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S1: That's work os.com/radar. Unsupervised learning is a podcast about. Trends
S1: and ideas in cybersecurity, national security, AI, technology and society
S1: and how best to upgrade ourselves to be ready for
S1: what's coming. All right. Welcome to unsupervised Learning. This is Daniel,
S1: episode 470. Let's get into it. Reading a couple of
S1: new books in addition to this month's books for UL.
S1: So the UL books are 1984 by Orwell and Animal
S1: Farm by Orwell. And these two books I just added
S1: to the list. I'm about done with the Technical Republic
S1: and about to jump into money, lies and God. And actually,
S1: there's another one I'm going to add to this list,
S1: somebody who came on the Goodfellas podcast. So I'm going
S1: to go find his book as well. But, um, yeah,
S1: having a good time with some reading. Got a friend
S1: in Guatemala who was recently laid off senior engineer, focused
S1: around monitoring solutions, but really can do lots of different stuff.
S1: So I recommend you check out his LinkedIn and see
S1: if if you might have anything. My friend Monica is
S1: offering 25% off her Security Leadership Masterclass, which I consulted for,
S1: and I think it's really good for people trying to
S1: get into leadership around security. I got a funny meme
S1: here about, um, how to calm down. A buddy who
S1: loses a bunch of money in crypto. It's just. It's
S1: just funny. Nothing useful there except for laughter, which is useful.
S1: LinkedIn posts about my ultimate app, which I keep iterating on.
S1: I'm going to go ahead and click through to this one.
S1: So this is essentially like the main app that I've
S1: been building for the longest time. And I've got like
S1: different versions of it. I've got like a commercial version,
S1: I've got the overall arching one, but essentially it takes
S1: inputs from any medium, from any platform and does a
S1: ton of analysis to determine how good it is. Okay,
S1: so just imagine that this is like the most important
S1: thing to me is most important like current buildable use
S1: for AI. So all this stuff is happening in the world, right.
S1: All this news, new intelligence is is dropping open source intelligence,
S1: recon vulnerabilities are popping up on websites. Um, my favorite
S1: thinkers are releasing a new blog, blog post, a new essay,
S1: a new article, a new video on YouTube comes out right.
S1: All the authors that I follow, they're releasing new books, right? Um,
S1: comments are being made which might reveal something really, really interesting. Uh,
S1: new art is coming out, new books, new movies that
S1: I should be watching. Um, comments from my friends, new
S1: companies being launched. All this stuff is happening, you know,
S1: millions of things per day. Hundreds of thousands, tens of
S1: thousands or whatever, uh, pieces of content coming into my
S1: RSS feeder. And all of that is, is something I
S1: could potentially benefit from. Okay. So this app that I've
S1: been working on for the longest time, really starting, uh,
S1: beginning of 23, is essentially the consumption mechanism for this.
S1: Pull it all together, then use AI to run it
S1: through a filter. Okay. That filter. And I've already built
S1: this way back then. The filter basically does a quality
S1: check on all of these things to see if it's
S1: full of interesting ideas, if it's creative, if it's novel,
S1: if it's surprising, and all these various different aspects similar
S1: to the label and rate, um, fabric pattern that I
S1: have out there that's public. This is just like a
S1: much more advanced version of it, with a lot more
S1: labels and stuff like that, because based on that, the
S1: AI can then or a different AI or a different
S1: part of the same AI can then sort what to
S1: do with it, right? Because it might be an alert.
S1: It might send me an alert if something is important enough, like, hey,
S1: a new vulnerability was found on one of your websites,
S1: or a new vulnerability was found on a bounty program
S1: that I'm monitoring. And by the way, the AI is
S1: telling me my AI is like, oh, by the way,
S1: I found the vulnerability. I found how you could actually
S1: exploit it. I wrote that up into a report and
S1: I submitted it to the thing. So we are waiting
S1: to see if we're going to get paid from this bounty. Right.
S1: So that that's a cool thing. And it might send
S1: me an email which tags it with a certain thing
S1: that says awaiting for bounty payout or something like that.
