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. So
S1: the first thing for this week is I finally turned
S1: my 9000 word I predictions essay into an actual video.
S1: So if you click on this thing all right I'm
S1: going to try to do something crazy right now I'm
S1: going to try. This is the whole video I go through.
S1: I thought it was going to be like 30 minutes.
S1: I'm like, knows what we want because it has all
S1: the prefaces in, it knows our journal, it knows all
S1: the stuff that we plus like two hours of editing,
S1: which I never should have done. But anyway, it is
S1: a full walkthrough of the illustrated essay, and I even
S1: give a lot more sort of expansion narration on top
S1: of the text that's in the essay, so it's quite good,
S1: if I do say so myself. I've had a lot
S1: of people say they enjoyed it, so I would say,
S1: go check that out. It gets me excited to even
S1: think about it. Talk about it. It's like the fun stuff.
S1: Plus I remember like doing the art. It's just super
S1: good time. Okay. Security. Yeah. But so go check out
S1: the video. All right. Security. So Israel's top spy, chief
S1: Jose Ariel, accidentally revealed his identity through an Amazon book sale.
S1: So I guess we're just doxing him now. That's rude. Well,
S1: I guess he's not going to be that anymore, because
S1: they're going to be like, you obviously can't do this.
S1: So they probably got rid of him and replaced him
S1: with someone who is still anonymous. So now he's no
S1: longer the spy chief. He's just a guy doing an
S1: Amazon book sale. All right, cvn, Nvda databases are struggling. Um,
S1: it's causing gaps and inaccuracies. So somebody needs to fix that. Uh,
S1: criminals in Montreal are using Apple's AirTags to track and
S1: steal cars. And police are using Apple's AirTags to track criminals.
S1: So a lot of AirTag use on both sides of
S1: the fence there. And this one's super cool. This sponsor
S1: I want to talk about this one because I'm actually
S1: advising for them the first AI SoC analyst that autonomously
S1: investigates alerts. This thing will pull alerts. I've seen this
S1: live pull alerts. And this is a sponsor, by the way. Sponsor.
S1: And I'm an advisor for them. So I'm just excited
S1: about them. It's called drop zone AI. So you take
S1: an alert from anywhere in your stack, some tool that
S1: you have that produces an alert like an endpoint cloud
S1: doesn't matter. And it takes alerts from your environment and
S1: performs autonomous. It basically goes and starts researching exactly like
S1: a human. It's like starts digging in, boom, get some
S1: results from that lookup and that investigation takes that goes
S1: to the next step and just starts doing multiple steps,
S1: just like a regular SoC analyst, just like a human.
S1: And once it gets done, it puts that all together
S1: and generates a decision ready report. So you could basically
S1: use that. And it's basically exactly as if you had
S1: got that from a SoC analyst. And you can make
S1: a decision based on that. And it's no playbooks, no code,
S1: no prompts required. It just you feed it alerts and
S1: it goes and does investigations and brings back a report.
S1: It's absolutely insane. It's exactly what I've been talking about
S1: as being like how AI is most going to affect security.
S1: And I've been saying for the longest time it's all
S1: going to be agent based. And that's exactly what this is.
S1: And like I said, it's so good. I just became
S1: an advisor and strop sonar AI and you could actually
S1: go and see a demo of it. Working on a
S1: real alert. Panera's week long incident was, in fact, a
S1: ransomware attack. Cece's new High Risk Communities webpage offers a
S1: bunch of guides and volunteer support and discounted tools, thanks
S1: to Defender Fee for sponsoring as well. Israel's military used
S1: an AI named lavender to pinpoint 37,000 potential Hamas targets,
S1: and that's definitely getting people pretty upset about that, because
S1: it's one thing to identify someone and do further investigation.
S1: It's another thing if you're identifying and then like targeting.
S1: And again, I don't know if that's actually happening. I
S1: don't know the degree they're trusting this targeting that's coming
S1: up from lavender. I don't know if they're going directly
S1: to attacks or killing or anything like that. But the
S1: point is it's worth having a conversation about what they're
S1: doing with it. Given the fact that I can be
S1: super fast and super accurate, but it can also have
S1: a lot of flaws, and the more serious you're taking
S1: the results, the more important those flaws are, right? Technology.
