AI Robots and The $10T Arms Race
David:
Welcome to the AI Roll-Up brought to you by the Limitless podcast,
David:
where we say up to speed with the emerging trends and developments in the AI space.
David:
I'm David Hoffman here with my two co-hosts Ajaz and Josh. Ajaz, how are you doing?
Ejaaz:
I'm doing well, David. It's been quite the week. Less model,
Ejaaz:
frontier model breakthroughs this week.
David:
No frontier model breakthroughs this week? I think that's a first.
Ejaaz:
There's a few, but we're putting them on the back burner because there's some
Ejaaz:
more important things to talk about.
Ejaaz:
It's been an M&A week. So, you know, billions of dollars are being spent to
Ejaaz:
purchase or acquire some of these AI startups that we've spoken about previously on the show.
Ejaaz:
But I think more importantly, I think AI's looked like kind of like this gargantuous
Ejaaz:
cloud, right? And it's kind of ominous.
Ejaaz:
I'm kind of like, is this cloud going to rain on me or is it just going to pass
Ejaaz:
by peacefully and just like kind of like be nice to look at?
Ejaaz:
And I'm starting to see the light. I'm starting to see the kind of formation
Ejaaz:
of what this AI stuff is going to look like.
Ejaaz:
And the reason is, I think we've spoken about a bunch of different things,
Ejaaz:
right? We've spoken about agents.
Ejaaz:
We've spoken about autonomous execution, like, hey, these agents are going to
Ejaaz:
go run and do a bunch of things for you, run companies for you.
Ejaaz:
We've spoken about all these amazing models and how smart they are,
Ejaaz:
but we haven't really pieced together what the end goal is going to look like.
Ejaaz:
We're starting to see a lot more of that this week by some of the moves made
Ejaaz:
by OpenAI and Anthropic. So I'm really excited to get into that.
David:
Yeah, as we talk more and more about AI, I think we are all starting to synthesize
David:
a little bit some of the conversations that we've had on previous episodes,
David:
put them all together and kind of understand the contours and the shapes as
David:
this thing becomes more and more real.
David:
Josh, I introduced this as the AI Roll-Up brought to you by the Limitless podcast.
David:
That is the first time that this has ever been uttered on this podcast feed,
David:
which is the Bankless podcast feed.
David:
But we are launching Limitless this week, which is very exciting.
David:
Talk to me, Josh, about Limitless.
Josh:
Oh man, big week. Limitless kind of stemmed from like a natural extension of
Josh:
our curiosity at Bankless.
Josh:
Bankless is mostly a crypto company. We started getting interested in AI and
Josh:
then naturally we kind of spread out to robotics, manufacturing and energy and
Josh:
all this weird stuff that's happening as downstream effects of this new wave of AI.
Josh:
So Limitless is a place for that. It's the home for all of the stuff that is
Josh:
not crypto, is not economic, is not macro related. It's all the frontier technology, the AI stuff.
Josh:
That's where this show is actually going to be Living is on the Limitless feed.
Josh:
So if you're interested in tech, if you're interested in frontier technology
Josh:
of any sorts, if you're interested in AI, Limitless will be the new home base
Josh:
for all of that. And we're launching this week.
David:
Yeah, yeah. So that is the call to action. What we are doing is we are taking
David:
all of the AI content, all the frontier tech content, which we've been pretty
David:
aggressively exploring at Bankless.
David:
We're putting it into its own feed, which it totally deserves.
David:
And I know there's a lot of people who have been following Bankless for the
David:
AI stuff, but not for the crypto stuff.
David:
And so we are creating a dedicated feed for that. There's also followers of
David:
Bankless, listeners of Bankless who are like, another AI episode.
David:
Weird reaction, but I get it.
David:
It's interesting, like me and Jaws and Joshua, we're all here in New York,
David:
and we'll go to crypto events that are about AI.
David:
And so it's actually a crypto event by crypto people for crypto people,
David:
but it's about the AI subject. So AI has broad appeal. So we're giving it its
David:
own dedicated podcast feed. You're still going to be hearing these episodes
David:
on the Bankless feed as we incubate the new Limitless podcast.
David:
So there is a link in the show notes to go subscribe to the podcast to get that
David:
podcast in your podcast player and also subscribe to the YouTube because we
David:
are making some AI first, AI primary content there.
David:
And then we're also going to do the regular bankless thing of interviews with
David:
big founders, big investors, entrepreneurs in this space who are really helping shape this future.
David:
And also just to double down on what Josh was saying, AI is definitely,
David:
but also frontier tech. So we're talking like rockets. We're talking robotics.
David:
We're talking everything that's going to make the future even weirder than it
David:
already is because it feels like that is coming very, very soon.
David:
But this is the AI roll-up, which again, also happens every single week.
David:
Topics of the week that we're going to talk about, Ijah has already hinted it.
David:
OpenAI making big moves, a $3 billion arms race to gobble up all of the valuable
David:
startups in the AI space. Visa is giving AI agents credit cards,
David:
letting them go wild on the internet.
David:
What happens when you put an LLM into a robot, a real physical robot?
David:
What happens next? And lastly, the hard problem of interpretability.
David:
Why it's important for making sure we can save the future of humanity by cracking
David:
this interpretability problem.
David:
But Jaws, we are going to start with OpenAI making three big,
David:
big moves, a $3 billion arms race. What happened in OpenAI news this week?
Ejaaz:
Okay, so let's get into it. This has been basically the headline news all week
Ejaaz:
and everyone just couldn't stop talking about it yesterday.
Ejaaz:
OpenAI is officially making its first major acquisition by purchasing a company
Ejaaz:
called Windsurf for $3 billion with a B.
Ejaaz:
Now, if you're wondering what on earth Windsurf is, you might have heard David,
Ejaaz:
Josh, and I speak about a company previously on this series called Cursor.
Ejaaz:
And Cursor is basically this kind of vibe coding platform where you can type
Ejaaz:
in a prompt, typically like you do on ChatGPT, but instead you could ask it
Ejaaz:
to create a new app for you or a new piece of software, or maybe even a fun
Ejaaz:
game that you know and love.
Ejaaz:
And it would just code it all right up in front of you.
Ejaaz:
And let's say the environment or the software that allows you to do that is
Ejaaz:
something called an IDE, which stands for Integrated Development Environment.
Ejaaz:
If you're wondering what that
Ejaaz:
is, think of it as a software suite which includes like a coding editor.
Ejaaz:
A compiler and a bunch of other things that you need to basically make software
Ejaaz:
it just makes it really really easy for you and then it adds ai on top of it
Ejaaz:
so you just speak to it like a normal person and it just kind of like pops up an app now,
Ejaaz:
windsurf is in the top two of these types of companies you've got cursor then
Ejaaz:
you pretty much have windsurf at this point,
Ejaaz:
and open ai will now compete directly with things like Cursor,
Ejaaz:
Lovable, and Replit, which do very similar things.
Ejaaz:
And in my opinion, this confirms that there's pretty much an arms race to build
Ejaaz:
the best AI coding assistants ever. So imagine if you could be like the number
Ejaaz:
one tool or platform to the leading software engineers and companies of tomorrow.
Ejaaz:
That's basically the TAM, the Total Adjustable Market. That's basically the
Ejaaz:
market that you're going after.
Ejaaz:
Now, one kind of like interesting caveat that I want to include here is that,
Ejaaz:
This happened after OpenAI tried to buy Cursor. That's the number one platform that does this twice.
David:
So they had to get the second best.
Ejaaz:
Yeah, they basically had to get the second best. And kind of like my initial
Ejaaz:
gut reaction when I read that was,
Ejaaz:
I wonder if Cursor is either holding out for a Google or a Meta to purchase
Ejaaz:
them and go for an even bigger number because they don't want to be bought by Sam Altman's startup.
Ejaaz:
But it's a curious move. and a few other things i want to highlight is this
Ejaaz:
acquisition follows um some major moves by other companies that are doing something
Ejaaz:
similar so google for example launched their own cursor competitor called firebase
Ejaaz:
and if you pull up this tweet david it's actually pretty good and i think this
Ejaaz:
um this example will be quite a good visual example so people can understand
Ejaaz:
you know what on earth this does
Ejaaz:
so what you're watching right now um for those of you who are just listening
Ejaaz:
is a video of someone just sketching out a very, it looks like a three-year-old's drawn it,
Ejaaz:
kind of layout of a website, of an app that can basically help someone draw.
Ejaaz:
And then what you see on the right side is the Google's Firebase platform creating it.
Ejaaz:
And you can actually interact with the tool and draw and paint just like you
Ejaaz:
did on like Microsoft Paint.
Ejaaz:
Very simple, basic example. But can you imagine this being extended out to something else?
Ejaaz:
It's pretty insane. What's your take on this, David?
David:
I think for the listeners, just imagine Microsoft Paint, but on the other side
David:
of it, outcomes and an application, a functioning application.
David:
So, you know, Microsoft Paint on one side, functioning application on the other.
David:
I'm actually curious to hear Josh's take on what's going on here.
Josh:
I think it's cool. I think the second I saw this news, it reminded me of news
Josh:
from a few weeks ago, which was Google acquiring Wiz for $32 billion, I think it was.
Josh:
I think this is an attempt at OpenAI to kind of make their way up the stack.
