WEBVTT - UL NO. 484: STANDARD EDITION: OpenAI's Malicious AI Report, Disappointed with WWDC, AI's First Actual Science Breakthrough, and more...

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<v S1>All right. Really excited about this episode. Like I said, uh,

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<v S1>in the newsletter, I think it is one of my

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<v S1>favorite episodes ever. Actually. Last few. I've been feeling really

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<v S1>good about. I love the way the links are working out. So, uh,

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<v S1>if you want to give back any positive feedback, I

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<v S1>would appreciate it. But, uh, let's get into it. Let's

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<v S1>see here. All right. I ordered some noise canceling earbuds.

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<v S1>I haven't unpacked them yet, but, uh, they're for sleeping.

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<v S1>And basically I'm going to try to put them in,

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<v S1>and you can either stream music to them or you

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<v S1>can stream, like, white or brown noise, or you could

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<v S1>just have them noise cancel. And the idea is if

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<v S1>you combine that with like an eye mask, which I

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<v S1>already wear, then it's supposed to really help with sleep.

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<v S1>So I'm going to see. I know a few people

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<v S1>who do both and I just want to try it out.

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<v S1>I did a huge blog post called Why Google I

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<v S1>o scared this 2007 Apple fanboy for the first time,

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<v S1>and it's basically a review of WD DC juxtaposed with

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<v S1>Google I o, which was a couple weeks back. And yeah,

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<v S1>I've been an Apple fanboy for I mean, I mean,

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<v S1>I guess acolyte. I don't really like the word fanboy,

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<v S1>but yeah, really drinking the Apple Kool-Aid for a very

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<v S1>long time. And if you're listening to this, you probably

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<v S1>already know that. But, um, I like to think that

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<v S1>I'm logical about it, but I'm already admitting to being biased. Uh,

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<v S1>so that's what being an acolyte is, right? But what

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<v S1>I saw essentially this year at Google, I o is

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<v S1>it seemed like they are switching to Gemini and I

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<v S1>in general to be like their core mission. I feel

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<v S1>like they're moving away from ads. I feel like they're

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<v S1>moving away from that, being like the future in the

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<v S1>center of their business to like data and AI being

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<v S1>the center of their business. And I think this is really,

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<v S1>really cool on on their part. And I feel like

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<v S1>Google I o they did so well because of that

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<v S1>integration right there talking about integration with glasses and, you know,

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<v S1>XR or AR or whatever they're calling it, and Gemini

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<v S1>being integrated in like all the different apps. So it

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<v S1>just felt like they're doing something new and they're doing

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<v S1>something different. I've always been kind of averse to Google

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<v S1>because they are fundamentally an ad company, or they were

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<v S1>fundamentally an ad company. And I really like the CEO.

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<v S1>I feel like he gets it. I feel like it's

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<v S1>not gross. I don't feel like he's gross. I don't

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<v S1>feel like he's there to maximize ad revenue. I think

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<v S1>he really gets the AI stuff. So my perception of

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<v S1>Google has overall just like improved, I would say over

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<v S1>the last say year or two. just in the context

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<v S1>of them switching to this AI model as opposed to

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<v S1>like an advertising model now. Then you have Apple, which,

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<v S1>like I said, I'm massively biased towards. I love their stuff.

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<v S1>I worked there for like three years, I worked in

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<v S1>their security group and I just love their way of

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<v S1>thinking about the world. I love their way of doing

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<v S1>UI and UX, and I love how they are building

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<v S1>in my opinion. Not that I have any inside information

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<v S1>and it's not like actual product, but I think for

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<v S1>the last ten years they've been building what I'm calling

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<v S1>life OS, right? So forget iOS or Mac OS or

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<v S1>whatever they're building life OS. I mean, they just launched

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<v S1>the Journal app on the Mac, for example, and they

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<v S1>just brought the phone app to the Mac, which is

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<v S1>like the coolest thing ever. And like, AirPods seem to

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<v S1>work better. So there's lots of improvements in iOS or

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<v S1>in Mac OS 26, by the way. But, um, basically

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<v S1>their ecosystem is what keeps me their their focus on

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<v S1>UI and UX is what keeps me their their focus

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<v S1>on art and creativity and like enabling people to be

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<v S1>creative and enabling people to be their best selves or whatever.

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<v S1>Like that's the vibe that I've always liked about Apple,

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<v S1>and I think they do UI and UX better than

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<v S1>anyone else. I think they've had this unified vision of

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<v S1>context and, you know, having finance and creativity and work

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<v S1>and play and personal and all of that, all integrated

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<v S1>into the operating system. They've always just done that better

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<v S1>than anyone else. So that's why I'm so into Apple now.

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<v S1>Obviously AI is happening has been for the last three

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<v S1>years or however long it's been. And Apple is behind. Right. I've,

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<v S1>I've been saying for you know whatever a year that

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<v S1>look they're going to come out with their unified AI

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<v S1>product which is going to go on top of their

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<v S1>life OS or whatever. And basically Siri is going to

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<v S1>jump way ahead of everyone. And I thought that was

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<v S1>going to be like end of last year. And of

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<v S1>course they stumbled on that. And I believe it's because

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<v S1>of prompt injection. I think it is too difficult to

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<v S1>put an AI in front of all the personal context

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<v S1>that Apple has about us. And to do it in

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<v S1>a secure way, I think it's too difficult to do

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<v S1>that right now. That is my guess. And I know

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<v S1>this technically because I know how to do prompt injection and, um,

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<v S1>I know some of the best other prompt injection people

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<v S1>in the world. And it is pretty trivial still to

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<v S1>bypass most protections. So I think they are struggling with that.

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<v S1>Maybe they're struggling with other parts of it as well,

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<v S1>but I imagine they're definitely struggling with that piece. Like

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<v S1>right now I just got a pop up screening call,

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<v S1>and if I click view and this is while I'm

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<v S1>recording on my desktop, if I click view, it, um,

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<v S1>it shows this person like spamming me. And there it's

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<v S1>actively live transcribing that thing that's going to voicemail right now.

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<v S1>So I think that's really, really cool. Um, and then

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<v S1>I could also just click block. Uh, so that's, that's

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<v S1>pretty cool that I have that option. And the phone

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<v S1>is now integrated with the Mac, which it should be. Right.

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<v S1>That's just a voice call. It's not tied to a

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<v S1>physical device anyway. UI stuff, the way I'm kind of

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<v S1>seeing the world now is UI. UX is Apple always

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<v S1>has been. Seems like it will be going forward. And

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<v S1>then Google is now becoming like less of a negative

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<v S1>for me. And it's more about the data and services

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<v S1>and specifically AI. And obviously I wish that Apple had

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<v S1>all of that. They don't have it yet. I think

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<v S1>they will get there hopefully. And obviously Google is probably

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<v S1>working on UI and UX as well. Like I assume

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<v S1>it's getting better. I've seen some, you know, UI stuff

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<v S1>from them that seems to be halfway decent. So the

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<v S1>real question to me is will Google figure out the UI,

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<v S1>UX life, OS, full integration of ecosystem? Will they figure

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<v S1>that out before Apple, or will Apple figure out data

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<v S1>and AI before Google figures out that UI UX piece? Right.

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<v S1>That's really the question. Which one gets the the one

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<v S1>that they're weak on up to a certain bar first?

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<v S1>I can't conceivably think of myself switching over to the

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<v S1>Google ecosystem, because there's so many pieces of it that

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<v S1>I know I would miss, but I am. I am 100%

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<v S1>open to it. I honestly, I is a much bigger

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<v S1>movement than any other tech movement. Um, it's bigger than

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<v S1>UI and UX, especially since I shouldn't be typing on

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<v S1>a keyboard anyway. I shouldn't be, um, you know, thumb

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<v S1>typing on a phone, right? This should all be moving

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<v S1>to voice and virtual interfaces and glasses. So as that

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<v S1>starts to happen, like I'm more likely to move towards

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<v S1>the Google side if Apple doesn't have that. Um, keeping

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<v S1>in mind that I really do care about my interface

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<v S1>to tech. Oh, here's the other thing. The other big

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<v S1>reason that I really prefer Apple is because I've been

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<v S1>on the inside, and I know how seriously and crazy, um,

0:08:41.277 --> 0:08:44.437
<v S1>they take the security and privacy stuff like it is

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<v S1>not marketing, it is not made up. It is absolutely

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<v S1>dead serious. So if I'm building my whole life ecosystem

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<v S1>around this, plus agents, I'm building all this stuff on it,

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<v S1>they got to do it perfectly right. Now, I do

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<v S1>think Google is really, really good at security. I just

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<v S1>don't think their incentives have been aligned, you know, in

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<v S1>the past because they were primarily an ad company, the

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<v S1>more they become an OS and life OS for everyone.