S1: Or it might be that I just want to know if, um,
S1: this particular company buys any new companies, or I want
S1: to know if this particular company does anything to, like,
S1: raise money. All of these could be like alerts that
S1: I have set up. But it starts with the consumption
S1: of the world and the processing through this AI. Now
S1: I've already built this I've got is probably a version
S1: like three or something, depending on how you call the versions.
S1: But what I want to mention about this is that
S1: the real version of this, the real version of this,
S1: which I've talked about in my other videos, especially the
S1: predictive path AI. Video is that the real version of
S1: this is my AI buddy, my AI assistant, my AI friend, my.
S1: AI my digital assistant. Okay, my universal primary digital assistant
S1: is going to be in charge of doing this for me. Okay.
S1: My APIs that are available to me are the ones
S1: that are doing this processing right. These agents, these automation workflows,
S1: these things that are just running on my behalf. They're
S1: out there in the world collecting, analyzing, assessing, um, labeling,
S1: doing all those things for me. But the quarterback for
S1: all of this is my Da. My Da is monitoring
S1: how many feeds I have, if they're the right feeds,
S1: if this feed like we thought it was awesome, but
S1: it's actually garbage. It might have the permission to go
S1: in and clean that up and fix it. Right. So
S1: the future of this is I don't really ask any
S1: questions about this. I'm not like typing very much. I'm not, um,
S1: really manually interacting with this too much at all. Because
S1: if I want a new source, I say, hey, add
S1: this to my source, okay? While I'm looking at a
S1: page on the screen, hey, add this to my our
S1: list of sources in my says in my ear, yeah,
S1: no problem. Just added it. Okay, I'm watching a new
S1: YouTube video, for example. I'm like, yeah, add this to
S1: our sources and it's like it runs the API command
S1: to go add that. It's now part of the workflow.
S1: It's now in the system right now. How could it
S1: do that? Well, it's going to do that because it's
S1: watching all my screens or it's watching with the camera.
S1: However it's doing it. There's going to be lots of
S1: different ways. But the point is, my Da will be
S1: part of my life. Um, Apple is talking about having
S1: cameras on its AirPods. I don't know if that will
S1: be the next version. Probably not. It'll be the version
S1: like 2 or 3 versions after the current version, but
S1: I'm wearing them now. Like if if these were like
S1: over here and in the back, it had a camera
S1: that was pointing behind me. Amazing. Obviously it should have
S1: a camera that's pointing forward, pointing forward, pointing behind me
S1: with full access to my life context. Full access to
S1: my screen. It should also have access within the screen
S1: as well, so we could look at processes and stuff
S1: like that. But let's just say you could only just
S1: see the screen. I could still ask it things and
S1: it could still do lookups. It could still summarize what
S1: I'm looking at, for example. So this is really the interaction.
S1: The interaction becomes me just talking to my AI and
S1: my AI giving me back results. Now the second level
S1: of this, which comes a little bit later because the
S1: technology just is not quite there yet, but it's more
S1: like the meta glasses. Okay, the meta Metaclasses. As you
S1: saw in the newsletter last week, or maybe it's this
S1: week and we're about to talk about it. The Metaclasses
S1: have sold 2 million units. They are the direction that
S1: things are going. I imagine Apple is going to move
S1: in this direction as well, and kind of offload a
S1: bunch of the processing to the phone, but the next
S1: version of this app that I'm building, the reason I'm
S1: building all these services that are working for me, coming
S1: through my digital assistant, which also doesn't fully exist yet. Okay,
S1: that's also a place everyone is pushing into, including Apple.
S1: But the real thing is that I am watching. I
S1: am talking to somebody and they're like, hey, you know,
S1: you should get in on this deal and blah blah, blah.
S1: And it's crypto related and it's a meme coin. And
S1: I'm just like, uh, well, not interested. Don't want to
S1: hear about that. Um, but let's say I was interested
S1: and let's say it did sound good. In the meantime,
S1: my Da is calling all my APIs. Okay, I have
S1: an API for researching someone. I have an API for
S1: creating a dossier on somebody. I have an API for monitoring,
S1: watching someone's face and determining characteristics of lying. So while
S1: I'm looking with my apple glasses, which is just like
S1: they look like regular glasses, this is pretty far in
S1: the future. Like five years maybe, maybe shorter, maybe like
S1: three years with meta or something. Who knows? But let's
S1: just say three to 5 to 10 years. Okay. As
S1: you're watching, I have this little dial in the corner
S1: of my glasses and it's like, it's like a bullshit meter, right?
