S1: Unsupervised Learning is a podcast about trends and ideas in cybersecurity,
S1: national security, AI, technology and society, and how best to
S1: upgrade ourselves to be ready for what's coming. All right,
S1: in this video, I'm going to talk about the AI
S1: ecosystem that I think everyone is actually building and moving
S1: towards without even realizing that they're doing so. And I'm
S1: going to break it down into four pieces, which are
S1: assistance APIs, agents, and augmented reality. And I think once
S1: you see this model, you're going to realize that the
S1: news coming in from OpenAI and anthropic and all these
S1: different companies, it's all moving in this direction toward this model.
S1: And I think it's going to be really helpful for
S1: you to just have that mental model of it. So
S1: let's jump into it. So I actually broke this down
S1: into a much longer explanation that you could see above, uh,
S1: back in December of 2023. And I wrote a kind
S1: of a little bit of a crappy book about it
S1: in 2016. I really just wanted to capture the ideas,
S1: which it was decent at doing that. It was called
S1: The Real Internet of Things. You could put a link
S1: to that in there. Don't really need to read the book.
S1: This is actually much better. But, um, this stuff is
S1: actually starting to happen now. And what I want to
S1: do today is take the concepts from the book and
S1: from that video above, and show how they're actually falling
S1: into this model and how it's actually starting to happen today,
S1: which we could see throughout the news from all these
S1: different companies. So the first a here is assistant or
S1: what I call a digital assistant. So a million different
S1: companies are actually building this piece in various ways. Some
S1: companies are building like digital companions or like smart assistants
S1: or personal agents. But to me like this is all
S1: actually kind of the same thing. It is basically a
S1: piece of tech that is the most intimate to you
S1: because it knows everything about you your preferences, your calendar,
S1: your contacts like health information. Your finances is going to
S1: be our best advocate, our best tutor, right? It's a
S1: filter against like incoming stuff that you don't want to see.
S1: And hopefully that filter and those filters are actually assigned
S1: by you and not by someone else. But, um, yeah,
S1: filtering out messages and emails and stuff you don't want.
S1: It's basically figuring out exactly what you want and figuring
S1: out how to make that happen all the time. Now,
S1: if you're insecurity like me, you're probably thinking, well, that's crazy.
S1: All this stuff on the screen here, like, knows everything
S1: about you. History, trauma preferences, remembers everything, has multiple agents.
S1: Like nobody's going to actually put that information into their Da.
S1: But I think we already know that's not true. We
S1: already know that people are doing this. That's why these
S1: digital companion companies are doing so well already. This is
S1: functionality that is just so powerful. Like it's just going
S1: to happen, right? And this is kind of the centerpiece
S1: of this whole model that I'm going to break down.
S1: This is the first one. This is the assistant. So
S1: let's call RDA Kai hours is going to be called
S1: Kai okay. So the second A is APIs. So your
S1: Da isn't that useful if it can't do stuff for
S1: you right. So the way it'll do stuff is through APIs. Uh,
S1: I didn't say in 2016 which of like the Da
S1: or the APIs was going to come first because I
S1: didn't know. And I still really kind of don't know,
S1: but it seems like they're kind of happening at the
S1: same time. Basically, your Da Chi is over here being
S1: an agent for you, right? It's being like your advocate,
S1: like we already talked about. It's it is an agent.
S1: It has agents working for it. But ultimately it's like
S1: one personality with a collection of agents behind it. It's
S1: effectively kind of like one entity or one person, which
S1: is why we give it a name. You know, we're
S1: treating it like a person, like like a friend, right?
S1: So ultimately it's encapsulated in one personality, in one sort
S1: of entity. So Chi is constantly looking at your state
S1: and trying to figure out how to make it better.
S1: That's the core concept for the Da. That's what it's doing.
S1: Are you hungry? Are you angry? Are you stressed out?
S1: Do you have a meeting coming up? Right. That it
S1: needs to help you prepare for. And all of this
S1: is proactive. You haven't even asked it. Anything else yet.
S1: So basically, these are going to do something I talked
S1: about a couple of weeks ago, which is managing your
S1: current state relative to your ideal state or your desired state. Right.
