letting you skip phone number for options

0:16:59.150 --> 0:17:03.109
<v S1>like authenticator or keys. Marines are testing robot dogs with

0:17:03.110 --> 0:17:10.040
<v S1>AI aimed rifles. Awesome awesome awesome awesome 95% of international

0:17:10.040 --> 0:17:14.179
<v S1>data travels through undersea cables. Okay, so this is one

0:17:14.180 --> 0:17:19.909
<v S1>that's really interesting. I've never understood why undersea cables weren't

0:17:19.910 --> 0:17:23.450
<v S1>more targeted and just like totally abused by terrorists. I

0:17:23.450 --> 0:17:26.209
<v S1>guess there is the small matter of like you're in

0:17:26.210 --> 0:17:29.540
<v S1>a boat, you're way, way above this cable. It takes

0:17:29.540 --> 0:17:32.450
<v S1>time and money and skill to get down there. So

0:17:32.450 --> 0:17:35.720
<v S1>I guess that's a barrier. But once you're down there,

0:17:35.720 --> 0:17:39.500
<v S1>Holy crap. I mean, it seems pretty easy to do

0:17:39.500 --> 0:17:42.590
<v S1>damage to these things, and the amount of disruption you

0:17:42.590 --> 0:17:47.359
<v S1>could do if you're disrupting international internet traffic is is

0:17:47.359 --> 0:17:51.650
<v S1>pretty serious. Plus, you think this has got to get easier. Like,

0:17:51.650 --> 0:17:54.949
<v S1>if you can send drones down there like underwater water,

0:17:54.950 --> 0:18:00.140
<v S1>drones with like explosives, this wouldn't be easy for low

0:18:00.140 --> 0:18:03.710
<v S1>level attackers to do. But for a state actor to

0:18:03.710 --> 0:18:08.060
<v S1>want to just continuously like send drones after it or

0:18:08.060 --> 0:18:11.330
<v S1>teams or whatever, it seems so easy for any state

0:18:11.330 --> 0:18:18.320
<v S1>actor to basically sever internet communications through undersea cables. And

0:18:18.320 --> 0:18:22.940
<v S1>the US just closed another door essentially for Huawei getting

0:18:22.940 --> 0:18:28.129
<v S1>AI stuff with Intel chips. So another attack against the

0:18:28.130 --> 0:18:33.980
<v S1>Chinese trying to get AI chips. And someone from Andreessen

0:18:33.980 --> 0:18:37.850
<v S1>Horowitz basically says half a Google staff or just pretending

0:18:37.880 --> 0:18:40.490
<v S1>to work, they're not actually doing anything. Yeah, and a

0:18:40.490 --> 0:18:43.940
<v S1>lot of people are talking about this trend of fake work,

0:18:43.940 --> 0:18:46.639
<v S1>and I think it's a giant mess. It's fake in

0:18:46.640 --> 0:18:49.850
<v S1>multiple ways. Right. So I talked about David Graeber's bullshit

0:18:49.850 --> 0:18:52.910
<v S1>Jobs book. Really, really good. Basically, we have all these

0:18:52.910 --> 0:18:56.150
<v S1>jobs that shouldn't exist. You have all these people with

0:18:56.150 --> 0:19:03.200
<v S1>massive salaries, hardly doing anything and somehow being justified, especially

0:19:03.200 --> 0:19:05.869
<v S1>in Google where like they're not making much new stuff

0:19:05.869 --> 0:19:10.450
<v S1>at all. Because they don't have a product management focused

0:19:10.450 --> 0:19:14.919
<v S1>product teams. They're just like engineering focused teams. It's a

0:19:14.920 --> 0:19:17.679
<v S1>total mess. And you add AI to this and it's

0:19:17.680 --> 0:19:21.010
<v S1>just it's going to be a total mess. The safest

0:19:21.010 --> 0:19:23.980
<v S1>thing to do, in my opinion, the safest place to

0:19:23.980 --> 0:19:28.480
<v S1>be is building new things, creating new things. Be a programmer,

0:19:28.480 --> 0:19:31.930
<v S1>definitely be a programmer. But more so be a thinker

0:19:31.930 --> 0:19:37.179
<v S1>who focuses on problems. Solve those problems. Have the tech skills.

0:19:37.180 --> 0:19:40.900
<v S1>Have the humanities skills. You want to be broad. You

0:19:40.900 --> 0:19:44.620
<v S1>want to be general. I recommend everyone has tech skills.