S1: There's a rumor that Sam Altman and Johnny IV are
S1: building some sort of handheld device through a new secret company.
S1: Who knows if that's a real or not. It sounds
S1: real to me because we know that Johnny IV is
S1: actually working with them. We know he's a design person.
S1: We know we need these types of devices. So it
S1: makes sense to me. OpenAI released improved ways of doing
S1: fine tuning. Uh, new paper shows that adding more agents
S1: to large language models boosts their performance. How could it not?
S1: How could it not? I mean, like like I've been
S1: telling everyone agents is the way, agents is the way
S1: this is all going to move forward. And then each
S1: individual agent when it gets smarter because the AI models improve,
S1: that just makes the whole thing smarter. But the way
S1: to get ultimately smart and actually pass humans is to
S1: have that combination of agents working together. That system is
S1: what's smart. It's the same as our brain is no
S1: different than our brain. Our brain has a whole bunch
S1: of areas, each individually only do kind of one thing,
S1: and they're not very smart by themselves. The whole thing
S1: that's made it smart over all these millions of years
S1: is the fact that they work together and they're sharing information,
S1: and it's like it's a system. The system is what
S1: makes us smart. And it's going to be no different
S1: with agents. Now, eventually you might have an AI that's
S1: just one agent or one model or one agent or whatever.
S1: And it's so smart. It's just smart by itself because
S1: it's different than a human. But the way we're first
S1: going to get to AGI, mark my words, is going
S1: to be through a system of AI components working together.
S1: And I've got a blog on that somewhere. New paper
S1: explores how I might be leading us towards knowledge collapse
S1: by oversimplifying complex information. I like that, but I don't
S1: think the complex information goes away. Just because somebody is
S1: simplifying or summarizing complex information, it doesn't mean we have
S1: to stop feeding the AI the original raw form. One
S1: doesn't have to supplant the other, and we could just
S1: ask for the long form. We can ask for the
S1: short form. I don't see that as a trade off
S1: us is trying to get South Korea to stop exporting
S1: chipmaking tools to China, US testing, energy storage and heated sand.
S1: This tech is like trippy to me. Energy storage and
S1: heated sand 135MW of power output for five days straight
S1: and Aura's rolling out symptom radar. They're not calling it
S1: illness detection for obvious reasons. I haven't looked to my
S1: app to see if I have that yet. I do
S1: have an aura though. Okay, Amazon is ditching its Cashierless
S1: walkout technology is kind of sad. I guess it's too early,
S1: but they're switching to something a little more normal, like
S1: a hybrid humans. New studies are showing the wealthy are
S1: starting to have more kids than the poor. Again, need
S1: lots of studies to show that's actually true, but interesting trend.
S1: NASA is doing live streaming the eclipse. I watched it,
S1: it was super cool. It was actually moving through multiple
S1: cities and you would see each person, each city as
S1: it was moving. It would go to the full totality
S1: and everyone would freak out. It was quite cool. It
S1: was a very cool stream. TSMC did not take much
S1: damage at all. They were actually only down for like
S1: a day and they went back to start full production.
S1: And it's because their buildings have some really cool stabilization
S1: tech that allows them to not get too messed up
S1: from earthquakes. However, the earthquake was on the other side
S1: of the island, so who knows if it's a bigger
S1: like it was an eight and it was nearby. I'm
S1: not sure the buildings would be able to handle that,
S1: but who knows. Israeli military dismissed two senior officers and
S1: reprimanded three others for an airstrike that mistakenly killed World
S1: Central Kitchen volunteers in Gaza. The UK's exporting workers to
S1: fill higher paying US jobs and US venture capital investments
S1: went down $36.6 billion in 2024. Had a really cool
S1: conversation with Mike private from Return on Security about these
S1: overall economic trends, especially around cybersecurity, and that will go
S1: up soon. McKinsey is offering UK employee UK employees nine
S1: months of pay to voluntarily leave McKinsey. Gen Z is
S1: going for trades like welding and plumbing over college and
S1: student debt, and home insurers are now using aerial images
S1: from satellites to decide who gets dropped from coverage. I
S1: assume that's because maybe somebody's building something in their backyard,
S1: or they have too many cars. Like, I'm not sure
S1: what would be on the policy that they'd be able
S1: to see in a satellite photo, maybe add ons to
S1: the house or something, I don't know. And all right,
S1: got a couple cool ideas here. Another view of imposter syndrome.
