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 supervised learning. This is Daniel Missler. All right. In
S1: this one. What have we got here. This is episode 429.
S1: So llama three came out last week and it was
S1: super impressive. I'm getting more and more use out of it, actually.
S1: I'm finding it's doing a lot of stuff as well
S1: as GPT four, and sometimes it just completely fails. And
S1: it's worse than like GPT three. So I think that's
S1: the case with all these different models. Like, you never know,
S1: like how good it's going to be at certain things
S1: and how bad it's going to be at other things.
S1: And what I really hope we get before too long
S1: is like this really robust testing framework. So we know
S1: what things are good at and what they're not good at.
S1: And we could just have this continuous testing because a
S1: lot of the benchmarks that are used to test, you know,
S1: to show the quality of models, I feel like people
S1: are actually building their models to score good on them,
S1: and they're pretty useless. There's also this cool bolt AI application,
S1: which this link is actually bad, I think. I think
S1: this is the wrong thing, but if we do bolt AI,
S1: this should actually pull us up into it. Yeah, this
S1: is the one. So this is a pretty cool interface
S1: for actually dealing with working with LMS. It looks almost
S1: like ChatGPT, but it's a standalone app and you could
S1: use all your different models, right? So you got like
S1: you could use GPT four, you could use local models,
S1: you could put in your own model. This is just
S1: really good. And see here you got different commands AI
S1: and line. Yeah, it's just really powerful. I like this
S1: little lap here. So that's one one nice app to
S1: take a look at. Again it's called bolt AI. That
S1: link I have here, like I said it's not the
S1: correct link but whatever. Let's see here. Yeah llama three
S1: really impressive. At the seven B level there's also an
S1: eight B version which I don't really mess with. I
S1: only messed with the 70 B version. By the way,
S1: the 70 B version actually all the different versions of
S1: llama three are also in fabric, so you can use
S1: fabric with local models of course, and that includes llama three.
S1: And one thing I've noticed is that it's way less restricted.
S1: It actually will tell you a lot of stuff that
S1: llama two would not, and a lot of the other
S1: pinnacle models will not talk to you about at all.
S1: It's not quite uncensored, but it is a lot more
S1: similar to an uncensored, I would say 50% there or something.
S1: And of course, there's already dolphin versions of llama three
S1: that are uncensored. So, um, not just dolphin, but other versions.
S1: So definitely take a look at that if you need that.
S1: And one thing that's really interesting to me is like
S1: how good llama three is getting or local models in general,
S1: because Apple is now releasing open source models. Snowflake just
S1: released an open source model. And here's one thing I
S1: really think is interesting about this. If you think about
S1: the daily tasks that humans go through every day with like, oh,
S1: find me a car, get me a grocery list, give
S1: me a really good workout, play the best song for
S1: right now. You know, get a present for my partner
S1: because it's our anniversary or whatever. All these tasks that
S1: are like everyday things they have, this is a hypothesis,
S1: but they have a limit to how good they need
S1: to be. Right? So if you exceed that limit of like,
S1: they just get the most amazing flowers every single time
S1: they pick the best song or music every single time
S1: and it's really good. Then if that was GPT five
S1: that made it that good, then GPT seven isn't really needed.
S1: And if local models exceed what GPT five could do,
S1: which of course I think they will within a year
S1: or two or whatever, however long that takes. The point
S1: is the models keep getting better, including the local models,
S1: and that a task that a human wants to have
S1: done kind of hits a level of diminishing return. And
S1: I think for a lot of human tasks, we're about
S1: to hit that level with our pinnacle models. And then
S1: you have your local models that are like lagging behind it.
S1: Once that exceeds it, you have local models everywhere that
S1: could do most tasks. So for example, home automation, home management,
S1: automation of tasks around the home. Like I said, groceries,
S1: everyday things, those things can all be done almost instantly,
S1: basically instantly and locally on the device because the local
S1: chipset will be good enough, or there'll be like a
S1: local chipset in the house somewhere that you outsource to
S1: or whatever, but you don't need pinnacle models for those. Now,
S1: it could be that some of those tasks would actually
S1: benefit from a much bigger model, but I think so
S1: many of them actually won't. You won't need them. And
S1: that's really exciting because when local models can. You most
S1: of what we need. That's an insane world. And my
S1: buddy Joseph Thacker keeps talking about this thing. It's like,
S1: why not just have it in everything? And he keeps
S1: talking about this cool idea, which I want to touch
S1: on too, which is this concept of an oracle, which
S1: I've always wondered about too. It's like if you went
S1: back in time, how useful would you actually be? Could
S1: you actually describe, you know, chemistry or, you know, satellites
S1: or combustion engines or any of this stuff? It'd be
S1: amazing to have like a little soccer ball that talks
S1: to you. And inside of the soccer ball is this model,
S1: and you could somehow get power into it or whatever.