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<v S1>With AI, you know being the primary thing, I think

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<v S1>they should start to move more into the realm of

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<v S1>like what Apple does with like, okay, look, privacy first,

0:09:21.006 --> 0:09:24.247
<v S1>you know, security first. Obviously they say that obviously they

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<v S1>do a good job, but I'm saying there's going to

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<v S1>be less of a conflict because they're not trying to

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<v S1>make all their money off of your data. Right. Hopefully

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<v S1>that's the case. Hopefully they're migrating away from that, which

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<v S1>is why I, I just haven't been enthused about using

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<v S1>them as a core OS. All right. I think that's

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<v S1>enough about that. Basically a little bit of disappointment around WD, DC.

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<v S1>I mean, I love the operating stuff. I, I'm a

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<v S1>little halfway between like how much do I like the

0:09:55.727 --> 0:10:00.046
<v S1>liquid stuff? I've seen some places where the interface is

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<v S1>quite bad. I've seen some places where it's quite good.

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<v S1>I think we're going to let that bake for a

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<v S1>little while, see how it goes. We're on the first

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<v S1>beta right now. They're going to clean up a lot

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<v S1>of stuff. But what I have noticed is some really

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<v S1>good improvements around the fluidity of like moving from my

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<v S1>phone to my desktop, having the AirPods switch. Naturally, this

0:10:20.627 --> 0:10:21.946
<v S1>is the type of thing you lose when you go

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<v S1>to Google. Like you try to switch over and you

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<v S1>realize like nothing works, right? Because Apple has been working

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<v S1>on this for so many years, and this macOS and

0:10:31.026 --> 0:10:35.226
<v S1>iOS 26 update, it seems like things are really, really smooth.

0:10:35.347 --> 0:10:38.467
<v S1>I mean, my OS is just working better now, and

0:10:38.467 --> 0:10:40.867
<v S1>this is beta one. Back in the day when I

0:10:40.867 --> 0:10:45.266
<v S1>was doing these betas, like I would lose core functionality

0:10:45.307 --> 0:10:48.906
<v S1>like regular apps wouldn't launch. I would like go dark,

0:10:48.906 --> 0:10:51.627
<v S1>like I couldn't text people. It was crazy, you know,

0:10:51.666 --> 0:10:55.066
<v S1>running these Apple betas early on. But, um, no, it's

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<v S1>it's working great. I recommend you try it out. And

0:10:58.067 --> 0:11:01.307
<v S1>if you do, you could text me and we could

0:11:01.307 --> 0:11:04.516
<v S1>try out some of these new emoji features or whatever.

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<v S1>All right. Um, got a couple blogs. Yeah. So one

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<v S1>is the WWE one, the other one is, um, uh,

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<v S1>see here. Oh, yeah. It's an argument against. It's just

0:11:19.636 --> 0:11:22.197
<v S1>next token prediction. I thought that was a pretty good

0:11:22.197 --> 0:11:25.997
<v S1>way of encapsulating it. Uh, so definitely check that one out.

0:11:25.997 --> 0:11:28.316
<v S1>I'm about to do, like, a kind of, like a

0:11:28.317 --> 0:11:33.676
<v S1>personal project to profile, like all the CCP members and structure,

0:11:33.717 --> 0:11:36.997
<v S1>just profile them and, like, figure out who are they,

0:11:37.036 --> 0:11:41.117
<v S1>what are they up to? How are they different than she? What, uh,

0:11:41.877 --> 0:11:44.077
<v S1>what are their political opinions? What are they focused on?

0:11:44.077 --> 0:11:46.917
<v S1>What are their areas of expertise? What are their areas

0:11:46.916 --> 0:11:51.197
<v S1>of responsibility like how does legislation get. I guess it's

0:11:51.197 --> 0:11:53.997
<v S1>not legislation because people aren't voting, but how do they

0:11:53.997 --> 0:11:56.916
<v S1>decide what new laws to put out? Is there a process?

0:11:56.916 --> 0:11:59.117
<v S1>Is it on a particular timing? I just kind of

0:11:59.156 --> 0:12:03.647
<v S1>want to understand how the Chinese government works. So I'm

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<v S1>going to start with understanding all the CCP people, um,

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<v S1>because that is the government. And I and I want

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<v S1>to look at the different echelons, like, is there a

0:12:13.447 --> 0:12:16.127
<v S1>like is there like a Politburo? Is that a smaller group?

0:12:16.127 --> 0:12:19.926
<v S1>Is it like a larger thing of like hundreds of people? Um,

0:12:19.967 --> 0:12:22.687
<v S1>what's the difference between those tiers, like stuff like that?

0:12:22.687 --> 0:12:25.286
<v S1>So I'm going to do a study like that. And, uh,

0:12:25.286 --> 0:12:27.046
<v S1>I don't know how I'm going to put that out.

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<v S1>Maybe a blog post, maybe some member content. I have

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<v S1>no idea. Uh, the other thing I'm going to do

0:12:31.926 --> 0:12:35.166
<v S1>is I'm going to do a future trend investment analysis exercise,

0:12:35.166 --> 0:12:37.727
<v S1>which I did, I want to say like five years ago,

0:12:38.127 --> 0:12:41.607
<v S1>and it basically told me to buy Amazon and Nvidia.

0:12:42.166 --> 0:12:44.727
<v S1>I forget what that exercise told us to buy, but

0:12:44.727 --> 0:12:48.286
<v S1>I did it with my good buddy Tai Sabarno, and

0:12:48.286 --> 0:12:50.487
<v S1>I think we ended up making a number of purchases

0:12:50.487 --> 0:12:55.167
<v S1>based on that, and I think they've done well for us. But, um, yeah,

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<v S1>I want to do another one this time. We'll get

0:12:57.127 --> 0:13:01.016
<v S1>to use things like, you know, O3 Pro and I

0:13:01.057 --> 0:13:03.456
<v S1>get to throw in tons of context about myself and

0:13:03.457 --> 0:13:06.416
<v S1>what I'm looking for and the, you know, the types

0:13:06.416 --> 0:13:08.497
<v S1>of investments I'm looking for and the type of risk

0:13:08.497 --> 0:13:12.176
<v S1>I want to be open to. Um, and this isn't

0:13:12.176 --> 0:13:16.577
<v S1>only for investment. That'll be kind of like a side product, um, of,

0:13:16.617 --> 0:13:19.817
<v S1>like the exhaust that comes out of it. The biggest

0:13:19.817 --> 0:13:22.136
<v S1>thing I'm trying to do here is just figure out trends.

0:13:22.136 --> 0:13:25.057
<v S1>So here's like the I'll give you like kind of

0:13:25.057 --> 0:13:27.497
<v S1>what I'm going to feed to this thing. Right. I'm

0:13:27.497 --> 0:13:29.776
<v S1>going to set this entire thing up, which is going

0:13:29.776 --> 0:13:33.056
<v S1>to be like 20 pages of me writing up contacts

0:13:33.097 --> 0:13:35.857
<v S1>to my own thoughts and my own predictions, my own like,

0:13:36.016 --> 0:13:40.816
<v S1>concerns or whatever. And I want to know what it

0:13:40.817 --> 0:13:42.656
<v S1>thinks could happen. And I'm sure it's going to be

0:13:42.656 --> 0:13:44.776
<v S1>very careful and be like, look, we can't predict the future,

0:13:44.776 --> 0:13:48.857
<v S1>which obviously everyone knows that. But, um, what I'm going

0:13:48.896 --> 0:13:52.497
<v S1>to be is what I'm going to say is like, look, um,

0:13:53.097 --> 0:13:56.857
<v S1>if this were to happen, what seems obvious to you,

0:13:56.857 --> 0:14:01.707
<v S1>that would be some second order effects. That is the power, right,

0:14:01.747 --> 0:14:04.227
<v S1>that I didn't have before where I is like, well,

0:14:04.266 --> 0:14:06.786
<v S1>obviously this is the type of thing that happens and

0:14:06.786 --> 0:14:11.427
<v S1>it gives you like 150 different things. So when certain

0:14:11.426 --> 0:14:14.627
<v S1>things are scarce, prices of certain other things go up.

