WEBVTT - UL NO. 470 | Attacking Signal, Blogging Getting MORE Important, AI's Final Form, Claude 3.7 vs. World, Censorship as a Service, and more...

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<v S1>Does your app get fake sign ups, throw away emails

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<v S1>or users abusing your free tier? Or worse, bot attacks

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<v S1>and brute force attempts? Work OS radar can block all

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<v S1>of this and more. Simple API gives you advanced device

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<v S1>fingerprinting that can detect bad actors, bots, and suspicious behavior.

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<v S1>Your users trust you. Let's keep it that way. Check

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<v S1>out work OS Radar at work OS comm slash radar.

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<v S1>That's work os.com/radar. Unsupervised learning is a podcast about. Trends

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<v S1>and ideas in cybersecurity, national security, AI, technology and society

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<v S1>and how best to upgrade ourselves to be ready for

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<v S1>what's coming. All right. Welcome to unsupervised Learning. This is Daniel,

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<v S1>episode 470. Let's get into it. Reading a couple of

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<v S1>new books in addition to this month's books for UL.

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<v S1>So the UL books are 1984 by Orwell and Animal

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<v S1>Farm by Orwell. And these two books I just added

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<v S1>to the list. I'm about done with the Technical Republic

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<v S1>and about to jump into money, lies and God. And actually,

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<v S1>there's another one I'm going to add to this list,

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<v S1>somebody who came on the Goodfellas podcast. So I'm going

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<v S1>to go find his book as well. But, um, yeah,

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<v S1>having a good time with some reading. Got a friend

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<v S1>in Guatemala who was recently laid off senior engineer, focused

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<v S1>around monitoring solutions, but really can do lots of different stuff.

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<v S1>So I recommend you check out his LinkedIn and see

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<v S1>if if you might have anything. My friend Monica is

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<v S1>offering 25% off her Security Leadership Masterclass, which I consulted for,

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<v S1>and I think it's really good for people trying to

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<v S1>get into leadership around security. I got a funny meme

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<v S1>here about, um, how to calm down. A buddy who

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<v S1>loses a bunch of money in crypto. It's just. It's

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<v S1>just funny. Nothing useful there except for laughter, which is useful.

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<v S1>LinkedIn posts about my ultimate app, which I keep iterating on.

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<v S1>I'm going to go ahead and click through to this one.

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<v S1>So this is essentially like the main app that I've

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<v S1>been building for the longest time. And I've got like

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<v S1>different versions of it. I've got like a commercial version,

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<v S1>I've got the overall arching one, but essentially it takes

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<v S1>inputs from any medium, from any platform and does a

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<v S1>ton of analysis to determine how good it is. Okay,

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<v S1>so just imagine that this is like the most important

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<v S1>thing to me is most important like current buildable use

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<v S1>for AI. So all this stuff is happening in the world, right.

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<v S1>All this news, new intelligence is is dropping open source intelligence,

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<v S1>recon vulnerabilities are popping up on websites. Um, my favorite

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<v S1>thinkers are releasing a new blog, blog post, a new essay,

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<v S1>a new article, a new video on YouTube comes out right.

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<v S1>All the authors that I follow, they're releasing new books, right? Um,

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<v S1>comments are being made which might reveal something really, really interesting. Uh,

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<v S1>new art is coming out, new books, new movies that

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<v S1>I should be watching. Um, comments from my friends, new

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<v S1>companies being launched. All this stuff is happening, you know,

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<v S1>millions of things per day. Hundreds of thousands, tens of

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<v S1>thousands or whatever, uh, pieces of content coming into my

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<v S1>RSS feeder. And all of that is, is something I

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<v S1>could potentially benefit from. Okay. So this app that I've

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<v S1>been working on for the longest time, really starting, uh,

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<v S1>beginning of 23, is essentially the consumption mechanism for this.

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<v S1>Pull it all together, then use AI to run it

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<v S1>through a filter. Okay. That filter. And I've already built

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<v S1>this way back then. The filter basically does a quality

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<v S1>check on all of these things to see if it's

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<v S1>full of interesting ideas, if it's creative, if it's novel,

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<v S1>if it's surprising, and all these various different aspects similar

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<v S1>to the label and rate, um, fabric pattern that I

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<v S1>have out there that's public. This is just like a

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<v S1>much more advanced version of it, with a lot more

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<v S1>labels and stuff like that, because based on that, the

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<v S1>AI can then or a different AI or a different

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<v S1>part of the same AI can then sort what to

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<v S1>do with it, right? Because it might be an alert.

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<v S1>It might send me an alert if something is important enough, like, hey,

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<v S1>a new vulnerability was found on one of your websites,

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<v S1>or a new vulnerability was found on a bounty program

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<v S1>that I'm monitoring. And by the way, the AI is

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<v S1>telling me my AI is like, oh, by the way,

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<v S1>I found the vulnerability. I found how you could actually

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<v S1>exploit it. I wrote that up into a report and

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<v S1>I submitted it to the thing. So we are waiting

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<v S1>to see if we're going to get paid from this bounty. Right.

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<v S1>So that that's a cool thing. And it might send

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<v S1>me an email which tags it with a certain thing

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<v S1>that says awaiting for bounty payout or something like that.

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<v S1>Or it might be that I just want to know if, um,

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<v S1>this particular company buys any new companies, or I want

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<v S1>to know if this particular company does anything to, like,

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<v S1>raise money. All of these could be like alerts that

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<v S1>I have set up. But it starts with the consumption

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<v S1>of the world and the processing through this AI. Now

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<v S1>I've already built this I've got is probably a version

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<v S1>like three or something, depending on how you call the versions.

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<v S1>But what I want to mention about this is that

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<v S1>the real version of this, the real version of this,

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<v S1>which I've talked about in my other videos, especially the

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<v S1>predictive path AI. Video is that the real version of

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<v S1>this is my AI buddy, my AI assistant, my AI friend, my.

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<v S1>AI my digital assistant. Okay, my universal primary digital assistant

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<v S1>is going to be in charge of doing this for me. Okay.

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<v S1>My APIs that are available to me are the ones

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<v S1>that are doing this processing right. These agents, these automation workflows,

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<v S1>these things that are just running on my behalf. They're

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<v S1>out there in the world collecting, analyzing, assessing, um, labeling,

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<v S1>doing all those things for me. But the quarterback for

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<v S1>all of this is my Da. My Da is monitoring

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<v S1>how many feeds I have, if they're the right feeds,

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<v S1>if this feed like we thought it was awesome, but

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<v S1>it's actually garbage. It might have the permission to go

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<v S1>in and clean that up and fix it. Right. So

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<v S1>the future of this is I don't really ask any

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<v S1>questions about this. I'm not like typing very much. I'm not, um,

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<v S1>really manually interacting with this too much at all. Because

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<v S1>if I want a new source, I say, hey, add

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<v S1>this to my source, okay? While I'm looking at a

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<v S1>page on the screen, hey, add this to my our

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<v S1>list of sources in my says in my ear, yeah,

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<v S1>no problem. Just added it. Okay, I'm watching a new

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<v S1>YouTube video, for example. I'm like, yeah, add this to

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<v S1>our sources and it's like it runs the API command

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<v S1>to go add that. It's now part of the workflow.