S1: How could this current situation that I am in that
S1: Chi is monitoring? How could that be better? So if
S1: you're hungry, Chi will go find food. If if you're
S1: worried they're going to find camera feeds to like see
S1: around corners, like if you're worried about your security or
S1: you're walking around or something. Or they'll listen to scanners
S1: and see if there's, like police activity nearby. Or look
S1: at crime stats for like the, the neighborhood that you're
S1: in or whatever. Never. And that's actually what all these
S1: APIs are over here that you see, right. These are
S1: all the different things that Cai that your Da will
S1: have access to. So APIs are essentially the representations of
S1: people and companies and services. Basically everything becomes an API.
S1: And we're already seeing this as we're going to talk
S1: about we're already seeing this with MCC. This is actually
S1: starting to happen. So so what I said in 2016
S1: was basically everything gets an API. Every person objects, businesses
S1: most importantly people and businesses, but also other objects. That's
S1: why I called it the real Internet of Things. Basically,
S1: everything gets an API and you have your Da navigating
S1: those APIs for you on your behalf, right? So all
S1: these APIs you see here, uh, except for there's going
S1: to be millions of them, right? Eventually billions. But you
S1: start off with thousands and then millions or whatever, but
S1: every company will be an API. Every product will be
S1: an API. People will be broadcasting APIs of ourselves, which
S1: which I call demons is just a Greek word for
S1: like soul, basically. And think of this like your own
S1: personal like MCP server. And these are not designed to
S1: be used by you or me. We can't read all
S1: these APIs. You need help reading all these APIs. You
S1: can't walk into a mall or walk into a city,
S1: or walk down a road or whatever, and read all
S1: the cars and the trees and all the people and
S1: all the businesses. You can't do that. That's why you
S1: need your Da to do that for you. Right. So
S1: all these systems, all these APIs here and the agents
S1: that sort of represent them, they're all designed to be
S1: used by your Da, right? That's their purpose. So it's
S1: like the interface to the world, like changes. It's no
S1: longer about what we see with our eyes, like Google
S1: like old Google now. It's about what do agents see?
S1: What do DAC write? That's the world that starts to
S1: matter a lot more. And a big part of this
S1: is going to be a bunch of APIs that are
S1: actually just concatenations or lists or directories of other APIs,
S1: because one of the things that Midia has to do
S1: is it has to ask, hey, what's the best restaurant
S1: or whatever? And I've got a few here, right? Best food. Um, yeah.
S1: Lookups or whatever. These are all just be, you know,
S1: third party services that do nothing but crawl all the
S1: other ones and rate them so that when Kai reaches
S1: out and says, hey, I need to find the best food,
S1: you know, within like three minutes, uh, close to this location,
S1: but it can't have chicken in it or whatever. All
S1: those different criterias, it can find the right one, right?
S1: So there'll be a whole bunch of like lookup service
S1: type of things like that. Okay. So that takes us
S1: right into the third one which is agent. So we've
S1: got a few agents here. And the way I like
S1: to define an agent, there's lots of different definitions. I
S1: think the agent should be super obvious, like from the definition,
S1: like what it actually means and why it has value.
S1: So I say it's an AI system component that autonomously
S1: pursues a goal by taking multiple steps that previously would
S1: have required a human. I think that is a really
S1: good definition. Um, it's autonomous and it's taking a goal,
S1: and it's pursuing that with multiple steps in a way
S1: that only humans could do before. The part that makes
S1: an agent different than automation, this is really important. This
S1: is why I have it in the definition. The part
S1: that makes it different is the fact that when a
S1: human is trying to get something done, like say you're
S1: an assistant for your boss or whatever, and you're trying
S1: to get something done, like you call the first place.
S1: They don't answer the phone, you call the first place.
S1: The phone number doesn't work. Life is just broken, right? Like,
S1: all these different steps are broken. Now, if you have automation,
S1: automation is static, right? It's a whole bunch of if thens.
S1: Agents aren't. If then they are. I have all these
S1: tools available. I'm going to keep going. I'm going to keep,
S1: you know, exhausting my resources, trying different things to try
S1: to get it done right. I will, you know, maybe,
S1: maybe none of the things work. So I'm going to
S1: do more research to find another, uh, API that I
S1: could use or another service to find this person. Pizza.