S1: But this one little thing, this tiny little device has
S1: something like Lama three on it, which is a large
S1: percentage of all human knowledge ever. And it's local, doesn't
S1: need to call out to any cloud. And you can
S1: put that in a soccer ball or a park bench
S1: or anything like that. It's insane to me that you
S1: could basically bootstrap humanity to some degree with something that's
S1: completely local on a chip. All right, more stuff going
S1: on prepping for RSA. Definitely come by and say hi.
S1: I might be crazy busy or distracted or socially awkward
S1: at the time. Whatever. Just come say hi. What have
S1: we got here? We got hugs, waves, finger guns, always appropriate.
S1: Fist bumps, whatever. Whatever you got I should be comfortable with.
S1: Last few talks have gone really well. There's something to
S1: be said for speaking, to share an idea rather than
S1: trying to, like, do a presentation. I've crossed over for
S1: most of my talks. At least I'm trying to cross
S1: over completely to this thing where I'm just I have
S1: this idea that I want to share, and the goal
S1: of the talk has nothing to do with the talk
S1: or the slides. It has to do with how many
S1: people actually get converted over to this way of thinking
S1: at the end. And when you are trying to do that,
S1: it makes the slides not matter. It makes like if
S1: whether you stumble, your words not matter. Nervousness kind of
S1: goes away. And I've got a couple of talks already
S1: or essays about how to make that happen. Anyway, there's
S1: a breathing technique for like the tactical version, and then
S1: there's like this concept for getting rid of the overall
S1: problem of stage fright. If you simply have something to
S1: share and you are sharing it, that is not a
S1: stage fright issue. It's very strange. It's like, what are
S1: you actually looking at? If you go up on stage
S1: and you are thinking about your talk in terms of
S1: like the slides, the slide notes, where are the cameras,
S1: where's the monitor, where are the people, who are they
S1: looking at? If you pull into yourself like that, you're
S1: going to get stressed. You're going to get nervous. The
S1: way to fix that is to go outside of yourself.
S1: What's bigger than yourself? What? What is outside of yourself?
S1: The idea is the thing that matters. You focus on
S1: that and suddenly you're very calm because what you want
S1: to do is you want to convert your excitement away
S1: from anxiousness and into excitement around sharing the idea. And
S1: you could view this as a hack, or you could
S1: view it as just a better way of thinking about presenting. Period.
S1: And I think it is both, but I frame it
S1: as the second one. Updated the intro to the newsletter
S1: focusing on human to 2.0 transitioning to 3.0. Let me
S1: know what you think of that. I put discovery actually
S1: into each section instead of having a dedicated discovery this time.
S1: And if you have time, you've got to go listen
S1: to this conversation between Tyler Cohen and Peter Thiel. I'm
S1: not a Peter Thiel fan in general. I didn't like
S1: a lot of his political views. While back they had
S1: this wide ranging conversation from like Star Wars to the
S1: Antichrist to the Bible to Shakespeare to economics, political theory,
S1: just theology. It was an insane conversation. What I like
S1: most about it, because I've shown a few people and
S1: they were like, yeah, I don't know why you liked
S1: it so much. And a few people said, look, they
S1: just talked about a whole bunch of stuff that I
S1: didn't understand. Here's my trick for you, and this is
S1: why I was so excited about this talk. I don't
S1: often find anyone lately because I read so much who
S1: says a string of words and actually just a string
S1: of answers to questions. And in those answers I'm like,
S1: what does that mean? Like Strachan, for example, Strachan was
S1: Stross was one of the people that he was talking
S1: about in this thing. And I'm like, I don't know
S1: Stross yet, I don't what does that mean? So I
S1: ended up having to go in Google and look up
S1: all these different things. Google more like talk to my
S1: Da and have her explain the stuff to me. And
S1: then I also put a set of books into audible
S1: as well. So now I'm going to go read these
S1: canonical books that came from these thinkers. So I don't
S1: accept when somebody talks over my head because I essentially say, well,
S1: you can only do that once because. Now I'm going
S1: to research all that stuff. And first of all, figure
S1: out what you were actually saying just so it doesn't
S1: appear smart when it's actually not smart. But what I
S1: came away with after deciphering all the stuff and learning
S1: like a quick primer on this stuff, is I came
S1: away realizing that Peter Thiel knows a lot of stuff
S1: and what I'm really attracted to. And I don't know
S1: if this is something where he changed or where I changed,
S1: or maybe both or something, but he doesn't seem bound
S1: to any sort of side. He seems bound to principles
S1: of like what he wants to see happen. And I
S1: think that is really powerful. And I talked about that.
