S1: All right. Really excited about this episode. Like I said, uh,
S1: in the newsletter, I think it is one of my
S1: favorite episodes ever. Actually. Last few. I've been feeling really
S1: good about. I love the way the links are working out. So, uh,
S1: if you want to give back any positive feedback, I
S1: would appreciate it. But, uh, let's get into it. Let's
S1: see here. All right. I ordered some noise canceling earbuds.
S1: I haven't unpacked them yet, but, uh, they're for sleeping.
S1: And basically I'm going to try to put them in,
S1: and you can either stream music to them or you
S1: can stream, like, white or brown noise, or you could
S1: just have them noise cancel. And the idea is if
S1: you combine that with like an eye mask, which I
S1: already wear, then it's supposed to really help with sleep.
S1: So I'm going to see. I know a few people
S1: who do both and I just want to try it out.
S1: I did a huge blog post called Why Google I
S1: o scared this 2007 Apple fanboy for the first time,
S1: and it's basically a review of WD DC juxtaposed with
S1: Google I o, which was a couple weeks back. And yeah,
S1: I've been an Apple fanboy for I mean, I mean,
S1: I guess acolyte. I don't really like the word fanboy,
S1: but yeah, really drinking the Apple Kool-Aid for a very
S1: long time. And if you're listening to this, you probably
S1: already know that. But, um, I like to think that
S1: I'm logical about it, but I'm already admitting to being biased. Uh,
S1: so that's what being an acolyte is, right? But what
S1: I saw essentially this year at Google, I o is
S1: it seemed like they are switching to Gemini and I
S1: in general to be like their core mission. I feel
S1: like they're moving away from ads. I feel like they're
S1: moving away from that, being like the future in the
S1: center of their business to like data and AI being
S1: the center of their business. And I think this is really,
S1: really cool on on their part. And I feel like
S1: Google I o they did so well because of that
S1: integration right there talking about integration with glasses and, you know,
S1: XR or AR or whatever they're calling it, and Gemini
S1: being integrated in like all the different apps. So it
S1: just felt like they're doing something new and they're doing
S1: something different. I've always been kind of averse to Google
S1: because they are fundamentally an ad company, or they were
S1: fundamentally an ad company. And I really like the CEO.
S1: I feel like he gets it. I feel like it's
S1: not gross. I don't feel like he's gross. I don't
S1: feel like he's there to maximize ad revenue. I think
S1: he really gets the AI stuff. So my perception of
S1: Google has overall just like improved, I would say over
S1: the last say year or two. just in the context
S1: of them switching to this AI model as opposed to
S1: like an advertising model now. Then you have Apple, which,
S1: like I said, I'm massively biased towards. I love their stuff.
S1: I worked there for like three years, I worked in
S1: their security group and I just love their way of
S1: thinking about the world. I love their way of doing
S1: UI and UX, and I love how they are building
S1: in my opinion. Not that I have any inside information
S1: and it's not like actual product, but I think for
S1: the last ten years they've been building what I'm calling
S1: life OS, right? So forget iOS or Mac OS or
S1: whatever they're building life OS. I mean, they just launched
S1: the Journal app on the Mac, for example, and they
S1: just brought the phone app to the Mac, which is
S1: like the coolest thing ever. And like, AirPods seem to
S1: work better. So there's lots of improvements in iOS or
S1: in Mac OS 26, by the way. But, um, basically
S1: their ecosystem is what keeps me their their focus on
S1: UI and UX is what keeps me their their focus
S1: on art and creativity and like enabling people to be
S1: creative and enabling people to be their best selves or whatever.
S1: Like that's the vibe that I've always liked about Apple,
S1: and I think they do UI and UX better than
S1: anyone else. I think they've had this unified vision of
S1: context and, you know, having finance and creativity and work
S1: and play and personal and all of that, all integrated
S1: into the operating system. They've always just done that better
S1: than anyone else. So that's why I'm so into Apple now.
S1: Obviously AI is happening has been for the last three
S1: years or however long it's been. And Apple is behind. Right. I've,
S1: I've been saying for you know whatever a year that
S1: look they're going to come out with their unified AI
S1: product which is going to go on top of their
S1: life OS or whatever. And basically Siri is going to
S1: jump way ahead of everyone. And I thought that was
S1: going to be like end of last year. And of
S1: course they stumbled on that. And I believe it's because
S1: of prompt injection. I think it is too difficult to
S1: put an AI in front of all the personal context
S1: that Apple has about us. And to do it in
S1: a secure way, I think it's too difficult to do
S1: that right now. That is my guess. And I know
S1: this technically because I know how to do prompt injection and, um,
S1: I know some of the best other prompt injection people
S1: in the world. And it is pretty trivial still to
S1: bypass most protections. So I think they are struggling with that.