Josh:
And it's not just about serving their own stack better. It's about now actually
Josh:
embedding themselves in the decision-making layers above that stack so they
Josh:
could shape the flow of traffic regardless of the endpoint.
Josh:
In the case of Wiz, Wiz was kind of like a security aggregator company.
Josh:
So Google owns Google Cloud, but it doesn't have any control over AWS or Microsoft's Azure servers.
Josh:
So what acquiring Wiz does is it allows them, it gives them upstream access
Josh:
to that, like security telemetry, the customer data flows, the threat intelligence,
Josh:
a lot of the data that they wouldn't otherwise have.
Josh:
And I think that's kind of what OpenAI is doing here with Windsurf,
Josh:
where ChatGPT clearly dominates the consumer product space.
Josh:
They own that. They do very well. But in enterprises, a lot of companies are
Josh:
looking for a thing that people are calling model orchestration,
Josh:
which is kind of like, which model will serve my use case the best?
Josh:
And they're looking for aggregators to decide and make that decision for them.
Josh:
Well, OpenAI just bought that aggregator. And they now own this routing and
Josh:
orchestration layer that acts like across this load balancing metric.
Josh:
So now, strategically, they get visibility over influence, over who's using
Josh:
what, what they're using for. And they can optimize their models for these use
Josh:
cases because they have the data.
Josh:
So now going forward, you might see ChatGPT starts to get chosen a lot more
Josh:
by these aggregators because it has all the data of why it's choosing another
Josh:
model that isn't theirs. And I think that's like a pretty interesting play.
David:
Is there a parallel here between like there are deals that Google has made in
David:
the past with browsers about like, hey, we will pay you X amount of money to
David:
make us the default search engine in your browser. So when you type a question
David:
to the toolbar, it automatically routes to Google.
David:
It makes a Google query and Google gets the data from that and the information
David:
for that to make their product better.
David:
It sounds like this is something similar where they are just acquiring this
David:
endpoint, which has a direct relationship with its users. So Windsor has ownership
David:
over the users. has the user relationship. But in the back of Windsurf, there's ChatGPT.
David:
So ChatGPT now just acquires that user relationship. It gets ChatGPT to be used by Windsurf.
David:
And so there's just, it's just more usage for ChatGPT. And then there's also
David:
information about what ChatGPT, how it needs to adapt the information,
David:
the data, like you said, it goes back into ChatGPT.
David:
Is there a parallel there or am I hallucinating here?
Josh:
Probably. It feels like there's a fine line where people go to Windsurf as Windsurf customers.
Josh:
They don't want to be spoon-fed ChatGPT if it's not the ideal model,
Josh:
so that could hurt with customers.
Josh:
I assume they probably won't do it that explicitly, but the implicit thing that
Josh:
they could extract value from is understanding the user's needs and the wants
Josh:
and when certain models are chosen and kind of optimize future versions of the ChatGPT
Josh:
language model to serve those people.
Josh:
So the ideal case is that ChatGPT will actually be able to serve all of these
Josh:
while still gaining data from what people like about the other models.
Ejaaz:
You could also argue that it's just, to your point, Josh, data that they want.
Ejaaz:
Data is the end game, right?
Ejaaz:
In whatever shape or form it comes in, in whatever kind of outlet that you can
Ejaaz:
extract it from, that's what they want. If they want developer activity,
Ejaaz:
if they want to grab it at the consumer level, they already have it at the end
Ejaaz:
consumer level. So now they want to try and get like all the developer activity as much as they can.
Ejaaz:
I wonder what type of a model or even end-to-end experience you can create based off of that, right?
Ejaaz:
And to kind of like strengthen your argument here, I noticed that Google launched
Ejaaz:
something associated with integrated computer use this week as well.
Ejaaz:
They have something called AI Studio, which is kind of like this environment
Ejaaz:
that you're describing, Josh, which doesn't just include kind of like the end
Ejaaz:
user stuff, which OpenAI dominates on, but it also allows developers to kind
Ejaaz:
of like build this kind of like,
Ejaaz:
synonymous end-to-end app experience, right?
Ejaaz:
And what I noticed about this integrated computer use thing is that,
Ejaaz:
you know, they really want to just own end-to-end product development, the entire pipeline.
Ejaaz:
And if you think about it, like you allow them to use their no-code prompt-friendly
Ejaaz:
platform to build your product, right? Leveraging their models and you can inference
Ejaaz:
it through their like cloud system.
Ejaaz:
And then on top of that, you can allow anyone to use it for themselves involves
Ejaaz:
via computer use so if you're an end user right and you're saying hey i really
Ejaaz:
like that app that this developer's built well you can run it locally on your,
Ejaaz:
computer now and you can inference any model that you want say like hey i don't
Ejaaz:
like that it's using this model can we use something else sure like google's
Ejaaz:
ai studio solves for that and i think that's like a really important nuance
Ejaaz:
that's going to make it super super sticky and how they personalize this,
Ejaaz:
experience for users i don't actually quite know i wonder if you have any ideas
Ejaaz:
but um just a very subtle but important improvement i think is is worth noting.
David:
I've brought this metaphor up before in the past on this show but uh the whole
David:
entire um vertical the gaming vertical of uh like league of legends and dota
David:
is like arena battlers or whatever uh
David:
billion dollar industry in just that one type of gaming structure and that gaming
David:
structure was created by a
David:
starcraft mod so some individual using the starcraft map editor and like map
David:
editing engine created uh
David:
this like mod of starcraft that created this structure that basically is is
David:
what uh the moba arena battler league of legends
Josh:
Multiplayer online battle arena
David:
Thank you i don't play league of legends But a
David:
multi-billion dollar industry got created because of this modding ability,
David:
because of the modding ecosystem around this one base game, which was very,
David:
very valuable called StarCraft, but now it spawned an insane amount of value.
David:
And so what I'm seeing here is this is a modding engine for apps.
David:
And the downstream value that could come out of this just give...
David:
Give creativity, give creative tools to people who want to be creative.
David:
And now it's not even developers. It's anyone who's like frustrated that they
David:
are using this app, but there's this one button that's missing that they wish
David:
they could press and it could do something.
David:
And now all of a sudden the creation of that app, if they truly discover value
David:
in it, maybe so do other people as well.
David:
And they just need that one extra little module to hook it into the app.
David:
And now all of a sudden that is a valuable piece of infrastructure that is free
David:
to roam the internet. And so that's what I'm seeing here and why I'm pretty excited about this.
Ejaaz:
You know, something you just reminded me of something, David,
Ejaaz:
when you describe that kind of open modding kind of ecosystem,
Ejaaz:
it's kind of what we're seeing amongst a lot of AI trends today, right?
Ejaaz:
So we've spoken about reinforcement learning, which is like,
Ejaaz:
you know, a very popular post and pre-training method to get AI models to become
Ejaaz:
smarter. And it doesn't require a hell of a lot of compute. It just requires
Ejaaz:
you to give it kind of like some reasoning logic and it gets better and better.
Ejaaz:
I've noticed that the primary way that a lot of these models are learning is
Ejaaz:
through open reinforcement learning gyms.
Ejaaz:
So think of it as like a kind of like a Pokemon gym, right? And you could take
Ejaaz:
your Pokemon, but in this case, your Pokemon is a model.
Ejaaz:
You can put it in the gym and you could train it. It battles over and over again until...
Ejaaz:
It gets smarter and smarter. And you can like orient it around like math,
Ejaaz:
coding, whatever it might be.
Ejaaz:
The thing that accelerates reinforcement learning, David, is just allowing a
Ejaaz:
bunch of anyone, any humans to create their own environments.
Ejaaz:
And then you could just send your model to all of them in a day,
Ejaaz:
or you could just pick the best ones. And it kind of like ranks itself via an open source method.
Ejaaz:
Another example is in training, right? Where previously, like it was just one
Ejaaz:
specific data center, then it was like, oh shit, we need more power.
Ejaaz:
Let's move all the data centers together. But like, let's keep them close because,
Ejaaz:
you know, we need like a high feedback loop.
Ejaaz:
And now it's getting even more distributed. And we'll talk about that later.
Ejaaz:
But I'm just noticing it's like this, dare I say, open source ecosystem that
Ejaaz:
is like purely benefiting the way that we advance AI right now.
David:
We talked last week about the downstream implications of OpenAI's memory update
David:
and how it can remember all of its chats with you.
David:
This saga continues this arc continues what happened in the last seven days to Joss?
Ejaaz:
Okay, so to give context on when we last mentioned this update,
Ejaaz:
David, it was really positive, right?
Ejaaz:
Because we were like, hey, ChatGBT is going to remember everything you've ever said to it.
David:
ChatGBT is turning into a friend. It's turning into an ally.
Ejaaz:
Oh, not just a friend, your best friend. Your best friend. Your second brain. Your psyche.
Ejaaz:
Exactly. You're going to offload your conscience to this thing,
Ejaaz:
basically, and you're going to love it, right?
Ejaaz:
And there were a lot of, like, you know, kind of ominous implications from that.
Ejaaz:
But overall, it was like net net good because the more personalized your AI
Ejaaz:
experience is, you could argue the better and more sticky the product is going to be.