0:14:14.627 --> 0:14:16.947
<v S1>Which companies are associated with those? I don't know all

0:14:16.987 --> 0:14:19.946
<v S1>that information. Like I'm not like a commodities expert. I'm

0:14:19.987 --> 0:14:23.267
<v S1>not a trading expert, I'm not a stock expert. So

0:14:23.827 --> 0:14:26.107
<v S1>I think there are some things that don't involve that

0:14:26.107 --> 0:14:29.586
<v S1>much prediction or that much conjecture on the side of

0:14:29.587 --> 0:14:33.147
<v S1>the eye. That's actually just benefits from it. Understanding how

0:14:33.147 --> 0:14:38.066
<v S1>the world works. So I could say, okay, um, like,

0:14:38.067 --> 0:14:40.747
<v S1>what am I? You know, hypotheses is like, okay, private

0:14:40.747 --> 0:14:42.946
<v S1>security is going to go up. Oh, there's probably going

0:14:42.947 --> 0:14:46.587
<v S1>to be a bunch more prisons built, uh, because, you know,

0:14:46.867 --> 0:14:49.467
<v S1>we're stupid. And we took down all the mental health facilities.

0:14:49.467 --> 0:14:53.587
<v S1>So what happens when there's like UBI comes out? But

0:14:53.587 --> 0:14:57.997
<v S1>UBI is limited to only citizens. So they start doing

0:14:57.997 --> 0:15:01.477
<v S1>mass deportations, not because of the current kind of vibe

0:15:01.477 --> 0:15:04.717
<v S1>of like anti-immigrant stuff that's going on, but more along

0:15:04.717 --> 0:15:06.717
<v S1>the lines of like, we need to control how many

0:15:06.717 --> 0:15:09.637
<v S1>people were sending UBI to, we're not going to send

0:15:09.637 --> 0:15:12.956
<v S1>UBI to everyone in the country just because they're physically here.

0:15:13.637 --> 0:15:16.117
<v S1>So now there's a bunch of tech to find who

0:15:16.277 --> 0:15:20.677
<v S1>is and isn't supposed to be receiving UBI, and more

0:15:20.677 --> 0:15:23.757
<v S1>and more people will become homeless because, you know, AI

0:15:23.797 --> 0:15:26.836
<v S1>is taking jobs. Okay, so they're homeless. So then you

0:15:26.837 --> 0:15:30.517
<v S1>have the fact that they don't have a place to live. Uh,

0:15:30.517 --> 0:15:33.877
<v S1>then you have addiction, then you have violence. So who

0:15:33.877 --> 0:15:36.997
<v S1>goes into prison, right? Prison is mostly full of people

0:15:36.997 --> 0:15:41.157
<v S1>who have addiction, who have mental illnesses, and obviously some

0:15:41.157 --> 0:15:44.077
<v S1>people who are violent. Right. And the percentages, you might

0:15:44.077 --> 0:15:47.717
<v S1>be surprised how much it's actually people that just couldn't

0:15:47.717 --> 0:15:49.797
<v S1>find a way to get it going. Right. So they

0:15:49.797 --> 0:15:53.237
<v S1>end up on drugs, they end up mentally ill. Those

0:15:53.797 --> 0:15:56.497
<v S1>ideally in some world, like the world we're supposed to

0:15:56.497 --> 0:15:59.617
<v S1>be building, that would be like drug treatment programs and

0:15:59.617 --> 0:16:02.417
<v S1>it would be mental health facilities. But all of that

0:16:02.417 --> 0:16:05.697
<v S1>is going to collapse down into basically like prisons. Get

0:16:05.697 --> 0:16:10.777
<v S1>them away from society, separate them from society. So what

0:16:10.777 --> 0:16:13.137
<v S1>does that mean? What does that mean for water? What

0:16:13.137 --> 0:16:16.177
<v S1>does that mean for food? What does that mean for, um,

0:16:16.297 --> 0:16:19.297
<v S1>what companies are going to do well in that world? Um, like,

0:16:19.337 --> 0:16:22.297
<v S1>I'll tell you one of mine Costco I love Costco.

0:16:22.337 --> 0:16:26.097
<v S1>I'm like, so like into Costco. Um, and also Google

0:16:26.097 --> 0:16:28.497
<v S1>and also Apple. But those are like my three main

0:16:28.497 --> 0:16:32.697
<v S1>investments right now. So the question is like, how is

0:16:32.737 --> 0:16:36.577
<v S1>how can I find other ways to connect these dots.

0:16:36.937 --> 0:16:39.337
<v S1>And I'm going to tell it, look, don't be doing conjecture.

0:16:39.337 --> 0:16:41.217
<v S1>Don't be trying to predict the future. I'm going to

0:16:41.217 --> 0:16:44.057
<v S1>give you a bunch of options of ways. I think

0:16:44.057 --> 0:16:47.137
<v S1>maybe it could go. But I have no idea. And

0:16:47.137 --> 0:16:49.457
<v S1>you as this I you also have no idea. But

0:16:49.457 --> 0:16:54.427
<v S1>there's there are lanes of probability, Right? Uh, turns out

0:16:54.427 --> 0:16:56.347
<v S1>if people don't have jobs, they have no way to

0:16:56.387 --> 0:16:59.267
<v S1>pay for food, especially for their families. They might get

0:16:59.267 --> 0:17:03.427
<v S1>a little upset. Right. So certain things don't require a

0:17:03.467 --> 0:17:07.987
<v S1>lot of, like, future prediction or futurist type crap. Um,

0:17:07.987 --> 0:17:09.547
<v S1>so I'm going to use the AI to help me

0:17:09.587 --> 0:17:13.907
<v S1>sort of navigate that stuff that seems a little more obvious. And, um,

0:17:15.187 --> 0:17:17.227
<v S1>the main output is going to be like, it looks

0:17:17.227 --> 0:17:20.466
<v S1>like if these things happen, then these things might happen

0:17:20.467 --> 0:17:25.347
<v S1>as well. And then, um, maybe some investment thing of like, okay, well,

0:17:25.547 --> 0:17:28.707
<v S1>for all of those different ones, what companies or what

0:17:28.706 --> 0:17:32.947
<v S1>products or what raw materials or where would I want

0:17:32.946 --> 0:17:34.947
<v S1>to live? Where would I want to move? What is

0:17:34.946 --> 0:17:38.107
<v S1>a good city to be in if something like, you know,

0:17:38.147 --> 0:17:40.787
<v S1>three through seven were to happen, right? That's the type

0:17:40.787 --> 0:17:42.786
<v S1>of analysis I'm going to do. And similar to the

0:17:42.787 --> 0:17:44.667
<v S1>CCP one, I'm not sure how I'm going to put

0:17:44.667 --> 0:17:47.227
<v S1>that out. Maybe I'll make a giant PDF, maybe I'll

0:17:47.226 --> 0:17:49.907
<v S1>do a video. Maybe it'll be like member content, maybe,

0:17:49.946 --> 0:17:52.917
<v S1>you know, charge for it, Make it free. No idea.

0:17:54.157 --> 0:17:57.917
<v S1>Probably some combination of those. All right. What else? Doo

0:17:57.917 --> 0:18:02.477
<v S1>doo doo. All right. Cybersecurity. So Trump overhauled Biden's cybersecurity

0:18:02.476 --> 0:18:06.757
<v S1>policies with a new executive order. Uh, he removed focus

0:18:06.757 --> 0:18:09.677
<v S1>on mandated digital IDs. That must have been, like an

0:18:09.716 --> 0:18:15.236
<v S1>immigration type thing. Accounting, compliance checklists, micromanaging, agency decisions. I

0:18:15.236 --> 0:18:17.837
<v S1>think that might have been like Cisa, maybe like harnessing

0:18:18.277 --> 0:18:21.677
<v S1>or like trying to control Cisa ads focus on defeating

0:18:21.677 --> 0:18:26.917
<v S1>foreign threats, secure software practices, border gateway protection. That's BGP,

0:18:27.077 --> 0:18:32.397
<v S1>I believe. Um, yeah. Like, you know, hijacking BGP routes.