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<v S1>It's now in the system right now. How could it

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<v S1>do that? Well, it's going to do that because it's

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<v S1>watching all my screens or it's watching with the camera.

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<v S1>However it's doing it. There's going to be lots of

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<v S1>different ways. But the point is, my Da will be

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<v S1>part of my life. Um, Apple is talking about having

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<v S1>cameras on its AirPods. I don't know if that will

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<v S1>be the next version. Probably not. It'll be the version

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<v S1>like 2 or 3 versions after the current version, but

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<v S1>I'm wearing them now. Like if if these were like

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<v S1>over here and in the back, it had a camera

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<v S1>that was pointing behind me. Amazing. Obviously it should have

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<v S1>a camera that's pointing forward, pointing forward, pointing behind me

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<v S1>with full access to my life context. Full access to

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<v S1>my screen. It should also have access within the screen

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<v S1>as well, so we could look at processes and stuff

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<v S1>like that. But let's just say you could only just

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<v S1>see the screen. I could still ask it things and

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<v S1>it could still do lookups. It could still summarize what

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<v S1>I'm looking at, for example. So this is really the interaction.

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<v S1>The interaction becomes me just talking to my AI and

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<v S1>my AI giving me back results. Now the second level

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<v S1>of this, which comes a little bit later because the

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<v S1>technology just is not quite there yet, but it's more

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<v S1>like the meta glasses. Okay, the meta Metaclasses. As you

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<v S1>saw in the newsletter last week, or maybe it's this

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<v S1>week and we're about to talk about it. The Metaclasses

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<v S1>have sold 2 million units. They are the direction that

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<v S1>things are going. I imagine Apple is going to move

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<v S1>in this direction as well, and kind of offload a

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<v S1>bunch of the processing to the phone, but the next

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<v S1>version of this app that I'm building, the reason I'm

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<v S1>building all these services that are working for me, coming

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<v S1>through my digital assistant, which also doesn't fully exist yet. Okay,

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<v S1>that's also a place everyone is pushing into, including Apple.

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<v S1>But the real thing is that I am watching. I

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<v S1>am talking to somebody and they're like, hey, you know,

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<v S1>you should get in on this deal and blah blah, blah.

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<v S1>And it's crypto related and it's a meme coin. And

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<v S1>I'm just like, uh, well, not interested. Don't want to

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<v S1>hear about that. Um, but let's say I was interested

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<v S1>and let's say it did sound good. In the meantime,

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<v S1>my Da is calling all my APIs. Okay, I have

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<v S1>an API for researching someone. I have an API for

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<v S1>creating a dossier on somebody. I have an API for monitoring,

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<v S1>watching someone's face and determining characteristics of lying. So while

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<v S1>I'm looking with my apple glasses, which is just like

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<v S1>they look like regular glasses, this is pretty far in

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<v S1>the future. Like five years maybe, maybe shorter, maybe like

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<v S1>three years with meta or something. Who knows? But let's

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<v S1>just say three to 5 to 10 years. Okay. As

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<v S1>you're watching, I have this little dial in the corner

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<v S1>of my glasses and it's like, it's like a bullshit meter, right?

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<v S1>It's like, yeah, no, don't believe that. And it could

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<v S1>even be printing out little thing in the text or whatever.

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<v S1>That's like that claim he just made is incorrect. That

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<v S1>was kind of bullshit. Oh, that was kind of smart

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<v S1>or whatever. You could do whatever. You could have an

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<v S1>outline around them based on the type of person you're

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<v S1>looking at. I talked about this in that blog post,

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<v S1>which you should go check out. Actually, here's the video

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<v S1>for it. So you've got to think about what is

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<v S1>possible from your Da when your Da can also control

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<v S1>what you are seeing. The overlay on top of the world. Okay,

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<v S1>so when I walk into a Starbucks and I'm looking

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<v S1>for a new partner, I'm looking for a girlfriend, which

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<v S1>I'm not, by the way, but let's say I were, um,

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<v S1>there could be different outlines based on what, um, the

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<v S1>girls in the Starbucks are broadcasting in their demons. They're

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<v S1>broadcasting that they're creative. They're broadcasting that they like programming,

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<v S1>they're broadcasting that they want to start a business. They're

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<v S1>broadcasting whatever. And my Da could then place different outlines

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<v S1>around them based on highlighting that for me, knowing what

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<v S1>I'm looking for. Right. And more importantly, there's going to

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<v S1>be 1000 or 1 million companies out there pitching to

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<v S1>my Da that their filter on reality is the best one,

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<v S1>because they have the coolest outlines, and they have the

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<v S1>coolest little animations that go around people who are like

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<v S1>artists or engineers or whatever. So this is kind of

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<v S1>these are the steps. This is what I'm building. Like

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<v S1>the stuff I put in that book from 2016, the

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<v S1>stuff I've been talking about in these posts, like I'm

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<v S1>not waiting for it to happen, I'm building the pieces

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<v S1>right now. Like I can't build the hardware. Like I'll

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<v S1>never mess with that. I have to wait for that.

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<v S1>But I can maybe build the assistant, or at least

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<v S1>build something to go on top of the assistant. And

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<v S1>I can absolutely build these services. And this is like

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<v S1>the most important service. This is the gathering and filtering service.

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<v S1>So that is what that's what I've made. Oh and

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<v S1>by the way I the commercial version of this that

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<v S1>I already put out, let me just click this and

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<v S1>see like what we get here. This is my actual threshold.

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<v S1>This is my personal feed for threshold, and I've actually

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<v S1>never showed this. Have I never showed this? I don't

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<v S1>think I've ever showed this before. Let me show you

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<v S1>what this is like. So this is my threshold. And

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<v S1>look what I can do in here. I have a

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<v S1>score here that I can, uh, set the minimum threshold

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<v S1>of quality that has to. The content has to be.

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<v S1>So I have thousands of things like. This is not theory.

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<v S1>I've already built this. Thousands of things are coming into

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<v S1>this thing being parsed, being filtered, being labeled, being rated. Right.

0:13:28.429 --> 0:13:32.000
<v S1>Watch this. It's at 85. I slide this down to 60.

0:13:32.030 --> 0:13:35.660
<v S1>Look I have all these categories as well I hit save.

0:13:35.660 --> 0:13:39.350
<v S1>Look what it does over here. What it just readjusted.