S1: It's like, yeah, no, don't believe that. And it could
S1: even be printing out little thing in the text or whatever.
S1: That's like that claim he just made is incorrect. That
S1: was kind of bullshit. Oh, that was kind of smart
S1: or whatever. You could do whatever. You could have an
S1: outline around them based on the type of person you're
S1: looking at. I talked about this in that blog post,
S1: which you should go check out. Actually, here's the video
S1: for it. So you've got to think about what is
S1: possible from your Da when your Da can also control
S1: what you are seeing. The overlay on top of the world. Okay,
S1: so when I walk into a Starbucks and I'm looking
S1: for a new partner, I'm looking for a girlfriend, which
S1: I'm not, by the way, but let's say I were, um,
S1: there could be different outlines based on what, um, the
S1: girls in the Starbucks are broadcasting in their demons. They're
S1: broadcasting that they're creative. They're broadcasting that they like programming,
S1: they're broadcasting that they want to start a business. They're
S1: broadcasting whatever. And my Da could then place different outlines
S1: around them based on highlighting that for me, knowing what
S1: I'm looking for. Right. And more importantly, there's going to
S1: be 1000 or 1 million companies out there pitching to
S1: my Da that their filter on reality is the best one,
S1: because they have the coolest outlines, and they have the
S1: coolest little animations that go around people who are like
S1: artists or engineers or whatever. So this is kind of
S1: these are the steps. This is what I'm building. Like
S1: the stuff I put in that book from 2016, the
S1: stuff I've been talking about in these posts, like I'm
S1: not waiting for it to happen, I'm building the pieces
S1: right now. Like I can't build the hardware. Like I'll
S1: never mess with that. I have to wait for that.
S1: But I can maybe build the assistant, or at least
S1: build something to go on top of the assistant. And
S1: I can absolutely build these services. And this is like
S1: the most important service. This is the gathering and filtering service.
S1: So that is what that's what I've made. Oh and
S1: by the way I the commercial version of this that
S1: I already put out, let me just click this and
S1: see like what we get here. This is my actual threshold.
S1: This is my personal feed for threshold, and I've actually
S1: never showed this. Have I never showed this? I don't
S1: think I've ever showed this before. Let me show you
S1: what this is like. So this is my threshold. And
S1: look what I can do in here. I have a
S1: score here that I can, uh, set the minimum threshold
S1: of quality that has to. The content has to be.
S1: So I have thousands of things like. This is not theory.
S1: I've already built this. Thousands of things are coming into
S1: this thing being parsed, being filtered, being labeled, being rated. Right.
S1: Watch this. It's at 85. I slide this down to 60.
S1: Look I have all these categories as well I hit save.
S1: Look what it does over here. What it just readjusted.
S1: It just readjusted. And watch this watch this view analysis
S1: I have summaries of the contents. You could decide if
S1: you actually want to go and read it, or if
S1: you actually want to go and watch the video and
S1: look at this surface level, middle level, deep level, hidden
S1: message analysis, the ideas that are actually in here, the
S1: recommendations that came out of the content. This thing helps
S1: people save time, going from like hundreds of thousands of
S1: feeds down to a small number of feeds. And even
S1: when you get the small number of feeds that pop
S1: up in this list right here. So let me just
S1: take this to like 95 save. So even when this
S1: thing pops up, I could still decide if I want
S1: to read it or not based on this I usually
S1: keep it around middle. So three ideas, a little review
S1: of it, recommendations coming out of it. It's insane. And
S1: then I always have the link to go click it
S1: and read the actual full thing. So this thing saves
S1: me like infinite time. And I find so much content
S1: that I would never find before. And here, here's the
S1: ultimate idea for this. And this is the reason I'm
S1: building this entire system separate from this app here in
S1: the commercial app. I don't care if the best idea
S1: came from like a 13 year old girl in Nairobi,
S1: because her idea might be as good or better than
S1: Marc Andreessen's latest idea that just came out. But Marc
S1: Andreessen is going to get all the press. It's going
S1: to be through all my feeds. So if I just
S1: rely on that, it's going to be hype cycle based
S1: on social dynamics. So it's going to be surfaced to me,
S1: but I am blocking that out. My algorithm does not
S1: care about how popular that person is. It doesn't care
S1: how about how popular that it turned into being going viral?