0:18:32.436 --> 0:18:38.677
<v S1>Post-quantum cryptography, modern encryption protocols, AI for vulnerabilities, IoT security

0:18:38.677 --> 0:18:44.956
<v S1>standards and limiting sanctions scope. So that was, uh, a

0:18:44.956 --> 0:18:48.797
<v S1>combination of mine and an AI analysis of the talking points,

0:18:48.797 --> 0:18:51.887
<v S1>or it's called a fact sheet. Bellingcat tests whether or

0:18:51.887 --> 0:18:54.927
<v S1>not I can actually geolocate photos, and it found that

0:18:54.927 --> 0:18:59.966
<v S1>O3 actually did the best and beat out Google Lens, actually.

0:19:00.527 --> 0:19:04.767
<v S1>Sentinel one reveals details on Chinese supply chain attack attempt.

0:19:05.047 --> 0:19:10.446
<v S1>Protonvpn sees 1,000% sign up surge after Pornhub blocks France.

0:19:11.007 --> 0:19:16.567
<v S1>So France evidently loves Protonvpn. And, uh, yeah, they went

0:19:16.567 --> 0:19:20.287
<v S1>over there so they could still get access. Microsoft Teams

0:19:20.287 --> 0:19:23.767
<v S1>with Indian police to shut down fake tech support scammers

0:19:24.847 --> 0:19:28.887
<v S1>and Bishop Fox 2025 red team tools list. All right.

0:19:28.927 --> 0:19:32.206
<v S1>National security OpenAI published their annual report on how bad

0:19:32.206 --> 0:19:35.847
<v S1>actors are using AI maliciously, and I love the fact

0:19:35.847 --> 0:19:37.567
<v S1>that they put these out. So four out of ten

0:19:37.567 --> 0:19:40.927
<v S1>major abuse cases look like they came from China, from

0:19:40.927 --> 0:19:45.247
<v S1>social engineering to cyber threats. They're seeing deceptive employment schemes.

0:19:45.247 --> 0:19:50.736
<v S1>So task scams from like Cambodia comment spamming from Philippines

0:19:51.377 --> 0:19:54.897
<v S1>and a covert influence operations potentially leaked to Russia and

0:19:54.897 --> 0:20:00.137
<v S1>Iran using AI as force multipliers. Um, I'm actually going

0:20:00.137 --> 0:20:02.256
<v S1>to mention something right now. I can't figure out what

0:20:02.257 --> 0:20:03.857
<v S1>I'm going to do with this. I might do another

0:20:03.857 --> 0:20:06.297
<v S1>report like the one I just the two I just

0:20:06.297 --> 0:20:12.017
<v S1>talked about. So my Twitter feed is full, full of

0:20:12.017 --> 0:20:17.217
<v S1>what I am absolutely certain is like widespread propaganda. So

0:20:17.377 --> 0:20:20.577
<v S1>the content that I see is like, don't you hate

0:20:20.577 --> 0:20:24.137
<v S1>black people because they do this? Um, don't you wish

0:20:24.137 --> 0:20:26.057
<v S1>the world looked like this? And then if you click

0:20:26.097 --> 0:20:28.097
<v S1>the video, it's like a whole bunch of white people

0:20:28.097 --> 0:20:30.857
<v S1>walking around and there's like, no crime and there's like

0:20:30.857 --> 0:20:34.977
<v S1>a fountain with, like, a nice water sound, and there's, like,

0:20:34.976 --> 0:20:38.097
<v S1>somebody buying something at, like, an Abercrombie or something, and

0:20:38.097 --> 0:20:42.216
<v S1>it's like. It's like massive propaganda to like, uh, don't

0:20:42.216 --> 0:20:45.657
<v S1>you wish the world was the way it was before? Before, like,

0:20:45.696 --> 0:20:49.227
<v S1>brown people messed it all up, right? And then there'll

0:20:49.267 --> 0:20:51.706
<v S1>be another one. It'll be like about fighting or something

0:20:51.706 --> 0:20:55.067
<v S1>like that. Or it'll be like masculine movies. Don't you

0:20:55.067 --> 0:20:58.307
<v S1>wish movies were like this? And it's like someone holding

0:20:58.307 --> 0:21:02.067
<v S1>a Budweiser. Budweiser. And, like, shooting a crossbow or something.

0:21:02.587 --> 0:21:04.987
<v S1>And I'm just like, what is going on? So every

0:21:05.027 --> 0:21:06.787
<v S1>time I go back to Twitter, which I probably check

0:21:06.787 --> 0:21:09.186
<v S1>it like, I don't know, like 15, 20 times a

0:21:09.186 --> 0:21:11.466
<v S1>day or something, and then I'll just be browsing to

0:21:11.466 --> 0:21:12.786
<v S1>see what people are saying. But if I go to

0:21:12.827 --> 0:21:15.427
<v S1>the home tab, which is like impossible to clean up

0:21:15.427 --> 0:21:17.466
<v S1>because I block all these things when I see them,

0:21:17.747 --> 0:21:20.266
<v S1>although lately I've started bookmarking them because I'm going to

0:21:20.267 --> 0:21:24.306
<v S1>do this research project. But normally I just block, block, block.

0:21:24.307 --> 0:21:28.107
<v S1>But it's just an endless supply. Like these people have

0:21:28.147 --> 0:21:31.387
<v S1>like multiple accounts. So what I started doing is clicking

0:21:31.387 --> 0:21:35.427
<v S1>on the account and scrolling through their feed, and it's nonstop.

0:21:35.427 --> 0:21:39.587
<v S1>It's nonstop narratives about how messed up the country is,

0:21:40.547 --> 0:21:44.547
<v S1>reasons for why the country got messed up, which is scapegoating, basically.

0:21:45.067 --> 0:21:48.647
<v S1>And then, um. Don't you wish it was like, uh,

0:21:48.647 --> 0:21:50.807
<v S1>the new thing, right? Don't you wish it was like

0:21:50.807 --> 0:21:52.647
<v S1>it used to be? Don't you know? Don't you think

0:21:52.647 --> 0:21:56.246
<v S1>we could do better? And I'm just, like, seeing this everywhere.

0:21:56.247 --> 0:21:59.327
<v S1>Just like hundreds of accounts doing this. And I sent

0:21:59.327 --> 0:22:02.327
<v S1>this a few of these accounts to, uh, some friends

0:22:02.327 --> 0:22:06.326
<v S1>of mine who go and research this stuff. And, yeah,

0:22:06.327 --> 0:22:12.726
<v S1>I'm just really surprised that, like, I guess I'm not surprised, given, uh,

0:22:12.847 --> 0:22:15.326
<v S1>given Elon's situation and the fact that he lost so

0:22:15.327 --> 0:22:18.407
<v S1>many advertisers and the fact that I guess he's like

0:22:18.607 --> 0:22:23.647
<v S1>conspiracy friendly, I would say, um, but ultimately people click

0:22:23.647 --> 0:22:26.527
<v S1>on this stuff. People watch this stuff because it is,

0:22:26.647 --> 0:22:30.127
<v S1>you know, specifically designed to be that way, to be

0:22:30.167 --> 0:22:35.007
<v S1>very watchy and clicky. Um, so I guess that's why

0:22:35.007 --> 0:22:37.486
<v S1>it's there. But but it's really gross. Like, I really

0:22:37.486 --> 0:22:39.687
<v S1>wish there were a platform or I wish there were

0:22:39.686 --> 0:22:43.287
<v S1>options in this platform where it's like, look, I'm paying money. Like,

0:22:43.936 --> 0:22:46.256
<v S1>Can you not show me this garbage? I want to

0:22:46.257 --> 0:22:50.057
<v S1>see stuff from people I follow and stuff that's very

0:22:50.057 --> 0:22:52.417
<v S1>tightly correlated with people I follow. Which he says he's

0:22:52.456 --> 0:22:55.337
<v S1>working on that actually, he says he's working on similar

0:22:55.337 --> 0:22:57.617
<v S1>content matching, which is similar to the app I have

0:22:57.657 --> 0:23:02.057
<v S1>called threshold. But, um, yeah, this whole thread of like,

0:23:02.097 --> 0:23:04.577
<v S1>who is sending all this stuff to us, who is

0:23:04.577 --> 0:23:08.377
<v S1>basically trying to change the narrative or try to put

0:23:08.657 --> 0:23:12.617
<v S1>inject into our minds, like this feeling of the US

0:23:12.657 --> 0:23:16.297
<v S1>is messed up. It was messed up by them pointing

0:23:16.297 --> 0:23:20.937
<v S1>at trans people or brown people or black people or whatever.