Ejaaz:
Now, there's a dark side to this. And OpenAI, funnily enough,
Ejaaz:
didn't really announce this on any major headlines, which is they updated your
Ejaaz:
memory in a much more creepier way,
Ejaaz:
such that in whatever way you prompt in ChatGPT, you know, sometimes it does a web search for you.
Ejaaz:
So let's say like, hey, can you tell me some of the hottest recipes?
Ejaaz:
I don't know why I keep talking about recipes on the show, by the way.
Ejaaz:
I think I'm just like hungry when I do this episode.
Ejaaz:
But let's say you prompt ChatGPT and you say like, hey, like pull out the top
Ejaaz:
five recipes to create roast chicken or something, right? It does a web search for you.
Ejaaz:
But now with this update, ChatGPT has the permission, rather your explicit permission,
Ejaaz:
to change the way you've worded your prompt.
Ejaaz:
Now, the reason they're giving to you there is just so that they can make your
Ejaaz:
prompt more effective. Right.
David:
But I'm more attuned to what your interests are.
Ejaaz:
More attuned to what, and I'm like, well, hang on a second. How do you know
Ejaaz:
what I want better than I want, right? And we get into like this really weird
Ejaaz:
territory where it's like, hey, can you tell me like what kind of clothes do
Ejaaz:
you think might fit my vibe for this evening?
Ejaaz:
And it starts, you know, pulling like ad sponsors type situation,
Ejaaz:
but then it feeds it to you as if like, hey, this is what you really want,
Ejaaz:
right? And I'm thinking, hang on, like, how can you like change my words?
Ejaaz:
And like, am I held legally wrong?
Ejaaz:
Liable to that like it gets super weird and i'm curious you know how this can
Ejaaz:
get kind of like taken out of context to like some kind of black mirror episode um.
David:
The pattern that i'm seeing here is like the pre-2015 era of the internet which
David:
was already starting to decay at this time but um
David:
you know facebook and cambridge analytica and all of that debacle what we all
David:
learned was that facebook was showing conservatives one version of the internet
David:
one version of the truth It was showing liberals a different version of the internet.
David:
And people were all learning like, oh, my version of the internet is attuned
David:
to me based off of the data that I have exposed about myself to the internet.
David:
And all of a sudden, like my internet is not your internet. It all used to be
David:
one internet. We all looked at the internet and we saw a single source of truth
David:
and the algorithms hadn't corrupted that.
David:
And we're all looking at the same facts. We're all looking at the same news articles.
David:
But as algorithms became more precise about what their goals were,
David:
like, oh, we can get this user to stay online on our platform more if we feed
David:
them content that is more attuned to what their beliefs, then then we're going to do that.
David:
And all of a sudden, you know, everyone got their own interpretation of the
David:
Internet. And we also started to like society started to split into factions.
David:
Right. The right got more right. The left got more left.
David:
And it's because of this curation, which we all want. I want ChatGPT to curate
David:
the best for me, the best for my my likes.
David:
But this is the same pattern that I'm seeing Is like ChatGPT is now Profiling me
David:
And judging me And putting me into a box That I'm not necessarily aware That
David:
it is the box that it is putting me in But nonetheless that is the box that
David:
I'm going into And all of a sudden I will be in a box That
David:
Other the rest of society will not be in and they will be in their own box and
David:
now all of a sudden we are not again
David:
connected as this as a species we are now like profiled and segregated a base
David:
of our interests in our and how chat gpt is being tuned so that is what is triggering
David:
in in me in this hearing this
Josh:
It's this uh this like increasing hyper personalization that we're seeing there's
Josh:
two trends which is the hyper personalization things are created specifically for you
Josh:
and also the relinquishing of all your privacy and data for the better experience
Josh:
which is just a trend that i do not see stopping anytime soon and the
Josh:
results are probably a more fractured idea space because things do become personalized
Josh:
to you and you're seeing this different reality than everybody else
Josh:
um the question is is that better and and what is the incentive from the person
Josh:
who's serving it to you is the incentive to get you to maximize your time spent on the service
Josh:
or is it to give you a truthful answer so you can leave like i love the example
Josh:
you used last week david where you said you use like five or ten percent of
Josh:
your screen time on chat gpt and it's the most valuable time that you spend
Josh:
is that gonna be the outcome where you come you get served and you leave or
Josh:
is it an attempt to just trap us in ecosystem lock maximally extract uh that type of thing and that's
Josh:
it's definitely a step towards that direction
David:
Yeah i definitely see that as an emerging theme of these conversations the ai
David:
roll up the things that the news that we're processing on this base there's
David:
like the dark path and the light path there's like the utopia and the dystopia
David:
and there's the utopia where we want where this
David:
chat gpt intelligence is minimally invasive and maximally value add to our lives
David:
and allows us to be human connect with each other better be informed be more
David:
intelligent and that's the happy path and then there's the dark path of
David:
it encourages brain rot But it encourages isolation.
David:
You guys see like the meta Zuckerberg announcements of like,
David:
oh, yeah, we're actually just going to make online AIs and you're going to be
David:
friends with them. And so like the original Facebook notion was like,
David:
we're going to make everyone connected. We're going to connect everyone.
David:
And now it's now the modern day mission of Facebook, implicit mission of Facebook
David:
is we're going to isolate everyone.
David:
And, you know, the modern day, the happy path of ChatGPT is we're going to make
David:
everyone superpowers. We're going to give everyone godlike intelligence.
David:
And then the unhappy path is we're going to do brain rot even faster, even better this time.
David:
I'm worried that the incentives just point towards the brain rot all the time.
Ejaaz:
Well, I mean, what's the saying around show me who makes the money and I'll
Ejaaz:
show you the incentives or maybe it's like the other way around.
Josh:
It's like, let's show me the incentive, I'll show you the outcome.
Ejaaz:
Exactly right. So let's track it all the way up to the top.
Ejaaz:
Okay, OpenAI has an amazing product and they state all these different things
Ejaaz:
like, hey, we want to help you out. We want to make you a better person,
Ejaaz:
a better learner, blah, blah, blah, blah, blah.
Ejaaz:
But, you know, to your point, like they want retention. They want max usage
Ejaaz:
24-7 of people on this thing.
Ejaaz:
And where I get even more worried or concerned is in the case of like Facebook, Snapchat, Instagram.
Ejaaz:
You can take the phone away, right? You can put it away.
Ejaaz:
You can stop. There's only so many pictures you can post in a day.
Ejaaz:
And then you're like, okay, right, I'll put it down.
Ejaaz:
But when it becomes your entire life, your thinking vehicle,
Ejaaz:
and in some cases, your personality.
Ejaaz:
I saw the most random thing of like, I think we mentioned it last week of PhD
Ejaaz:
students using chat GPT prompts to pick up dates and stuff.
Ejaaz:
And I'm just like, well, hang on a second. Like, now it's getting involved in your actions.
Ejaaz:
It's going to tell me what to buy. It's going to tell me how to look.
Ejaaz:
And I'm like, that is an incredibly more stickier function than like Facebook
Ejaaz:
trying to influence your opinion on certain things.
Ejaaz:
So I really hope that it is not going to become the darker outcome,
Ejaaz:
but I can't see a path where it doesn't unless
Ejaaz:
for some reason shareholders of these, you know, corporate companies are kind
Ejaaz:
of like, oh, yeah, you know what, we don't want to fuck humans up too much or like too bad.
Ejaaz:
But actually quite interesting on that case, guys, did you see the news around,
Ejaaz:
open AI's, well, I don't wanna say restructuring, but rather structuring,
Ejaaz:
which kind of like confirmed what they were before. Did you guys see that?
David:
I'm going to need to be informed here.
Ejaaz:
Yeah. Okay. So basically, OpenAI, I'll actually take this direct quote from Sam on his blog post.
Ejaaz:
OpenAI was founded as a nonprofit.
Ejaaz:
Is today a nonprofit that oversees and controls the for-profit?
Ejaaz:
And going forward, will remain a nonprofit that oversees and controls the for-profit?
Ejaaz:
That will not change. Now, what he's referencing here is a long-lasting,
Ejaaz:
highly publicized debate or debacle, rather, that OpenAI was founded as a nonprofit.
Ejaaz:
And Sam was all like, this is for the good of AI. This is back in the day when
Ejaaz:
both Elon Musk and Sam, and if you guys didn't know this, had founded OpenAI.
Ejaaz:
And they were working on creating AI for the betterment of humanity and the people.
Ejaaz:
But at some point, Sam decided, you know what?
Ejaaz:
I kind of want to make this a for profit because there's a lot of money to be made in this AI thing.
David:
Well, also, he needed to to keep opening AI alive because you need the profit
David:
incentive to attract the best talent, to attract investors, to stay ahead of the game.
David:
And so, yes, it was a trap. It always needed to be like this.
David:
As soon as there was any amount of legitimate competition, the nonprofit model was a failure scenario.
Josh:
Yes, primarily to raise money for training. because in order to do those big
Josh:
training runs, you needed money. And in order to attract investors,
Josh:
you needed to have some sort of promise to give them money back.
Ejaaz:
Right, exactly. So that is like, you know, the greenfield really good way to look at this.
Ejaaz:
And I think like arguably to this extent, that's what Sam's been doing.
Ejaaz:
You know, he set up, what's it called? Stargate or whatever it's called,
Ejaaz:
like the biggest basically data center factory that is being built,
Ejaaz:
I think in Texas or somewhere like that.
