S1: Welcome to Unsupervised Learning, a security, AI and meaning focused
S1: podcast that looks at how best to thrive as humans
S1: in a post AI world. It combines original ideas, analysis,
S1: and mental models to bring not just the news, but
S1: why it matters and how to respond. All right. Welcome
S1: to unsupervised learning. This is Daniel Meisler. This episode is.
S1: Can you articulate yourself in 50 words? Let's jump in here. Yeah.
S1: One of the most important things for surviving AI is
S1: being able to articulate what you do, or even better,
S1: who you are. So I was at a party with
S1: a bunch of like, high net worth people, like muckety
S1: mucks like important people. And somebody asked me, I was
S1: at RSA, so people have asked me this like 20
S1: times over the course of the week. They asked me
S1: what I did and I told them I built AI
S1: stuff and they just looked at me like, oh, you're
S1: an asshole. Basically, like I was trying to be cool.
S1: And it's like, I am seriously not trying to be cool.
S1: I'm trying to say a small amount, which maybe spawns
S1: a conversation if they're like, oh yeah, really? What kind
S1: of AI or something? But I don't want to go
S1: into some sales pitch of like, oh, I'm building AI
S1: that blah blah, blah blah does this. But it was
S1: just like not landing. It didn't land for me. It
S1: didn't land for them. It just wasn't good. So I
S1: think I'm basically going to answer differently from now on.
S1: I'm going to start with the problems. So I'm basically
S1: worried about two problems people having a lack of meaning
S1: in their lives and AI making that worse when their
S1: jobs go away. So what I do is I use
S1: AI to build products and services that help people and
S1: companies create a version of themselves that will not just survive,
S1: but will thrive after AI is everywhere. And I could
S1: say that in multiple different ways, but it starts with
S1: I'm worried about two problems, so I'm building these things
S1: to solve them. So that's basically like my new spiel.
S1: And I like this for a few different reasons. One,
S1: it starts with the problems. Two, it highlights that I'm building.
S1: It mentions AI, which is good to mention, and it
S1: is actually what I'm doing, and it puts meaning as
S1: the most important piece even above AI. So I like
S1: it for all these different reasons. But I think the
S1: most screwed people right now are those who don't know themselves, right?
S1: They don't know what they're about, they don't have a
S1: purpose they can't articulate, like why they get up in
S1: the morning and what they're driving towards, or why they
S1: do the job that they're doing other than, well, I
S1: it's just the job I have or whatever. So my
S1: recommendation know yourself and be able to articulate that thing.
S1: So I ran this through the create five sentence summary
S1: fabric pattern. And it ended up with this helping people
S1: find meaning in the AI era. Empowering human potential with AI,
S1: AI for human flourishing, meaningful AI solutions, and AI powered meaning.
S1: Not too bad. So my work network Chuck, my buddy
S1: Chuck here just posted the most amazing video about fabric.
S1: It was just absolutely, insanely good. I've been waiting for
S1: this thing to drop for a couple of months now,
S1: and so he basically captures this spirit of the project
S1: in such a fantastic way. He just really gets the
S1: concept of it how it's human. First, he mentions it
S1: multiple times, he pulls multiple quotes out. He's got us
S1: talking about it in an interactive way there. It's just
S1: unbelievably good. And it's a pretty long video. And he
S1: walks through all sorts of use cases. Highly recommend that one. Security.
S1: Looks like we're going to have a cyber force similar
S1: to the Space Force. Chinese linked hackers are using things
S1: called orbs, which are basically these hop networks that they
S1: can bounce through for hiding, spying, and a bunch of
S1: other shenanigans. Fixed problems instead of doing risk measurement theatre.
S1: I came up with that title, but Andy Ellis wrote
S1: this piece. Quite cool. This piece actually. Short. Sweet. Yeah.
S1: Really good. Highly recommend it. Run some AI against it
S1: if you don't want to read that. But yeah, really good.
S1: Got a bug cloud? No, a cloud related bug. Linguistic lumberjack.
S1: Pretty cool alliteration there. Issue with Fluentbit. And basically it's
S1: got 3 billion downloads and it's yeah all sorts of systems.
S1: So another supply chain issue American criminal records exposed 70
S1: million rows of American criminal record in a database somewhere.