0:23:20.936 --> 0:23:24.577
<v S1>Gay people or you know, the wrong religion or whatever

0:23:24.577 --> 0:23:28.496
<v S1>it is. Liberals, definitely, um, people who aren't right enough

0:23:28.497 --> 0:23:33.577
<v S1>or aren't right in the correct way. Um, it's just

0:23:33.577 --> 0:23:36.577
<v S1>it's worse than I've ever seen. It's absolutely worse than

0:23:36.577 --> 0:23:39.337
<v S1>I've ever seen. Um, so I don't know if their

0:23:39.337 --> 0:23:41.857
<v S1>skill level is just going up. I imagine it's because

0:23:41.857 --> 0:23:44.587
<v S1>it's all a lot of it's being AI generated. So

0:23:44.587 --> 0:23:46.506
<v S1>you could just do it at more scale. That's probably

0:23:46.507 --> 0:23:49.827
<v S1>a reason. But anyway, it's something I'm going to look

0:23:49.827 --> 0:23:52.387
<v S1>into and probably do some kind of essay or report

0:23:52.387 --> 0:23:57.147
<v S1>or whatever. All right. AI. Okay. This is the craziest story,

0:23:57.427 --> 0:24:02.467
<v S1>the absolute craziest story of the week. Um, and honestly,

0:24:02.466 --> 0:24:04.427
<v S1>for a long time. And I've got a follow up

0:24:04.427 --> 0:24:06.266
<v S1>to it as well, because my buddy told me about

0:24:06.267 --> 0:24:09.587
<v S1>this one company. But check this out. So I finally

0:24:09.587 --> 0:24:13.867
<v S1>found something that trains scientists have missed for decades. So

0:24:13.867 --> 0:24:16.147
<v S1>a number of professional scientists have been trying to figure

0:24:16.147 --> 0:24:19.466
<v S1>out how a particular kind of bacteriophage, which is a

0:24:19.466 --> 0:24:24.707
<v S1>virus that infects bacteria, uh, which I didn't know that. So, um,

0:24:24.706 --> 0:24:27.907
<v S1>there's a podcast here that supports this that's basically like, um,

0:24:28.226 --> 0:24:30.907
<v S1>it's all the scientists who actually did this. So basically

0:24:30.907 --> 0:24:33.667
<v S1>they have been studying this thing for over a couple

0:24:33.706 --> 0:24:36.507
<v S1>of decades. They are the world's experts in how these

0:24:36.507 --> 0:24:43.476
<v S1>particular bacteriophages, um, gain mobility and move out of the cell. Basically,

0:24:43.476 --> 0:24:45.317
<v S1>what they do is they take over the cell. They

0:24:45.317 --> 0:24:48.277
<v S1>blow it open and spread the virus. That's what these

0:24:48.277 --> 0:24:52.796
<v S1>things do. So they study how these things get their

0:24:52.797 --> 0:24:55.556
<v S1>heads and their tails, which allows them to move and

0:24:55.557 --> 0:24:58.357
<v S1>propagate and, you know, take over other things. And I'm

0:24:58.357 --> 0:25:00.996
<v S1>simplifying and probably messing up some details because it's a

0:25:00.997 --> 0:25:05.397
<v S1>very complex, you know, specific topic. But I went and

0:25:05.397 --> 0:25:07.756
<v S1>listened to the entire one hour episode with the actual

0:25:07.757 --> 0:25:11.517
<v S1>experts talking about this. Now the story is they were

0:25:11.517 --> 0:25:14.917
<v S1>given this new version of a Google model, which is

0:25:14.917 --> 0:25:20.877
<v S1>specifically for researching and coming up with novel hypotheses, novel ideas. Okay,

0:25:20.997 --> 0:25:23.277
<v S1>so what they did was they they had this thing

0:25:23.277 --> 0:25:25.717
<v S1>where they're like, how is this thing possible? They've been

0:25:25.716 --> 0:25:28.716
<v S1>thinking about this for years and years and years. They've

0:25:28.716 --> 0:25:32.476
<v S1>done numerous studies. They are the world's premier experts on this.

0:25:32.877 --> 0:25:35.597
<v S1>And they have been stumped by this fact. The fact

0:25:35.597 --> 0:25:39.316
<v S1>that this one bacteriophage, I believe it was there, were

0:25:39.317 --> 0:25:41.726
<v S1>stumped by the fact of how was it actually propagating

0:25:41.767 --> 0:25:44.086
<v S1>or how was it becoming mobile. It was something like that.

0:25:44.087 --> 0:25:46.047
<v S1>It was some sort of problem that they could not

0:25:46.047 --> 0:25:49.407
<v S1>figure out, and they know exactly how it works. You know,

0:25:49.486 --> 0:25:52.087
<v S1>they were very sure about this and that. Therefore, you know,

0:25:52.127 --> 0:25:54.927
<v S1>they're like, this makes no sense. So they gave a

0:25:54.927 --> 0:25:58.967
<v S1>bunch of this observational data to it, you know, stuff

0:25:58.966 --> 0:26:01.887
<v S1>that they've had for years and years. And it came

0:26:01.887 --> 0:26:05.726
<v S1>back with hypotheses. And one of the hypotheses out of

0:26:05.726 --> 0:26:09.167
<v S1>a very short list was like, hey, um, it might

0:26:09.167 --> 0:26:12.286
<v S1>be this actually, because, um, what you could do is

0:26:12.327 --> 0:26:14.647
<v S1>you could just do this instead of this, and it

0:26:14.647 --> 0:26:16.527
<v S1>puts a tail on there and it actually picks up

0:26:16.527 --> 0:26:18.966
<v S1>the one, um, once it's outside of the cell, it

0:26:18.966 --> 0:26:21.526
<v S1>picks up someone else's. And I'm kind of messing up

0:26:21.527 --> 0:26:24.206
<v S1>the details here, but they describe it pretty good in this,

0:26:24.247 --> 0:26:28.327
<v S1>in this, uh, full episode of, uh, Cognitive Revolution, I

0:26:28.327 --> 0:26:32.247
<v S1>think is the name of the podcast. But, um, when

0:26:32.247 --> 0:26:35.526
<v S1>they heard this, when they saw it written down, they're like, oh,

0:26:36.287 --> 0:26:39.576
<v S1>that that's probably what it is. So here. Here's the thing.

0:26:39.577 --> 0:26:42.697
<v S1>They had made an assumption that a certain type of

0:26:42.696 --> 0:26:46.177
<v S1>mobility or a certain type of propagation was not possible,

0:26:46.417 --> 0:26:48.857
<v S1>and it was a very silly assumption that they had made.

0:26:49.337 --> 0:26:52.777
<v S1>And this, this assumption had stopped them from solving this

0:26:52.777 --> 0:26:57.817
<v S1>problem for years upon years. How many hundreds of hours,

0:26:57.857 --> 0:27:01.097
<v S1>thousands of hours have they spent stumped on this as

0:27:01.097 --> 0:27:06.417
<v S1>the world's premier humans on the entire planet? The smartest

0:27:06.417 --> 0:27:09.336
<v S1>people working on this in the entire world, on the

0:27:09.337 --> 0:27:14.537
<v S1>entire planet, were stumped by a thing. And Google came back,

0:27:15.736 --> 0:27:18.617
<v S1>I think within a couple of minutes, I think, and

0:27:18.617 --> 0:27:22.137
<v S1>it was like, yeah, I think it's probably this. They

0:27:22.137 --> 0:27:27.696
<v S1>go and check and it's 100% verified that was correct.

0:27:27.696 --> 0:27:32.536
<v S1>And they here's here's the thing. They were kind of, uh,

0:27:32.537 --> 0:27:35.296
<v S1>I believe what they were saying is they were about

0:27:35.297 --> 0:27:38.477
<v S1>to figure this out. Maybe. Maybe this year. Maybe next year.