S1: So somebody said outwork your imposter syndrome. That was the
S1: post outwork your imposter syndrome. And I'm, like, working harder
S1: isn't the solution. In my opinion, the solution is to
S1: work on bigger problems that are super important to solve.
S1: That way your focus isn't internal, it's actually external. And
S1: I actually go into this, so I'm going to go
S1: ahead and open this up. So I say framed this way,
S1: imposter syndrome is ultimately a problem of thinking too much
S1: internally versus externally. Because you're thinking how do I compare
S1: to them? What do they think of me? Right. And
S1: so the solution I think is to. Focus on. Something
S1: outside of you, right? Stop putting the focus on yourself.
S1: How do I compare? What do they think of me?
S1: That's thinking about yourself. Instead, focus on the problem. And
S1: now you won't really have imposter syndrome because you're thinking about, like,
S1: what am I doing that's useful to help me with
S1: this really big problem, which has nothing to do with me.
S1: It's about me working on that thing. So instead, focus
S1: on the problem and how to fix it. And this
S1: also works for happiness. It doesn't come from focusing on self,
S1: it comes from focusing on other. So that was that
S1: piece there. And this one's really interesting. It's the first
S1: time I've ever seen Tyler Cohen be wrong. It's like
S1: one of the smartest people that I know of on
S1: the planet. And he had Jonathan Height on and Jonathan
S1: High was talking about how bad social media is for
S1: young girls and how I could potentially make that worse
S1: and everything. And Tyler Cohen is like, don't worry about it.
S1: AI is going to solve this because I is going
S1: to summarize everything, and the summarization of of social media
S1: is going to solve this problem and fix it. And
S1: I'm like, how are you not seeing this now? Jonathan
S1: didn't have this point, but I'm going to make this
S1: point right now. That is how Tyler Cohen is going
S1: to use AI, right? It's how I'm using AI right now,
S1: and it's how, you know, Jonathan's probably going to use
S1: it as well. Summarization of content. So you're just getting
S1: the thing. And that might actually take you away from
S1: being caught up in like, oh he said she said
S1: and all the drama or toxicity or whatever. Well that's fine.
S1: And that again, that's how they're going to use it.
S1: That's how a whole bunch of intellectual people who have
S1: made it in life and are older are probably going
S1: to use it, but not for young people consuming viral
S1: and toxic content, because for them, the content itself is
S1: the point, not the summary. And here's my example of this.
S1: Does Tyler think I will send people who love stand
S1: up comedy a summary of the jokes made in a
S1: given standup as a substitute for going to actual comedy shows.
S1: And I've got I've got an I summary here. Here's
S1: your summary of this standup. There were three jokes on
S1: women in stereotypes, four jokes on how clumsy the comedian
S1: is to playful racist jokes. Two hecklers were addressed. Applause
S1: was three out of five compared to other performers. We
S1: hope you've enjoyed this hilarious I summary from comics I.
S1: Does that work for comedy? No, that doesn't work for comedy.
S1: And it won't work for young kids consuming viral or
S1: toxic content unless you have some sort of like draconic like,
S1: I guess, massive control where they weren't actually allowed to
S1: go to the real thing. They couldn't go to TikTok,
S1: they can't go to Instagram, and all they get is
S1: the stupid summary. Nobody would. They they wouldn't even care
S1: about the summary. I mean, that's not even going to
S1: be a thing. Nobody cares. And if it did, they
S1: wouldn't use it. And if they had the option or
S1: if they had both, they wouldn't choose the summaries. They
S1: would not use the summaries at all, and they would
S1: just go to the original thing. Now that being said,
S1: it is Tyler Cohen. So there's a chance that I
S1: didn't understand what he was saying. And also Jonathan definitely
S1: didn't either. So he could be misunderstanding Tyler's point. So
S1: I want to offer him that. There's also the other thing,
S1: which is you might just be right, and I'm just wrong. Now,
S1: I wouldn't normally say that because I think fairly highly
S1: of my thinking capabilities, but it's Tyler Cohen, so I'm
S1: leaving that window a little more open than usual. All right.