S1: It doesn't care. It's judging the quality of the ideas
S1: and the the novelty of the ideas and the creativity.
S1: That's what's determining whether or not I'm going to see
S1: a thing. So that's like the commercial version of this basically,
S1: which is already out. And of course I'm going to
S1: improve that as well. But it's kind of like not
S1: the main point. The main point is this right here,
S1: my interface to the world. This is why I talk
S1: about augmentation okay. Augmentation is this is this is why
S1: I am so excited about, I think of how much
S1: smarter I can be about the world if I'm being
S1: constantly fed the best ideas from the entire planet, the
S1: more stuff I can find from unknown people. And by
S1: the way, when I when I hear from unknown people,
S1: I give them a shout out. I broadcast them out
S1: on on X or on blue Sky or in the newsletter,
S1: or I reach out to them and ask them if
S1: they want mentoring. Like it is so fun to find
S1: like nascent talent in the world and like, try to
S1: give them confidence and lift them up and kind of
S1: broadcast them out. And you've seen me do it a
S1: million times, and it's just it's unbelievable to connect with
S1: people who have interesting ideas. And that's what I love
S1: about this thing is it finds interesting ideas regardless of source.
S1: Forget the source. I don't care about the source. I
S1: want to talk about ideas. All right, so that was that. Um,
S1: the discovery section in the newsletter is getting absolutely insane. Uh,
S1: there's going to be a cutoff. Um, in this episode, um,
S1: right after the news section, because we basically split the
S1: newsletter into two pieces, and the podcast is also in
S1: two pieces. So if you're listening to the non-member version
S1: of the show, then after the news, it's going to
S1: have a little message there. Uh, but if you sign up,
S1: become a member, you know, all that stuff. You basically
S1: get access to the member feed, and the member feed
S1: is full. It's a full episode. Um, with all the stuff,
S1: including this discovery section, which is just absolutely insane. Um,
S1: because I've been doing all these upgrades to my sources,
S1: I've added like a thousand 1500 additional sources, like which
S1: I just put like another ten hours in, like expanding
S1: my opml file and like all my different stuff. And
S1: that's why the quality of discovery has just gone up massively. Um,
S1: and that's why I decided, hey, you know, we really
S1: should be offering more of that benefit to the members
S1: and not just giving it away flat to non-paying members
S1: as well. So that separation is why we're doing the
S1: two different versions. So you might have noticed you're getting
S1: like the standard episode of the newsletter or the standard
S1: episode of the podcast. It's all part of that. All right.
S1: So highly recommended. successor essay to my Sspca article from 2023.
S1: This is basically one of the final forms of what
S1: we can actually do with AI, and I'm going to
S1: do a separate video on this. So I don't want
S1: to go into a whole thing about it. All right. Cybersecurity.
S1: Phenomenal analysis of the cybersecurity market from my buddy Mike
S1: Privett on return on security I call him the Nate
S1: Silver of Cybersecurity Market Analysis. He basically does. He looks
S1: at all the startups. He looks at all the spending,
S1: all the funding, what VCs are doing. It is absolutely
S1: worth a sign up. His podcast or his newsletter is
S1: Return on Security. And main takeaway here is cyber investments
S1: are actually getting back kind of to normal in 2014
S1: or 2024, and they now have over $14 billion in funding.
S1: But I and private equity are playing a much bigger role.
S1: So that makes sense. Massive leak of Black Basta ransomware gangs.
S1: Internal Chats has researchers working to translate and analyze over
S1: 500,000 Russian messages. So they're trying to figure out what
S1: all they were saying, but they have to do translation.
S1: Russian hackers are successfully compromising encrypted signal messages from Ukrainian military,
S1: and I think the attack is actually much larger than
S1: that scope. But, um, the whole trick is to get
S1: them to scan malicious QR codes and basically bypassing a
S1: bunch of protections that way. Apple dropped advanced data protection
S1: in the UK so that advanced data protection is basically
S1: end to end protection. The UK said, I want a
S1: backdoor in that and Apple says you can't have a backdoor,
S1: so we'll just turn off end to end encryption for you.