0:27:38.476 --> 0:27:41.277
<v S1>They were doing some experiments that might have got them

0:27:41.277 --> 0:27:43.597
<v S1>to this. But the point is, Google found it instantly.

0:27:43.597 --> 0:27:47.717
<v S1>Which means if they had this Google research assistant earlier,

0:27:47.956 --> 0:27:51.196
<v S1>maybe last year, maybe years ago, maybe it would have

0:27:51.196 --> 0:27:53.917
<v S1>found this right. And they not would not have had

0:27:53.917 --> 0:27:56.677
<v S1>this problem for this entire time. Now, what excites me

0:27:56.677 --> 0:27:59.957
<v S1>about this is not this specific use case. It's the

0:27:59.997 --> 0:28:03.476
<v S1>how they reacted to it. They were like, this is insane.

0:28:04.037 --> 0:28:07.356
<v S1>Because the thing I'm so excited about, and it's the

0:28:07.357 --> 0:28:10.836
<v S1>same thing they were talking about, is how many other

0:28:10.837 --> 0:28:14.637
<v S1>things are like this. There is data everywhere. There is

0:28:14.637 --> 0:28:19.436
<v S1>evidence everywhere. There are dots. Okay, think of connect the dots.

0:28:19.476 --> 0:28:22.517
<v S1>Think of how many dots are lying around in papers,

0:28:22.757 --> 0:28:28.517
<v S1>lying around in data sets. Raw data sets. Unfiltered. Unreviewed. Why?

0:28:28.557 --> 0:28:33.717
<v S1>Because there aren't enough academics. There aren't enough researchers. Forget academics.

0:28:33.716 --> 0:28:38.687
<v S1>There aren't enough humans with the training required, write either

0:28:38.687 --> 0:28:42.287
<v S1>the formal current training or like even rudimentary training. There

0:28:42.287 --> 0:28:46.607
<v S1>aren't enough human eyes on all this raw data. There

0:28:46.607 --> 0:28:48.807
<v S1>are no human eyes to look at the stuff and

0:28:48.807 --> 0:28:54.247
<v S1>find the dots and connect them. How many cures for illnesses?

0:28:54.927 --> 0:28:58.367
<v S1>How many novel ways are we sitting on the ability

0:28:58.567 --> 0:29:01.927
<v S1>to improve our IQs by 20%? Are we sitting on

0:29:01.927 --> 0:29:07.007
<v S1>the ability to solve aging? I would guess we absolutely are.

0:29:07.287 --> 0:29:10.967
<v S1>We absolutely are. And that the problem is not enough.

0:29:10.967 --> 0:29:14.967
<v S1>People are studying it using not enough data. So what

0:29:15.007 --> 0:29:18.847
<v S1>I now allows us to do with tools like this,

0:29:18.847 --> 0:29:21.207
<v S1>which are about to be drastically better. I mean, this

0:29:21.207 --> 0:29:25.087
<v S1>thing that found this is about to be 100% stupid

0:29:25.087 --> 0:29:27.927
<v S1>compared to whatever comes out next year or next week.

0:29:27.967 --> 0:29:31.847
<v S1>Right now, just imagine giving all that raw data and

0:29:31.847 --> 0:29:35.737
<v S1>even going to collect more, right? Getting sensory data from

0:29:35.737 --> 0:29:38.977
<v S1>cells or whatever from, you know, different layers of the

0:29:38.977 --> 0:29:42.137
<v S1>world and basically feeding it into this thing all the

0:29:42.137 --> 0:29:45.417
<v S1>time and saying your job is to connect dots. That's

0:29:45.457 --> 0:29:48.057
<v S1>that's the promise of AI. Your job is to connect dots.

0:29:48.097 --> 0:29:52.097
<v S1>So what we've basically done at that point is simulate

0:29:53.417 --> 0:29:58.177
<v S1>billions more people on the planet with training for connecting dots,

0:29:59.137 --> 0:30:00.657
<v S1>and then they could go, look, I came up with

0:30:00.657 --> 0:30:03.937
<v S1>all these hypotheses. And if you go test this, it's

0:30:03.937 --> 0:30:05.697
<v S1>probably going to work. Oh, and by the way, that

0:30:05.697 --> 0:30:09.577
<v S1>is actually a cure for, you know, 86% of cancers

0:30:09.577 --> 0:30:13.337
<v S1>or that will extend your life by 42 years, um,

0:30:13.337 --> 0:30:17.097
<v S1>or whatever. This will allow you to transfer your brain

0:30:17.097 --> 0:30:22.777
<v S1>into a, you know, digital, uh, synthetic form or whatever. Um,

0:30:23.217 --> 0:30:25.377
<v S1>I'm just blown away by this. Now, I sent this

0:30:25.377 --> 0:30:28.337
<v S1>article and my write up of this to a buddy,

0:30:28.337 --> 0:30:31.297
<v S1>and he's like, yeah, I'm actually, um, you know, invested

0:30:31.297 --> 0:30:36.067
<v S1>in and, you know, uh, an advisor for this company

0:30:36.107 --> 0:30:40.067
<v S1>who does that. Their specific thing is they are already

0:30:40.067 --> 0:30:44.867
<v S1>going and crawling all this other data. They are going

0:30:44.867 --> 0:30:48.987
<v S1>to find they have actively collected and are collecting all

0:30:48.987 --> 0:30:51.667
<v S1>this raw data and all these studies that basically didn't

0:30:51.667 --> 0:30:55.067
<v S1>go anywhere because they lost funding or whatever. That company,

0:30:55.347 --> 0:30:58.547
<v S1>this company he's talking about, it is actively doing that.

0:30:58.547 --> 0:31:02.787
<v S1>And guess what they're doing? They build the labs and

0:31:02.787 --> 0:31:06.787
<v S1>they're automating the labs. So when they do a hypothesis

0:31:06.947 --> 0:31:09.306
<v S1>and this is crazy, they already have use cases of

0:31:09.307 --> 0:31:12.027
<v S1>this working. So it's kind of even further than the

0:31:12.067 --> 0:31:15.587
<v S1>main story here. They have a use case of an

0:31:15.587 --> 0:31:20.307
<v S1>example of it actually, um, came up with a hypothesis.

0:31:21.187 --> 0:31:25.787
<v S1>It built a full, uh, methodology and schematic for how

0:31:25.787 --> 0:31:29.667
<v S1>to build the lab. And humans basically took that and

0:31:29.667 --> 0:31:31.877
<v S1>went into the lab. They built a little thing. They

0:31:31.877 --> 0:31:34.437
<v S1>basically set up the experiment exactly the way that the

0:31:34.437 --> 0:31:39.837
<v S1>I said to. And it 100% was true. They confirmed

0:31:40.397 --> 0:31:44.117
<v S1>experimentally that this hypothesis that it could come up with

0:31:44.117 --> 0:31:46.717
<v S1>was true. Now, if it had had the ability to

0:31:46.757 --> 0:31:50.517
<v S1>actually automate those tests, um, if it had the raw

0:31:50.517 --> 0:31:53.036
<v S1>materials in the lab and they had robotics or whatever,

0:31:53.637 --> 0:31:55.717
<v S1>that would have been even more insane, right? What if

0:31:55.717 --> 0:31:58.317
<v S1>it had the raw materials to to combine these molecules

0:31:58.317 --> 0:32:00.077
<v S1>or whatever? And there you got to be a little

0:32:00.077 --> 0:32:02.357
<v S1>bit careful because you don't want to just prompt inject

0:32:02.357 --> 0:32:05.477
<v S1>and it builds a, you know, a meth lab or a,

0:32:05.917 --> 0:32:10.117
<v S1>you know, sarin gas lab or whatever, a Covid lab, right.

0:32:10.237 --> 0:32:13.757
<v S1>Automated Covid generation. Um, so you got to be careful

0:32:13.757 --> 0:32:16.117
<v S1>with those. Obviously, this is what a lot of people

0:32:16.117 --> 0:32:21.557
<v S1>are worried about. But unbelievable, unbelievable possibility here in terms

0:32:21.557 --> 0:32:24.957
<v S1>of like connecting dots. And then the most important thing

0:32:24.997 --> 0:32:27.837
<v S1>and I talked about this, um, I got an essay

0:32:27.837 --> 0:32:30.167
<v S1>called The Path to Asi. I don't know. You guys

0:32:30.167 --> 0:32:32.647
<v S1>might have seen that it's came out. I don't know.