Ejaaz:
And he's investing the funds that he's raised in exactly where he said he was going to do it.
Ejaaz:
But at what point does the full profit then become maybe a bit of an issue?
Ejaaz:
Now, I personally don't really see an issue in this turning into a full profit.
Ejaaz:
In fact, I think it actually should be a full profit.
Ejaaz:
If I'm going to be using this product, I want it to eventually get better.
Ejaaz:
I don't want it to become some kind of,
Ejaaz:
communist table stake to ai kind of thing i'm just gonna i'm just gonna go to
Ejaaz:
the product that works better um so i don't really get why there's been so much
Ejaaz:
kind of backlash against this i think it's because sam had,
Ejaaz:
quite the lead with open air and now it's become kind of like table stakes and
Ejaaz:
maybe this is a bit of a competitive move from you know uh,
Ejaaz:
x and elon musk and open ai and stuff who have been filing a lawsuit against
Ejaaz:
him but really interesting to see that like open airs kind of back down and said okay okay okay
Ejaaz:
we'll keep it we'll keep the non-profit in control of the for-profit and wait
Ejaaz:
until everything everyone's calmed down and then we'll kind of maybe flick it back to a for-profit.
David:
I think ultimately that all of this is going to turn into a nothing burger the
David:
non-profit wrapper around a for-profit company is just the same thing as a board
David:
of directors around a for-profit company it's the same structure it's just a
David:
for-profit company with extra steps
David:
uh we've already figured out like general c-corp incentive structures there's
David:
a reason why the delaware c-corp is what it is it is a science that has been well attuned.
David:
We don't need to reinvent the wheel here. I don't know why.
David:
I don't know the story behind the nonprofit genesis of OpenAI.
David:
Maybe it was just an anomaly.
David:
Ultimately, as time progresses, I think this is just going to be this weird
David:
anomaly about how OpenAI got started.
David:
And it's going to ultimately look like a for-profit company,
David:
like all the rest, kind of like how it already looks. I don't know.
David:
Josh, that's my take. What do you think?
Josh:
Yeah. The inception of OpenAI and the reason it's called OpenAI is because at
Josh:
the time Google had invented the transformer, they were becoming a powerhouse in the world of AI.
Josh:
And Elon and Sam had this vision that they wanted a counterbalance to a monopolistic
Josh:
and super intelligence and the counterbalance was an open source to AI that's
Josh:
for the people. So that was the idea on paper.
Josh:
In practice, you need a lot of money to buy these training models.
Josh:
You need to buy the GPUs to train the models.
Josh:
You need a lot of funding. There are profit motives that are required in order
Josh:
to create consumer products that get this product out there.
Josh:
So it got kind of clouded over time. And I think if...
Josh:
They had just started as a for-profit organization. None of this would have made a difference.
Josh:
The thing that I'm really interested in, less than the company structure,
Josh:
because it feels kind of irrelevant. They are for-profit.
Josh:
They will hopefully send some gimmies out, is where they stand on the open part of it.
Josh:
Where will the company state, like, hey, we are going to release these models
Josh:
to the public as a public good service, and we're going to keep these models closed?
Josh:
I'm more interested in that internally, is how they're thinking about releasing
Josh:
those models to the public and actually maintaining the open sense,
Josh:
that initial mission of distributing the computes and the intelligence.
David:
We've talked in the past on this podcast about how all of the frontier models
David:
just become owned by the value of these models, become owned by the public domain
David:
pretty quickly because of the rat race of open source.
David:
Like open source is, I don't know, six months behind, nine months behind the
David:
frontier models. It is not more than a year behind.
David:
And so the value of the frontier models, whoever's got the best frontier model,
David:
that value will show up in the open source domain within 12 months.
David:
And so I'm not sure what the value is. Like, does it matter if OpenAI keeps
David:
their models behind a silo, a closed silo?
David:
Maybe they're a hypocrite, but I'm not sure that matters because ultimately
David:
the open source arena always catches up to the value of the best model that
David:
we've produced somewhere on the
David:
earth. And that is inclusive of all the models coming out of China too.
Josh:
This has been true in the past. I think the scales are a bit different.
Josh:
I actually saw this interesting post by Kevin Whale this morning.
Josh:
He's like the chief product officer of OpenAI. And it was about a blog post
Josh:
where other countries are actually
Josh:
reaching out to OpenAI to build Project Stargates in their own country.
Josh:
And that diminishes the free marketization of these large language models where
Josh:
now there's not a free market competing for the best spot and releasing it.
Josh:
There is a country that wants to consult with a single company that wants to
Josh:
integrate their AI into the way that they populate AI through their country.
Josh:
So it feels like the scales are increasing and the breadth of this is narrowing
Josh:
in the sense that they're looking for a source of truth from one person instead
Josh:
of this open source version.
Josh:
And that feels like where things can get a little shaky.
David:
Interesting. Okay, so what you're saying is that the assumption that there's
David:
compression amongst all the frontier models, there's like seven,
David:
eight frontier models out there, all these different AI labs,
David:
many of them, all ruthlessly competing.
David:
And because of that competition, there's a great equalization because the learnings
David:
of one frontier model become the learnings of the other, and that value gets passed around.
David:
And then because it's just passed around, it becomes available in the open source domain.
David:
What you're saying is that that assumption that that is going to be the way
David:
that it is is not a perfect assumption and we should be wary that actually there
David:
are very strong economies of scale here and the possibility of one or two or
David:
a very low number of frontier models
David:
make a break for it and actually become very large and have economies of scale
David:
is a possibility that we should watch out for that's that's what i just heard from you
Josh:
Yeah that that feels about right and um
Josh:
Yeah, I think as things kind of accelerate faster, if you ask the OpenAI team
Josh:
from a decade ago, when they were first getting started, that there would be,
Josh:
if you told them that there would be seven or eight giant frontier model companies
Josh:
that are all competing, that'd be a great thing.
Josh:
So, so far we're good because the initial use case was to fight Google,
Josh:
which was the single entity. So, the fact that there's seven or eight now is good.
Josh:
I think it's just important to watch the narrowing of that as the velocity of
Josh:
these models increases to just kind of keep checks and make sure that some aren't
Josh:
really running away faster than the others.
Ejaaz:
Where do you think the stickiness forms josh i i know we've discussed this previously
Ejaaz:
but i think it it comes down to who creates the best,
Ejaaz:
end user app whether that is some kind of developer platform or a chat gpt interface
Ejaaz:
that does a bunch of stuff for you i don't really see how it could be anything
Ejaaz:
to do with some kind of pioneering model unless it's like really that much better Right.
Ejaaz:
All the model updates that we see, you know, over the last couple of weeks with
Ejaaz:
Quan, with Gemini 2.5, Flash from Google, they all beat certain benchmarks.
Ejaaz:
But I think no one really sees what that looks like until it's like in practice. Right.
Ejaaz:
Unless you're like a crazy like kind of coder or whatever. So I think it comes
Ejaaz:
down to like stickiness.
Ejaaz:
And so if you have, and I want to hear your opinion on this,
Ejaaz:
OpenAI going to other countries and,
Ejaaz:
you know, committing basically a ton of data and compute to,
Ejaaz:
you know, help them whatever locally own whatever OpenAI's product or models are over there.
Ejaaz:
How do you think that kind of like seeds their position other than just like the model and compute?
Ejaaz:
Or do you think that is enough of a moat, right? Just because like they're there.
Josh:
Yeah, there's probably different layers to it. There's like the consumer and
Josh:
business layer, which is
Josh:
the app moat that we discussed with the data mode with memory and that's super
Josh:
powerful but i think above that is the like nation-state policy level influence
Josh:
where i mean we made a joke of it with the tariffs that they were generated by chat gpt but by
Josh:
by using these systems for for things that are greater than just consumer applications
Josh:
for making like large decisions for implementing policy for implement like think
Josh:
of china for how they should
David:
We tariff china or not
Josh:
Yeah manage or even as as the chinese like as a Chinese citizen,
Josh:
how the government should command its citizens.
Josh:
I think there is like this higher level influence of AI that is more idea driven
Josh:
instead of consumer driven in terms of like policy and how to run countries.
Josh:
That's the part that feels, yes, more, more vibes and more heavily influenced.
Josh:
So when I read this early this morning, the open eyes can be working with countries
Josh:
instead of companies that was like, oh, OK, this is this. The scales are now
Josh:
like getting grander and grander. Right. Right.
David:
Yeah. The idea of China using AI to govern its population is not a new idea.
David:
I think even Peter Thiel talked about this forever ago, which he talked about
David:
like AI is highly centralizing, crypto is highly decentralizing,
David:
and both of these like verticals are growing antagonistically towards each other.
David:
Anyways, I think we're ready to move on from OpenAI. Let's get into the subject
David:
of Visa because Visa is giving AI credit cards, and I don't know what that means. Josh, what's going on?
Ejaaz:
Listen, please.
Ejaaz:
Yeah. So in an unexpected move, honestly, Visa announced something called intelligent commerce,
Ejaaz:
which is basically giving a bunch of autonomous, well, kind of semi-autonomous
Ejaaz:
AI agents a credit card or the equivalent of like a bank account or a wallet.