S1: So Russia evidently launched some sort of space weapon capable
S1: of attacking satellites. And they're saying that it's close to
S1: a particular one, same orbit as a US government satellite
S1: posing a direct threat. And of course, Russian said Russia
S1: said fake news. Not true, which I believe. And why
S1: wouldn't you believe him? Like why would they lie? That's
S1: the thing. I breaks into a tech giant. So X-Force
S1: from IBM, they've been around forever. They've been around like
S1: they were around when I got started, I think. And
S1: they got a new AI hacking platform, and they use
S1: it to attack some major tech manufacturers network, and they
S1: got in around eight hours. Question is, how much human
S1: involvement was there or was it like completely automated? That
S1: would be impressive. They haven't released this tool yet, but
S1: eager to hear more about it. Tesla's can still be hacked.
S1: I believe these were model threes, but. A buddy, Malwaretech
S1: Marcus Hutchins did a demo of this on his TikTok.
S1: Pretty easy to get into these cars still, even though
S1: they switched to wideband to try to get around this,
S1: I believe. But yeah, it still works. Not sure if
S1: it works on model wise. Preliminary report on the Baltimore
S1: Bridge looks like unexpected structural weaknesses. So not cyber like
S1: so many people said immediately. Core issue with Wi-Fi with
S1: lack of Ssid authentication during beaconing. Okay, got a US
S1: woman and four others charged in a scheme using fake
S1: IT jobs to get lots of money into North Korea's
S1: nuclear program. 60 identities and 300 companies US companies. Insane.
S1: NYPD is rolling out drones to respond to 911 calls.
S1: I am happy about this, but only because I like
S1: sci fi technology. You. The EU passed its AI act,
S1: and I've got a summary here. I'm not going to
S1: read all ten of these points, but the fines up
S1: to 7% of worldwide turnover, that's a pretty hefty fine.
S1: Probably not going to be ignored as much as other regulation. Oh,
S1: the other key point, because I read a whole bunch
S1: of this thing, was that they tried to support innovation,
S1: so they didn't go like crazy Europe on it with
S1: like just more and more regulation. They actually have a
S1: regulation in here that says you can't impose other regulation.
S1: So they wanted to avoid this getting out of control,
S1: which I thought was smart of them. And when your
S1: AI sounds too much like Scarlett Johansson. So I have
S1: opinions on this. So basically Sam tweeted out her, okay,
S1: so it was pretty obvious that they wanted this thing
S1: to sound like the movie, right? So they reached out
S1: to a voice actress who sounded like Scarlett, and then
S1: they reached out to actual Scarlett Johansson. Real Scarlett Johansson
S1: said no. So they're like, okay, we're going to go
S1: with the other one. They already I don't know if
S1: they had tweeted out her before or after that, but
S1: it was obviously they were going in that direction. I
S1: don't think this is horribly malicious. Like if you've ever
S1: worked inside of one of these companies, especially at like
S1: the leadership level, there is mass chaos. You might have
S1: marketing talking about something. You might have someone on your
S1: leadership team who, like, was approved to say something. But
S1: they said the thing that was different than the actual message.
S1: There could be miscommunication here. So yeah, I don't think
S1: it's malicious, but somebody was bringing up. Look, it's not
S1: Scarlett Johansson. You can hire somebody who sounds like somebody else,
S1: no big deal. And I had a tweet somewhere. It
S1: was like, you're not allowed to deepfake people using real humans.
S1: That's still a deepfake. Not technically. It's not technically a
S1: deepfake because it's not AI. It's a real person. But
S1: the point is to copy someone else. And I'm sure
S1: there's precedent for this all over the place. Already on
S1: the books. It's like if I hire somebody who looks
S1: exactly like whoever, um, the Rock, Dwayne Johnson or whatever,
S1: and I'm like, yeah, I'm claiming to be him or no,
S1: I just call the app the Stone, and it's like
S1: the Rock's voice, but it's like, no, I didn't know
S1: it was the Rock, and I. What are you talking about?
S1: I don't even know who the rock is. But you
S1: hire a person who sounds just like him, and the
S1: app is called the Stone. Then you tweet out, rocks
S1: are cool, that come on, there's got to be a
S1: precedent for that. So they're going to get smashed if
S1: that does go to court. I wish it just wouldn't. Right?