S1: Maybe they're struggling with other parts of it as well,
S1: but I imagine they're definitely struggling with that piece. Like
S1: right now I just got a pop up screening call,
S1: and if I click view and this is while I'm
S1: recording on my desktop, if I click view, it, um,
S1: it shows this person like spamming me. And there it's
S1: actively live transcribing that thing that's going to voicemail right now.
S1: So I think that's really, really cool. Um, and then
S1: I could also just click block. Uh, so that's, that's
S1: pretty cool that I have that option. And the phone
S1: is now integrated with the Mac, which it should be. Right.
S1: That's just a voice call. It's not tied to a
S1: physical device anyway. UI stuff, the way I'm kind of
S1: seeing the world now is UI. UX is Apple always
S1: has been. Seems like it will be going forward. And
S1: then Google is now becoming like less of a negative
S1: for me. And it's more about the data and services
S1: and specifically AI. And obviously I wish that Apple had
S1: all of that. They don't have it yet. I think
S1: they will get there hopefully. And obviously Google is probably
S1: working on UI and UX as well. Like I assume
S1: it's getting better. I've seen some, you know, UI stuff
S1: from them that seems to be halfway decent. So the
S1: real question to me is will Google figure out the UI,
S1: UX life, OS, full integration of ecosystem? Will they figure
S1: that out before Apple, or will Apple figure out data
S1: and AI before Google figures out that UI UX piece? Right.
S1: That's really the question. Which one gets the the one
S1: that they're weak on up to a certain bar first?
S1: I can't conceivably think of myself switching over to the
S1: Google ecosystem, because there's so many pieces of it that
S1: I know I would miss, but I am. I am 100%
S1: open to it. I honestly, I is a much bigger
S1: movement than any other tech movement. Um, it's bigger than
S1: UI and UX, especially since I shouldn't be typing on
S1: a keyboard anyway. I shouldn't be, um, you know, thumb
S1: typing on a phone, right? This should all be moving
S1: to voice and virtual interfaces and glasses. So as that
S1: starts to happen, like I'm more likely to move towards
S1: the Google side if Apple doesn't have that. Um, keeping
S1: in mind that I really do care about my interface
S1: to tech. Oh, here's the other thing. The other big
S1: reason that I really prefer Apple is because I've been
S1: on the inside, and I know how seriously and crazy, um,
S1: they take the security and privacy stuff like it is
S1: not marketing, it is not made up. It is absolutely
S1: dead serious. So if I'm building my whole life ecosystem
S1: around this, plus agents, I'm building all this stuff on it,
S1: they got to do it perfectly right. Now, I do
S1: think Google is really, really good at security. I just
S1: don't think their incentives have been aligned, you know, in
S1: the past because they were primarily an ad company, the
S1: more they become an OS and life OS for everyone.
S1: With AI, you know being the primary thing, I think
S1: they should start to move more into the realm of
S1: like what Apple does with like, okay, look, privacy first,
S1: you know, security first. Obviously they say that obviously they
S1: do a good job, but I'm saying there's going to
S1: be less of a conflict because they're not trying to
S1: make all their money off of your data. Right. Hopefully
S1: that's the case. Hopefully they're migrating away from that, which
S1: is why I, I just haven't been enthused about using
S1: them as a core OS. All right. I think that's
S1: enough about that. Basically a little bit of disappointment around WD, DC.
S1: I mean, I love the operating stuff. I, I'm a
S1: little halfway between like how much do I like the
S1: liquid stuff? I've seen some places where the interface is
S1: quite bad. I've seen some places where it's quite good.
S1: I think we're going to let that bake for a
S1: little while, see how it goes. We're on the first
S1: beta right now. They're going to clean up a lot
S1: of stuff. But what I have noticed is some really
S1: good improvements around the fluidity of like moving from my
S1: phone to my desktop, having the AirPods switch. Naturally, this
S1: is the type of thing you lose when you go
S1: to Google. Like you try to switch over and you
S1: realize like nothing works, right? Because Apple has been working
S1: on this for so many years, and this macOS and
S1: iOS 26 update, it seems like things are really, really smooth.
S1: I mean, my OS is just working better now, and
S1: this is beta one. Back in the day when I
S1: was doing these betas, like I would lose core functionality
S1: like regular apps wouldn't launch. I would like go dark,
S1: like I couldn't text people. It was crazy, you know,
S1: running these Apple betas early on. But, um, no, it's
S1: it's working great. I recommend you try it out. And
S1: if you do, you could text me and we could
S1: try out some of these new emoji features or whatever.