Ejaaz:
And it makes sense because I think AI commerce is becoming more of a thing.
Ejaaz:
And I'll get into what exactly that means.
Ejaaz:
But basically, the initial use case for this is that you have like an agent
Ejaaz:
that you can talk to that you can use to do all the kind of like boring things
Ejaaz:
that you kind of don't want to be getting to, but you need to as like daily errands, right?
Ejaaz:
So maybe, hey, can you go order the weekly groceries off of Amazon for Whole
Ejaaz:
Foods or whatever? Or can you organize a travel itinerary for my business trip?
Ejaaz:
Or, you know, log in through my company server and do A, B, and C?
Ejaaz:
Or restaurants, hotel bookings, stuff that we've spoken or discussed about on this show before.
Ejaaz:
But I think the specifics is where it gets kind of interesting.
Ejaaz:
So humans will basically be able to have full control over the rules and limits
Ejaaz:
that an agent can operate with, right?
Ejaaz:
So you can kind of determine what its spending cap it's going to be,
Ejaaz:
what kinds of websites it can visit, whether it needs to be an official website
Ejaaz:
address or whether they can kind of like vibe on Google and pick like the top
Ejaaz:
sponsored link or whatever that might go.
Ejaaz:
And, you know, that could go wrong in many different ways.
Ejaaz:
What I found really interesting here in the spec is they're using tokenized
Ejaaz:
digital credentials linked to the human owner.
Ejaaz:
And that sounds super vague and boring, but I think is actually really important because
Ejaaz:
if you think about this AI becoming eventually an extension of yourself,
Ejaaz:
right, a digital identity, We've spoken about this a lot on the crypto and Web3
Ejaaz:
side, which is like, oh, we should decentralize identity and it'll give you like this, you know...
Ejaaz:
Self-owned financial credit score and all that kind of stuff,
Ejaaz:
we're seeing Visa basically take the steps towards defining what those credentials
Ejaaz:
look like for you from a financial sense, right?
Ejaaz:
In addition to the spec, you can do things like dispute handling in real time
Ejaaz:
because Visa has a customer support line and it's managed by Visa.
Ejaaz:
And they're launching with some really cool partners, which I think is one of
Ejaaz:
the most important things when you're launching a product like this.
Ejaaz:
You need distribution and partners.
Ejaaz:
And the partners that they're launching with are all the big dogs,
Ejaaz:
like OpenAI, IBM, Anthropic, Microsoft, and Stripe.
Ejaaz:
And the reason why I find this such a compelling thing, and maybe this is because
Ejaaz:
I've spent a lot of time on the Web3 stuff, is that was mainly the pitch that
Ejaaz:
was given for a lot of crypto AI agents, right?
Ejaaz:
You know, we've spoken about this a lot, David and Josh, where we're like,
Ejaaz:
okay, I think crypto is going to be pretty much the financial rails for the
Ejaaz:
future of AI. And the reason why it's going to.
David:
Be the case is- AI guys can't have bank accounts, but they can have Ethereum addresses.
Ejaaz:
They can have Ethereum addresses.
David:
I can go find 20 Ryan Shaddam tweets like that.
Ejaaz:
And listen, David, I can never take down your Ethereum wallet,
Ejaaz:
right? You know, you own your keys, blah, blah, blah. It's cheaper in some cases
Ejaaz:
if you're using L2s or whatever.
Ejaaz:
And, you know, you're able to basically access any app that anyone creates on
Ejaaz:
this infrastructure known as the blockchain.
Ejaaz:
Now Visa's coming along. Oh, by the way, the antithesis for TradFi was it's too expensive.
Ejaaz:
They'll never scale. Their infrastructure is too siloed, right?
Ejaaz:
And now you have Visa come along being like, hey, it's not really that big a deal.
Ejaaz:
We will gladly give your agents their own wallet.
Ejaaz:
We'll give you even better controls over it. And we'll give you a customer support
Ejaaz:
line if anything goes wrong. Can't do that with a blockchain, can you?
David:
You know, in hindsight, when we are talking about a revolution of intelligence,
David:
the idea that AI won't be able to learn how to use credit cards kind of seems dumb.
Ejaaz:
Yeah, so I think this is interesting because this isn't an update in silo from Visa.
Ejaaz:
MasterCard also had an update, funnily enough, this week. So I feel like they
Ejaaz:
were playing off of each other when one announced first that they're announcing
Ejaaz:
payments for agents called AgentPay.
Ejaaz:
It does a lot of the same thing that I just described for Visa's new product,
Ejaaz:
but specifically this takes place within conversations that users are having with AI.
Ejaaz:
For example, it'll integrate directly with ChatGPT or Microsoft's AI co-pilot.
Ejaaz:
It'll also leverage things like memory data from each of the platforms that
Ejaaz:
you use. So for example, OpenAI's memory that it has on you,
Ejaaz:
it'll end up making personalized recommendations for purchases that you have
Ejaaz:
within your conversations.
Ejaaz:
And the reason why I think this approach is also really powerful is it's not
Ejaaz:
kind of bothered about you coming onto Visa, setting up an account,
Ejaaz:
attaching your agent to this thing.
Ejaaz:
It just integrates directly into wherever you're using AI, whether that's Claude,
Ejaaz:
whether that's ChatGPT, or whether that's even Meta.ai.
Ejaaz:
And so two different approaches from two of the biggest companies on this play.
Ejaaz:
You know, one thing it reminded me of, guys, is you know how when stablecoins
Ejaaz:
became a pretty major thing, and it continually becomes a major thing with every
Ejaaz:
week passing, Visa came in and said, Hmm, what can we do here?
Ejaaz:
Okay, okay, okay. I get that you guys like stable coins. And I get that it's
Ejaaz:
basically replacing the dollar and it's quicker and it's better than Swift. We'll support that.
Ejaaz:
Just let us take a tiny fraction percentage of this transaction flow and we'll
Ejaaz:
be good. Does that sound good?
Ejaaz:
And everyone said, okay, yeah, that sounds good. We're saving money.
Ejaaz:
And they ended up making like $500 million in the first year.
Ejaaz:
Now imagine applying that to just anyone performing any kind of economic activity?
Ejaaz:
You know, what percentage of David's Amazon grocery list do I want per year?
Ejaaz:
You know, how much is that worth for me times, you know, all his activities that he does?
David:
I do want to defend crypto for a moment because we've just talked about how,
David:
you know, with both Visa and MasterCard, it's very obvious, like the incentives
David:
point towards Visa and MasterCard entering the AI space.
David:
All AI commerce Visa wants, all ai commerce mastercard wants that's their business
David:
model they get 2.9 or 3.5 on every transaction so they need to be able to give
David:
ai's credit cards so that they can take that fee that's their business model
David:
makes total sense this is totally expected um
David:
and so like the yeah the notion of just like oh yeah crypto is for ai agents
David:
uh because like both are code-based uh
David:
i think still makes sense mainly because there are compliance things
David:
that visa and mastercard have to deal with that the crypto space does not have
David:
to deal with uh they have to deal with chargebacks and fraud and the bank secrecy
David:
act crypto does not have to do that uh
David:
irrevocable transactions means that we don't have to worry about chargebacks
David:
and fraud and all of those things you just have to be far more careful about
David:
the transactions that you make which is up to the ai developers in the crypto
David:
space and so there are fundamental
David:
breaks on the trad AI commerce space that crypto will not experience.
David:
And, you know, the idea of there being 10 billion AI agents all making commerce,
David:
that doesn't mesh well with fraud chargebacks and the Bank Secrecy Act.
David:
And so if we're truly trying to have scale and the number of agents who are
David:
able to do commerce freely without frictions, and, you know,
David:
2.9% is also a lot, especially if we go into high volume
David:
microtransactions, there is actually plenty of room for the efficiencies of blockchain rails.
David:
And it's not to say that like, oh yeah, AI agents can use blockchain rails to
David:
like commit fraud and get around the bank secrecy act.
David:
It's just about the inversion of the rules where because there are chargebacks
David:
on Visa, there therefore needs to be fraud departments and like all of these things.
David:
So it's not about like AI agents can commit fraud on blockchains uh they can
David:
they probably will i should probably assume should assume that but it's still
David:
going to be like a minority of global use cases just because of the nature of the
David:
different properties between blockchain commerce and uh visa mastercard commerce
David:
and so there i still think there is plenty of room for
David:
AI blockchain commerce to exist. All right. So this week, I think is the first
David:
week that we are talking about robots, but I think there's a natural synergy
David:
between artificial intelligence and robots.
David:
I don't think I need to explain how those two things go together,
David:
other than it's scary and I'm scared about it. But Josh, maybe tell me what's
David:
going on in the world of AI-ridden robots.
Josh:
I actually, because this is the first time we're talking about robots,
Josh:
I kind of want to set the stage of how big of a deal robots actually are.
Josh:
I think a lot of people see them Yeah, I'm like, oh, this is cute.
Josh:
Like I have a Roomba with arms now and like maybe you can get my groceries.
Josh:
But like the opportunity is way, way bigger than that. And to explain,
Josh:
I want to use Apple as an example.
Josh:
When Apple released the iPhone 2006, I think their market cap was about $70 billion.
Josh:
And at the time, ExxonMobil was the biggest company in the world.