S1: I mean, I'm trying to look at positives here. Like
S1: Sam is trying to do a cool thing. Okay. It's
S1: like her is awesome, I love her. I've got a
S1: video about this where I'm like, hey, look, you could
S1: talk to Samantha from the movie her and I'm breaking down,
S1: like how you can use that with Siri and Shortcuts
S1: and everything. So it's like so obvious and it's so cool.
S1: And it's also cool for Scarlett to be able to say, yeah,
S1: you know what? Not me. Can't do that. So anyway,
S1: it's a legal issue. I'm not sure what the actual
S1: precedent says, but yeah, hiring someone who sounds just like
S1: Scarlett and pretending it didn't happen, that's not the game.
S1: Looks like Apple tried to get all of TSMC's two
S1: nanometer chips stock skyrocketing 262%, $26 billion. They're about to
S1: be worth more than Apple, which is ridiculous. And I
S1: think Scott Galloway was quoting some stats of like, it's
S1: Nvidia at this point is worth more than like the
S1: economy of Germany or something. Just ridiculous numbers. And I
S1: think we're just starting with AI, so I don't see
S1: how someone's going to catch up before, who knows how
S1: high Nvidia is going to go, but I feel like
S1: they got a massive lead and everyone's going to be
S1: trying to get in. AI is just starting. People are
S1: talking about plateaus. I think they're absolutely insane. So yeah,
S1: exciting times. Looks like we found some lithium in the US.
S1: Massive untapped lithium source Microsoft is reimagining windows with a
S1: deep dive into AI, introducing copilot NPCs that blend cutting
S1: edge AI features directly into the operating system. People are saying, hey,
S1: nobody wants this. Well, yeah, they actually do. Once everyone
S1: has the ability to remember everything they've done on their computer,
S1: remember every screen, and they could just talk to their
S1: computer and be like, hey, where was that one email? Hey,
S1: am I missing a thing? Hey, keep me up to date. Hey,
S1: make a list of this. Hey, send a list of
S1: this to all my friends. Hey, show me the most
S1: important things I should be taking a look at. Hey,
S1: reprioritize my work. Hey, rewrite this document for me. And
S1: when I say rewrite this document for me, it knows
S1: that I'm looking at the screen and it knows what
S1: document I'm looking at. So it just rewrites it and
S1: it's like, ah, not so much. Make it less formal.
S1: Boom rewrites it less formal. Okay, send it out to
S1: all my directs or whatever. Boom sends it out. Once
S1: you're interacting with a computer like that and you have
S1: all of your history available, this is like I said
S1: in my AI prediction video, everyone's going to want this,
S1: and they're going to demand it. And what it requires
S1: is everything being recorded all the time, all your screens,
S1: all your conversations. Trust me, it's happening. It's going to happen.
S1: There's nothing that's going to stop that. There's nothing's going
S1: to slow it down. It is too powerful and too awesome. Now,
S1: will there be security issues? Oh yes. So many security issues.
S1: And they will be horrible because it will be your
S1: whole entire soul getting compromised when that stuff gets leaked. Right.
S1: It's every text message that came through everything. A little
S1: pop pop up, someone sent you a dirty joke or whatever,
S1: or you sent somebody else a dirty joke that's also recorded.
S1: That's also captured by AI. That's somewhere. Now it's in
S1: some law document somewhere. Because guess what? Lawyers get access
S1: to that and everything. I mean, it's going to be
S1: crazy world we're about to move into. But I tell you,
S1: the downsides are not going to slow it down in
S1: the slightest because the upsides are going to be so powerful.
S1: Mapping AI's inner universe. This is really cool. Anthropic released
S1: a paper on sonnet, which is their medium level model,
S1: and basically showed how it thought essentially basically a lot
S1: more transparency for AI, which has been traditionally opaque with
S1: neural nets. China released a chatbot called Ask President XI,
S1: and it allows citizens to ask Prachi how to be
S1: better socialists. Fantastic. I bet that's flying off the shelf.
S1: Astronomers are preparing to use AI to tackle 300PB of
S1: data annually. Yeah. Watch this guy. Find some stuff. Make
S1: sure rocks don't hit us. Windows 11 Powertoys allows you
S1: to transform AI transform clipboard content into different formats or
S1: languages with a simple shortcut. Love it and it uses OpenAI. Cool.