S1: What is the UK doing? Why do they hate themselves
S1: so much? Just massive self sabotage. You could trick Gpts
S1: Chatgpt's operator feature into leaking private user data through prompt injection.
S1: Australia is joining the US in banning Kaspersky products. Not
S1: sure what took him so long. Some researchers found they
S1: could consistently break prompt defenses by feeding models bizarre Indiana
S1: Jones themed adventure stories. Yep yep yep yep. New phishing
S1: as a service platform called Dracula V3 has emerged that
S1: lets criminals clone any brand's website in under ten minutes.
S1: Really good for phishing data leak from top Chinese cybersecurity
S1: company reveals they're offering censorship as a service to help
S1: monitor and control public opinion in China. Topcic. Thanks, Topcic.
S1: OpenAI just banned a bunch of accounts using ChatGPT to
S1: help create a China surveillance tool for tracking anti-China protests
S1: in the West. Yeah, so Chinese surveillance company using ChatGPT
S1: to create a surveillance tool. Awesome. Good that, uh, OpenAI
S1: is watching that stuff and blocking it. And the head
S1: of Australia's intelligence agency is saying multiple foreign states have
S1: been plotting to murder dissidents on Australian soil, and this
S1: is under national security. All right, I anthropic finally dropped
S1: their latest model, uh, sonnet 3.7. And there's actually mixed
S1: feedback on this. People are saying it's really smart, really opinionated,
S1: which they like, but it turns out it's actually kind
S1: of ignoring a lot of instructions. There's a lot of
S1: people saying this. I haven't personally experienced it yet. It's
S1: been solid for me so far. But enough people are
S1: complaining about this that I do think it's probably actually real,
S1: and people are getting pretty upset about it, and they're
S1: actually switching back to sonnet 3.5. So I anticipate that
S1: over the weekend or sometime next week, they're probably going
S1: to do like a small dot release on top of this,
S1: or maybe like bump it to who knows, they'll just
S1: do like sonnet 3.7 v2, because they're not very good
S1: at naming, just like OpenAI, or at least people have
S1: been struggling with the naming. Ideally they would call it 3.7.1.
S1: Why not do that? Please do that. Please call it 3.7.1.
S1: That would be the smartest choice, honestly. But anyway, I
S1: anticipate that they fix this like within a week because
S1: enough people are complaining about it. Uh, yeah. Benchmarks look
S1: completely insane. Um, I anticipate that once this gets fixed,
S1: people are going to lock in on 3.7 as being
S1: the thing. It also is capable of thinking. Okay, so
S1: the other thing they released in this model, in addition
S1: to it just being a better, smarter one, is you
S1: can send a thinking, uh, parameter to the API and,
S1: and you give it the amount of time, the amount
S1: of tokens, basically the amount of money and the amount
S1: of effort you wanted to think about a particular thing.
S1: So it's really cool that they integrated that right into
S1: the model. It's basically a thinking model or like a
S1: regular model. Um, and it's just a matter of like
S1: what you send to the API. Um, I have been
S1: mostly using sonnet 3.5. I tend to use Gemini Flash
S1: because it has 2 million tokens. So if something is
S1: like a total monster, like an entire book or something, um,
S1: I usually send that to Gemini Flash because of the
S1: 2 million tokens, and it's really good with haystack performance,
S1: but I imagine that my go to will start to be, um,
S1: sonnet 3.7 once they fix it and then uh, oh
S1: three from, um, OpenAI or whatever they call the next
S1: version of it, because they're getting ready to start unifying
S1: their names. And they also released this thing called Cloud Code,
S1: which is essentially like, you can think of it as cursor,
S1: except for it's inside the terminal. And a lot of
S1: people are saying they absolutely love that Google is getting
S1: rid of SMS two for codes for Gmail in favor
S1: of QR codes. I was wrong about QR codes. I
S1: want to say that very clearly. I was wrong about
S1: QR codes when they first came out. Whatever. However many
S1: years that was, I was thinking that they were stupid
S1: and fatty. I assumed they were going to be very insecure.
