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S1: That's one password.com/unsupervised learning. Welcome to Unsupervised Learning, a security
S1: I and meaning focused podcast that looks at how best
S1: to thrive as humans in a post AI world. It
S1: combines original ideas, analysis, and mental models to bring not
S1: just the news, but why it matters and how to respond.
S1: All right. Welcome to unsupervised learning. This is Daniel Meisler
S1: and this is episode 431. This is RSA week. Got
S1: grok support coming to fabric. If you've not messed with
S1: grok yet you absolutely need to go do this. It
S1: is insanely cool to use. It is so fast! I
S1: would love to do a demo, but we need to
S1: get through the show, so I'll probably do a demo
S1: in a separate talk or uh, little video soon. My
S1: buddy Clint Gibler and also Caleb Simon gave awesome talks
S1: at Bsides, so that's super cool. Be sure to check
S1: those out when they come out. I got a new
S1: essay here on how consultancies are about to move into
S1: departments and companies, and basically break them into pieces and
S1: apply AI to them. I've been wanting to write this
S1: one for a very long time. It's called companies are
S1: a just a graph of algorithms, and I'm probably going
S1: to record this as a standalone episode as well. Second
S1: new essay this week is how I think prompting is
S1: kind of the center of AI, and even though there's
S1: lots of cool stuff you could do with like fine
S1: tuning and training your own models and stuff, I think
S1: prompting is still where it's at, and this is kind
S1: of like an important walk through, or at least a
S1: decent walk through. On why I believe that, security wise,
S1: Biden administration is changing it so that you can they
S1: can basically hire within it, and especially security. They can
S1: hire essentially people who don't have a degree, which has
S1: been a huge limiting factor for them to get talent.
S1: So that's really, really good news. The CEO of UnitedHealth
S1: took personal responsibility for paying the $22 million ransom to
S1: get business back running, and that is really interesting that
S1: he did that. We'll see what the fallout is. I
S1: do worry a little bit about the signaling that it's
S1: basically saying, hey, it's okay to pay ransoms, which of
S1: course kind of propagates it. It's like, oh, we never
S1: negotiate with terrorists type of deal. That policy makes it
S1: so that people are less likely to become terrorists. So
S1: we'll see how that plays out. Satya Nadella sent out
S1: a Bill gates type memo saying that security was the
S1: top priority, which is cool to see history repeat itself there.
S1: Cybersecurity consultancy got busted for trying to well, no, a
S1: consultant got busted for trying to extort an IT firm
S1: for $1.5 million by threatening to leak their secrets. Not
S1: the way to get what you want. Or maybe it is,
S1: I don't know. Verizon, AT&T, T-Mobile and sprint got hit
S1: with a $200 million fine for selling customer location data. Oh,
S1: this is insane. A team trained a robot dog in
S1: a simulation. Completely in a simulation how to walk on
S1: a ball. And then they took that code and put
S1: it in an actual robot dog and put it on
S1: an actual ball. And it just worked. I mean, think
S1: about how that's going to transfer to lots of different
S1: human problems. Google is pushing for a change to immigration policies.
S1: They basically say that we're losing AI and security talent
S1: because they're going to other countries. This is a tweet
S1: of mine about the difference between a company that uses
S1: back end models versus the whole company is actually the
S1: back end model. So it's like, what's your vulnerability to
S1: getting sherlocked by someone like OpenAI or anthropic? And this
S1: is basically a breakdown for how you should actually build
S1: your company so that it just gets better when those
S1: things improve, it doesn't actually get replaced. I got a
S1: doctor buddy who loves AI note taking. She said she
S1: was basically going to give up and just get out
S1: of practicing medicine. And basically I note taking saved her
S1: from doing that. So that's cool. Someone's criticizing Sam Altman's
S1: approach as a blend of fear, ignoring uncertainties and riding
S1: the hype wave. Apple is supposedly working on a big
S1: AI team, pulling people from Google and building up some
S1: sort of lab in Zurich. My buddy Joseph Thacker just
S1: wrote a great post on assumptions in Lm's assumptions made.
S1: This is the article you want to go check it out? It's, uh,
S1: really good. Somebody automated a YouTube shorts channel entirely entirely
S1: with free tools. So it's a short book. Summaries is
S1: what it is, and it's just releasing episodes. It's doing
S1: the whole thing. It's just automation. Uh, really cool to
S1: go check that out, especially because it's book summaries, which
S1: are useful complexities, allure and simplicity is power. Basically, this
S1: article is arguing that simplicity is powerful, but complexity is
S1: what actually sells and gets people excited. Uh, I'm I
S1: don't agree with that for myself, but I think the
S1: article made a pretty good case for it. 30 Useful concepts.
S1: So I just found like 27,500 asteroids in old telescope photos.