S1: All right. Um, got a couple blogs. Yeah. So one
S1: is the WWE one, the other one is, um, uh,
S1: see here. Oh, yeah. It's an argument against. It's just
S1: next token prediction. I thought that was a pretty good
S1: way of encapsulating it. Uh, so definitely check that one out.
S1: I'm about to do, like, a kind of, like a
S1: personal project to profile, like all the CCP members and structure,
S1: just profile them and, like, figure out who are they,
S1: what are they up to? How are they different than she? What, uh,
S1: what are their political opinions? What are they focused on?
S1: What are their areas of expertise? What are their areas
S1: of responsibility like how does legislation get. I guess it's
S1: not legislation because people aren't voting, but how do they
S1: decide what new laws to put out? Is there a process?
S1: Is it on a particular timing? I just kind of
S1: want to understand how the Chinese government works. So I'm
S1: going to start with understanding all the CCP people, um,
S1: because that is the government. And I and I want
S1: to look at the different echelons, like, is there a
S1: like is there like a Politburo? Is that a smaller group?
S1: Is it like a larger thing of like hundreds of people? Um,
S1: what's the difference between those tiers, like stuff like that?
S1: So I'm going to do a study like that. And, uh,
S1: I don't know how I'm going to put that out.
S1: Maybe a blog post, maybe some member content. I have
S1: no idea. Uh, the other thing I'm going to do
S1: is I'm going to do a future trend investment analysis exercise,
S1: which I did, I want to say like five years ago,
S1: and it basically told me to buy Amazon and Nvidia.
S1: I forget what that exercise told us to buy, but
S1: I did it with my good buddy Tai Sabarno, and
S1: I think we ended up making a number of purchases
S1: based on that, and I think they've done well for us. But, um, yeah,
S1: I want to do another one this time. We'll get
S1: to use things like, you know, O3 Pro and I
S1: get to throw in tons of context about myself and
S1: what I'm looking for and the, you know, the types
S1: of investments I'm looking for and the type of risk
S1: I want to be open to. Um, and this isn't
S1: only for investment. That'll be kind of like a side product, um, of,
S1: like the exhaust that comes out of it. The biggest
S1: thing I'm trying to do here is just figure out trends.
S1: So here's like the I'll give you like kind of
S1: what I'm going to feed to this thing. Right. I'm
S1: going to set this entire thing up, which is going
S1: to be like 20 pages of me writing up contacts
S1: to my own thoughts and my own predictions, my own like,
S1: concerns or whatever. And I want to know what it
S1: thinks could happen. And I'm sure it's going to be
S1: very careful and be like, look, we can't predict the future,
S1: which obviously everyone knows that. But, um, what I'm going
S1: to be is what I'm going to say is like, look, um,
S1: if this were to happen, what seems obvious to you,
S1: that would be some second order effects. That is the power, right,
S1: that I didn't have before where I is like, well,
S1: obviously this is the type of thing that happens and
S1: it gives you like 150 different things. So when certain
S1: things are scarce, prices of certain other things go up.
S1: Which companies are associated with those? I don't know all
S1: that information. Like I'm not like a commodities expert. I'm
S1: not a trading expert, I'm not a stock expert. So
S1: I think there are some things that don't involve that
S1: much prediction or that much conjecture on the side of
S1: the eye. That's actually just benefits from it. Understanding how
S1: the world works. So I could say, okay, um, like,
S1: what am I? You know, hypotheses is like, okay, private
S1: security is going to go up. Oh, there's probably going
S1: to be a bunch more prisons built, uh, because, you know,
S1: we're stupid. And we took down all the mental health facilities.
S1: So what happens when there's like UBI comes out? But
S1: UBI is limited to only citizens. So they start doing
S1: mass deportations, not because of the current kind of vibe
S1: of like anti-immigrant stuff that's going on, but more along
S1: the lines of like, we need to control how many
S1: people were sending UBI to, we're not going to send
S1: UBI to everyone in the country just because they're physically here.
S1: So now there's a bunch of tech to find who
S1: is and isn't supposed to be receiving UBI, and more
S1: and more people will become homeless because, you know, AI
S1: is taking jobs. Okay, so they're homeless. So then you
S1: have the fact that they don't have a place to live. Uh,
S1: then you have addiction, then you have violence. So who
S1: goes into prison, right? Prison is mostly full of people
S1: who have addiction, who have mental illnesses, and obviously some
S1: people who are violent. Right. And the percentages, you might
S1: be surprised how much it's actually people that just couldn't
S1: find a way to get it going. Right. So they
S1: end up on drugs, they end up mentally ill. Those
S1: ideally in some world, like the world we're supposed to
S1: be building, that would be like drug treatment programs and
S1: it would be mental health facilities. But all of that
S1: is going to collapse down into basically like prisons. Get
S1: them away from society, separate them from society. So what
S1: does that mean? What does that mean for water? What
S1: does that mean for food? What does that mean for, um,
S1: what companies are going to do well in that world? Um, like,
S1: I'll tell you one of mine Costco I love Costco.