S1: Sarah wants pizza. I'm going to get Sarah pizza, and
S1: she's going to do you know, the Da is going
S1: to do multiple things to make sure that she gets
S1: that pizza. That's the difference between automation and agent. So
S1: that's our definition here. And we see that our Da
S1: actually has the use of multiple agents. These agents might
S1: be like researchers. They might be like security bots uh,
S1: to lock down your infrastructure. That could be whatever. But
S1: they all kind of work for Kai, right? Kai is, like,
S1: the centerpiece here. And this is going to be a
S1: theme we're going to see throughout. Agents all over the place,
S1: including inside of companies like we have over here with like,
S1: United or whatever. It's the concept of you're talking to
S1: one agent, but behind it, it has a whole bunch
S1: of other agents. So you give it the goal and
S1: it breaks that down into sub goals and gives that
S1: to the smaller agents, which are then doing the other
S1: things like building a marketing campaign, uh, hacking a website,
S1: doing whatever it is. Right. So that's really the concept
S1: of agents. And Google actually just released a thing called
S1: agent to agent, I think was the name of it.
S1: And what it does is it makes it so that
S1: all these different agents here, they could talk to each
S1: other with a common protocol, which is very similar to MCP,
S1: where it's a common protocol for creating APIs for an
S1: application or, you know, a company or whatever. So we're
S1: starting to see the glue, the protocol glue that's going
S1: to make all this stuff possible with this agent agent
S1: protocol in MCP and stuff like that. So the final
S1: piece here, so we've got we've got the Da, we've
S1: got the assistant, we've got the APIs, we've got the agents.
S1: So the final piece or the final A here in
S1: the four A's is AR or augmented reality. And this
S1: is the one you might be thinking is fringe or
S1: it's like ten years away, but it's actually much closer.
S1: Meta and Apple are currently fighting over this now. Tim
S1: Cook just recently said, look, I'm not going to let
S1: anyone beat us here. They want to beat meta at
S1: this game. Meta already has really good glasses. Um, they're
S1: not actually displaying anything inside of it, but you can
S1: see out of it that takes pictures like it's pretty decent.
S1: And obviously it's not big and heavy and super expensive
S1: like the Vision Pro. So that is a battle that
S1: is happening right now. So we are all eventually I
S1: don't know how long this is going to take. It's
S1: hard to make like specific predictions. Right. So 2 to
S1: 5 years, who knows. It's going to be something relatively soon.
S1: Meta or Apple or maybe someone comes out of the
S1: dark and just kind of crushes this. Who knows? But
S1: the point is, we're all going to have these AR
S1: glasses eventually, like contact lenses or something better than that.
S1: But it's going to start off with glasses. And here's
S1: the trick. This is how the whole ecosystem starts to
S1: come together. Our Das are going to be showing us
S1: stuff that is time based, and that is contextually relevant
S1: to whatever we're doing at that moment. Remember, our Da
S1: is trying to optimize everything according to our goals. It's
S1: trying to get to our desired state from our current state.
S1: So if we're walking down a street like this here,
S1: we're walking down a street and like we think it's
S1: kind of dangerous. Yeah, it's going to present this interface here,
S1: which I've got over here coming from this, this demon
S1: called bastion, which is really it's just a company. It's
S1: a company. It's called bastion. And they have feeds called
S1: get feed, poll cameras, poll microphones, query personal mics, get
S1: local CCTV. Right. So maybe it could pull all the different, um,
S1: people who are broadcasting their feed because people are going
S1: to be wearing cameras as well. This is coming soon. Uh, basically.
S1: Camera ahead of you. Camera behind. Behind you. And maybe
S1: you sell your camera feed to Bastian. People will do this.