0:19:44.619 --> 0:19:49.150
<v S1>Everyone has programming skills. Everyone has AI skills. Everyone has

0:19:49.150 --> 0:19:53.350
<v S1>writing and speaking and presentation skills. These are like the universals,

0:19:53.350 --> 0:19:56.560
<v S1>and I'm actually working on a big post around this,

0:19:56.560 --> 0:19:59.470
<v S1>which is going to be a member post around this.

0:19:59.470 --> 0:20:01.870
<v S1>That's going to be super key of like how to

0:20:01.869 --> 0:20:05.830
<v S1>get ready for what's coming, what skills you need. So

0:20:05.830 --> 0:20:09.220
<v S1>that's pretty much a teaser for that. Mitra is partnering

0:20:09.220 --> 0:20:14.020
<v S1>with Nvidia to create a $20 million AI supercomputer to

0:20:14.020 --> 0:20:18.760
<v S1>to make US government operations more efficient, which is cool

0:20:18.760 --> 0:20:24.520
<v S1>and terrifying. Joe Biden is converting the Foxconn debacle, which

0:20:24.520 --> 0:20:28.870
<v S1>didn't go well in Wisconsin into a $3.3 billion Microsoft

0:20:28.869 --> 0:20:33.160
<v S1>AI center. I feel like this administration is doing well

0:20:33.190 --> 0:20:36.909
<v S1>on AI, both in countering China but also building ourselves up.

0:20:36.910 --> 0:20:41.169
<v S1>And the acquired podcast is basically like biographies of people,

0:20:41.170 --> 0:20:43.600
<v S1>except for it's for companies. So a lot of people

0:20:43.600 --> 0:20:46.090
<v S1>are super into that. In the Bay area, Biden is

0:20:46.090 --> 0:20:49.360
<v S1>quadrupling tariffs on Chinese EVs. These things are a real

0:20:49.359 --> 0:20:52.899
<v S1>threat to the American car industry. So he's going to

0:20:52.900 --> 0:20:58.210
<v S1>tariff them quite a bit. This one said 400% but quadrupling. Yeah,

0:20:58.210 --> 0:21:02.439
<v S1>this one said quadrupling. But I've seen it say doubling.

0:21:02.440 --> 0:21:05.320
<v S1>So I'm not sure the exact numbers. But he's definitely

0:21:05.320 --> 0:21:09.070
<v S1>increasing the tariffs. California is going to start charging your

0:21:09.070 --> 0:21:13.870
<v S1>bill for electricity based on your income starting in 2025.

0:21:13.960 --> 0:21:19.210
<v S1>Scientists have found all DNA and RNA bases in meteorites,

0:21:19.540 --> 0:21:23.919
<v S1>basically hinting that building blocks might be extraterrestrial. This is

0:21:23.920 --> 0:21:26.800
<v S1>not surprising in the slightest. To me, it just seems

0:21:26.800 --> 0:21:30.850
<v S1>logical and there's life floating around everywhere. I don't think

0:21:30.850 --> 0:21:36.670
<v S1>life is that special. In one characterization of special in

0:21:36.670 --> 0:21:40.179
<v S1>terms of special of like, oh, we're we're a snowflake

0:21:40.180 --> 0:21:42.100
<v S1>and we're the only ones who have it. I don't

0:21:42.100 --> 0:21:44.470
<v S1>think we're special in that way. That does not mean

0:21:44.470 --> 0:21:50.440
<v S1>it's not special in terms of having high, interesting, unique value.

0:21:50.440 --> 0:21:53.470
<v S1>I think we absolutely have. That doesn't mean it has

0:21:53.470 --> 0:21:56.140
<v S1>to be unique. Does it mean it has to be

0:21:56.140 --> 0:21:59.890
<v S1>one of a kind? Okay. Scientists constructed a one millimetre

0:21:59.890 --> 0:22:06.220
<v S1>square piece of the human cerebral cortex at a nanoscale resolution.

0:22:06.220 --> 0:22:09.939
<v S1>So they basically get to see the actual neurons and

0:22:09.940 --> 0:22:13.300
<v S1>I believe synapses as well. I haven't looked at this

0:22:13.300 --> 0:22:16.450
<v S1>document fully yet or this image fully yet. I'm not

0:22:16.450 --> 0:22:19.240
<v S1>sure I would even understand it, but I love the

0:22:19.240 --> 0:22:20.860
<v S1>fact that we could see that. I love the fact

0:22:20.859 --> 0:22:24.189
<v S1>that it's only one millimetre square and we're getting all that,

0:22:24.369 --> 0:22:28.180
<v S1>all those, you know, millions of different cells and neurons

0:22:28.180 --> 0:22:32.440
<v S1>and everything in there. The study says very large study,

0:22:32.470 --> 0:22:39.100
<v S1>154 million deaths prevented due to vaccines. Streaming is basically cable.