S1: I'm like, so like into Costco. Um, and also Google
S1: and also Apple. But those are like my three main
S1: investments right now. So the question is like, how is
S1: how can I find other ways to connect these dots.
S1: And I'm going to tell it, look, don't be doing conjecture.
S1: Don't be trying to predict the future. I'm going to
S1: give you a bunch of options of ways. I think
S1: maybe it could go. But I have no idea. And
S1: you as this I you also have no idea. But
S1: there's there are lanes of probability, Right? Uh, turns out
S1: if people don't have jobs, they have no way to
S1: pay for food, especially for their families. They might get
S1: a little upset. Right. So certain things don't require a
S1: lot of, like, future prediction or futurist type crap. Um,
S1: so I'm going to use the AI to help me
S1: sort of navigate that stuff that seems a little more obvious. And, um,
S1: the main output is going to be like, it looks
S1: like if these things happen, then these things might happen
S1: as well. And then, um, maybe some investment thing of like, okay, well,
S1: for all of those different ones, what companies or what
S1: products or what raw materials or where would I want
S1: to live? Where would I want to move? What is
S1: a good city to be in if something like, you know,
S1: three through seven were to happen, right? That's the type
S1: of analysis I'm going to do. And similar to the
S1: CCP one, I'm not sure how I'm going to put
S1: that out. Maybe I'll make a giant PDF, maybe I'll
S1: do a video. Maybe it'll be like member content, maybe,
S1: you know, charge for it, Make it free. No idea.
S1: Probably some combination of those. All right. What else? Doo
S1: doo doo. All right. Cybersecurity. So Trump overhauled Biden's cybersecurity
S1: policies with a new executive order. Uh, he removed focus
S1: on mandated digital IDs. That must have been, like an
S1: immigration type thing. Accounting, compliance checklists, micromanaging, agency decisions. I
S1: think that might have been like Cisa, maybe like harnessing
S1: or like trying to control Cisa ads focus on defeating
S1: foreign threats, secure software practices, border gateway protection. That's BGP,
S1: I believe. Um, yeah. Like, you know, hijacking BGP routes.
S1: Post-quantum cryptography, modern encryption protocols, AI for vulnerabilities, IoT security
S1: standards and limiting sanctions scope. So that was, uh, a
S1: combination of mine and an AI analysis of the talking points,
S1: or it's called a fact sheet. Bellingcat tests whether or
S1: not I can actually geolocate photos, and it found that
S1: O3 actually did the best and beat out Google Lens, actually.
S1: Sentinel one reveals details on Chinese supply chain attack attempt.
S1: Protonvpn sees 1,000% sign up surge after Pornhub blocks France.
S1: So France evidently loves Protonvpn. And, uh, yeah, they went
S1: over there so they could still get access. Microsoft Teams
S1: with Indian police to shut down fake tech support scammers
S1: and Bishop Fox 2025 red team tools list. All right.
S1: National security OpenAI published their annual report on how bad
S1: actors are using AI maliciously, and I love the fact
S1: that they put these out. So four out of ten
S1: major abuse cases look like they came from China, from
S1: social engineering to cyber threats. They're seeing deceptive employment schemes.
S1: So task scams from like Cambodia comment spamming from Philippines
S1: and a covert influence operations potentially leaked to Russia and
S1: Iran using AI as force multipliers. Um, I'm actually going
S1: to mention something right now. I can't figure out what
S1: I'm going to do with this. I might do another
S1: report like the one I just the two I just
S1: talked about. So my Twitter feed is full, full of
S1: what I am absolutely certain is like widespread propaganda. So
S1: the content that I see is like, don't you hate
S1: black people because they do this? Um, don't you wish
S1: the world looked like this? And then if you click
S1: the video, it's like a whole bunch of white people
S1: walking around and there's like, no crime and there's like
S1: a fountain with, like, a nice water sound, and there's, like,
S1: somebody buying something at, like, an Abercrombie or something, and
S1: it's like. It's like massive propaganda to like, uh, don't
S1: you wish the world was the way it was before? Before, like,
S1: brown people messed it all up, right? And then there'll
S1: be another one. It'll be like about fighting or something
S1: like that. Or it'll be like masculine movies. Don't you
S1: wish movies were like this? And it's like someone holding
S1: a Budweiser. Budweiser. And, like, shooting a crossbow or something.