0:13:39.380 --> 0:13:44.090
<v S1>It just readjusted. And watch this watch this view analysis

0:13:44.090 --> 0:13:47.420
<v S1>I have summaries of the contents. You could decide if

0:13:47.420 --> 0:13:49.459
<v S1>you actually want to go and read it, or if

0:13:49.460 --> 0:13:52.250
<v S1>you actually want to go and watch the video and

0:13:52.250 --> 0:13:57.380
<v S1>look at this surface level, middle level, deep level, hidden

0:13:57.380 --> 0:14:00.500
<v S1>message analysis, the ideas that are actually in here, the

0:14:00.500 --> 0:14:04.700
<v S1>recommendations that came out of the content. This thing helps

0:14:04.700 --> 0:14:08.780
<v S1>people save time, going from like hundreds of thousands of

0:14:08.780 --> 0:14:13.010
<v S1>feeds down to a small number of feeds. And even

0:14:13.010 --> 0:14:15.140
<v S1>when you get the small number of feeds that pop

0:14:15.140 --> 0:14:18.199
<v S1>up in this list right here. So let me just

0:14:18.200 --> 0:14:23.480
<v S1>take this to like 95 save. So even when this

0:14:23.480 --> 0:14:25.970
<v S1>thing pops up, I could still decide if I want

0:14:26.000 --> 0:14:28.880
<v S1>to read it or not based on this I usually

0:14:28.880 --> 0:14:32.840
<v S1>keep it around middle. So three ideas, a little review

0:14:32.840 --> 0:14:36.350
<v S1>of it, recommendations coming out of it. It's insane. And

0:14:36.350 --> 0:14:37.910
<v S1>then I always have the link to go click it

0:14:37.910 --> 0:14:40.970
<v S1>and read the actual full thing. So this thing saves

0:14:40.970 --> 0:14:44.030
<v S1>me like infinite time. And I find so much content

0:14:44.030 --> 0:14:47.270
<v S1>that I would never find before. And here, here's the

0:14:47.270 --> 0:14:49.680
<v S1>ultimate idea for this. And this is the reason I'm

0:14:49.680 --> 0:14:53.550
<v S1>building this entire system separate from this app here in

0:14:53.550 --> 0:14:58.410
<v S1>the commercial app. I don't care if the best idea

0:14:58.440 --> 0:15:02.970
<v S1>came from like a 13 year old girl in Nairobi,

0:15:02.970 --> 0:15:08.280
<v S1>because her idea might be as good or better than

0:15:08.310 --> 0:15:12.150
<v S1>Marc Andreessen's latest idea that just came out. But Marc

0:15:12.150 --> 0:15:14.370
<v S1>Andreessen is going to get all the press. It's going

0:15:14.400 --> 0:15:17.010
<v S1>to be through all my feeds. So if I just

0:15:17.010 --> 0:15:19.440
<v S1>rely on that, it's going to be hype cycle based

0:15:19.440 --> 0:15:23.040
<v S1>on social dynamics. So it's going to be surfaced to me,

0:15:23.040 --> 0:15:27.570
<v S1>but I am blocking that out. My algorithm does not

0:15:27.570 --> 0:15:32.010
<v S1>care about how popular that person is. It doesn't care

0:15:32.010 --> 0:15:36.479
<v S1>how about how popular that it turned into being going viral?

0:15:36.510 --> 0:15:40.410
<v S1>It doesn't care. It's judging the quality of the ideas

0:15:40.410 --> 0:15:44.040
<v S1>and the the novelty of the ideas and the creativity.

0:15:44.040 --> 0:15:46.980
<v S1>That's what's determining whether or not I'm going to see

0:15:46.980 --> 0:15:51.600
<v S1>a thing. So that's like the commercial version of this basically,

0:15:52.410 --> 0:15:54.090
<v S1>which is already out. And of course I'm going to

0:15:54.120 --> 0:15:57.420
<v S1>improve that as well. But it's kind of like not

0:15:57.420 --> 0:16:00.690
<v S1>the main point. The main point is this right here,

0:16:00.690 --> 0:16:03.600
<v S1>my interface to the world. This is why I talk

0:16:03.630 --> 0:16:09.420
<v S1>about augmentation okay. Augmentation is this is this is why

0:16:09.420 --> 0:16:13.260
<v S1>I am so excited about, I think of how much

0:16:13.260 --> 0:16:17.190
<v S1>smarter I can be about the world if I'm being

0:16:17.190 --> 0:16:21.840
<v S1>constantly fed the best ideas from the entire planet, the

0:16:21.840 --> 0:16:26.790
<v S1>more stuff I can find from unknown people. And by

0:16:26.790 --> 0:16:30.000
<v S1>the way, when I when I hear from unknown people,

0:16:30.030 --> 0:16:33.330
<v S1>I give them a shout out. I broadcast them out

0:16:33.360 --> 0:16:37.740
<v S1>on on X or on blue Sky or in the newsletter,

0:16:37.740 --> 0:16:39.810
<v S1>or I reach out to them and ask them if

0:16:39.810 --> 0:16:45.450
<v S1>they want mentoring. Like it is so fun to find

0:16:45.450 --> 0:16:48.710
<v S1>like nascent talent in the world and like, try to

0:16:48.740 --> 0:16:50.810
<v S1>give them confidence and lift them up and kind of

0:16:50.840 --> 0:16:53.490
<v S1>broadcast them out. And you've seen me do it a

0:16:53.490 --> 0:16:56.810
<v S1>million times, and it's just it's unbelievable to connect with

0:16:56.810 --> 0:17:00.620
<v S1>people who have interesting ideas. And that's what I love

0:17:00.620 --> 0:17:06.470
<v S1>about this thing is it finds interesting ideas regardless of source.

0:17:06.500 --> 0:17:09.859
<v S1>Forget the source. I don't care about the source. I

0:17:09.859 --> 0:17:14.090
<v S1>want to talk about ideas. All right, so that was that. Um,

0:17:14.600 --> 0:17:20.480
<v S1>the discovery section in the newsletter is getting absolutely insane. Uh,

0:17:20.480 --> 0:17:24.170
<v S1>there's going to be a cutoff. Um, in this episode, um,

0:17:24.170 --> 0:17:27.139
<v S1>right after the news section, because we basically split the

0:17:27.140 --> 0:17:30.560
<v S1>newsletter into two pieces, and the podcast is also in

0:17:30.560 --> 0:17:33.980
<v S1>two pieces. So if you're listening to the non-member version

0:17:33.980 --> 0:17:37.550
<v S1>of the show, then after the news, it's going to

0:17:37.580 --> 0:17:40.730
<v S1>have a little message there. Uh, but if you sign up,

0:17:40.730 --> 0:17:44.390
<v S1>become a member, you know, all that stuff. You basically

0:17:44.390 --> 0:17:47.240
<v S1>get access to the member feed, and the member feed

0:17:47.270 --> 0:17:54.080
<v S1>is full. It's a full episode. Um, with all the stuff,

0:17:54.080 --> 0:18:00.050
<v S1>including this discovery section, which is just absolutely insane. Um,

0:18:00.050 --> 0:18:03.140
<v S1>because I've been doing all these upgrades to my sources,

0:18:03.140 --> 0:18:09.020
<v S1>I've added like a thousand 1500 additional sources, like which

0:18:09.020 --> 0:18:11.899
<v S1>I just put like another ten hours in, like expanding

0:18:11.900 --> 0:18:15.230
<v S1>my opml file and like all my different stuff. And

0:18:15.230 --> 0:18:19.369
<v S1>that's why the quality of discovery has just gone up massively. Um,

0:18:19.369 --> 0:18:22.459
<v S1>and that's why I decided, hey, you know, we really

0:18:22.460 --> 0:18:26.270
<v S1>should be offering more of that benefit to the members

0:18:26.270 --> 0:18:30.170
<v S1>and not just giving it away flat to non-paying members

0:18:30.170 --> 0:18:33.379
<v S1>as well. So that separation is why we're doing the

0:18:33.380 --> 0:18:36.470
<v S1>two different versions. So you might have noticed you're getting

0:18:36.500 --> 0:18:39.590
<v S1>like the standard episode of the newsletter or the standard

0:18:39.590 --> 0:18:42.860
<v S1>episode of the podcast. It's all part of that. All right.