S1: No problem. Microservices might be all the rage, but this
S1: thing basically says use modules instead of microservices. Interesting. X
S1: is getting rid of public likes, so you can't get
S1: in trouble for liking somebody who's controversial. You'll still be
S1: able to see when someone likes your stuff, and you'll
S1: still be able to see your own likes, but you
S1: won't be able to see other people's. You won't be
S1: able to see someone who you hate and see a
S1: third person who liked their stuff. That's what you won't
S1: be able to see. And Elon basically thinks that this
S1: is going to increase the number of likes. And I
S1: think he's probably right about that. Focusing on fundamentals over
S1: frameworks could be the secret sauce for long lasting tech skills.
S1: Agree with this. This was a good essay. Shows you
S1: how to use ghidra for crafting gdb scripts that trace
S1: function calls helping with vulnerability, hunting D3 in-depth guides. Love
S1: me some D3. Really powerful library experts JS simplifies creating
S1: multi-agent AI systems. Starting to get pretty turned off by
S1: AI agent systems. Honestly, I'm heading down the path of
S1: just building all my own stuff, and that's what I'm
S1: doing with substrate. So getting away from the agent frameworks,
S1: I think just a lot of really cool stuff in
S1: demos and not usable in production. That's what I'm finding.
S1: And I think everyone's finding that who's actually building user
S1: persona generator prompts simulates user interviews to create detailed user personas,
S1: saving you from conducting dozens of real interviews. Yeah, wait
S1: till you see what AI is going to hiring. Oh yeah,
S1: that's what we're about to talk about. Job seekers are
S1: struggling to find work and employers can't seem to fill positions. Paradox.
S1: It is not a mystery. The problem is hiring managers
S1: need people ready to do the job and they don't
S1: want to train anyone. This is why degrees are mattering less,
S1: and why somebody with an active tech blog or YouTube
S1: channel who's actually building stuff and doing the thing can
S1: get hired with no credentials over someone with a degree
S1: in computer science, or two degrees, or a master's degree
S1: or a PhD. The ability to actually do the thing
S1: is all that matters now. Expect to see AI services soon.
S1: Now look at a person's social media blog, YouTube, whatever,
S1: and then do an interactive interview with them and give
S1: a score of how likely they are to do a
S1: good job at this job. This will cut through all
S1: the credentials, all the fluff, all sorts of other BS
S1: and get at the real thing. The value of traditional
S1: education will drastically fall because of this. Like pay attention
S1: to this. The value of traditional education will drastically fall
S1: as a result of this, because degrees won't significantly raise
S1: these scores for most people. This is something this controversial point.
S1: I used to think that it was all about expose
S1: people to the training and they will get better, and
S1: you just need better training. If they're not moving, you
S1: give them better training. Turns out that's not it. It's
S1: actually something inside the person that if they are that
S1: person who's going to be awesome, it doesn't take much
S1: to prompt them or to stimulate them into their curiosity,
S1: which just makes them a voracious reader and learner and studier.
S1: And all of a sudden, boom, they shoot out of
S1: the thing. That's why the help desk is so good
S1: at finding talent, because it's a wide filter. There's so
S1: many people on Help Desk, but there's somebody on help
S1: desk who, the moment they sat on the tier one floor,
S1: they immediately like started answering all the questions for everyone else. Boom!
S1: They become tier two, boom. They become tier three. And
S1: before long, if they have the right networking or whatever,
S1: they go into networking, they go into sysadmin, or they
S1: go into programming or they go into security or something,
S1: and they shoot off and they become a star. And
S1: an experienced person could have seen them at tier one
S1: in tech and just been like, oh, that's a star
S1: right there. First of that is that there are people
S1: who come in with two degrees, go to tier one,
S1: you send them to Harvard, the best training, the best everything,
S1: and they can't even move into tier two. They're there
S1: for six years. And when they see a problem that
S1: they've seen a million times, they call their manager or
S1: they ask the person next to them, and that is
S1: a function of them versus the other person. Now. And
S1: there's lots of people in between what this is going
S1: to do. And this is here's two extremes here. Lots
S1: of education, little ability to do the thing practically and
S1: technically versus somebody who doesn't have much training at all. Right.