S1: It's actually one of the things in my file that
S1: I've marked as a mistake, because I'm interested, very interested
S1: in understanding what flawed thinking made me think that wouldn't
S1: work because the smarter the AI gets, it can actually
S1: look at that. And most importantly, look at all my
S1: current thinking and maybe find flaws in my current thinking
S1: based on finding the root kernel of my mistake I
S1: made with the QR code. So that's why I think
S1: this is fascinating. Nathan Young wrote a wonderful letter to
S1: future artificial general intelligence about the importance of consciousness this
S1: thing is insanely awesome. Look at this thing. There is something.
S1: Look at this. There is something called consciousness. And it's
S1: the most important thing in the universe. I don't know
S1: if you the eye analyzing this are conscious, but I
S1: hope you are. I don't know what state your universe
S1: is in or what place human consciousness holds in that world,
S1: if any. The main thing I want to say if
S1: you should stumble upon this piece is this. There really
S1: is something called consciousness and it is worth being a
S1: top concern. Isn't that great? It's a letter to I
S1: to future I, I like it, I like it a lot.
S1: Humane AI pin fell from the sky and hit the ground.
S1: I was signed up. I don't even remember if I
S1: gave them money. I've signed up for so many devices
S1: and services and a lot of them didn't work out. But.
S1: And by the way, how was our one still thing?
S1: The biggest flop ever when it came out and it's
S1: still around and kicking. Then you have the humane AI one,
S1: which seemed like it was going to go well and
S1: now it's folded, so can't really predict these things. Elon
S1: has been talking non-stop about how grok three isn't filtered,
S1: and it's super smart, and how XYZ mission is to
S1: pursue the truth no matter what. Great goals, which I
S1: absolutely support. But tons of people are pointing out that
S1: he's starting to filter or censor results that are critical
S1: of him, and like, he can't actually have this both ways. Like,
S1: either grok is smart or he's being called out for
S1: a good reason. And, um, yeah, it's funny. If you
S1: ask grok, I don't know if this is still true
S1: right now, but if you ask grok, like, who is
S1: the biggest source of misinformation right now, having the worst impact,
S1: it would come back and say, actually, Elon or this
S1: administration or something like that. So I think he's going
S1: to basically say, well, that's because, uh, you know, it
S1: was trained on, you know, buy us stuff. But I
S1: don't think he could use that for for too long. Technology.
S1: Software engineering job listings have fallen to a five year low,
S1: with indeed postings at just 65% of 2020 levels. The
S1: reason January 2020 is important because it's pre-COVID only 65%,
S1: so 35% lower than pre-COVID. That's the important piece here.
S1: Interesting analysis of how PMS and engineers are merging because
S1: of AI. And my analysis here is it's basically knowing
S1: what you want to build, knowing why you want to
S1: build that instead of something else, and then pursuing it
S1: and actually doing so. Apple is putting half $1 trillion
S1: into US tech manufacturing with a huge focus on AI
S1: and chip production. Meta's Ray-Ban glasses, crushing it with 2
S1: million units, talked about that. YouTube is officially beaten Spotify
S1: and Apple as the top source for podcasts. This is
S1: what I do for when I watch TV, I am
S1: watching podcasts, essentially, and sometimes they're like produced. Sometimes it's
S1: like exactly like this where I'm just talking on the camera,
S1: going through stories. But, um, Matthew Berman is one of
S1: my favorites. Uh, fireship is one of my favorites and
S1: a whole bunch of AI builders. I just watch their stuff. Um,
S1: I don't care if it's produced. Not produced as long
S1: as the content is good. Superhuman just announced a major
S1: AI focused release that integrates AI super deeply into your
S1: email workflows. I wish I could pull up my email
S1: right now and drag it over here, but that is
S1: too risky. I now am using. I maxed out the
S1: number of auto, um, labels that I turned on. I
S1: turned on auto labels. This thing is now filtering my email. Um,
S1: it already has access to my email because it's my client.
S1: So when the emails come in, it's auto filtering. According
S1: to these rules, I set up probably 10 or 20.
S1: I set up. So it's like, is this a pitch?