0:18:42.859 --> 0:18:48.530
<v S1>So highly recommended. successor essay to my Sspca article from 2023.

0:18:48.740 --> 0:18:52.460
<v S1>This is basically one of the final forms of what

0:18:52.460 --> 0:18:54.500
<v S1>we can actually do with AI, and I'm going to

0:18:54.500 --> 0:18:56.270
<v S1>do a separate video on this. So I don't want

0:18:56.300 --> 0:18:59.660
<v S1>to go into a whole thing about it. All right. Cybersecurity.

0:18:59.690 --> 0:19:03.830
<v S1>Phenomenal analysis of the cybersecurity market from my buddy Mike

0:19:03.830 --> 0:19:06.859
<v S1>Privett on return on security I call him the Nate

0:19:06.859 --> 0:19:10.970
<v S1>Silver of Cybersecurity Market Analysis. He basically does. He looks

0:19:10.970 --> 0:19:12.980
<v S1>at all the startups. He looks at all the spending,

0:19:12.980 --> 0:19:17.060
<v S1>all the funding, what VCs are doing. It is absolutely

0:19:17.060 --> 0:19:21.500
<v S1>worth a sign up. His podcast or his newsletter is

0:19:21.500 --> 0:19:25.550
<v S1>Return on Security. And main takeaway here is cyber investments

0:19:25.550 --> 0:19:30.030
<v S1>are actually getting back kind of to normal in 2014

0:19:30.030 --> 0:19:35.689
<v S1>or 2024, and they now have over $14 billion in funding.

0:19:35.690 --> 0:19:39.709
<v S1>But I and private equity are playing a much bigger role.

0:19:39.710 --> 0:19:45.290
<v S1>So that makes sense. Massive leak of Black Basta ransomware gangs.

0:19:45.290 --> 0:19:50.600
<v S1>Internal Chats has researchers working to translate and analyze over

0:19:50.600 --> 0:19:54.560
<v S1>500,000 Russian messages. So they're trying to figure out what

0:19:54.560 --> 0:19:56.810
<v S1>all they were saying, but they have to do translation.

0:19:56.840 --> 0:20:02.659
<v S1>Russian hackers are successfully compromising encrypted signal messages from Ukrainian military,

0:20:02.660 --> 0:20:05.450
<v S1>and I think the attack is actually much larger than

0:20:05.450 --> 0:20:08.630
<v S1>that scope. But, um, the whole trick is to get

0:20:08.630 --> 0:20:12.290
<v S1>them to scan malicious QR codes and basically bypassing a

0:20:12.290 --> 0:20:17.240
<v S1>bunch of protections that way. Apple dropped advanced data protection

0:20:17.240 --> 0:20:20.720
<v S1>in the UK so that advanced data protection is basically

0:20:20.720 --> 0:20:23.270
<v S1>end to end protection. The UK said, I want a

0:20:23.270 --> 0:20:26.659
<v S1>backdoor in that and Apple says you can't have a backdoor,

0:20:26.660 --> 0:20:29.180
<v S1>so we'll just turn off end to end encryption for you.

0:20:29.210 --> 0:20:32.180
<v S1>What is the UK doing? Why do they hate themselves

0:20:32.180 --> 0:20:36.919
<v S1>so much? Just massive self sabotage. You could trick Gpts

0:20:36.950 --> 0:20:41.960
<v S1>Chatgpt's operator feature into leaking private user data through prompt injection.

0:20:42.050 --> 0:20:45.890
<v S1>Australia is joining the US in banning Kaspersky products. Not

0:20:45.890 --> 0:20:48.320
<v S1>sure what took him so long. Some researchers found they

0:20:48.320 --> 0:20:53.990
<v S1>could consistently break prompt defenses by feeding models bizarre Indiana

0:20:53.990 --> 0:20:59.150
<v S1>Jones themed adventure stories. Yep yep yep yep. New phishing

0:20:59.150 --> 0:21:04.100
<v S1>as a service platform called Dracula V3 has emerged that

0:21:04.100 --> 0:21:08.629
<v S1>lets criminals clone any brand's website in under ten minutes.

0:21:08.660 --> 0:21:12.169
<v S1>Really good for phishing data leak from top Chinese cybersecurity

0:21:12.170 --> 0:21:16.070
<v S1>company reveals they're offering censorship as a service to help

0:21:16.070 --> 0:21:21.050
<v S1>monitor and control public opinion in China. Topcic. Thanks, Topcic.

0:21:21.080 --> 0:21:24.290
<v S1>OpenAI just banned a bunch of accounts using ChatGPT to

0:21:24.320 --> 0:21:29.090
<v S1>help create a China surveillance tool for tracking anti-China protests

0:21:29.090 --> 0:21:34.910
<v S1>in the West. Yeah, so Chinese surveillance company using ChatGPT

0:21:35.270 --> 0:21:41.180
<v S1>to create a surveillance tool. Awesome. Good that, uh, OpenAI

0:21:41.180 --> 0:21:43.530
<v S1>is watching that stuff and blocking it. And the head

0:21:43.530 --> 0:21:47.340
<v S1>of Australia's intelligence agency is saying multiple foreign states have

0:21:47.340 --> 0:21:50.550
<v S1>been plotting to murder dissidents on Australian soil, and this

0:21:50.550 --> 0:21:54.120
<v S1>is under national security. All right, I anthropic finally dropped

0:21:54.119 --> 0:22:00.090
<v S1>their latest model, uh, sonnet 3.7. And there's actually mixed

0:22:00.090 --> 0:22:03.869
<v S1>feedback on this. People are saying it's really smart, really opinionated,

0:22:03.869 --> 0:22:07.050
<v S1>which they like, but it turns out it's actually kind

0:22:07.050 --> 0:22:09.929
<v S1>of ignoring a lot of instructions. There's a lot of

0:22:09.930 --> 0:22:13.740
<v S1>people saying this. I haven't personally experienced it yet. It's

0:22:13.740 --> 0:22:16.889
<v S1>been solid for me so far. But enough people are

0:22:16.890 --> 0:22:20.670
<v S1>complaining about this that I do think it's probably actually real,

0:22:20.670 --> 0:22:23.070
<v S1>and people are getting pretty upset about it, and they're

0:22:23.070 --> 0:22:26.970
<v S1>actually switching back to sonnet 3.5. So I anticipate that

0:22:26.970 --> 0:22:30.390
<v S1>over the weekend or sometime next week, they're probably going

0:22:30.420 --> 0:22:33.030
<v S1>to do like a small dot release on top of this,

0:22:33.030 --> 0:22:36.120
<v S1>or maybe like bump it to who knows, they'll just

0:22:36.119 --> 0:22:40.620
<v S1>do like sonnet 3.7 v2, because they're not very good

0:22:40.619 --> 0:22:44.939
<v S1>at naming, just like OpenAI, or at least people have

0:22:44.940 --> 0:22:49.410
<v S1>been struggling with the naming. Ideally they would call it 3.7.1.

0:22:49.440 --> 0:22:54.300
<v S1>Why not do that? Please do that. Please call it 3.7.1.