0:32:32.687 --> 0:32:35.007
<v S1>I put that out a few months ago and it

0:32:35.007 --> 0:32:39.567
<v S1>basically describes this process, right? You have hypotheses, you test them.

0:32:40.327 --> 0:32:43.567
<v S1>That's it. Right. Humans have hypotheses. They test them. But

0:32:43.567 --> 0:32:47.807
<v S1>we do it at such small scale. And more importantly, um,

0:32:47.967 --> 0:32:50.567
<v S1>real innovation comes from getting a bunch of smart people together,

0:32:50.567 --> 0:32:52.927
<v S1>like Bell Labs or the Renaissance, and a whole bunch

0:32:52.927 --> 0:32:56.047
<v S1>of smart people are together there talking about their ideas.

0:32:56.287 --> 0:32:59.127
<v S1>But the other person's idea that they're talking to influences

0:32:59.127 --> 0:33:04.647
<v S1>them slightly, changes their idea. Or even somebody, um, somebody, uh,

0:33:04.647 --> 0:33:09.727
<v S1>copies the idea, but they copy it incorrectly with a

0:33:09.727 --> 0:33:14.127
<v S1>slight deviation that actually makes it better. And that's absolutely insane.

0:33:14.247 --> 0:33:17.207
<v S1>So essentially what you have is like this evolution. You

0:33:17.207 --> 0:33:23.807
<v S1>have evolutionary biology or evolutionary, um, improvement happening to the

0:33:23.807 --> 0:33:29.827
<v S1>realm of ideas. Now, that is 100% Sense automatable as well.

0:33:29.827 --> 0:33:31.747
<v S1>You could use AI to do that. You could use

0:33:31.747 --> 0:33:35.187
<v S1>genetic algorithms to do that. You know, it's easy to

0:33:35.187 --> 0:33:37.947
<v S1>do this in a not sophisticated way, and I'm sure

0:33:37.947 --> 0:33:40.307
<v S1>you could do it in a lot more sophisticated ways

0:33:40.307 --> 0:33:42.306
<v S1>the more you think about it. But essentially you have

0:33:42.307 --> 0:33:46.187
<v S1>this engine of human generated ideas, AI generated ideas, and

0:33:46.187 --> 0:33:50.627
<v S1>then you have this evolutionary petri dish which constantly evolves them,

0:33:51.067 --> 0:33:54.827
<v S1>that spits out hypotheses which go through some sort of filter,

0:33:55.187 --> 0:33:58.667
<v S1>and then the higher quality ones go into this automated

0:33:58.707 --> 0:34:03.467
<v S1>testing lab and we start to have this giant Bell Labs.

0:34:05.627 --> 0:34:13.147
<v S1>Renaissance mechanism for inventing new things. Right. Inventing completely new things,

0:34:13.387 --> 0:34:17.227
<v S1>solving things like aging and cancer and all these different illnesses,

0:34:17.867 --> 0:34:21.907
<v S1>extending lifespan, like solving world hunger, like creating abundance on

0:34:21.907 --> 0:34:24.947
<v S1>the planet, like, you know, getting away from the zero

0:34:24.947 --> 0:34:28.477
<v S1>sum game of like capitalism and all this stuff. Like

0:34:29.117 --> 0:34:32.357
<v S1>you could literally use this engine to solve human problems,

0:34:32.677 --> 0:34:35.957
<v S1>you know, at scale. So all this is just massively

0:34:35.957 --> 0:34:39.117
<v S1>exciting to me. And I thought that was like the

0:34:39.117 --> 0:34:43.357
<v S1>most interesting story of the week. Apple releases controversial paper

0:34:43.357 --> 0:34:48.677
<v S1>on AI. Yeah, yeah. It was silly. It was a

0:34:48.677 --> 0:34:51.517
<v S1>silly paper. Um, some people are like, oh, you're behind

0:34:51.517 --> 0:34:53.917
<v S1>on AI. So now you release a paper that basically

0:34:53.917 --> 0:34:58.477
<v S1>says AI is stupid. Anyway. Um, I didn't even want AI. Uh,

0:34:58.477 --> 0:35:00.837
<v S1>it's dumb anyway. So that's why. That's why I'm not

0:35:00.837 --> 0:35:03.556
<v S1>trying hard. That's why other people are beating me. That's

0:35:03.557 --> 0:35:06.957
<v S1>not actually what happened though, because Apple Apple air quotes.

0:35:06.997 --> 0:35:12.477
<v S1>Apple isn't saying this. It is some ML team within Apple. Right.

0:35:12.517 --> 0:35:16.557
<v S1>Releasing this. So, um, anyway, it was a funny narrative.

0:35:16.717 --> 0:35:20.357
<v S1>OpenAI massively drops O3 prices. They dropped by 80% and

0:35:20.357 --> 0:35:24.877
<v S1>they also released O3 Pro. Um, OpenAI doubles revenue to

0:35:25.007 --> 0:35:29.567
<v S1>$10 billion annually. And OpenAI also must keep all ChatGPT

0:35:29.607 --> 0:35:33.927
<v S1>conversations indefinitely due to a legal hold related to a lawsuit.

0:35:34.567 --> 0:35:38.207
<v S1>I find this weird. I don't know how accurate this is.

0:35:38.207 --> 0:35:41.607
<v S1>If it's all like what exactly the scope is. There's

0:35:41.607 --> 0:35:43.647
<v S1>a quote here that says we are required to retain

0:35:43.647 --> 0:35:47.087
<v S1>all data. Cannot process deletion requests during this period. What

0:35:47.087 --> 0:35:49.607
<v S1>I don't know is if it applies to like tenants

0:35:49.607 --> 0:35:52.767
<v S1>where they've paid extra money just to have their stuff

0:35:52.807 --> 0:35:55.487
<v S1>be ephemeral, right? There are a lot of people with

0:35:55.527 --> 0:35:58.487
<v S1>like private Azure instances where like that was the whole

0:35:58.487 --> 0:36:01.607
<v S1>reason they're paying extra is the fact that it's ephemeral,

0:36:01.607 --> 0:36:04.967
<v S1>or it gets deleted constantly or they're able to delete it,

0:36:05.327 --> 0:36:07.767
<v S1>but I don't know if it applies there. I doubt it,

0:36:07.767 --> 0:36:12.286
<v S1>but who knows? OpenAI makes ChatGPT voice mode sound way

0:36:12.287 --> 0:36:18.007
<v S1>more human. Okay, go play with voice mode. Advanced voice

0:36:18.007 --> 0:36:22.367
<v S1>mode on ChatGPT. It is ridiculous. I mean, it is

0:36:22.367 --> 0:36:25.777
<v S1>absolutely ridiculous. I was having a conversation with it yesterday,

0:36:25.777 --> 0:36:28.737
<v S1>which I haven't talked to in a while, and it

0:36:28.737 --> 0:36:33.137
<v S1>felt so incredibly human. The pauses, the voice tones, it

0:36:33.137 --> 0:36:37.937
<v S1>actually sang. Um. At first it did like vocal song

0:36:37.977 --> 0:36:41.217
<v S1>and I was like, no, not, you know, uh, spoken

0:36:41.217 --> 0:36:46.177
<v S1>word actually sing. And it actually sung with, like, tone. Um, anyway,

0:36:46.577 --> 0:36:48.897
<v S1>I still use the Cove one because it sounds like, uh,

0:36:48.897 --> 0:36:52.497
<v S1>one of the AIS from interstellar, and that's my favorite voice, uh,

0:36:52.497 --> 0:36:57.697
<v S1>since they got rid of, uh, Samantha. All right, Stanford

0:36:57.697 --> 0:37:01.777
<v S1>study shows doctors put AI beat. Oh, plus, I beat

0:37:01.777 --> 0:37:08.297
<v S1>traditional diagnostic tools. So doctors normally in this particular test

0:37:09.537 --> 0:37:17.097
<v S1>were 75% accurate. Doctors with the AI were 85% accurate, 10% jump.