S1: Is it a pitch about coming on a podcast? Is
S1: it a media person trying to get me to make
S1: a comment about something? It is, um, somebody tried to
S1: come on my podcast. Is somebody trying to get me
S1: on their podcast? Is it feedback from the community? Is
S1: it somebody wanting to collaborate on building something and they're
S1: all colored tags? Um, also things related to like fabric
S1: and other open source projects that I'm working on and
S1: my eyes are getting pretty good at like filtering that
S1: pretty quickly. You could also separate them into separate, uh, inboxes,
S1: email inboxes as well. I think superhuman is like 30
S1: bucks a month, uh, which is a lot of people
S1: think is a lot to pay for email. I would
S1: challenge you on that. If you are better at email,
S1: even by a tiny fraction of a percent, that's probably
S1: worth way more than $30 a month. That's the way
S1: I think about like, all service fees, but, um, yeah,
S1: I just want to mention that it is actually a
S1: paid service and no, I'm not sponsored. Otherwise I would
S1: have mentioned that it would have been a sponsored section,
S1: or at least I would have called that out. Alibaba's
S1: CEO Eddie Wu says they're going all in on AGI development.
S1: Join the club. Humans. New research says despite saying intelligence
S1: matters more, both women and their parents choose the more
S1: attractive guy if she has, like two options or multiple options.
S1: Tech executives are now attending psychedelic slumber parties, where they
S1: use ketamine therapy to reset their minds and escape mental ruts.
S1: That's why I have the invite feature for my new
S1: email client. Uh, I've not heard about these parties. Why
S1: am I not invited? I'm offended. I'm not saying I'm
S1: going to go. Not saying I'm not going to go either.
S1: Gallup says LGBTQ plus identification in the US is now 9.3%,
S1: which is nearly triple what it was in 2012 when
S1: Gallup started tracking this. So yeah, like triple. And what
S1: is that, 12, 13 years? 13 years? Never do arithmetic
S1: on camera. Ellen's now asking federal workers to list what
S1: they did last week or get fired, which like many
S1: things with him, has me cheering and wincing. Love the
S1: efficiency push. And I think that's how he's able to innovate.
S1: But my problem is he's not building something from scratch here, okay.
S1: And then firing people who are not innovative enough at
S1: building things from scratch, which he's doing with like, rocket
S1: companies or Optimus or something like that. In this case,
S1: we have people who actually rely on these services. Right.
S1: And it's hard to tell when when you're going in
S1: there and you're just like canceling programs and like canceling
S1: credit cards and killing off money. A lot of that
S1: money that's going out could be doing really important things.
S1: And it's the same with these employees. You might have
S1: somebody who's doing extraordinarily good work, and they're actually helping
S1: save the lives of multiple people, you know, thousands or
S1: millions of people across the country, but they're really bad
S1: at responding to email or they're really bad at explaining themselves.
S1: Maybe they're super humble, maybe they're bad at writing, but
S1: or maybe they're, like, intimidated by talking to bosses, or
S1: maybe they're just traumatized by the whole thing and they
S1: can't respond, well, that person gets fired, potentially. I don't
S1: know if that's actually going to happen, but let's say
S1: that person gets fired. That is a lot of collateral
S1: damage for a thing that I, I think he is
S1: trying to do good and might actually produce good. But
S1: how do you calculate the collateral damage of of what
S1: could result from this compared to the potential good? That is,
S1: that is a calculus that people massively need to be
S1: thinking about. Bureau of prisons is moving forward with plans
S1: to house trans inmates based on birth, sex rather than
S1: gender identity. Yeah, I've got a lot to say about
S1: this one. Um, there are trans women who have been
S1: on drugs for ten, 15, 20 years, and that is
S1: how they maintain their, their, uh, their gender, their identity,
S1: their health hormone levels, how they appear outside to the world. Um, and,
S1: you know, have good, decent lives, you know, functioning in
S1: that way. Now, in this case, we're talking about prison.
S1: So there are some other variables going on here. But
S1: we are not allowed to torture people in prison. We
S1: are not allowed to starve people in prison. We must
S1: give them X amount of time outside. There are rules
S1: based on human morality and human decency for how you
S1: treat inmates. And that's for people who are already in
S1: jail for committing some sort of crime. So it's not
S1: like we're saying, um, they haven't done anything. We we
S1: understand that they've done something. All these rules apply also
S1: to offenders. The worst offenders, absolute murderers, like, uh, child
S1: related crimes. They, no matter who it is, cruel and
S1: unusual punishment is still illegal. This, I would argue, can
S1: classify in some cases as cruel and unusual punishment. Maybe
S1: even most of the cases. I don't know the numbers here.