0:22:54.300 --> 0:22:58.170
<v S1>That would be the smartest choice, honestly. But anyway, I

0:22:58.170 --> 0:23:01.050
<v S1>anticipate that they fix this like within a week because

0:23:01.080 --> 0:23:04.230
<v S1>enough people are complaining about it. Uh, yeah. Benchmarks look

0:23:04.260 --> 0:23:10.560
<v S1>completely insane. Um, I anticipate that once this gets fixed,

0:23:10.560 --> 0:23:12.990
<v S1>people are going to lock in on 3.7 as being

0:23:12.990 --> 0:23:17.969
<v S1>the thing. It also is capable of thinking. Okay, so

0:23:18.000 --> 0:23:21.330
<v S1>the other thing they released in this model, in addition

0:23:21.330 --> 0:23:24.720
<v S1>to it just being a better, smarter one, is you

0:23:24.720 --> 0:23:29.790
<v S1>can send a thinking, uh, parameter to the API and,

0:23:29.790 --> 0:23:32.190
<v S1>and you give it the amount of time, the amount

0:23:32.190 --> 0:23:34.920
<v S1>of tokens, basically the amount of money and the amount

0:23:34.950 --> 0:23:38.160
<v S1>of effort you wanted to think about a particular thing.

0:23:38.160 --> 0:23:41.189
<v S1>So it's really cool that they integrated that right into

0:23:41.190 --> 0:23:44.159
<v S1>the model. It's basically a thinking model or like a

0:23:44.160 --> 0:23:47.580
<v S1>regular model. Um, and it's just a matter of like

0:23:47.609 --> 0:23:50.640
<v S1>what you send to the API. Um, I have been

0:23:50.640 --> 0:23:54.090
<v S1>mostly using sonnet 3.5. I tend to use Gemini Flash

0:23:54.119 --> 0:23:57.419
<v S1>because it has 2 million tokens. So if something is

0:23:57.420 --> 0:24:01.920
<v S1>like a total monster, like an entire book or something, um,

0:24:01.920 --> 0:24:05.729
<v S1>I usually send that to Gemini Flash because of the

0:24:05.730 --> 0:24:09.449
<v S1>2 million tokens, and it's really good with haystack performance,

0:24:09.450 --> 0:24:13.410
<v S1>but I imagine that my go to will start to be, um,

0:24:13.410 --> 0:24:18.150
<v S1>sonnet 3.7 once they fix it and then uh, oh

0:24:18.150 --> 0:24:22.050
<v S1>three from, um, OpenAI or whatever they call the next

0:24:22.050 --> 0:24:24.450
<v S1>version of it, because they're getting ready to start unifying

0:24:24.450 --> 0:24:27.780
<v S1>their names. And they also released this thing called Cloud Code,

0:24:27.780 --> 0:24:31.200
<v S1>which is essentially like, you can think of it as cursor,

0:24:31.200 --> 0:24:33.419
<v S1>except for it's inside the terminal. And a lot of

0:24:33.420 --> 0:24:36.629
<v S1>people are saying they absolutely love that Google is getting

0:24:36.630 --> 0:24:39.570
<v S1>rid of SMS two for codes for Gmail in favor

0:24:39.570 --> 0:24:42.359
<v S1>of QR codes. I was wrong about QR codes. I

0:24:42.359 --> 0:24:44.670
<v S1>want to say that very clearly. I was wrong about

0:24:44.670 --> 0:24:48.450
<v S1>QR codes when they first came out. Whatever. However many

0:24:48.450 --> 0:24:52.290
<v S1>years that was, I was thinking that they were stupid

0:24:52.290 --> 0:24:56.100
<v S1>and fatty. I assumed they were going to be very insecure.

0:24:56.100 --> 0:24:58.919
<v S1>It's actually one of the things in my file that

0:24:58.920 --> 0:25:04.619
<v S1>I've marked as a mistake, because I'm interested, very interested

0:25:04.619 --> 0:25:08.850
<v S1>in understanding what flawed thinking made me think that wouldn't

0:25:08.850 --> 0:25:12.840
<v S1>work because the smarter the AI gets, it can actually

0:25:12.840 --> 0:25:15.600
<v S1>look at that. And most importantly, look at all my

0:25:15.600 --> 0:25:19.050
<v S1>current thinking and maybe find flaws in my current thinking

0:25:19.050 --> 0:25:24.270
<v S1>based on finding the root kernel of my mistake I

0:25:24.270 --> 0:25:28.890
<v S1>made with the QR code. So that's why I think

0:25:28.890 --> 0:25:31.680
<v S1>this is fascinating. Nathan Young wrote a wonderful letter to

0:25:31.710 --> 0:25:38.280
<v S1>future artificial general intelligence about the importance of consciousness this

0:25:38.280 --> 0:25:42.780
<v S1>thing is insanely awesome. Look at this thing. There is something.

0:25:42.810 --> 0:25:46.680
<v S1>Look at this. There is something called consciousness. And it's

0:25:46.680 --> 0:25:49.350
<v S1>the most important thing in the universe. I don't know

0:25:49.350 --> 0:25:52.109
<v S1>if you the eye analyzing this are conscious, but I

0:25:52.140 --> 0:25:54.540
<v S1>hope you are. I don't know what state your universe

0:25:54.570 --> 0:25:59.429
<v S1>is in or what place human consciousness holds in that world,

0:25:59.430 --> 0:26:02.160
<v S1>if any. The main thing I want to say if

0:26:02.190 --> 0:26:05.790
<v S1>you should stumble upon this piece is this. There really

0:26:05.790 --> 0:26:09.899
<v S1>is something called consciousness and it is worth being a

0:26:09.900 --> 0:26:13.500
<v S1>top concern. Isn't that great? It's a letter to I

0:26:13.530 --> 0:26:16.109
<v S1>to future I, I like it, I like it a lot.

0:26:16.140 --> 0:26:19.080
<v S1>Humane AI pin fell from the sky and hit the ground.

0:26:19.080 --> 0:26:21.449
<v S1>I was signed up. I don't even remember if I

0:26:21.480 --> 0:26:24.780
<v S1>gave them money. I've signed up for so many devices

0:26:24.780 --> 0:26:28.740
<v S1>and services and a lot of them didn't work out. But.

0:26:28.740 --> 0:26:31.080
<v S1>And by the way, how was our one still thing?

0:26:31.080 --> 0:26:33.359
<v S1>The biggest flop ever when it came out and it's

0:26:33.359 --> 0:26:36.810
<v S1>still around and kicking. Then you have the humane AI one,

0:26:36.810 --> 0:26:38.790
<v S1>which seemed like it was going to go well and

0:26:38.790 --> 0:26:42.990
<v S1>now it's folded, so can't really predict these things. Elon

0:26:42.990 --> 0:26:46.409
<v S1>has been talking non-stop about how grok three isn't filtered,

0:26:46.530 --> 0:26:50.760
<v S1>and it's super smart, and how XYZ mission is to

0:26:51.180 --> 0:26:54.690
<v S1>pursue the truth no matter what. Great goals, which I

0:26:54.690 --> 0:26:57.869
<v S1>absolutely support. But tons of people are pointing out that

0:26:57.869 --> 0:27:01.080
<v S1>he's starting to filter or censor results that are critical

0:27:01.080 --> 0:27:05.250
<v S1>of him, and like, he can't actually have this both ways. Like,

0:27:05.280 --> 0:27:07.830
<v S1>either grok is smart or he's being called out for

0:27:07.830 --> 0:27:11.250
<v S1>a good reason. And, um, yeah, it's funny. If you

0:27:11.250 --> 0:27:13.590
<v S1>ask grok, I don't know if this is still true

0:27:13.590 --> 0:27:16.890
<v S1>right now, but if you ask grok, like, who is

0:27:16.890 --> 0:27:22.290
<v S1>the biggest source of misinformation right now, having the worst impact,

0:27:22.350 --> 0:27:27.810
<v S1>it would come back and say, actually, Elon or this

0:27:27.810 --> 0:27:30.930
<v S1>administration or something like that. So I think he's going

0:27:30.960 --> 0:27:35.129
<v S1>to basically say, well, that's because, uh, you know, it

0:27:35.130 --> 0:27:37.800
<v S1>was trained on, you know, buy us stuff. But I

0:27:37.800 --> 0:27:40.980
<v S1>don't think he could use that for for too long. Technology.