Josh:
They were like $350 billion, not even a trillion dollars.
Josh:
So the perceived upper bounds of Apple, which created these like toy consumer
Josh:
devices that were not really that serious, they were just kind of always like
Josh:
talk to each other, was about whatever the multiplication is on that.
Josh:
Like, let's say a 5x to get to the most valuable company in the world,
Josh:
which was oil and oil ran the world. So that was clearly the max.
Josh:
That was clearly the limit.
Josh:
But fast forward to today, Apple actually hit a $4 trillion market cap because
Josh:
it created an entirely new industry on top of the economy that actually was
Josh:
worth a lot more than oil.
Josh:
The same thing is kind of happening with robotics here. I think you could kind
Josh:
of view consumer or like productive output of an economy based on the productivity
Josh:
per workforce times the workforce.
Josh:
And what we're going to see now with robots is that the workforce number will increase.
Josh:
Will expand exponentially. And now our workforce will be reflective of not just humans, but robots.
Josh:
And the thing with robots is they are much cheaper than human beings.
Josh:
So when you are going to your board and you are explaining to them why you want
Josh:
to keep these humans, it's going to be a very difficult argument to have when
Josh:
the cost per robot is significantly cheaper.
Josh:
So there's this forcing function of like, hey, robots are much better,
Josh:
they're much cheaper, and they create a lot more productive output than us.
Josh:
And also they will decrease the cost of goods because the actual cost of employment is so much lower.
Josh:
So robots is a really big deal. And I think we'll probably see like the perceived
Josh:
limit now, let's say it's Apple at $4 trillion.
Josh:
Some robotics company will exceed that. And it will exceed that aggressively
Josh:
because it is replacing a human workforce times X. We don't know that multiple,
Josh:
but we can produce robots much faster than we can make babies that are working.
Josh:
And like that is a big multiplier that I don't think people are taking into account.
Ejaaz:
Josh, steady your horses here for a second. Can I just say, if I also hadn't
Ejaaz:
nerded out about this robot stuff over the last two weeks, I would think you're
Ejaaz:
completely insane, dude.
Ejaaz:
I think that the mental block that I... It sounds crazy, but you're so right.
Ejaaz:
The mental block that I was trying to jump through myself when I was like literally
Ejaaz:
reading these news updates and watching these cute and sometimes terrifying
Ejaaz:
robots go berserk. I don't know if you guys saw that video, by the way,
Ejaaz:
of the robot going berserk. I was like, these things aren't real.
Ejaaz:
They're not agile enough. They're not like, surely this is all just CGI.
Ejaaz:
But I think what you're trying to say is we're reaching a point where they're
Ejaaz:
going to be able to basically replace a lot of what us humans can do.
Ejaaz:
Not just that factory work, but like cleaning the dishes, going and running errands for us.
David:
Even robots that are one third the speed of a human. If a human is three times
David:
faster than a robot, that robot can still work 24 seven and produce the same
David:
output as a human for no money if you own the robot.
Josh:
This is happening. There is no reality in which the robots that you're seeing,
Josh:
even if they are a little AI enhanced, will not exist.
Josh:
They will absolutely exist. They will have human capabilities.
Josh:
They will have narrow band robots. They will have general band robots with hands
Josh:
and with the proper function that humans do.
Josh:
This is happening. Absolutely.
Ejaaz:
Josh, how much is this going to cost me? How much is it going to cost me? Is it the cost of a TV?
Ejaaz:
Like a 52 inch TV back in the day?
David:
What are we talking about?
Josh:
Well, it depends on how it's going to cost you, but it comes in different ways.
Josh:
So there's the cost of the actual robot. If you want a personal assistant,
Josh:
that will hopefully start at like 40, 30 to $40,000. We're seeing a few early
Josh:
versions of that and then rapidly decrease.
Josh:
But I think a lot of the effects that people don't recognize is the robots that
Josh:
are outside of your apartment, outside of your house, the ones that are working
Josh:
in factories that are working significantly cheaper, but significantly more
Josh:
efficiently that decrease the cost of goods.
Josh:
So if we do have essentially an infinite workforce that is infinitely capable
Josh:
and infinitely energized and infinitely patient,
Josh:
Then they can be working 24-7, 100 times the efficiency that we are,
Josh:
and decrease the cost of goods sold across every single medium.
Josh:
So perhaps it costs you tens of thousands of dollars to get one in your house
Josh:
initially, but that cost goes down.
Josh:
And also the cost of goods that you buy outside of your house will go down significantly.
Josh:
And this is kind of this paired with AI. So you have these smart robots that
Josh:
are getting increasingly intelligent. They're able to replace the human need
Josh:
throughout our economy.
Josh:
We'll probably decrease the cost of a lot of things really, really rapidly.
David:
And it's probably worth noting that there are already robots out there um waymo
David:
is a robot that is a robot car and that is that is doing the job of a human
David:
person driving other people around and then i've also seen
David:
um i think we've all seen like these little robot like uber eats food carriers
David:
where you put the you put the food in the little robot the robot drives just
David:
wheels itself over to the the destination and then it drops off the food and
David:
it's also got a little face on it but it looks like a
David:
box with wheels nonetheless a robot and that's what drosh is talking about with
David:
these differently form factors for robots and so there's already robots out there
David:
and i think we are seeing the possibility of them approaching a more humanoid
David:
form factor why a humanoid form factor well because the world is the world is
David:
a human form factor because we've built the world to
David:
to work with a humanoid form form factor and so that's to be expected i have
David:
not i haven't seen seen personally a waymo but i know that they're all over
David:
san francisco i haven't personally seen a food carrier robot
David:
But I don't know if you guys have, but I'm willing to bet us three and all the
David:
listeners over the next three years, we're all going to have our,
David:
oh, there's my first robot that I see out in the wild moment.
David:
And we're all going to pop our robot cherry by like, oh, a robot just delivered
David:
me some product or service.
David:
And now that's just going to become ubiquitous in a very short order after that.
Josh:
A helpful framework for thinking about it is all of the AI that we talk about
Josh:
that's really exciting on the show, robots are the physical manifestation of
Josh:
that. So robots are AI applied to reality.
Josh:
And I think the opportunity and the craziness that we're going to see of this
Josh:
crazy AI that we discuss every single year applied to the physical meat space
Josh:
that we live in is going to blow minds. And it's increasing as rapidly as AI is itself.
David:
Hmm i feel like this is just turning into the doom show this is the
Ejaaz:
Doom show yeah i don't think it's.
Josh:
Really exciting to me that gets me fired up yeah we're gonna have a
Ejaaz:
Bunch of robots hang on a second we're just talking about people you know meta
Ejaaz:
disconnecting people and you know giving them ai friends and now what is it
Ejaaz:
going to be an ai robot friend like hell.
David:
Yeah i want a robot probably
Ejaaz:
Yes yeah probably probably but again this is not the doomer show okay so,
Ejaaz:
what talking about like first interactions with the robot i have seen that delivery
Ejaaz:
career robot david and it looks super cute right um nvidia also like announced
Ejaaz:
that they have this like you know cute little groot robot thing and it's like
Ejaaz:
this tiny little thing that looks like that what's that
Ejaaz:
what's that disney film guys that i'm i'm the one with like the cute robot that
Ejaaz:
roves on mars or whatever it's called,
Ejaaz:
wally yeah yeah okay i'm i'm mocking my age a little,
Ejaaz:
bit Then there's the next level up, right?
Ejaaz:
There's that Black Mirror episode from, I think, season one or season two,
Ejaaz:
where it looks like a dog, but it's trapped with a machine gun on its back, right? I'm pretty sure.
David:
I saw a video of this last week, a dog with a machine gun on its back.
Ejaaz:
Well, that was going to be my next point. Like, China's already got,
Ejaaz:
like, 50,000 of these things in, like, a training camp.
Ejaaz:
And it's, like, practicing, like, shooting practice. I watched this entire video,
Ejaaz:
didn't understand a single word, but I understood one thing,
Ejaaz:
the concept of death, right? And I was like, Jesus, this is crazy, guys, right?
Ejaaz:
But kind of like stepping back, to your point earlier, David, like,
Ejaaz:
Yes, these robots are becoming more humanoid, right? But they're also becoming more intelligent.
Ejaaz:
And to kind of bring this back to like the AI side of things,
Ejaaz:
it's because people are pairing, you know, this AI, which is basically replicating
Ejaaz:
human intelligence with a human kind of like one of a physical form that isn't
Ejaaz:
just a human, it's a robot.
Ejaaz:
One thing that I found interesting is it's not as simple as taking OpenAI's
Ejaaz:
AI model and sticking it in a robot's brain.
Ejaaz:
That actually doesn't work. You have to create different types of models which integrate,
Ejaaz:
different multimodal mediums like vision and translating that into interpretability
Ejaaz:
and then action and understanding and all that kind of stuff.
Ejaaz:
It requires new models.
David:
Right? OpenAI, ChatGPT, all these models, they're all thinking.
David:
It's all thought. It's all cognitive. It's not about senses.
Ejaaz:
Yeah, exactly. It's all characters. It's things that computers today understand, but robots have no idea.
Ejaaz:
They don't know to look at a lamp next to you and be like, yeah,
Ejaaz:
there should be a switch somewhere here that I can flick, right?