S1: And I'm just like, what is going on? So every
S1: time I go back to Twitter, which I probably check
S1: it like, I don't know, like 15, 20 times a
S1: day or something, and then I'll just be browsing to
S1: see what people are saying. But if I go to
S1: the home tab, which is like impossible to clean up
S1: because I block all these things when I see them,
S1: although lately I've started bookmarking them because I'm going to
S1: do this research project. But normally I just block, block, block.
S1: But it's just an endless supply. Like these people have
S1: like multiple accounts. So what I started doing is clicking
S1: on the account and scrolling through their feed, and it's nonstop.
S1: It's nonstop narratives about how messed up the country is,
S1: reasons for why the country got messed up, which is scapegoating, basically.
S1: And then, um. Don't you wish it was like, uh,
S1: the new thing, right? Don't you wish it was like
S1: it used to be? Don't you know? Don't you think
S1: we could do better? And I'm just, like, seeing this everywhere.
S1: Just like hundreds of accounts doing this. And I sent
S1: this a few of these accounts to, uh, some friends
S1: of mine who go and research this stuff. And, yeah,
S1: I'm just really surprised that, like, I guess I'm not surprised, given, uh,
S1: given Elon's situation and the fact that he lost so
S1: many advertisers and the fact that I guess he's like
S1: conspiracy friendly, I would say, um, but ultimately people click
S1: on this stuff. People watch this stuff because it is,
S1: you know, specifically designed to be that way, to be
S1: very watchy and clicky. Um, so I guess that's why
S1: it's there. But but it's really gross. Like, I really
S1: wish there were a platform or I wish there were
S1: options in this platform where it's like, look, I'm paying money. Like,
S1: Can you not show me this garbage? I want to
S1: see stuff from people I follow and stuff that's very
S1: tightly correlated with people I follow. Which he says he's
S1: working on that actually, he says he's working on similar
S1: content matching, which is similar to the app I have
S1: called threshold. But, um, yeah, this whole thread of like,
S1: who is sending all this stuff to us, who is
S1: basically trying to change the narrative or try to put
S1: inject into our minds, like this feeling of the US
S1: is messed up. It was messed up by them pointing
S1: at trans people or brown people or black people or whatever.
S1: Gay people or you know, the wrong religion or whatever
S1: it is. Liberals, definitely, um, people who aren't right enough
S1: or aren't right in the correct way. Um, it's just
S1: it's worse than I've ever seen. It's absolutely worse than
S1: I've ever seen. Um, so I don't know if their
S1: skill level is just going up. I imagine it's because
S1: it's all a lot of it's being AI generated. So
S1: you could just do it at more scale. That's probably
S1: a reason. But anyway, it's something I'm going to look
S1: into and probably do some kind of essay or report
S1: or whatever. All right. AI. Okay. This is the craziest story,
S1: the absolute craziest story of the week. Um, and honestly,
S1: for a long time. And I've got a follow up
S1: to it as well, because my buddy told me about
S1: this one company. But check this out. So I finally
S1: found something that trains scientists have missed for decades. So
S1: a number of professional scientists have been trying to figure
S1: out how a particular kind of bacteriophage, which is a
S1: virus that infects bacteria, uh, which I didn't know that. So, um,
S1: there's a podcast here that supports this that's basically like, um,
S1: it's all the scientists who actually did this. So basically
S1: they have been studying this thing for over a couple
S1: of decades. They are the world's experts in how these
S1: particular bacteriophages, um, gain mobility and move out of the cell. Basically,
S1: what they do is they take over the cell. They
S1: blow it open and spread the virus. That's what these
S1: things do. So they study how these things get their
S1: heads and their tails, which allows them to move and
S1: propagate and, you know, take over other things. And I'm
S1: simplifying and probably messing up some details because it's a
S1: very complex, you know, specific topic. But I went and
S1: listened to the entire one hour episode with the actual
S1: experts talking about this. Now the story is they were
S1: given this new version of a Google model, which is
S1: specifically for researching and coming up with novel hypotheses, novel ideas. Okay,
S1: so what they did was they they had this thing
S1: where they're like, how is this thing possible? They've been
S1: thinking about this for years and years and years. They've
S1: done numerous studies. They are the world's premier experts on this.
S1: And they have been stumped by this fact. The fact
S1: that this one bacteriophage, I believe it was there, were
S1: stumped by the fact of how was it actually propagating
S1: or how was it becoming mobile. It was something like that.