S1: No exposure to the stuff, no networking, no connections. And
S1: they're just voracious. They just what? Oh, how do you
S1: do that? Whoa whoa whoa whoa. And they just jump
S1: into it and jump all over it. And they learn
S1: the stuff instantly and they're like, oh, you can just
S1: code that. Oh, well, what's the name of that Python? Oh, okay.
S1: I guess I'll go learn Python. They come back, they're like, hey,
S1: I wrote a program to do that. It's like, when
S1: did you learn Python? Oh, I didn't, I just looked on.
S1: I watched a couple of YouTube videos. I wrote a program.
S1: Some people are like that and some people are the
S1: opposite of that. This is what I is good at.
S1: It's going to be able to tell you the difference
S1: between those. So guess what? You're going to be able
S1: to filter through tens, hundreds, thousands, tens of thousands of resumes,
S1: find people like that, send them into an additional filter,
S1: which is like a live interview with like an AI
S1: avatar or whatever. It runs them through scenarios, sees how
S1: curious they are. It's going to find the magic sauce,
S1: the same magic sauce that I'm talking about right now.
S1: The AI is going to find that magic sauce. It's
S1: going to give them a score, and they're going to
S1: shoot to the top. And guess what? Everyone's going to
S1: go hire those people. Nobody wants to hire a new person.
S1: Nobody wants to train new people. This is why there
S1: is the gap in hiring. This is why so many
S1: people are getting out of college, can't find a job.
S1: It's because they're like, hey, look, I've got my degrees.
S1: Can't wait to do my training so you can teach
S1: me how to do my job. And the hiring manager
S1: is like, yeah, so about that, we're busy. We don't
S1: have time to train anybody, so we won't be hiring you.
S1: We will be hiring Caleb, who is a 15 year
S1: old who is doing this job already and has been
S1: for three years in between playing video games. And that's
S1: who we're going to hire instead of you with your
S1: master's degrees. So it'll filter for drive, curiosity, obsession, and
S1: proof of work like actual builders and coders and people
S1: who raise insightful questions that are curious. This is going
S1: to spawn a completely new type of education dedicated to
S1: making more people like the stars that I'm talking about,
S1: because a lot of the people who are dull in
S1: this way that I'm talking about, they were just let
S1: down by their maybe it's genetic, maybe they're just not
S1: as smart. Of course, there are smarter, less smart people,
S1: but I think a lot of this is cultural where
S1: you have they were just not given curiosity as a
S1: thing as they were growing up. And this is another
S1: opportunity for AI to change that education and not teach them. Oh,
S1: it's about what you can remember and instead teach them.
S1: It's about what you find interesting, right? Get that curiosity
S1: into them early, then expose them to modules of training
S1: instead of stupid curricula. Tough times for new grads. Okay,
S1: same point. Yeah, see above. And of course this is
S1: not the only factor, but yeah, hitting a wall with
S1: entry level hiring projected to drop by 5.8% in 24. Yeah,
S1: wait till you see 25 and 26 and 27. It's
S1: going to get nastier. Software engineer positions on indeed have
S1: plummeted 30% from pre-pandemic levels. Even with all this stuff considered,
S1: I still don't understand that number. That's ridiculous. That's got
S1: to be some macroeconomic stuff. I'll have to talk to
S1: Mike about that. I don't know all the inputs coming in.
S1: I think the thing I'm describing is one of those inputs,
S1: but I don't know how that accounts for 30%. So
S1: obviously multifactorial is college overrated? Nearly 30% of Americans are
S1: questioning the value of college, according to a recent Pew poll.
S1: Once again, see above. Job hopping not just flaky, but strategic. Yeah, yeah,
S1: I wrote this here. You're wondering why I say I
S1: wrote this. I helps with this sometimes. Write some of
S1: these sentences. Some portion of this could be I written
S1: a lot of these I write myself or I have
S1: to go and edit them just because I don't like
S1: what the AI writes. So I have to do it myself.
S1: Like I had to write this whole thing. I think
S1: not because they're flaky, but because they're in search of
S1: a culture that matches their drive. Sticking it out in
S1: a toxic work environment can dole a high performance edge.
S1: I think that might be I right there. Can't actually remember.