0:22:39.100 --> 0:22:42.700
<v S1>Now there's a racket around emotional support animals. That was

0:22:42.700 --> 0:22:48.070
<v S1>quite hilarious and disturbing. And I think Mark Andreessen is

0:22:48.070 --> 0:22:54.369
<v S1>mistaken about paradox applying to AI. This this podcast here.

0:22:54.369 --> 0:22:57.970
<v S1>He basically says that AI will not make it easier

0:22:57.970 --> 0:23:02.770
<v S1>to build companies because of Jevons Paradox, which basically says

0:23:02.770 --> 0:23:07.540
<v S1>that you think if you make roads wider, it would

0:23:07.540 --> 0:23:10.240
<v S1>reduce the amount of traffic, but in fact it just

0:23:10.240 --> 0:23:14.140
<v S1>makes more people drive on them, which actually increases traffic.

0:23:14.140 --> 0:23:19.810
<v S1>Now Mark basically said, well, I think that means that

0:23:19.900 --> 0:23:23.830
<v S1>AI making it easier to start a company will make

0:23:23.830 --> 0:23:26.740
<v S1>it actually harder to start a company because more people

0:23:26.740 --> 0:23:29.770
<v S1>will be doing it and the standard will be higher.

0:23:29.770 --> 0:23:33.879
<v S1>And I think he is misunderstanding that. And so basically

0:23:33.880 --> 0:23:36.340
<v S1>what I say about that is it's only when it's

0:23:36.340 --> 0:23:41.650
<v S1>a resource. Jevons paradox applies to a resource. It basically

0:23:41.650 --> 0:23:46.510
<v S1>says if you make that thing cheaper, it won't reduce

0:23:46.510 --> 0:23:50.500
<v S1>the total amount of usage across the world because more

0:23:50.500 --> 0:23:53.409
<v S1>people will use it. So usage actually goes up. That's

0:23:53.410 --> 0:23:56.920
<v S1>the limit of the paradox, at least as I understand it.

0:23:56.920 --> 0:24:01.540
<v S1>And the situation with AI helping startups is actually a

0:24:01.540 --> 0:24:04.600
<v S1>friction issue. It's reducing friction to get into the market.

0:24:04.600 --> 0:24:07.130
<v S1>It's not about there's only so. Much of X or

0:24:07.130 --> 0:24:10.250
<v S1>so much of Y, and if it were, the thing

0:24:10.250 --> 0:24:13.400
<v S1>that would be talking about is there's only so much energy.

0:24:13.520 --> 0:24:17.000
<v S1>There's only so much compute. So that's a limited resource

0:24:17.000 --> 0:24:20.570
<v S1>that would actually apply to Jevons paradox, but not friction

0:24:20.570 --> 0:24:22.669
<v S1>of getting into a market. So I think he was

0:24:22.670 --> 0:24:25.850
<v S1>wrong about that. And that basically cleared that up. Courage

0:24:25.850 --> 0:24:29.960
<v S1>is everything I've been throwing around this three level system here.

0:24:29.960 --> 0:24:34.490
<v S1>Courage is action versus fear. Discipline is courage versus laziness.

0:24:34.490 --> 0:24:36.410
<v S1>You see how they build on each other. This one

0:24:36.410 --> 0:24:41.119
<v S1>is this one. And then success is discipline versus mediocrity.

0:24:41.119 --> 0:24:44.390
<v S1>So it goes from courage to discipline to success. So

0:24:44.390 --> 0:24:46.910
<v S1>everything you want is on the other side of courage,

0:24:46.910 --> 0:24:51.229
<v S1>whether it's courage against fear or courage against laziness. And

0:24:51.230 --> 0:24:53.930
<v S1>this applies to all sorts of real life situations. So

0:24:53.930 --> 0:24:58.430
<v S1>it's like hard conversations, you know, getting more healthy, eating right,

0:24:58.460 --> 0:25:01.939
<v S1>not wasting time doing the wrong things, or quitting a

0:25:01.940 --> 0:25:04.609
<v S1>soul crushing job. So if you're trying to quit a job,

0:25:04.609 --> 0:25:07.100
<v S1>it's like you're scared if you're eating right, it's a

0:25:07.100 --> 0:25:10.430
<v S1>matter of discipline becoming fit. It's a matter of discipline.