S1: It was some sort of problem that they could not
S1: figure out, and they know exactly how it works. You know,
S1: they were very sure about this and that. Therefore, you know,
S1: they're like, this makes no sense. So they gave a
S1: bunch of this observational data to it, you know, stuff
S1: that they've had for years and years. And it came
S1: back with hypotheses. And one of the hypotheses out of
S1: a very short list was like, hey, um, it might
S1: be this actually, because, um, what you could do is
S1: you could just do this instead of this, and it
S1: puts a tail on there and it actually picks up
S1: the one, um, once it's outside of the cell, it
S1: picks up someone else's. And I'm kind of messing up
S1: the details here, but they describe it pretty good in this,
S1: in this, uh, full episode of, uh, Cognitive Revolution, I
S1: think is the name of the podcast. But, um, when
S1: they heard this, when they saw it written down, they're like, oh,
S1: that that's probably what it is. So here. Here's the thing.
S1: They had made an assumption that a certain type of
S1: mobility or a certain type of propagation was not possible,
S1: and it was a very silly assumption that they had made.
S1: And this, this assumption had stopped them from solving this
S1: problem for years upon years. How many hundreds of hours,
S1: thousands of hours have they spent stumped on this as
S1: the world's premier humans on the entire planet? The smartest
S1: people working on this in the entire world, on the
S1: entire planet, were stumped by a thing. And Google came back,
S1: I think within a couple of minutes, I think, and
S1: it was like, yeah, I think it's probably this. They
S1: go and check and it's 100% verified that was correct.
S1: And they here's here's the thing. They were kind of, uh,
S1: I believe what they were saying is they were about
S1: to figure this out. Maybe. Maybe this year. Maybe next year.
S1: They were doing some experiments that might have got them
S1: to this. But the point is, Google found it instantly.
S1: Which means if they had this Google research assistant earlier,
S1: maybe last year, maybe years ago, maybe it would have
S1: found this right. And they not would not have had
S1: this problem for this entire time. Now, what excites me
S1: about this is not this specific use case. It's the
S1: how they reacted to it. They were like, this is insane.
S1: Because the thing I'm so excited about, and it's the
S1: same thing they were talking about, is how many other
S1: things are like this. There is data everywhere. There is
S1: evidence everywhere. There are dots. Okay, think of connect the dots.
S1: Think of how many dots are lying around in papers,
S1: lying around in data sets. Raw data sets. Unfiltered. Unreviewed. Why?
S1: Because there aren't enough academics. There aren't enough researchers. Forget academics.
S1: There aren't enough humans with the training required, write either
S1: the formal current training or like even rudimentary training. There
S1: aren't enough human eyes on all this raw data. There
S1: are no human eyes to look at the stuff and
S1: find the dots and connect them. How many cures for illnesses?
S1: How many novel ways are we sitting on the ability
S1: to improve our IQs by 20%? Are we sitting on
S1: the ability to solve aging? I would guess we absolutely are.
S1: We absolutely are. And that the problem is not enough.
S1: People are studying it using not enough data. So what
S1: I now allows us to do with tools like this,
S1: which are about to be drastically better. I mean, this
S1: thing that found this is about to be 100% stupid
S1: compared to whatever comes out next year or next week.
S1: Right now, just imagine giving all that raw data and
S1: even going to collect more, right? Getting sensory data from
S1: cells or whatever from, you know, different layers of the
S1: world and basically feeding it into this thing all the
S1: time and saying your job is to connect dots. That's
S1: that's the promise of AI. Your job is to connect dots.
S1: So what we've basically done at that point is simulate
S1: billions more people on the planet with training for connecting dots,
S1: and then they could go, look, I came up with
S1: all these hypotheses. And if you go test this, it's
S1: probably going to work. Oh, and by the way, that
S1: is actually a cure for, you know, 86% of cancers
S1: or that will extend your life by 42 years, um,
S1: or whatever. This will allow you to transfer your brain
S1: into a, you know, digital, uh, synthetic form or whatever. Um,
S1: I'm just blown away by this. Now, I sent this
S1: article and my write up of this to a buddy,
S1: and he's like, yeah, I'm actually, um, you know, invested
S1: in and, you know, uh, an advisor for this company
S1: who does that. Their specific thing is they are already
S1: going and crawling all this other data. They are going
S1: to find they have actively collected and are collecting all
S1: this raw data and all these studies that basically didn't
S1: go anywhere because they lost funding or whatever. That company,
S1: this company he's talking about, it is actively doing that.
S1: And guess what they're doing? They build the labs and
S1: they're automating the labs. So when they do a hypothesis
S1: and this is crazy, they already have use cases of
S1: this working. So it's kind of even further than the
S1: main story here. They have a use case of an
S1: example of it actually, um, came up with a hypothesis.