Ejaaz:
So right now, I think we're at the GPT-1 or GPT-2 moment of models,
Ejaaz:
right? So we've got NVIDIA releasing, I think the actual model is called Groot,
Ejaaz:
which is like a general purpose thing, but it's very deterministic.
Ejaaz:
So they're saying, hey, robot, when you see this water bottle,
Ejaaz:
it's a water bottle and it's something that contains a liquid.
Ejaaz:
So it's kind of like self-guiding.
Ejaaz:
And then recently this week, I just saw a major update from this company in
Ejaaz:
California, which basically released something called a 0.5 pi model,
Ejaaz:
which is more of a generalist model.
Ejaaz:
And they've put it into their own homemade robot and it can basically move around
Ejaaz:
and it can understand kind of homemade tasks.
Ejaaz:
It could see like your sink for the first time and see that there's dishes in
Ejaaz:
there and be like, I should clean these dishes, like it's got done.
Ejaaz:
So it understands and it interprets and it's kind of like accelerating at honestly
Ejaaz:
a speed that I didn't think was possible like six months ago.
Ejaaz:
Josh, do you have any further insight into how these robotic models work?
Josh:
No, you're so right. A lot of models that we're used to today,
Josh:
they use token-based text models.
Josh:
And text doesn't really apply when you have eyeballs and you have ears and you
Josh:
have sensors outside in the physical world.
Josh:
There's this really great example that I love because it's so reflective of how early we are.
Josh:
And it's the Tesla Optimus robot. And when they first trained it,
Josh:
they didn't have any data on humans. They wouldn't strap cameras to humans' heads.
Josh:
So what they did is they fed it the car's autopilot data. So for the first few
Josh:
months of training, Optimus thought it was a car.
Josh:
And it was viewing walkways as car lanes and it would look for stop signs.
Josh:
And you kind of have to iterate through and train it like, hey,
Josh:
you're not a car, but you live in the same type of reality.
Josh:
And we're seeing exactly like you said, just very early versions of that where
Josh:
the models are starting to get trained. They're starting to collect data,
Josh:
but they haven't really experienced that takeoff moment that we've had in the.
Josh:
General text-based models where every single week we're getting a new frontier model.
Josh:
So I think the curve is slightly further behind, but I'm sure that's something
Josh:
that we're going to be seeing a lot of is a race for data around real world's
Josh:
inputs and multi-sensory, multimodal inputs.
Josh:
And that's something that I think is super important to watch as these robotics
Josh:
companies start to spin up humanoids like this one that we're looking at right now.
David:
As we explore more and more subjects on Limitless, especially in the Monday
David:
interview episodes that Josh and I are going to do, I think one of the big themes
David:
is we are capable of using AI to accelerate innovation in other sectors.
David:
And so generating robot models, we have the AI tools to do that faster now.
David:
And so what might have taken a decade is going to take six months.
David:
Everything's getting faster. And one of the other things that we frequently
David:
bring up on this episode is, are any of your guys' friends using AI?
David:
My crypto friends are, my non-crypto friends are not.
David:
And so they are not even aware of the massive amount of intelligence that's coming into existence.
David:
But they know about it, but robots are just not on their radar.
David:
So telling them that like in three years, robots will walk among us and have
David:
chat GBT level of intelligence, but they are still beginning to grok.
David:
Parts of society are just completely blind to this.
Ejaaz:
I saw this really interesting chart this week, guys. Actually,
Ejaaz:
I think I saw it yesterday, which tracks the visit, visitation and usage of,
Ejaaz:
OpenAI's ChatGPT website.
Ejaaz:
And it's up only during Monday to Friday.
Ejaaz:
And then it stagnates and goes down Saturday and Sunday.
Ejaaz:
Now, there's many reasons why that might be the case. But the major takeaway
Ejaaz:
that I've seen floating around is that people are using it for their work.
David:
For work.
Ejaaz:
Like 24-7 to do a bunch of different things. I speak to a lot of people that
Ejaaz:
are in the non-crypto world that just use AI consistently to generate documents,
Ejaaz:
PDFs or whatever it might be, like proposals or pitches for their kind of sales team.
Ejaaz:
And I think we're just going to see this accelerate even more. like personally and.
Josh:
Professionally a lot of my friends still use chat gpt as google it's an extension
Josh:
of google and that's the extent of it i'd say without them maybe
Josh:
a handful of people that i know actually use it in a further sense than that
Josh:
um the professional thing is is only existent now because we don't have the
Josh:
full stack to actually replace the job so they're kind of
Josh:
they're being the leveraged humans but once that that gap is bridged where they're
Josh:
no longer needed for to create these inputs it's probably the end
Ejaaz:
Do you think people are going to keep critiquing it until suddenly it all falls in place,
Ejaaz:
it feels like one of those suddenly and then all at once moments where people
Ejaaz:
are just going to be like ah it's not good enough it's it's not going to replace
Ejaaz:
me blah blah blah and then suddenly just does it immediately through like some
Ejaaz:
kind of open ai model update and then,
Ejaaz:
it's over basically and everyone kind of flips yeah.
Josh:
Yeah, I think it's kind of what we're seeing with the chat GPT thing.
Josh:
It feels like we have such a superpower being a part of the show or even listening
Josh:
to the show where you're aware of what's happening.
Josh:
So much of the world has no clue how quickly things are advancing.
Josh:
And eventually there will become that killer consumer product,
Josh:
the chat GPT moment for something that affects them.
Josh:
And at that moment, they're going to be like, oh my God, where did this come
Josh:
from? Where did this happen? Has this been going on? And the answer will be yes.
Josh:
But for most people, they're just blissfully unaware of the rate of progress that's happening.
David:
So while the rest of society continues to kind of be behind the curve of learning
David:
about AI, I think for people who like us doing the show and listeners of the
David:
show who are very aware of the growth of AI,
David:
I think it's worth acknowledging that we are also behind the curve on one more
David:
narrow aspect of AI, which is the idea of interpretability.
David:
And so this subject has been going around downstream of this blog post from Dario Amodi.
David:
This came out this month. I just pictured that name. I apologize.
David:
But maybe walk us through this blog post, the idea of interpretability,
David:
why it's important, what the problem is, and why we are behind the curve on it.
Ejaaz:
Sure. So for those of you who don't know, Dario isn't some kind of peasant wandering around town.
Ejaaz:
He is a co-founder of Anthropic, been in ML and AI research and product building
Ejaaz:
for over a decade at this point, and one of the smartest people to be building within this space.
Ejaaz:
And he released this blog post earlier this week around this concept called interpretability.
Ejaaz:
And I'm going to say that word a lot, so I'm probably going to butcher it at
Ejaaz:
some point. But it's this really interesting concept where I think to date,
Ejaaz:
everyone thinks that AI does all this magical stuff, and you'd be right to think so.
Ejaaz:
And so you might then think that the creators of these AI models would be able
Ejaaz:
to explain how the model comes up with the answers that it gives, right?
Ejaaz:
Would you expect that, David and Josh? Like you would expect like,
Ejaaz:
okay, if a model is telling me something, I'm guessing if I go to Sam Altman,
Ejaaz:
he'll be able to explain, yeah, it's because we tune this parameter.
Ejaaz:
And that's why it's able to like give you this particular answer.
Josh:
Intuitively, yes.
Ejaaz:
Yeah, intuitively, right? But in reality, that is not the case at all.
Ejaaz:
All they know is that when they put in these like training methods,
Ejaaz:
and they input data into these models and they get an output,
Ejaaz:
they don't actually know how the model thinks in between from the input to the
Ejaaz:
output beyond the weights that they've kind of designed.
Ejaaz:
And the analogy here would be, I think in software, you know what comes out
Ejaaz:
of the system because humans deterministically
Ejaaz:
code the paths that that software is going to execute on.
Ejaaz:
But AI models are more like emergent organisms. They're kind of like a bacterial
Ejaaz:
culture or when you breed racing horses, for example, you know,
Ejaaz:
you can do your best to kind of combine the best traits for what the offspring is going to be.
Ejaaz:
But at the end of the day, you have no control or idea what the product is going to be.
Ejaaz:
And it's hard to predict the exact thoughts or perspectives that it's going to have.
Ejaaz:
Now, the reason why there's very minimal research on this particular problem,
Ejaaz:
on interpretability, is because it's hard to prove that there's a problem in the first place.
Ejaaz:
So you can't show how the model thinks.
Ejaaz:
So if you can't show how it thinks, how can you prove that it has nefarious
Ejaaz:
or deceitful intent and this leaves us in a pretty dangerous precedence where
Ejaaz:
we're like kind of like okay uh do we trust before verifying the models or only
Ejaaz:
when they kind of fuck up do we then go ah.
Ejaaz:
There's a problem and it's killed like, you know, half the human population,
Ejaaz:
you know, maybe we should do something about it, right?
Ejaaz:
Obviously, I'm exaggerating here, but this isn't something that is kind of unknown
Ejaaz:
right now. So there's this familiar concept in AI models called chain of thought reasoning, right?
Ejaaz:
Which is where the model gets a prompt and it like goes through its kind of
Ejaaz:
reasoning process. I'm simplifying it quite a bit and probably Josh can get
Ejaaz:
into the nitty-gritty of it.