0:25:10.430 --> 0:25:12.530
<v S1>You got to go to the gym. You got to,

0:25:12.560 --> 0:25:15.500
<v S1>you know, eat right. You got to exercise. Not wasting

0:25:15.500 --> 0:25:18.470
<v S1>so much time with games. It also discipline, having a

0:25:18.470 --> 0:25:22.100
<v S1>hard conversation. That's courage. I guess what I'm saying here

0:25:22.100 --> 0:25:24.470
<v S1>is all of these can be thought of as courage.

0:25:24.470 --> 0:25:27.740
<v S1>And what I'm trying to do here is build a frame.

0:25:27.740 --> 0:25:29.570
<v S1>I want to build a frame that says when I'm

0:25:29.570 --> 0:25:32.930
<v S1>being lazy, I'm not being courageous. So I want to

0:25:32.930 --> 0:25:37.040
<v S1>frame this to myself as have the courage to not

0:25:37.040 --> 0:25:40.550
<v S1>be lazy, have courage to go to the gym. So

0:25:40.550 --> 0:25:44.570
<v S1>if I'm presenting that as there's somebody to go save

0:25:44.570 --> 0:25:47.149
<v S1>in a fire and I'm going to get burnt and

0:25:47.150 --> 0:25:51.530
<v S1>that inflames my my interest to be a moral person, well,

0:25:51.530 --> 0:25:54.200
<v S1>that can motivate me. I will walk through that fire

0:25:54.200 --> 0:25:57.380
<v S1>to go do that thing because that's what my identity is.

0:25:57.380 --> 0:26:00.080
<v S1>I want that to be my identity. And it is.

0:26:00.080 --> 0:26:03.620
<v S1>So that's the thing I want to do now. I

0:26:03.619 --> 0:26:06.740
<v S1>don't naturally, and most of us don't naturally have that

0:26:06.740 --> 0:26:09.320
<v S1>for going to the gym. It's not a moral issue.

0:26:09.320 --> 0:26:12.080
<v S1>I want to turn it into a moral issue. I

0:26:12.080 --> 0:26:14.389
<v S1>want to frame it as a moral issue so that

0:26:14.390 --> 0:26:16.490
<v S1>I'm like, look, oh, you don't want to go to

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<v S1>the gym. Okay, well, that's because I don't want to

0:26:20.150 --> 0:26:22.730
<v S1>use bad language, but I basically want to talk to

0:26:22.730 --> 0:26:26.000
<v S1>myself in this bad language of, you know, man up,

0:26:26.000 --> 0:26:29.209
<v S1>go do it, have the courage to do the right thing.

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<v S1>And I think that can massively help. Recommendation of the week.

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<v S1>Know yourself. Think about what someone should say when they

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<v S1>introduce you. So this is Sarah. Sarah does this do

0:26:41.060 --> 0:26:43.610
<v S1>you want them to say about Sarah? What do you

0:26:43.609 --> 0:26:46.730
<v S1>want them to say about you? Mine is something like

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<v S1>he has a company that builds products and services that

0:26:49.070 --> 0:26:53.780
<v S1>help people transition to something called human 3.0, so they

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<v S1>can survive what's happening and thrive with what's happening with AI.

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<v S1>It's something like that, and it's different for different audiences.

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<v S1>But that's the basic vibe. And you basically want to

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<v S1>know what this is for you, not only so that

0:27:08.150 --> 0:27:10.700
<v S1>you can deliver it, but that other people can do

0:27:10.700 --> 0:27:13.129
<v S1>it when you're not there. And the aphorism for the

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<v S1>week where your fear is, there's your task. Where your

0:27:17.750 --> 0:27:24.200
<v S1>fear is, there is your task. Carl Jung. Unsupervised Learning

0:27:24.200 --> 0:27:26.840
<v S1>is produced and edited by Daniel Meisler on a Neumann

0:27:26.840 --> 0:27:31.430
<v S1>U87 AI microphone using Hindenburg. Intro and outro music is

0:27:31.430 --> 0:27:34.669
<v S1>by zombie with the why and to get the text

0:27:34.670 --> 0:27:36.830
<v S1>and links from this episode, sign up for the newsletter

0:27:36.830 --> 0:27:42.199
<v S1>version of the show at Daniel meisler.com/newsletter. We'll see you

0:27:42.200 --> 0:27:42.830
<v S1>next time.