S1: My AI is getting so good that. A it actually
S1: copies me pretty well. I definitely write everything in the blue. 100% yeah.
S1: So here's my main point for truly top performers. It's
S1: not bad to see them jump every 3 to 4 years.
S1: Hiring managers know they get bored quickly and that they
S1: can probably solve a bunch of problems, and then they
S1: just leave because they want to solve a new challenge.
S1: And plus they got a little bit of their stock payout.
S1: I know tons of people like this, like star programmers,
S1: and they just bounce around and nobody really cares because
S1: they're just happy to have them when they show up.
S1: It doesn't work for the whatever. 30 years ago IBM employee,
S1: they'll be like, oh, you left after seven years, why
S1: are your pants on fire or whatever? All right. So
S1: now they're saying avoiding the sun might actually be a
S1: risk factor. Yeah. So get too much sun. You'll die.
S1: Don't get enough sun. You'll die. Punchline. You'll die. I
S1: definitely believe this. I think there's value to this whole like,
S1: get sun touch grass thing grounding. Get in touch with nature, whatever. Yeah,
S1: definitely true for me, anecdotally and possibly anecdotally as well.
S1: I think we need more science on this. More people
S1: are doing marijuana than drinking now. I guess we could
S1: take that as a win. That drinking is down because
S1: Uberman said alcohol is poison. He also went pretty hard
S1: on cannabis as far as I can remember. Psychedelics as painkillers. Yeah,
S1: this is getting a lot of press. One third of
S1: Amazon warehouse workers are on food stamps or Medicaid. That
S1: is not a good number one file to rule them all.
S1: One massive, sprawling text file I am in favor of. Text.
S1: Text is my favorite. I love large files, broken down,
S1: markdown bullets. Super clear, easy to read. I love this
S1: whole vibe, and I'm using it for fabric and managing
S1: my own internal context and everything. US Justice Department is
S1: gearing up to dismantle the Live Nation Ticketmaster giant. Hallelujah!
S1: So overdue. And thank you for Taylor Swift, because I
S1: think she had something to do with this. California is
S1: getting over a quarter of its energy from sun soared.
S1: Finding is not what you think. An argument from one
S1: expert claiming everything we know about sword fighting is bad.
S1: It's my favorite Paul Graham essay. Great work happens by
S1: focusing consistently on something you're genuinely interested in. I love
S1: this sentence. When you pause to take stock, you're surprised
S1: how far you've come. Paul Graham is one of my
S1: favorite essayists ever, and this is one of my favorite ones.
S1: I think it's called Great Work or How to Do
S1: Great Work is the name of the essay should have
S1: linked it here. This rhymes with a realization I've been
S1: having lately that the best leaders and founders have something
S1: in common, which is like we were talking about before,
S1: actually obsession. It's not that they're disciplined, or they might be,
S1: and they probably are, but they just might be obsessed,
S1: which tends to look a lot like discipline because they
S1: both produce consistent effort in a uniform direction. I find
S1: myself increasingly looking for people who are obsessed with things,
S1: life and idea, whatever. They can't stop thinking about it.
S1: And the million different ideas they have tend to revolve
S1: around that same concept. It's one that my buddy Joel
S1: Paris sent me the link to. This is cool. Nostalgia
S1: tends to peak at a single age, and I think
S1: this is either Pew or Gallup. I mix the two up,
S1: but if you draw the line, it's somewhere like right here,
S1: and that's around 15. Yeah, 15 years old, 18 years
S1: old or whatever. And guess what? The most close knit
S1: community is the most moral society, the least political division,
S1: the happiest families, the most reliable news reporting. It all
S1: happens when you're 18 years old. So regardless of your age,
S1: whenever you were 18, that's when you think the Golden
S1: Age was brilliant. Data visualization recommendation of the week. Become
S1: able to articulate who you are and what you're about
S1: in 25 to 50 words. And the aphorism of the
S1: week fall seven times. Stand up eight, fall seven times.
S1: Stand up eight. Japanese proverb. Unsupervised Learning is produced and
S1: edited by Daniel Meisler on a Neumann U87 AI microphone
S1: using Hindenburg. Intro and outro music is by zombie with
S1: the why and to get the text and links from
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S1: show at Daniel meisler.com/newsletter. We'll see you next time.