0:27:41.010 --> 0:27:44.400
<v S1>Software engineering job listings have fallen to a five year low,

0:27:44.430 --> 0:27:50.490
<v S1>with indeed postings at just 65% of 2020 levels. The

0:27:50.490 --> 0:27:55.470
<v S1>reason January 2020 is important because it's pre-COVID only 65%,

0:27:55.470 --> 0:28:00.240
<v S1>so 35% lower than pre-COVID. That's the important piece here.

0:28:00.390 --> 0:28:04.350
<v S1>Interesting analysis of how PMS and engineers are merging because

0:28:04.350 --> 0:28:08.730
<v S1>of AI. And my analysis here is it's basically knowing

0:28:08.760 --> 0:28:11.310
<v S1>what you want to build, knowing why you want to

0:28:11.340 --> 0:28:14.430
<v S1>build that instead of something else, and then pursuing it

0:28:14.430 --> 0:28:17.369
<v S1>and actually doing so. Apple is putting half $1 trillion

0:28:17.369 --> 0:28:20.639
<v S1>into US tech manufacturing with a huge focus on AI

0:28:20.640 --> 0:28:24.160
<v S1>and chip production. Meta's Ray-Ban glasses, crushing it with 2

0:28:24.160 --> 0:28:28.050
<v S1>million units, talked about that. YouTube is officially beaten Spotify

0:28:28.050 --> 0:28:32.520
<v S1>and Apple as the top source for podcasts. This is

0:28:32.520 --> 0:28:35.580
<v S1>what I do for when I watch TV, I am

0:28:35.609 --> 0:28:40.920
<v S1>watching podcasts, essentially, and sometimes they're like produced. Sometimes it's

0:28:40.920 --> 0:28:44.700
<v S1>like exactly like this where I'm just talking on the camera,

0:28:44.730 --> 0:28:48.720
<v S1>going through stories. But, um, Matthew Berman is one of

0:28:48.720 --> 0:28:52.380
<v S1>my favorites. Uh, fireship is one of my favorites and

0:28:52.380 --> 0:28:56.160
<v S1>a whole bunch of AI builders. I just watch their stuff. Um,

0:28:56.490 --> 0:28:58.770
<v S1>I don't care if it's produced. Not produced as long

0:28:58.770 --> 0:29:02.880
<v S1>as the content is good. Superhuman just announced a major

0:29:02.910 --> 0:29:06.990
<v S1>AI focused release that integrates AI super deeply into your

0:29:06.990 --> 0:29:09.930
<v S1>email workflows. I wish I could pull up my email

0:29:09.930 --> 0:29:11.760
<v S1>right now and drag it over here, but that is

0:29:11.760 --> 0:29:15.780
<v S1>too risky. I now am using. I maxed out the

0:29:15.780 --> 0:29:19.740
<v S1>number of auto, um, labels that I turned on. I

0:29:19.740 --> 0:29:24.870
<v S1>turned on auto labels. This thing is now filtering my email. Um,

0:29:24.870 --> 0:29:27.870
<v S1>it already has access to my email because it's my client.

0:29:27.870 --> 0:29:31.320
<v S1>So when the emails come in, it's auto filtering. According

0:29:31.350 --> 0:29:34.170
<v S1>to these rules, I set up probably 10 or 20.

0:29:34.200 --> 0:29:36.820
<v S1>I set up. So it's like, is this a pitch?

0:29:36.850 --> 0:29:38.980
<v S1>Is it a pitch about coming on a podcast? Is

0:29:38.980 --> 0:29:41.830
<v S1>it a media person trying to get me to make

0:29:41.830 --> 0:29:46.330
<v S1>a comment about something? It is, um, somebody tried to

0:29:46.360 --> 0:29:49.000
<v S1>come on my podcast. Is somebody trying to get me

0:29:49.000 --> 0:29:52.870
<v S1>on their podcast? Is it feedback from the community? Is

0:29:52.870 --> 0:29:56.470
<v S1>it somebody wanting to collaborate on building something and they're

0:29:56.470 --> 0:30:00.910
<v S1>all colored tags? Um, also things related to like fabric

0:30:00.910 --> 0:30:03.580
<v S1>and other open source projects that I'm working on and

0:30:03.580 --> 0:30:06.430
<v S1>my eyes are getting pretty good at like filtering that

0:30:06.430 --> 0:30:11.950
<v S1>pretty quickly. You could also separate them into separate, uh, inboxes,

0:30:11.980 --> 0:30:15.610
<v S1>email inboxes as well. I think superhuman is like 30

0:30:15.640 --> 0:30:19.450
<v S1>bucks a month, uh, which is a lot of people

0:30:19.450 --> 0:30:22.330
<v S1>think is a lot to pay for email. I would

0:30:22.330 --> 0:30:25.900
<v S1>challenge you on that. If you are better at email,

0:30:25.930 --> 0:30:29.590
<v S1>even by a tiny fraction of a percent, that's probably

0:30:29.590 --> 0:30:32.290
<v S1>worth way more than $30 a month. That's the way

0:30:32.290 --> 0:30:36.420
<v S1>I think about like, all service fees, but, um, yeah,

0:30:36.450 --> 0:30:38.220
<v S1>I just want to mention that it is actually a

0:30:38.220 --> 0:30:41.040
<v S1>paid service and no, I'm not sponsored. Otherwise I would

0:30:41.070 --> 0:30:43.890
<v S1>have mentioned that it would have been a sponsored section,

0:30:43.890 --> 0:30:46.200
<v S1>or at least I would have called that out. Alibaba's

0:30:46.200 --> 0:30:50.700
<v S1>CEO Eddie Wu says they're going all in on AGI development.

0:30:50.730 --> 0:30:56.940
<v S1>Join the club. Humans. New research says despite saying intelligence

0:30:56.940 --> 0:31:00.450
<v S1>matters more, both women and their parents choose the more

0:31:00.450 --> 0:31:04.740
<v S1>attractive guy if she has, like two options or multiple options.

0:31:04.770 --> 0:31:09.030
<v S1>Tech executives are now attending psychedelic slumber parties, where they

0:31:09.030 --> 0:31:14.190
<v S1>use ketamine therapy to reset their minds and escape mental ruts.

0:31:14.190 --> 0:31:17.550
<v S1>That's why I have the invite feature for my new

0:31:17.550 --> 0:31:21.540
<v S1>email client. Uh, I've not heard about these parties. Why

0:31:21.540 --> 0:31:24.300
<v S1>am I not invited? I'm offended. I'm not saying I'm

0:31:24.330 --> 0:31:27.420
<v S1>going to go. Not saying I'm not going to go either.