S1: Trust me. It's going to happen. People are going to
S1: sell their camera feeds to Bastian. Right. It's not going
S1: to be for private stuff. Like it's going to get
S1: turned off when you go home. Stuff like that. You
S1: shouldn't trust that. You should also like cover the camera
S1: or whatever. But the point is, if you're sitting in
S1: Starbucks or whatever and say a fight altercation happens or
S1: something like that, Bastian will be able to show that
S1: to the police or show that to somebody else who's
S1: worried about it. So my Da, while I'm walking down
S1: the street, right? I'm walking down the street here, it's like, oh,
S1: I this neighborhood feels unsafe. That's what I'm saying. I'm
S1: saying this neighborhood feels unsafe or it hears me say
S1: something in a conversation where I'm just like, I don't know,
S1: it's kind of sketchy. I'm a little worried, right? I
S1: say anything like that or even before I say it,
S1: the da Chi goes out and looks at one of
S1: these services to find the best security interface, the best
S1: one for parsing feeds, uh, giving, you know, real time
S1: HUD data and stuff like that. So it gets one back.
S1: It's called bastion. So it starts pulling stuff like that,
S1: it gets back the content. It then goes to another interface,
S1: which is a whole separate company, which is the UI
S1: for this content. Okay. You see these red. This is
S1: a great example. But like let's say there's data here right.
S1: Let's say there's like, oh, how many people are around. Um,
S1: is anyone wearing a weapon. Let's do like gait analysis
S1: to see if they're leaning because they're carrying a gun
S1: or something like that. Right. All this stuff, all these
S1: different individual pieces, different companies are better at, okay, somebody
S1: is better at making this red, cool looking interface. Somebody
S1: is better at doing voice analysis of microphones coming from
S1: all around you. Somebody is better at doing camera analysis of, like,
S1: all the different dangers on the street. All of those
S1: are these right here. This is what every company becomes.
S1: It becomes a specialized thing at doing a thing better
S1: than everyone else, all judged by these indexing services, these
S1: rating services which are marketing to your Da. It is
S1: marketing to Chi. So when I'm walking down the street
S1: and I say, hey, show me what's going on around
S1: me or something like that, or I don't even have
S1: to say it. It just knows I'm freaking out. Why?
S1: Because Chi can see my heart rate. Chi can see
S1: that we're in a place I've never been. Um, somebody
S1: is laying on the street with, like, a needle sticking
S1: out of their arm. Chi figures out this is kind
S1: of seedy. It's a little bit dangerous. I don't like it.
S1: And obviously, my principal Daniel, doesn't like it either. Therefore,
S1: broom goes and searches, finds Bastian, finds a UI. The
S1: best UI. Okay, the best UI is called UI Wizard.
S1: Not too creative, but whatever it's called UI Wizard. UI
S1: Wizard pops up. That's this red interface, and it starts
S1: filling in data where the data come from. From Bastian,
S1: it came from the Bastian service. Where does that go?
S1: This interface is in these glasses, which is on my face.
S1: So now watch this. We've got other scenarios here. Okay?
S1: You start browsing for headphones. Your Da does this. It
S1: uses these services and it gives you back a response.
S1: So I'm looking for headphones. It goes and investigates all
S1: these different things. You mentioned your friend that you're getting hungry.
S1: It goes and looks researches all these different best food places,
S1: parses all 713 different places in like a second and
S1: a half. Gets back the results. Hey, you haven't had
S1: Thai in a while. There's a great little place with
S1: super high ratings if you take a right into blocks.
S1: I can call you in an order if you want. Right.
S1: This is the model. These four A's. This is the model.
S1: This is where this is all heading. This is the direction, right?
S1: So I'm telling you. I'm telling you this. This is
S1: what's happening. It is absolutely exciting to see this starting
S1: to unfold. Right. There's a million different companies working on
S1: this part. There's multiple companies working on the AR glasses part.
S1: Everything is turning into an API already. This is MCP
S1: over here. This is the unification of it. And then
S1: of course, over here we have what's happening on the
S1: corporate side where agents are basically going to be doing
S1: a whole bunch of work. You'll have a humans kind
S1: of in charge of things. The leaders and the in
S1: the extreme, SMEs will be human for quite some time,
S1: I think. I mean, it's going to be pretty hard
S1: to automate everyone away, but a lot of the work
S1: that was getting done is going to be getting done
S1: by agents and teams of agents. So that's agents inside
S1: the corporate place. But as far as the consumer side,
S1: as far as the stuff that you're seeing, like in the,
S1: you know, the OpenAI and anthropic and most of the
S1: stuff that they're talking about is mostly about the consumer
S1: and stuff like that. This is it. This is the structure. Okay.