S1: And this is a good example of where you need
S1: AI because there aren't enough people, professionals actually looking at
S1: the sky with telescopes. There's just not enough people. There's
S1: not enough eyes, there's not enough experts. So this is
S1: a perfect. For. I actually just having access to tons
S1: of different telescopes and then being able to just launch
S1: an alert if it sees one that looks big and
S1: it looks like it might be heading towards us, looks
S1: like we might have found a potential for extraterrestrial life
S1: by detecting a certain molecule. Looks like higher paid employees
S1: are struggling, which makes sense to me because. If you
S1: want to reduce how much you're paying in headcount, you
S1: reduce the people first. That make the most. I've seen
S1: this personally multiple times for people around me. So definitely true.
S1: Got an interesting measurement of the economy, essentially how well
S1: strippers are doing and how much they're getting tipped. Is
S1: a good indicator or at least an interesting indicator. Number
S1: one metric for longevity continues. Every study I've seen about this,
S1: it's basically VO2 max. And this is yet another study
S1: that's confirming that. Really cool essay. I didn't read it again,
S1: but I've read this like ten times. In Praise of
S1: Idleness by Bertrand Russell. And this one is really interesting.
S1: We got this woman here who is complaining about. Oh
S1: my God, they offered me. A help desk job. I
S1: keep getting these offers for help desk jobs, and then
S1: she proceeds to show off her two degrees. She's like,
S1: look at this degree and I have a second degree.
S1: Can't they see that I have these degrees? Why would
S1: they be offering me a lowly help desk job? First
S1: of all, help desk people are awesome. InfoSec Taylor Swift
S1: was a help desk person. I know so many people
S1: who started on the help desk. My buddy Jason Powell
S1: started on the help desk and now he's doing amazing
S1: things at Apple. And it's like, look, you can't. First
S1: of all, you're demeaning a group of people who work
S1: in a field. So that's a problem. Second of all,
S1: it's not above you. And third of all, those degrees
S1: don't actually mean anything for you, right? This is kind
S1: of the problem, right? She's in a heart for a
S1: hard time because. She believes that she's entitled to these things.
S1: I do want to mention, though, it's not her fault.
S1: It's the fault of the system for programming. And this
S1: is like the parents, this is the teachers, this is
S1: the whole school mechanism. And this tended to be more
S1: true in the past. Right? You put the work in,
S1: you pretty much get a job. It is just not
S1: the case anymore. And it's definitely not the case now
S1: with AI, it was already the case before. I mean, 2022.
S1: It was not the case that a credential was good enough.
S1: You already needed to be special in some sort of way.
S1: So this was already a bad take, you know, back
S1: in 2022. And now it's even worse, way worse with
S1: AI because people like this who think that their homework
S1: and their the fact that they finished these classes is
S1: actually going to be valuable to that company by itself.
S1: They're the ones who are going to get replaced by
S1: AI or just not hired at all. And this is
S1: another sort of thing around this. It's just like actually unrelated. But, um,
S1: it's basically if you're in tech and you're constantly dunking
S1: on AI, you should stop and you should think about this.
S1: AI is about to add billions or trillions of new,
S1: highly skilled and intelligent workers to the economy. And I mean,
S1: this is what's going to happen, right? And I've got
S1: a whole whole vibe here, but I'm not going to
S1: read the whole thing. Basically, the takeaway is that something
S1: about AI might be putting you off. Maybe it's like
S1: the fanboys, maybe it's the fan. The fact that it
S1: might sound to you like crypto or NFTs, you need
S1: to push that aside and like, push away the fact
S1: that you're you're turned off for some reason about this,
S1: because if you were turned off about driving or turned
S1: off about reading or writing it, just because somebody was
S1: going crazy with CrossFit around reading and writing or reading
S1: and writing, it's the best thing driving. It's the best thing.
S1: And when you saw those people talk, it annoyed you
S1: and you're like, you know what? Because of those people,
S1: I'm not going to learn how to read, write or drive.
S1: That's what you're doing with AI. That is what you're
S1: doing with AI. And guess what? It's not hurting them.
S1: It's going to hurt you. So that's why I'm saying here.
S1: That's the point of this one. And the recommendation of
S1: the week is my three minute video for how to
S1: Build a meaningful life. It's pretty cool. It's like three
S1: minutes 30s. And the aphorism of the week is one's
S1: destination is never a place, but a new way of
S1: seeing things. One's destination is never a place, but a
S1: new way of seeing things. Henry Miller Unsupervised Learning is
S1: produced and edited by Daniel Miller on a Neumann U87
S1: AI microphone using Hindenburg. Intro and outro music is by
S1: zombie with the why and to get the text and
S1: links from this episode, sign up for the newsletter version
S1: of the show at Daniel meisler.com/newsletter. We'll see you next time.