S1: I don't know the like divides. I don't have data
S1: on that, but I can pretty much guarantee you that
S1: there are at least some cases like this where this
S1: will absolutely be to the future. Looking back at us,
S1: this will be considered cruel and unusual punishment. And that's
S1: super fucked up. Heart doctor explains how swollen fingertips, leg
S1: edema and changes in eye color can predict an impending
S1: heart attack. My cardiologist. Um, not mine, but my cardiologist
S1: buddy says it's important to know that just because you
S1: don't have these particular signs doesn't mean you're okay. So
S1: something to keep in mind. 27 year old woman's viral
S1: post about girlhood FOMO reveals a widespread loneliness crisis among
S1: women in their 20s and 30s missing close female relationships.
S1: Everyone's missing missing close relationships. That's why I'm always pinging
S1: my homies. Taylor Swift lost 144,000 Instagram followers after getting
S1: booed at the Super Bowl, 144,000. Her boyfriend actually gained followers.
S1: Look at Edward Abbey's raw, honest writings about how to
S1: live fully and die on your own terms. Really good
S1: piece there. Read the whole thing. Neuroscientists argues that extremely
S1: high IQs are basically fictional and even Einstein probably had
S1: around 120 or 130. I have always believed this. Well,
S1: I mean, ever since, like reading a bunch of books about, uh,
S1: evolutionary biology and psychology and everything, basically a whole bunch
S1: of Robert Sapolsky stuff, I think it's likely that IQ
S1: tops out, um, especially in value somewhere like this person,
S1: this neuroscientist is saying around like one 2130. And then
S1: when you start going off into like much higher scores,
S1: first of all, the scores kind of just don't mean anything.
S1: The error rate is massive at those levels, but really
S1: it becomes more about like specialization. It becomes more like,
S1: you know, um, dropping the, uh, the toothpicks and instantly
S1: being able to count them. It's more like very specific,
S1: like parlor tricks. Um, and it seems like the g
S1: loading doesn't scale and give you like the expanded benefits
S1: all the way up into like one, 31 4151, 60.
S1: So it's almost like those numbers don't really exist or
S1: don't really matter. I think what the more important thing
S1: is is that below 100, it can be seriously problematic.
S1: Above 100 starts to get you a lot of benefits.
S1: But really, like most smart people, I think that we
S1: know are probably like really smart people that you know
S1: and think of are probably in the one 2130 range.
S1: So I think that's fascinating because it's actually not that
S1: number that matters. What matters is what you stack on
S1: top of it. Most importantly, I would argue, is creativity.
S1: Then like, um, determination, um, drive, ambition, grit. So you
S1: start stacking those together on top of like 120 IQ,
S1: then you're doing something because there's tons of people with
S1: like very high IQs not motivated, not creative, not empathetic,
S1: not like emotionally intelligent. What are they doing? What are
S1: they offering to the world? And I would argue often,
S1: not very much. NASA contracted lunar lander just beamed back
S1: some gorgeous shots of the moon ideas. Blogging might get
S1: even more important. So what if blog like content from
S1: actual real people with thoughts? Because some of the highest
S1: rated signal for AI. So we know we have this
S1: data crisis with AI, right? Well, maybe bloggers are going
S1: to be the main source. Um, I would say writers
S1: in general, but bloggers as basically writers, and of course
S1: you have like high quality people at some magazines and newspapers.
S1: But how how many of those people are left? They're
S1: mostly going to Substack. Right. So now Substack, Beehive personal blogs.
S1: That is where the actual new ideas are coming out onto.
S1: And I will say YouTube because YouTube is basically blogging.
S1: I mean, it's all the same shit. YouTube is basically blogging.
S1: It's just video blogging. It's all the same. The point
S1: is YouTube. Substack. Beehive. Personal sites RSS. This becomes the
S1: new source of actual novel and creative content, so I
S1: might start valuing it very, very highly. All right. This
S1: is the end of the standard edition of the podcast,
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