S1: So another example of this is like let's say you're
S1: in like a live conversation and you're having a conversation
S1: with somebody and it's like somebody you've never met before
S1: and you're considering whether to go into business with them
S1: or whatever, and they're making a whole bunch of claims.
S1: They're like, oh, yeah, I used to work with so-and-so
S1: and blah blah, blah. And actually I helped him start
S1: his business and, uh, yeah. Do you know Sarah? Yeah. Sarah.
S1: You know, I went to college with her and blah, blah, blah.
S1: So again, you're wearing glasses. Everyone's wearing glasses. The person
S1: you're talking talking to is actually wearing these glasses as well,
S1: and you're having this conversation. But in the whole time
S1: you're wondering like, is this actually true? Is all the
S1: stuff that this person claimed happened or the people that
S1: they claim they know or whatever? Is this all true? Right.
S1: So what will happen is you'll have like something going
S1: off to voice analysis. This depends how many things you're
S1: subscribed to. It depends how far along we are in
S1: this cycle. You know what all your Da can actually do.
S1: But this is this is all sort of being built
S1: right now. So like, if there's tension in their voice, like, uh,
S1: analyzing the claims that they're making, doing research on it,
S1: did they actually go to college? Did did Sarah and
S1: this person actually were they in college at the same time?
S1: That should be on LinkedIn. Let's go find that out.
S1: So if you're waiting on a delivery and this goes
S1: back to the R side, if you're waiting on the
S1: delivery you will see a timer timing down right. Just
S1: like you have on on your phone. Now that will
S1: be in your interface so you don't have to pick
S1: up a phone. The whole point is with AR glasses
S1: is to have to do much less with an actual
S1: physical device that you pick up and have to interact with.
S1: It'll be a lot more. It's visual here, and you're
S1: just talking to your Da, and your Da is doing
S1: most of the work yourself using all these different services, right.
S1: So where is the data coming from? Right. How is
S1: it being displayed in the glasses. That's exactly what we
S1: talked about earlier. The data is coming from these services
S1: moving through a UI being displayed in the glasses. Right.
S1: So in the case of like trying to determine if
S1: someone is lying, right. Let's say there's like a lie
S1: o meter interface inside of this little UI here inside
S1: your AR. Well, somebody is providing that lie o meter interface, right?
S1: There is some one of these companies is actually the
S1: voice analysis, uh, providing back data. And that's just like
S1: Jason coming back. That is like, um, saying, like the
S1: chances of them being lying about this particular thing, like,
S1: according to voice analysis or like, according to the research
S1: that was done. Right. All these things can be combined together.
S1: Like that stuff could actually just be returned. Roar back
S1: to Chi, and Chi could look at all that and
S1: send another feed into the UI to update that Leo meter, right?
S1: There's so many options here because because these are APIs,
S1: this is just JSON or whatever. The protocol is going
S1: to be flowing back and forth, right? That's the power
S1: of this entire thing. So let's zoom out again and
S1: let's just take a look at this entire thing. Okay.
S1: Again just as a review here. Look at the four A's.
S1: Chi knows what you want at all times. Constantly calling APIs,
S1: making requests, summarizing things, creating reports for you, researching the
S1: best options, anticipating your needs throughout the day and week
S1: and month or year or whatever. Adjusting your ah, interface.
S1: Constantly switching. Look, you're in the house. You maybe you
S1: see your books. Maybe you see how hungry everyone is.
S1: Like this. This interface is constantly changing. Chi is changing
S1: it for you using these different APIs. Right. And the
S1: interface that Chi is using will be coming from multiple
S1: companies as well. Maybe, maybe Chi's generic interface actually gets
S1: good enough. Maybe one of these companies is a generic
S1: interface creator, so you don't actually have to use individual ones. Right.