S1: Deep faked content summaries. Oh, yeah. This is crazy. So
S1: I don't know. I don't know if I woke up
S1: with this idea. I think the main interface that we're
S1: about to have for content, let's say, okay, I got
S1: buddies who make content. John Hammond makes content. Jason Haddix
S1: makes content. Clint Gibbler makes content. So they're putting out,
S1: let's say they're putting out videos, they're putting out text,
S1: they're doing live talks. They're doing all these different things,
S1: different mediums, different formats. I think what's going to be
S1: happening very soon is let's do the R version, even
S1: though we don't have R yet. The earlier version will
S1: just be little videos on your phone. But let's do
S1: the R version or the R version combined with a
S1: digital assistant, which is AI in your head or in
S1: your mobile device. So it's essentially you say, hey, look,
S1: what is Jason been up to? What is John been
S1: up to? What is Clint been up to? And it
S1: will actually deepfake them okay. Because it knows how much
S1: time I have. Let's say I want a two minute summary.
S1: It will take the long presentation that Jason is going
S1: to do. Jason is getting ready to do an AI
S1: talk called Red purple, blue AI. Let's say it's actually
S1: it is like it's a class. Oh, by the way,
S1: you should go sign up for this class. His class
S1: is called red purple blue I it's going to be
S1: an amazing class. I've heard a lot about it. I'm
S1: going to be in it as well. But for example,
S1: let's say he gives a talk about that a public talk.
S1: The other one's not public. But let's say he gives
S1: a talk about that. Actually he's doing a space con
S1: coming up soon. So that's a good example. Let's say
S1: I don't have the one hour or the two hours
S1: to watch that. I only have two minutes. I'm about
S1: to get on a train where I don't have any connection.
S1: Whatever it's going to make, Jason and Jason is going to.
S1: Teach me what he covered, but he's going to do
S1: it in 30s or he's going to do it in 60s.
S1: It's going to be a deepfake of Jason doing Jason's
S1: own content. Same for John. John Hammond has a thing
S1: about this new piece of malware. Clint has this new
S1: thing about this new tool that he made or that
S1: he saw, and he's talking about deepfakes are going to
S1: allow the actual creator to scale their delivery of their
S1: content as a video to any size chunk that the
S1: consumer wants to see. Give me a ten second summary.
S1: Give me a 32nd summary. Give me a one minute summary,
S1: a two minute summary, a ten minute summary, whatever. But
S1: it will dynamically write the content, which is a summary
S1: of the content, which smashes it down to that size,
S1: and then it will perfectly deepfake that creator and the
S1: mouth will match, the mouth will perfectly match. It'll look
S1: exactly or almost exactly and eventually exactly like the creator. Now,
S1: why would the creator want to do that? Because it's
S1: still their content, okay? It's still their content. It's not
S1: the original raw form, but in a lot of ways
S1: it's going to be better because it's not going to
S1: have ums and ors. It's going to be very crisp
S1: and concise, and most importantly, it won't be some third party, right?
S1: Because my digital assistant can also render it using their face.
S1: But it'll be really cool for the for the actual
S1: creator to be still the one that's delivering it. And
S1: what's cool about that? So here's what's really cool about that.
S1: It'll do multiple languages. So now it's still Clint. It's
S1: still John. It's still Jason. Jason is still saying the
S1: thing to me.
S2: Pedro diciendo la content.
S1: In.
S2: Espanol. Entonces puedo escuchar.
S1: En espanol and I won't know the difference. It'll look
S1: exactly as if Jason is speaking in Spanish instead of English.
S1: And I think that is wonderful. Same with Chinese, same
S1: with every language. Not any more difficult. So now your
S1: deepfake content is going out to every language all at once,
S1: as soon as you drop a piece of content. So
S1: watch this. You drop a piece of content. It's one
S1: hour long. Okay, perfect example. I just released a video.
S1: It's one hour and ten minutes long. I only did
S1: it in English because I'm only capable of doing it
S1: in English. I could do it partially in Spanish, but
S1: it would be kind of crappy. So that one hour
S1: and ten minute piece of content can now be put
S1: in Hindi, Spanish, Mandarin, Cantonese, Filipino, like all these different languages,
S1: but not just converted one for one to the language.
S1: Also converted to a ten second version, a 32nd version,
S1: a one minute version. And it's still me. It's still
S1: my face, it's still my whatever gestures, all this, it's
S1: still me delivering the content. That is a game changer.