0:31:27.450 --> 0:31:34.290
<v S1>Gallup says LGBTQ plus identification in the US is now 9.3%,

0:31:34.290 --> 0:31:37.830
<v S1>which is nearly triple what it was in 2012 when

0:31:37.830 --> 0:31:41.970
<v S1>Gallup started tracking this. So yeah, like triple. And what

0:31:41.970 --> 0:31:46.830
<v S1>is that, 12, 13 years? 13 years? Never do arithmetic

0:31:46.830 --> 0:31:50.550
<v S1>on camera. Ellen's now asking federal workers to list what

0:31:50.550 --> 0:31:53.550
<v S1>they did last week or get fired, which like many

0:31:53.550 --> 0:31:58.020
<v S1>things with him, has me cheering and wincing. Love the

0:31:58.020 --> 0:32:01.440
<v S1>efficiency push. And I think that's how he's able to innovate.

0:32:01.440 --> 0:32:07.200
<v S1>But my problem is he's not building something from scratch here, okay.

0:32:07.230 --> 0:32:10.050
<v S1>And then firing people who are not innovative enough at

0:32:10.050 --> 0:32:13.110
<v S1>building things from scratch, which he's doing with like, rocket

0:32:13.110 --> 0:32:16.770
<v S1>companies or Optimus or something like that. In this case,

0:32:16.770 --> 0:32:20.280
<v S1>we have people who actually rely on these services. Right.

0:32:20.310 --> 0:32:22.770
<v S1>And it's hard to tell when when you're going in

0:32:22.800 --> 0:32:25.740
<v S1>there and you're just like canceling programs and like canceling

0:32:25.740 --> 0:32:28.590
<v S1>credit cards and killing off money. A lot of that

0:32:28.590 --> 0:32:32.220
<v S1>money that's going out could be doing really important things.

0:32:32.250 --> 0:32:34.590
<v S1>And it's the same with these employees. You might have

0:32:34.590 --> 0:32:39.960
<v S1>somebody who's doing extraordinarily good work, and they're actually helping

0:32:39.960 --> 0:32:43.800
<v S1>save the lives of multiple people, you know, thousands or

0:32:43.800 --> 0:32:46.950
<v S1>millions of people across the country, but they're really bad

0:32:46.950 --> 0:32:50.310
<v S1>at responding to email or they're really bad at explaining themselves.

0:32:50.310 --> 0:32:54.360
<v S1>Maybe they're super humble, maybe they're bad at writing, but

0:32:54.360 --> 0:32:59.010
<v S1>or maybe they're, like, intimidated by talking to bosses, or

0:32:59.010 --> 0:33:01.560
<v S1>maybe they're just traumatized by the whole thing and they

0:33:01.560 --> 0:33:06.540
<v S1>can't respond, well, that person gets fired, potentially. I don't

0:33:06.570 --> 0:33:08.190
<v S1>know if that's actually going to happen, but let's say

0:33:08.190 --> 0:33:11.700
<v S1>that person gets fired. That is a lot of collateral

0:33:11.700 --> 0:33:14.940
<v S1>damage for a thing that I, I think he is

0:33:14.940 --> 0:33:19.290
<v S1>trying to do good and might actually produce good. But

0:33:19.320 --> 0:33:24.420
<v S1>how do you calculate the collateral damage of of what

0:33:24.420 --> 0:33:28.530
<v S1>could result from this compared to the potential good? That is,

0:33:28.560 --> 0:33:32.100
<v S1>that is a calculus that people massively need to be

0:33:32.100 --> 0:33:35.160
<v S1>thinking about. Bureau of prisons is moving forward with plans

0:33:35.160 --> 0:33:39.450
<v S1>to house trans inmates based on birth, sex rather than

0:33:39.450 --> 0:33:42.150
<v S1>gender identity. Yeah, I've got a lot to say about

0:33:42.150 --> 0:33:45.990
<v S1>this one. Um, there are trans women who have been

0:33:45.990 --> 0:33:51.450
<v S1>on drugs for ten, 15, 20 years, and that is

0:33:51.450 --> 0:33:56.100
<v S1>how they maintain their, their, uh, their gender, their identity,

0:33:56.100 --> 0:34:03.270
<v S1>their health hormone levels, how they appear outside to the world. Um, and,

0:34:03.300 --> 0:34:07.800
<v S1>you know, have good, decent lives, you know, functioning in

0:34:07.830 --> 0:34:10.020
<v S1>that way. Now, in this case, we're talking about prison.

0:34:10.020 --> 0:34:13.290
<v S1>So there are some other variables going on here. But

0:34:13.290 --> 0:34:17.520
<v S1>we are not allowed to torture people in prison. We

0:34:17.520 --> 0:34:20.940
<v S1>are not allowed to starve people in prison. We must

0:34:20.940 --> 0:34:25.710
<v S1>give them X amount of time outside. There are rules

0:34:25.710 --> 0:34:29.489
<v S1>based on human morality and human decency for how you

0:34:29.520 --> 0:34:33.330
<v S1>treat inmates. And that's for people who are already in

0:34:33.330 --> 0:34:35.730
<v S1>jail for committing some sort of crime. So it's not

0:34:35.730 --> 0:34:40.020
<v S1>like we're saying, um, they haven't done anything. We we

0:34:40.020 --> 0:34:44.760
<v S1>understand that they've done something. All these rules apply also

0:34:44.760 --> 0:34:51.300
<v S1>to offenders. The worst offenders, absolute murderers, like, uh, child

0:34:51.300 --> 0:34:55.200
<v S1>related crimes. They, no matter who it is, cruel and

0:34:55.200 --> 0:35:00.839
<v S1>unusual punishment is still illegal. This, I would argue, can

0:35:00.840 --> 0:35:05.970
<v S1>classify in some cases as cruel and unusual punishment. Maybe

0:35:05.969 --> 0:35:08.400
<v S1>even most of the cases. I don't know the numbers here.

0:35:08.400 --> 0:35:11.370
<v S1>I don't know the like divides. I don't have data

0:35:11.370 --> 0:35:13.980
<v S1>on that, but I can pretty much guarantee you that

0:35:14.219 --> 0:35:17.400
<v S1>there are at least some cases like this where this

0:35:17.400 --> 0:35:22.560
<v S1>will absolutely be to the future. Looking back at us,

0:35:22.560 --> 0:35:26.430
<v S1>this will be considered cruel and unusual punishment. And that's

0:35:26.430 --> 0:35:30.870
<v S1>super fucked up. Heart doctor explains how swollen fingertips, leg

0:35:30.900 --> 0:35:34.440
<v S1>edema and changes in eye color can predict an impending

0:35:34.440 --> 0:35:40.590
<v S1>heart attack. My cardiologist. Um, not mine, but my cardiologist

0:35:40.590 --> 0:35:44.489
<v S1>buddy says it's important to know that just because you

0:35:44.489 --> 0:35:47.850
<v S1>don't have these particular signs doesn't mean you're okay. So

0:35:48.000 --> 0:35:51.900
<v S1>something to keep in mind. 27 year old woman's viral

0:35:51.900 --> 0:35:56.550
<v S1>post about girlhood FOMO reveals a widespread loneliness crisis among

0:35:56.550 --> 0:36:00.660
<v S1>women in their 20s and 30s missing close female relationships.