S1: And Kyle just switched using that one. So when you're
S1: looking at books you're inside of a library. It's a
S1: different HUD. You know, walking down the street it's a
S1: different HUD talking to someone different HUD. Right. So if
S1: you take a step back and you look at this
S1: interface here, right, think of all the news that you've
S1: heard from the last few years in. I think about
S1: the latest news from OpenAI. They just added like long
S1: term memory, where it's going to remember all your previous conversations. Right. Um,
S1: think about digital companion companies, uh, digital helper apps that
S1: will like go and do tasks for you. Siri and
S1: Gemini on the mobile device. And of course, you all
S1: heard the stuff about Siri. Right? Where they're trying to
S1: make this thing a better assistant. They're trying to give
S1: it access to more and more data about you. Right.
S1: And they're trying to do it in a secure way, obviously.
S1: And Gemini is competing in that space as well. Samsung
S1: has their own version. Right. This is all like heading
S1: in that direction of like the Da. All of them
S1: are heading in this direction of the unified right. That's
S1: the easiest way to see this. So now think about
S1: all the news around MCP and APIs and how they'll
S1: be able to talk to each other with the agent
S1: agent protocol and all of those different things. Basically, that's
S1: what we're talking about with everything that's an API. And
S1: you already hear all the talk about agents. That's all
S1: everyone talks about now. And then you think about the
S1: news about Meta and Apple fighting about AR glasses. And
S1: that's this piece over here. Right. So everyone is moving
S1: towards these four A's. This is it. This is the
S1: ecosystem that we're creating. It's absolutely insane. And it's starting
S1: to fill in. And like again, now that you've seen it,
S1: I think you're going to realize that all the new
S1: news is just filling in pieces of this and eventually
S1: getting us to this. And it's very sort of cyberpunk
S1: y and very future oriented. But so many of these
S1: pieces are already exist, like this is just HTTP going
S1: back and forth like these protocols are not too difficult.
S1: The only difficult part right now is just like the
S1: hardware challenge of like the AR stuff is really difficult,
S1: and that's probably the thing that's going to take the longest.
S1: But agents are getting better. Like the AI itself is
S1: getting smarter and smarter. Like context size is a huge
S1: one and memory is a huge one that is dramatically
S1: getting better. Like for one now has a million tokens. Um,
S1: a couple of the Google ones now have 4 million tokens,
S1: I think, for context. So all of this is starting
S1: to come together. All right. So anyway, that's what I
S1: wanted to share. And I think this is a really
S1: powerful way of just interpreting what's coming in in terms
S1: of the news and putting that into a context and
S1: showing how it fits into a model. I think it's
S1: just useful to be able to parse things in that
S1: way and make sense of it. Keep in mind, we
S1: don't actually know the details of any of these pieces, right?
S1: Is MCP going to win? Who knows? That new agent
S1: to agent protocol that Google came out with? Is that
S1: actually going to be useful? Who knows. Like it might
S1: not be useful at all. Like nobody could adopt it.
S1: Like who's going to win with the glasses, right. Is
S1: it is it going to be Apple. Is it going
S1: to be meta? Is it going to be someone completely separate?
S1: I have no idea. Right. These things are not super predictable.
S1: I believe that my 2016 like outlook and predictions from
S1: back then, it's human based. It's based on the fact
S1: that I know what I want my agent to be
S1: able to do. And you know, I've been in tech
S1: for so long that I understand all these protocols and stuff,
S1: so I just assumed this is the way it was going.
S1: And it turns out to be happening. But you can't
S1: predict the companies. You can't predict the timelines, you can't
S1: predict any of this. So that's what makes it so exciting.
S1: I just hope that this model helps you sort of
S1: make sense of the news as it comes in, and
S1: hopefully moves it in this direction towards this model, and
S1: just makes it easier for you to parse the news
S1: and make sense of it. So, uh, do me a
S1: favor and subscribe and I'll see you in the next one.
S1: Unsupervised learning is produced on Hindenburg Pro using an Sm7
S1: B microphone. A video version of the podcast is available
S1: on the Unsupervised Learning YouTube channel, and the text version
S1: with full links and notes is available at Daniel Miessler newsletter.
S1: We'll see you next time.