S1: I think in a previous show. I can't remember where
S1: I talked about that recently, but I think it's really oh,
S1: it's actually in this newsletter actually. So I would say
S1: definitely check this out no matter what. Check it out.
S1: You might not like it, but listen to what I
S1: was saying before and see if that helps you like
S1: it more. All right, so I wrote a new essay
S1: on the old paradigm of planning a career no longer working,
S1: and basically saying you should plan your career around problems instead.
S1: And I actually have released a standalone video on this
S1: as well, which is also going to come out as
S1: a podcast, so you can check that out on YouTube.
S1: It should already be live. All right. Security, the House
S1: just passed a bill making it illegal for the government
S1: to buy your data without a warrant. Calling it the
S1: Fourth amendment is not for sale. This is really cool.
S1: That's bipartisan. It seems like it would. It would have
S1: had to have been. Not sure about that, but I'm
S1: pretty sure that's right. Sandworm. Notorious Russian hacking group linked
S1: to cyber attack on a water facility in Texas. The
S1: ban on TikTok looks like it's actually going forward. That
S1: is pretty cool. Biden signed it. So that's bipartisan as well.
S1: A little bit of light in the darkness there might
S1: have got compromised among a bunch of other companies by
S1: another China based attacker, and a flaw and putty lets
S1: people look at a whole bunch of different keys or
S1: cryptographic signatures. Basically figure out your private keys, which is
S1: no bueno. FBI Director Christopher Wray says that China is
S1: basically shifting to figuring out how to attack US critical infrastructure,
S1: possibly to go in concert with a move in 2027.
S1: So it would be like, you know, do these cyber
S1: or infrastructure things at the same time to kind of
S1: keep the enemy off balance? Marlinspike moxie basically says he's
S1: no longer affiliated with signal. I've not been a huge
S1: fan of signal. I don't like the fact that you
S1: need to restart it every 45 minutes. I don't like
S1: being outside of Apple Messages. I prefer to have as
S1: few messaging apps as possible because I'm on Apple. That
S1: tends to be my favorite. Not a fan of WhatsApp,
S1: not a fan of telegram, so I tend to just
S1: prefer messages. I was okay with signal a little bit
S1: because it was moxie, but now moxie is out. I'm
S1: going to try to get people to talk to me
S1: on messages again. Sacramento International Airport had to stop flights
S1: because somebody deliberately cut the AT&T internet cable that provided
S1: internet to the airport. Tale scale now has SSH. DeepMind's
S1: boss says Google is going to outspend everyone in AI.
S1: You know, it's not about outspending guys. You've been able
S1: to outspend and have been outspending people for a long time.
S1: It's you've lost the ability to ship good products because
S1: you don't have vision as your primary guide. You have
S1: basically engineers making stuff and throw them at the walls.
S1: And then like three years later, if it launches, you
S1: put it in the graveyard. It's just complete joke. I
S1: think you need new leadership, honestly, is what you need.
S1: And Stanford released a quality report on AI models and
S1: we did a micro summary from fabric. So basically I
S1: surpasses humans in specific tasks, not in complex reasoning. I
S1: think that'll probably change soon. US is ahead of model development.
S1: And yeah, pretty good breakdown here. Interesting argument about how
S1: search engines, especially Google, can actually move elections. Google fired
S1: 28 employees for protesting and they actually fired some more
S1: people as well recently. More recently, Google has merged its
S1: Android and hardware teams. Netflix is using FreeBSD current for
S1: its edge network. That is surprising to me. I would
S1: have thought those packages would be old, not well maintained,
S1: and definitely behind. Yeah, so that's surprising in a good way.
S1: Reddit showing up a lot more in Google results. They
S1: actually have some sort of contract together. I think they
S1: sent Reddit like $30 million or something. So something around there.
S1: Apple's Airplay is starting to come to hotel rooms. Hopefully
S1: Marriott's soon tiny S.A. is a budget. Friendly spectrum analyzer
S1: programming is mostly thinking this it is. This was a
S1: good essay, I enjoyed it. Broad introduction to AWS log
S1: sources and events and Gen Z is outperforming previous generations
S1: at their age. This was also surprising to me. This
S1: article says that societal decline mirrors the death spiral seen
S1: in ants. Why everything is becoming a game. This blog
S1: by the way. Really cool. I love this blog. Gurinder. Yeah,
S1: this guy is awesome. Definitely want to subscribe. Their study
S1: found that jobs that require you to think a lot
S1: or protective against Alzheimer's. I think that needs an H.
S1: Bayer is doing an experiment where they remove most of
S1: middle management and let basically like 100,000 employees mostly self-organize.