S1: It built a full, uh, methodology and schematic for how
S1: to build the lab. And humans basically took that and
S1: went into the lab. They built a little thing. They
S1: basically set up the experiment exactly the way that the
S1: I said to. And it 100% was true. They confirmed
S1: experimentally that this hypothesis that it could come up with
S1: was true. Now, if it had had the ability to
S1: actually automate those tests, um, if it had the raw
S1: materials in the lab and they had robotics or whatever,
S1: that would have been even more insane, right? What if
S1: it had the raw materials to to combine these molecules
S1: or whatever? And there you got to be a little
S1: bit careful because you don't want to just prompt inject
S1: and it builds a, you know, a meth lab or a,
S1: you know, sarin gas lab or whatever, a Covid lab, right.
S1: Automated Covid generation. Um, so you got to be careful
S1: with those. Obviously, this is what a lot of people
S1: are worried about. But unbelievable, unbelievable possibility here in terms
S1: of like connecting dots. And then the most important thing
S1: and I talked about this, um, I got an essay
S1: called The Path to Asi. I don't know. You guys
S1: might have seen that it's came out. I don't know.
S1: I put that out a few months ago and it
S1: basically describes this process, right? You have hypotheses, you test them.
S1: That's it. Right. Humans have hypotheses. They test them. But
S1: we do it at such small scale. And more importantly, um,
S1: real innovation comes from getting a bunch of smart people together,
S1: like Bell Labs or the Renaissance, and a whole bunch
S1: of smart people are together there talking about their ideas.
S1: But the other person's idea that they're talking to influences
S1: them slightly, changes their idea. Or even somebody, um, somebody, uh,
S1: copies the idea, but they copy it incorrectly with a
S1: slight deviation that actually makes it better. And that's absolutely insane.
S1: So essentially what you have is like this evolution. You
S1: have evolutionary biology or evolutionary, um, improvement happening to the
S1: realm of ideas. Now, that is 100% Sense automatable as well.
S1: You could use AI to do that. You could use
S1: genetic algorithms to do that. You know, it's easy to
S1: do this in a not sophisticated way, and I'm sure
S1: you could do it in a lot more sophisticated ways
S1: the more you think about it. But essentially you have
S1: this engine of human generated ideas, AI generated ideas, and
S1: then you have this evolutionary petri dish which constantly evolves them,
S1: that spits out hypotheses which go through some sort of filter,
S1: and then the higher quality ones go into this automated
S1: testing lab and we start to have this giant Bell Labs.
S1: Renaissance mechanism for inventing new things. Right. Inventing completely new things,
S1: solving things like aging and cancer and all these different illnesses,
S1: extending lifespan, like solving world hunger, like creating abundance on
S1: the planet, like, you know, getting away from the zero
S1: sum game of like capitalism and all this stuff. Like
S1: you could literally use this engine to solve human problems,
S1: you know, at scale. So all this is just massively
S1: exciting to me. And I thought that was like the
S1: most interesting story of the week. Apple releases controversial paper
S1: on AI. Yeah, yeah. It was silly. It was a
S1: silly paper. Um, some people are like, oh, you're behind
S1: on AI. So now you release a paper that basically
S1: says AI is stupid. Anyway. Um, I didn't even want AI. Uh,
S1: it's dumb anyway. So that's why. That's why I'm not
S1: trying hard. That's why other people are beating me. That's
S1: not actually what happened though, because Apple Apple air quotes.
S1: Apple isn't saying this. It is some ML team within Apple. Right.
S1: Releasing this. So, um, anyway, it was a funny narrative.
S1: OpenAI massively drops O3 prices. They dropped by 80% and
S1: they also released O3 Pro. Um, OpenAI doubles revenue to
S1: $10 billion annually. And OpenAI also must keep all ChatGPT
S1: conversations indefinitely due to a legal hold related to a lawsuit.
S1: I find this weird. I don't know how accurate this is.
S1: If it's all like what exactly the scope is. There's
S1: a quote here that says we are required to retain
S1: all data. Cannot process deletion requests during this period. What
S1: I don't know is if it applies to like tenants
S1: where they've paid extra money just to have their stuff
S1: be ephemeral, right? There are a lot of people with
S1: like private Azure instances where like that was the whole
S1: reason they're paying extra is the fact that it's ephemeral,
S1: or it gets deleted constantly or they're able to delete it,
S1: but I don't know if it applies there. I doubt it,
S1: but who knows? OpenAI makes ChatGPT voice mode sound way
S1: more human. Okay, go play with voice mode. Advanced voice
S1: mode on ChatGPT. It is ridiculous. I mean, it is
S1: absolutely ridiculous. I was having a conversation with it yesterday,
S1: which I haven't talked to in a while, and it
S1: felt so incredibly human. The pauses, the voice tones, it
S1: actually sang. Um. At first it did like vocal song
S1: and I was like, no, not, you know, uh, spoken
S1: word actually sing. And it actually sung with, like, tone. Um, anyway,
S1: I still use the Cove one because it sounds like, uh,
S1: one of the AIS from interstellar, and that's my favorite voice, uh,
S1: since they got rid of, uh, Samantha. All right, Stanford
S1: study shows doctors put AI beat. Oh, plus, I beat
S1: traditional diagnostic tools. So doctors normally in this particular test
S1: were 75% accurate. Doctors with the AI were 85% accurate, 10% jump.