S1: An absolute game changer because it's scalable content delivery in
S1: every language, at every bite sized chunk. So now when
S1: I'm on a train or I'm exercising, I could have
S1: my AR interface. I see the person is delivering the
S1: content and it's just like, I'm watching that now. Maybe
S1: there will be some sort of tag that says, there's
S1: this roar, or is this an AI deepfake of it?
S1: But it's not even quite a deepfake. It's using deepfake technology.
S1: But a deepfake is like almost unauthorized. This will be
S1: completely authorized. Um, and of course, there will be versions
S1: of this that are not authorized, and that will be
S1: an actual deepfake. But anyway, you get the idea. This
S1: is going to massively change how we consume content, because
S1: we want that content in different forms, different languages, but
S1: we still want to see the creator doing it. All right.
S1: AI and music. AI is not going to ruin music.
S1: Have we forgot about pop? Pop is, you know, a
S1: few chords and a hook. It's, you know, a lot
S1: of people would say it's low quality music, like low
S1: quality food. But it's the same with doing customer service calls,
S1: sales calls. We forget how low the bar is for
S1: being better than an average human, and that's why I
S1: music is going to be pretty good. And actually I
S1: think I have a link to one here anyway. Discovery
S1: section Luke Stefan's hack Luke put out an amazing blog
S1: talking about his evolution of bug bounty automation. Talks about
S1: going from Bash to Python to Golang, and how he
S1: eventually ended up at Cloud Native. Really great piece, Thomas wrote.
S1: He's super awesome and he wrote a piece about applying
S1: LMS to Threat Intelligence. Really cool. It's got a Jupyter
S1: notebook here for the code as well. SWE agent autonomously
S1: fixes bugs in GitHub repos BR is a Python framework.
S1: Simplifies building an AI apps using building blocks. Open source
S1: textbook makes the art of mathematics accessible. Jim Graham turns
S1: threat modeling into a self-hosted web app. This one is super,
S1: super cool. Chelsea now lets you tweak images so you
S1: can basically have an image that was created with Dall-E
S1: and you could just like rub a like the face
S1: or whatever and say, redo that part and it will
S1: redo it, but integrate it with everything around it. So
S1: that is something that Midjourney had that that Dall-E didn't,
S1: and now Dall-E has it as well. Claude's API now
S1: has a new tools feature that allows you to, like,
S1: browse the web and do all kinds of stuff. I
S1: kind of feel like agent functionality is going to blend
S1: right into the models, so I'm not quite sure how
S1: long we're going to have, like these elaborate agent frameworks,
S1: because that might just be part of using AI. You
S1: might just say exactly what you want to do in
S1: the prompt, and that will actually be the agent framework.
S1: It'll actually spin up how many agents are needed to
S1: do that. And maybe you have some parameters right there
S1: in the prompt that does it. But I kind of
S1: feel like that's going to just blend right into the
S1: language of the of the models themselves. And kids are
S1: learning math from deep fakes. Okay. This is another example
S1: of this learning math from deep fakes of Taylor Swift
S1: and Drake on TikTok. And it's going well. I'm excited
S1: for this. I am super excited for this look. There
S1: are negatives that are going to come from defects. Everyone
S1: knows that. Let's find the positives. The positives are if
S1: people love Taylor Swift, let's learn math. Let's learn calculus
S1: from Taylor Swift. I would do that. All right. Recommendation
S1: of the week. Check out Mozart on the bass. This
S1: is an eye track. Yeah. Go listen this tell me
S1: that this won't be popular. It's a little bit EDM ish.
S1: So if you don't like that, just compare it to
S1: other EDM that you don't like, and you'll see that
S1: I is actually quite good at making stuff you don't like.
S1: All right, aphorism of the week don't explain your philosophy.
S1: Embody it. Don't explain your philosophy, embody it. Epictetus. Unsupervised
S1: learning is produced and edited by Daniel Missler on a
S1: Neumann 87 AI microphone using Hindenburg. Intro and outro. Music
S1: is by zombie with the Y, and to get the
S1: text and links from this episode, sign up for the
S1: newsletter version of the show at Daniel missler.com/newsletter. We'll see
S1: you next time.