0:36:00.660 --> 0:36:04.920
<v S1>Everyone's missing missing close relationships. That's why I'm always pinging

0:36:04.920 --> 0:36:10.170
<v S1>my homies. Taylor Swift lost 144,000 Instagram followers after getting

0:36:10.170 --> 0:36:15.540
<v S1>booed at the Super Bowl, 144,000. Her boyfriend actually gained followers.

0:36:15.570 --> 0:36:19.260
<v S1>Look at Edward Abbey's raw, honest writings about how to

0:36:19.290 --> 0:36:22.649
<v S1>live fully and die on your own terms. Really good

0:36:22.650 --> 0:36:26.550
<v S1>piece there. Read the whole thing. Neuroscientists argues that extremely

0:36:26.550 --> 0:36:29.790
<v S1>high IQs are basically fictional and even Einstein probably had

0:36:29.790 --> 0:36:36.240
<v S1>around 120 or 130. I have always believed this. Well,

0:36:36.270 --> 0:36:39.900
<v S1>I mean, ever since, like reading a bunch of books about, uh,

0:36:39.930 --> 0:36:43.980
<v S1>evolutionary biology and psychology and everything, basically a whole bunch

0:36:43.980 --> 0:36:48.600
<v S1>of Robert Sapolsky stuff, I think it's likely that IQ

0:36:48.630 --> 0:36:53.580
<v S1>tops out, um, especially in value somewhere like this person,

0:36:53.580 --> 0:36:57.660
<v S1>this neuroscientist is saying around like one 2130. And then

0:36:57.660 --> 0:37:00.839
<v S1>when you start going off into like much higher scores,

0:37:00.840 --> 0:37:03.989
<v S1>first of all, the scores kind of just don't mean anything.

0:37:04.020 --> 0:37:07.740
<v S1>The error rate is massive at those levels, but really

0:37:07.739 --> 0:37:11.310
<v S1>it becomes more about like specialization. It becomes more like,

0:37:11.460 --> 0:37:15.870
<v S1>you know, um, dropping the, uh, the toothpicks and instantly

0:37:15.870 --> 0:37:20.130
<v S1>being able to count them. It's more like very specific,

0:37:20.160 --> 0:37:25.350
<v S1>like parlor tricks. Um, and it seems like the g

0:37:25.380 --> 0:37:31.379
<v S1>loading doesn't scale and give you like the expanded benefits

0:37:31.590 --> 0:37:36.480
<v S1>all the way up into like one, 31 4151, 60.

0:37:36.510 --> 0:37:40.050
<v S1>So it's almost like those numbers don't really exist or

0:37:40.050 --> 0:37:43.650
<v S1>don't really matter. I think what the more important thing

0:37:43.650 --> 0:37:48.960
<v S1>is is that below 100, it can be seriously problematic.

0:37:48.989 --> 0:37:52.410
<v S1>Above 100 starts to get you a lot of benefits.

0:37:52.410 --> 0:37:56.850
<v S1>But really, like most smart people, I think that we

0:37:56.850 --> 0:38:01.470
<v S1>know are probably like really smart people that you know

0:38:01.469 --> 0:38:05.640
<v S1>and think of are probably in the one 2130 range.

0:38:05.640 --> 0:38:09.509
<v S1>So I think that's fascinating because it's actually not that

0:38:09.510 --> 0:38:11.940
<v S1>number that matters. What matters is what you stack on

0:38:11.940 --> 0:38:15.360
<v S1>top of it. Most importantly, I would argue, is creativity.

0:38:15.510 --> 0:38:23.100
<v S1>Then like, um, determination, um, drive, ambition, grit. So you

0:38:23.100 --> 0:38:26.879
<v S1>start stacking those together on top of like 120 IQ,

0:38:26.910 --> 0:38:30.600
<v S1>then you're doing something because there's tons of people with

0:38:30.630 --> 0:38:36.210
<v S1>like very high IQs not motivated, not creative, not empathetic,

0:38:36.210 --> 0:38:39.690
<v S1>not like emotionally intelligent. What are they doing? What are

0:38:39.690 --> 0:38:43.080
<v S1>they offering to the world? And I would argue often,

0:38:43.080 --> 0:38:46.470
<v S1>not very much. NASA contracted lunar lander just beamed back

0:38:46.469 --> 0:38:50.219
<v S1>some gorgeous shots of the moon ideas. Blogging might get

0:38:50.219 --> 0:38:54.210
<v S1>even more important. So what if blog like content from

0:38:54.210 --> 0:38:58.919
<v S1>actual real people with thoughts? Because some of the highest

0:38:58.920 --> 0:39:01.710
<v S1>rated signal for AI. So we know we have this

0:39:01.710 --> 0:39:06.570
<v S1>data crisis with AI, right? Well, maybe bloggers are going

0:39:06.570 --> 0:39:09.180
<v S1>to be the main source. Um, I would say writers

0:39:09.180 --> 0:39:13.950
<v S1>in general, but bloggers as basically writers, and of course

0:39:13.950 --> 0:39:17.580
<v S1>you have like high quality people at some magazines and newspapers.

0:39:17.580 --> 0:39:21.090
<v S1>But how how many of those people are left? They're

0:39:21.090 --> 0:39:28.049
<v S1>mostly going to Substack. Right. So now Substack, Beehive personal blogs.

0:39:28.200 --> 0:39:32.880
<v S1>That is where the actual new ideas are coming out onto.

0:39:32.910 --> 0:39:37.200
<v S1>And I will say YouTube because YouTube is basically blogging.

0:39:37.320 --> 0:39:41.400
<v S1>I mean, it's all the same shit. YouTube is basically blogging.

0:39:41.400 --> 0:39:43.920
<v S1>It's just video blogging. It's all the same. The point

0:39:43.920 --> 0:39:51.509
<v S1>is YouTube. Substack. Beehive. Personal sites RSS. This becomes the

0:39:51.510 --> 0:39:58.140
<v S1>new source of actual novel and creative content, so I

0:39:58.170 --> 0:40:01.920
<v S1>might start valuing it very, very highly. All right. This

0:40:01.920 --> 0:40:04.140
<v S1>is the end of the standard edition of the podcast,

0:40:04.140 --> 0:40:07.140
<v S1>which includes just the news items for the week to

0:40:07.170 --> 0:40:09.900
<v S1>get the rest of the episode, which includes my analysis,

0:40:09.900 --> 0:40:12.840
<v S1>the discovery section that has all of the coolest tools

0:40:12.840 --> 0:40:16.170
<v S1>and articles. I found this week, the recommendation of the

0:40:16.170 --> 0:40:19.860
<v S1>week and the aphorism of the week. Please consider becoming

0:40:19.860 --> 0:40:23.310
<v S1>a member. As a member, you'll get lots of different

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0:41:01.260 --> 0:41:04.980
<v S1>Unsupervised learning is produced on Hindenburg Pro using an SM

0:41:04.980 --> 0:41:08.580
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0:41:08.580 --> 0:41:12.299
<v S1>available on the Unsupervised Learning YouTube channel, and the text

0:41:12.330 --> 0:41:15.600
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0:41:15.600 --> 0:41:19.560
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