S1: But the hilarious part and extremely sad part I by
S1: itself was 90%. It was 5% better than the doctor
S1: using I. So it's like, yeah, it's like, yeah, I
S1: am way better than the doctor. This is the I talking.
S1: I'm way better than the doctor. I am 15% of
S1: the doctor. Now, if the doctor uses me and asks
S1: me questions, it can almost be as smart as me,
S1: but not quite. And we all know how early the
S1: game is. We all know how bad I is at
S1: certain things, and it's already to this point. And this
S1: is not like some random study at a junior college.
S1: This is a pretty large Stanford study. Insane. Absolutely insane. Uh,
S1: Microsoft reshuffles leadership to focus on AI agents. My new
S1: favorite description of a business mode. This is from Jamin Bell.
S1: A real long term moat is just a sequence of
S1: smaller moats stacked together. Each one buys time. And what
S1: you do with that time, how fast you execute, how
S1: quickly you evolve, determines whether you stay ahead. And my
S1: analysis of this or my. You know, um. Clarification of
S1: it or tightening it up is to me, that means
S1: speed and adaptability is the only real moat. And a
S1: hat tip to, uh, Clint Gibler, uh, my buddy for, uh,
S1: sending me this, like, in a text or something. Um, really,
S1: really good technology. Why Bell labs works so well. Uh,
S1: we talked about that already. BYD's five minute charging puts
S1: China in the lead for EVs. Five minute charging. That's
S1: basically a gas station. Uh, very worried. Um, this is
S1: why I want Tesla to win so bad. And now
S1: also Waymo. Uh, I want, but it's got to be
S1: Tesla because they're the ones making the cars. I'm really
S1: worried about BYD. BYD is making extremely good cars. They
S1: are subsidizing them. They have 10,000 EVs. And we're talking
S1: about five minute charging like a gas station. I mean,
S1: if they were to come here, they would crush right now.
S1: So we need our options. We need American options to
S1: be getting better way faster than they are right now.
S1: Wing and Walmart expand drone delivery to 100 stores, which
S1: is five major cities. Uh, Chinese tech behind Amazon's humanoid robots. Great.
S1: So Amazon is doing humanoid robots now. Um, they're talking
S1: about potentially having humanoid delivery drivers. And the tech is Chinese. Great.
S1: YouTube loosens content rules using public interest as a standard.
S1: And AWS has opened a new region in Taiwan with
S1: three availability zones. Humans. Rents are dropping in most US
S1: cities for the first time since 2023. Caffeine keeps your
S1: brain awake even while you sleep, so you could actually sleep.
S1: According to the study. You could actually sleep and stay asleep,
S1: but you wake up more tired because your brain is
S1: not properly resting. Because the caffeine. Because caffeine basically blocks
S1: the sleep, um, receptor. Um, that's one of the mechanisms.
S1: So that's probably related to why this is the case,
S1: or at least why they found that to be the case.
S1: Las Vegas fights record heat with massive tree planting. And
S1: this is not, uh, like it's absorbing carbon. Uh, because
S1: that wouldn't be nearly the amount of skill you need. Uh,
S1: that's a planetary thing. But, um, for shade is what
S1: they're talking about. Mushrooms may communicate using up to 50 words.
S1: And forests offset global warming more than scientists previously thought.
S1: So replanting the trees that we lost since the 1800s
S1: could cool the planet by like half a degree, which
S1: I think is Celsius. Uh, which would be cool. Uh,
S1: I think we should do that. I think we should plant, like,
S1: trillions of trees and just, uh, see if the temperature
S1: falls really fast. See if CO2 levels fall really fast.
S1: And if they do, um, cut down some of the trees.
S1: That's what I think. And also carbon sequestration. And also
S1: we should go all in on solar discovery. Someone built
S1: an MCP server that actually runs on Cloudflare workers. So
S1: you don't have to stand up your own infrastructure. Data
S1: visualization reveals patterns in D&D monster designs. How anthropic teams
S1: use cloud code. We are No longer a serious country
S1: by Paul Krugman. Great explanation of how model context protocols
S1: is different from traditional APIs. I'm not sure I'm going
S1: to read all these, because they're actually just links for
S1: you to go and click on in the newsletter. Um,
S1: so I'm just going to go right to aphorism of
S1: the week. It is not death that we should fear,
S1: but never beginning to live. It is not death that
S1: we should fear, but never beginning to live. Marcus Aurelius.