S1: And they're hoping to save. I think that was 12 billion,
S1: not 2 billion. That might be a typo. Unfortunate. I
S1: think it was $12 billion. I think this is really cool.
S1: I love the idea of 100,000 people with all these
S1: layers of middle management, where it's just a giant waste machine.
S1: And who better to figure that out then? AI who
S1: figures out, okay, who's doing what, what functions actually need
S1: to get done? What who whose teams are structured in
S1: what way? How do they communicate with each other? What
S1: are the work products that are actually being produced? What
S1: are those pipelines look like for work being produced? You
S1: overlay that on the org structure, and you look at
S1: the budget and everything, and you look at the outcomes
S1: and actually how fast things move. And AI is going
S1: to look at it and just be like a horrible mess.
S1: Why do you have all these managers? What are they
S1: actually doing now? Humans have already known that we didn't
S1: need all those layers of middle management like this. It's
S1: so common. It's just a meme. It's common knowledge. But
S1: AI is going to be able to look at it
S1: for any given company and just be like, here's why
S1: this is a giant waste. You know, Chris isn't doing
S1: anything right. And he hands it to John, who's not
S1: doing anything either. And what is Mary doing? Like this
S1: makes no sense whatsoever. And it's going to recommend look,
S1: you need your experts and you're going to need you
S1: need your high level thinkers and you need very little
S1: middle management, which really is probably going to be AI
S1: agents very soon. And of course, at some point you
S1: can even use AI for the top and bottom pieces
S1: as well. But first they're going to come for those
S1: middle managers. And I think it's a good thing the
S1: term brainwashing morphed into a blanket term for unconventional behavior.
S1: And this came from MKUltra seeing a lot of stuff
S1: talking about MKUltra. I wonder what the reason for that is. Okay,
S1: ideas and analysis. All right. I like I said, I
S1: talked about Peter Thiel. I'm not going to read this
S1: whole thing. This is a bit of an essay here.
S1: I think I might turn this into a standalone essay. Okay.
S1: Let's see here. Okay. Recommendation of the week. Establish your
S1: ground truth in terms of morality and the society that
S1: you want to live in. And this is going to
S1: the essay above. Okay. Establish your ground truth in terms
S1: of morality and the society that you want to live in.
S1: Lock that in perfectly. You say, look, this is how
S1: I think the world should work and that is your morality, okay?
S1: And it's got no labels on it. Left, right, progressive, conservative.
S1: Nobody cares. You don't put anything on that. You just say,
S1: here's how I think the world should work. Then you say, okay,
S1: I'm going to listen to any ideas, right? I'm curious
S1: how those ideas or those structures or those religions or whatever.
S1: How would those affect this world that I want to
S1: see come to pass? And then you don't discard ideas
S1: just because you disagree with something else that they say
S1: somewhere else. So if people have like this idea, a
S1: constellation or belief constellation, you are free to pick and
S1: choose for where they they are smart in your mind,
S1: at least where they're smart about things, where they're dumb
S1: about things. I get so many comments where people are like, hey, listen,
S1: I absolutely love your stuff. I don't agree with everything,
S1: but I agree with you on most things, and I
S1: kind of feel like I'm happy when I hear that
S1: because I feel like they're parsing everything. They're deciding because
S1: they've already done number one. They've decided what they believe.
S1: And I've had other people also say that over time
S1: they came to believe something that I also believed, which
S1: is cool. And sometimes I'll switch and, you know, believe
S1: what they believe. The point is, you don't have to
S1: accept everything a person says to pull wisdom out of
S1: what they say, right? Maybe they're only good at making
S1: the best, you know, Reuben sandwiches. And maybe that's all
S1: I get from them, because the person's name is Tucker
S1: Carlson and they don't know anything other than sandwiches. That's fine,
S1: I will listen. I probably won't spend time like trying
S1: to seek out that content, but it doesn't matter. That's
S1: the point of this. Feel free to label people as
S1: bad overall or stupid, but realize it doesn't mean they're
S1: wrong about everything. So again, same concept. Be willing to
S1: take truth from anywhere. And basically you want to regularly
S1: revisit your number one, which. Is your basis of how
S1: you think the world should work and then regularly re-evaluate, right?
S1: Pull in lots of different opinions and see if it changes.
S1: Number one and the aphorism of the week, best way
S1: to have good ideas is to have lots of ideas.
S1: The best way to have good ideas is to have
S1: lots of ideas. Linus Pauling. Unsupervised Learning is produced and
S1: edited by Daniel Missler on a Neumann 87 AI microphone
S1: using Hindenburg. Intro and outro music is by zombie with
S1: a Y, and to get the text and links from
S1: this episode, sign up for the newsletter version of the
S1: show at Daniel Missler. Com slash newsletter. We'll see you
S1: next time.