0:37:17.577 --> 0:37:21.657
<v S1>But the hilarious part and extremely sad part I by

0:37:21.787 --> 0:37:26.467
<v S1>itself was 90%. It was 5% better than the doctor

0:37:26.467 --> 0:37:31.787
<v S1>using I. So it's like, yeah, it's like, yeah, I

0:37:31.827 --> 0:37:34.027
<v S1>am way better than the doctor. This is the I talking.

0:37:34.027 --> 0:37:36.907
<v S1>I'm way better than the doctor. I am 15% of

0:37:36.907 --> 0:37:40.427
<v S1>the doctor. Now, if the doctor uses me and asks

0:37:40.427 --> 0:37:43.547
<v S1>me questions, it can almost be as smart as me,

0:37:43.547 --> 0:37:47.827
<v S1>but not quite. And we all know how early the

0:37:47.827 --> 0:37:50.107
<v S1>game is. We all know how bad I is at

0:37:50.107 --> 0:37:53.467
<v S1>certain things, and it's already to this point. And this

0:37:53.467 --> 0:37:56.107
<v S1>is not like some random study at a junior college.

0:37:56.147 --> 0:38:03.067
<v S1>This is a pretty large Stanford study. Insane. Absolutely insane. Uh,

0:38:03.067 --> 0:38:06.627
<v S1>Microsoft reshuffles leadership to focus on AI agents. My new

0:38:06.627 --> 0:38:10.747
<v S1>favorite description of a business mode. This is from Jamin Bell.

0:38:10.987 --> 0:38:13.347
<v S1>A real long term moat is just a sequence of

0:38:13.347 --> 0:38:16.827
<v S1>smaller moats stacked together. Each one buys time. And what

0:38:16.827 --> 0:38:18.987
<v S1>you do with that time, how fast you execute, how

0:38:18.987 --> 0:38:23.277
<v S1>quickly you evolve, determines whether you stay ahead. And my

0:38:23.277 --> 0:38:28.197
<v S1>analysis of this or my. You know, um. Clarification of

0:38:28.197 --> 0:38:31.357
<v S1>it or tightening it up is to me, that means

0:38:31.397 --> 0:38:35.237
<v S1>speed and adaptability is the only real moat. And a

0:38:35.237 --> 0:38:38.917
<v S1>hat tip to, uh, Clint Gibler, uh, my buddy for, uh,

0:38:38.917 --> 0:38:42.717
<v S1>sending me this, like, in a text or something. Um, really,

0:38:42.717 --> 0:38:47.637
<v S1>really good technology. Why Bell labs works so well. Uh,

0:38:47.637 --> 0:38:50.437
<v S1>we talked about that already. BYD's five minute charging puts

0:38:50.477 --> 0:38:53.717
<v S1>China in the lead for EVs. Five minute charging. That's

0:38:53.717 --> 0:38:58.957
<v S1>basically a gas station. Uh, very worried. Um, this is

0:38:58.957 --> 0:39:02.157
<v S1>why I want Tesla to win so bad. And now

0:39:02.157 --> 0:39:06.397
<v S1>also Waymo. Uh, I want, but it's got to be

0:39:06.397 --> 0:39:08.997
<v S1>Tesla because they're the ones making the cars. I'm really

0:39:08.997 --> 0:39:13.237
<v S1>worried about BYD. BYD is making extremely good cars. They

0:39:13.277 --> 0:39:18.077
<v S1>are subsidizing them. They have 10,000 EVs. And we're talking

0:39:18.077 --> 0:39:20.977
<v S1>about five minute charging like a gas station. I mean,

0:39:22.057 --> 0:39:24.617
<v S1>if they were to come here, they would crush right now.

0:39:24.617 --> 0:39:27.417
<v S1>So we need our options. We need American options to

0:39:27.457 --> 0:39:31.297
<v S1>be getting better way faster than they are right now.

0:39:32.417 --> 0:39:36.497
<v S1>Wing and Walmart expand drone delivery to 100 stores, which

0:39:36.497 --> 0:39:43.657
<v S1>is five major cities. Uh, Chinese tech behind Amazon's humanoid robots. Great.

0:39:43.657 --> 0:39:47.097
<v S1>So Amazon is doing humanoid robots now. Um, they're talking

0:39:47.097 --> 0:39:52.657
<v S1>about potentially having humanoid delivery drivers. And the tech is Chinese. Great.

0:39:53.497 --> 0:39:57.137
<v S1>YouTube loosens content rules using public interest as a standard.

0:39:57.377 --> 0:40:00.497
<v S1>And AWS has opened a new region in Taiwan with

0:40:00.617 --> 0:40:06.257
<v S1>three availability zones. Humans. Rents are dropping in most US

0:40:06.257 --> 0:40:09.617
<v S1>cities for the first time since 2023. Caffeine keeps your

0:40:09.617 --> 0:40:12.177
<v S1>brain awake even while you sleep, so you could actually sleep.

0:40:12.177 --> 0:40:15.777
<v S1>According to the study. You could actually sleep and stay asleep,

0:40:15.777 --> 0:40:19.347
<v S1>but you wake up more tired because your brain is

0:40:19.347 --> 0:40:24.067
<v S1>not properly resting. Because the caffeine. Because caffeine basically blocks

0:40:24.547 --> 0:40:28.427
<v S1>the sleep, um, receptor. Um, that's one of the mechanisms.

0:40:28.427 --> 0:40:32.067
<v S1>So that's probably related to why this is the case,

0:40:32.507 --> 0:40:34.627
<v S1>or at least why they found that to be the case.

0:40:34.667 --> 0:40:38.387
<v S1>Las Vegas fights record heat with massive tree planting. And

0:40:38.387 --> 0:40:41.587
<v S1>this is not, uh, like it's absorbing carbon. Uh, because

0:40:41.627 --> 0:40:44.067
<v S1>that wouldn't be nearly the amount of skill you need. Uh,

0:40:44.067 --> 0:40:47.787
<v S1>that's a planetary thing. But, um, for shade is what

0:40:47.787 --> 0:40:51.587
<v S1>they're talking about. Mushrooms may communicate using up to 50 words.

0:40:51.587 --> 0:40:56.787
<v S1>And forests offset global warming more than scientists previously thought.

0:40:57.547 --> 0:41:00.827
<v S1>So replanting the trees that we lost since the 1800s

0:41:00.827 --> 0:41:06.267
<v S1>could cool the planet by like half a degree, which

0:41:06.267 --> 0:41:10.747
<v S1>I think is Celsius. Uh, which would be cool. Uh,

0:41:10.747 --> 0:41:13.387
<v S1>I think we should do that. I think we should plant, like,

0:41:13.427 --> 0:41:19.797
<v S1>trillions of trees and just, uh, see if the temperature

0:41:19.797 --> 0:41:22.757
<v S1>falls really fast. See if CO2 levels fall really fast.

0:41:23.157 --> 0:41:25.317
<v S1>And if they do, um, cut down some of the trees.

0:41:25.877 --> 0:41:29.997
<v S1>That's what I think. And also carbon sequestration. And also

0:41:29.997 --> 0:41:34.317
<v S1>we should go all in on solar discovery. Someone built

0:41:34.317 --> 0:41:36.997
<v S1>an MCP server that actually runs on Cloudflare workers. So

0:41:36.997 --> 0:41:39.317
<v S1>you don't have to stand up your own infrastructure. Data

0:41:39.317 --> 0:41:43.717
<v S1>visualization reveals patterns in D&amp;D monster designs. How anthropic teams

0:41:43.717 --> 0:41:46.957
<v S1>use cloud code. We are No longer a serious country

0:41:46.957 --> 0:41:51.197
<v S1>by Paul Krugman. Great explanation of how model context protocols

0:41:51.197 --> 0:41:54.997
<v S1>is different from traditional APIs. I'm not sure I'm going

0:41:55.037 --> 0:41:57.117
<v S1>to read all these, because they're actually just links for

0:41:57.117 --> 0:42:00.637
<v S1>you to go and click on in the newsletter. Um,

0:42:00.637 --> 0:42:03.677
<v S1>so I'm just going to go right to aphorism of

0:42:03.677 --> 0:42:06.797
<v S1>the week. It is not death that we should fear,

0:42:06.797 --> 0:42:09.797
<v S1>but never beginning to live. It is not death that

0:42:09.797 --> 0:42:14.157
<v S1>we should fear, but never beginning to live. Marcus Aurelius.