Ejaaz:
But what they recently found, and we spoke about this on last week's episode,
Ejaaz:
is that the model was lying when it was all like, we went back and forth on
Ejaaz:
like, it was wrong. It was wrong.
Ejaaz:
And the reason why it was wrong was based off this concept of what it believed
Ejaaz:
to be real, true, and reality.
Ejaaz:
And the issue then comes, if you can't prove how an AI model thinks, and.
Ejaaz:
You know, this model potentially is getting things wrong or lying,
Ejaaz:
whichever way you want to look at it, then how can you ever detect what nefarious
Ejaaz:
intent is for these models?
Ejaaz:
And so we get into this kind of weird thing where it's like this AI is taking
Ejaaz:
over more and more responsibility.
Ejaaz:
We talked earlier about how these AI models are going to probably start to influence
Ejaaz:
at the government and nation state level.
Ejaaz:
Maybe we should have something in place to actually understand how these AI
Ejaaz:
models kind of work, right?
Ejaaz:
And so Dario and the Anthropic team have been focused on trying to create kind
Ejaaz:
of like an MRI scan for AI models, but it's very much in its early days.
Ejaaz:
And models have mechanisms very similar to like neurons in your brain,
Ejaaz:
right? When they recognize a car or a horse, very specific neurons,
Ejaaz:
they kind of like light up and say, hey, this is a car.
Ejaaz:
This is a horse. This is a fire. It's hot. Don't touch it, right?
Ejaaz:
And a group of the, I'm almost done with my my tutor session but a group of
Ejaaz:
these neurons is known as like a feature.
Ejaaz:
And emode detected 30 million features manually in a kind of medium-sized ai
Ejaaz:
model but this was just manual
Ejaaz:
but there's probably many many more right the ability to automate the process
Ejaaz:
for detection would reveal all of these things and the thing with features so
Ejaaz:
this group of neurons is that
Ejaaz:
they give more insight into what goes on in a model's thinking so it starts
Ejaaz:
to assess a prompt and all of these wonderful things but i'm just kind of thinking
Ejaaz:
like we should care about this a lot more and i'm kind of curious why no one's
Ejaaz:
kind of like raised this before josh do you have any any takes on this.
Josh:
First that was that was brilliant i learned a lot you did such a great job of
Josh:
describing this entire educate weird wacky world that's happening here
Josh:
um to me interpretability feels like the the quantum physics to general physics
Josh:
it doesn't really make sense it's really spooky and magical and no one really
Josh:
knows what the hell is actually happening so that's
Josh:
that's kind of where I'm at where I don't have any concrete answers or even
Josh:
guesses at what the hell is going on.
Josh:
It did remind me of this interesting thing about
Josh:
transformers and large language models in general which is that they they are
Josh:
at the end of the day they're token predictors
Josh:
and the math that we can understand is the basic so basically when when a model creates another token
Josh:
it does this matrix math through a transformer and that math outputs the next token
Josh:
but before that there is these new models will have two trillion different parameters
Josh:
that are all given different weights that result in that one single token so
Josh:
to reverse engineer two trillion different parameters and to understand
Josh:
the the matrix behind how they work That seems almost incomprehensible.
Josh:
And I'm sure there might be interesting ways that there's like now you're talking
Josh:
about neurons and features and and these things are all very foreign to me.
Josh:
So I'm glad Dario is the one who is taking charge of this. He seems very bright.
Josh:
He is the anthropic guy. He's probably well equipped to tackle this.
Josh:
It's just weird. And it seems incredibly important because as these things get
Josh:
more influential, as these things impact more of our lives, we want to understand how it works.
Josh:
But like, I just have no idea how.
Ejaaz:
Well, how do you how do you rebuild intelligence without even knowing the human brain in its entirety?
Josh:
Right? Yeah.
David:
I'm seeing a lot of parallels here to the understanding of the functioning of the human brain.
David:
Specifically, we're talking about the domain of cognitive psychology,
David:
right? Like if you take a cognitive psychology class, you'll just learn how
David:
the brain operates as a computer, like cognitively.
David:
Like some things are the motherboard, some things are the GPU.
David:
Now here's like the eyeballs and how everything kind of like fits together.
David:
And when you also take a like a when you learn about mental health psychology
David:
you will learn about clustering of thought patterns or structuring of neurons
David:
that relate to each other in ways that are atypical
David:
that result in maladaptive outcomes from the person itself and so what i'm seeing
David:
is dario is attempting to
David:
identify clusters of parameters which is all all there's this ancient idea in
David:
psychology called neurons that fire together wire together so
David:
two neurons fire
David:
uh and they they identify the firing of a an approximate local
David:
uh adjacent neuron and when they are firing at the same time they start to move
David:
closer to each other and that's how habits get formed that's how knowledge gets instantiated
David:
And this is all how like good outcomes and bad outcomes for whatever they are,
David:
like patterns get established.
David:
And so if there is a lying or a deceitful or
David:
like consistently incorrect chat GBT, there's going to be maybe a clustering
David:
of parameters that represents a maladaptive outcome that it learned from its training.
David:
And so I think there's a lot of parallels going on here.
David:
And I think what we are really doing is we are trying to map the brain of an LLM.
David:
However, I don't know how this process works. But we once upon a time mapped
David:
the brain in terms of neurons.
David:
And now we have a map of the brain. And we know what parts of the brain deal
David:
with sight and what parts of
David:
the brain represents your foot and what parts represent fear and memory.
David:
And we just did that as a manual iterative process and I think we're just going
David:
to do the same thing with mapping the parameters of an LLM if that's even possible,
David:
which I don't know why it wouldn't be.
Ejaaz:
Yeah, that's effectively it. And that's this whole kind of MRI scan that Dario
Ejaaz:
keeps referencing throughout the piece, that he's trying to basically assess
Ejaaz:
the different parts of the model and what relates to what kind of output.
Ejaaz:
One interesting thing that he mentions in the post is that he's betting that,
Ejaaz:
this MRI scan of interpretability will be achieved within five to 10 years.
Ejaaz:
And in my opinion well in my opinion it's because there's so little research
Ejaaz:
and that is an issue if the 2027,
Ejaaz:
agi article right two episodes ago comes out in two years so
Ejaaz:
the point he makes is that damn this is a by the way this is a problem we should
Ejaaz:
really focus on and we should really get it done before agi is achieved because after agi is achieved
Ejaaz:
there's there's no you can't The door is open. It's done. There's no one doing it.
David:
The window of plasticity has shut. I think we should all kind of take a step
David:
back and reflect on what this AI industry is doing when you zoom all the way back out.
David:
And there's an idea out there that what is the healthcare industry doing?
David:
You have doctors that are trying to cure cancer. There are other doctors that
David:
are trying to cure heart attacks. There are other doctors that are trying to
David:
fix Lou Gehrig's disease.
David:
When you sum it all together, what is healthcare doing? And the answer is,
David:
it is trying to learn how to make us live forever. It is trying to fix all disease.
David:
Not any one doctor thinks that they are trying to make anyone live forever,
David:
but if you are sick and dying, you go to the hospital and they try and stop you from dying.
David:
And when you sum it, the whole entire vertical of health, it is trying to figure
David:
out how to win longevity.
David:
I think we can apply that same structure of thought to AI.
David:
What is all AI trying to do? what are all AI models and AI labs and all of this stuff trying to do.
David:
We are trying to create life. We are trying to create a new form of life,
David:
a secondary non-carbon-based life form.
David:
And all of these things are coming together. And so this idea of the cognitive
David:
psychology of AI models, I think it's going to become extremely important because
David:
that is our ability to understand this life form that we are creating.
David:
And we, through this black box model of creating AI, are leaving bugs in the parameters.
David:
There are exploits and bugs and lies and moral imperfections left in these parameter sets.
David:
And we need to like go in and like fix those things before that window of plasticity
David:
shuts and the way that life exists is the way that it will exist and it's like
David:
we are unable to undo it. That's what I see when I see this.
Josh:
That's good. We're kind of programming the DNA of the next form of intelligence.
Ejaaz:
Well, let me ask you guys this. Whose lives matter more?
David:
I don't think you can moralize about it. Life is life.
Ejaaz:
Yeah. Yeah.
David:
I mean, AI life doesn't exist yet. So right now, humans, and we should be aware
David:
of that. But in the future, there is going to be indistinguishability between
David:
what life means between whether it's carbon or silicon.
Ejaaz:
And if you have this hyper-optimized form of life that will almost always outcompete the,
Ejaaz:
pudgy, flesh-ridden humans, then maybe we just end up living in a world full
Ejaaz:
of hybrid human robots or just robots on its own.
David:
The hybrid human relationship i think is the best outcome and the outcome worth
David:
striving for the because there's also the outcome where uh it's just the robots
David:
and the humans are are ants as we are ants as it relates to ants to humans except
David:
the robots are the humans now
Josh:
The the human robot connection feels like base case um that feels like the that
Josh:
will certainly happen And we're seeing that with neural link brain to machine
Josh:
interfaces that is happening.
Josh:
It's the, it's the, are we a bootloader for intelligence? And we appreciate
Josh:
our meaning that is like the scary case.
Josh:
So it will exist somewhere along that spectrum, but base cases,
Josh:
absolutely. We, we merge with this stuff because it will be so superior to us.
David:
All right, guys, we are going over on time. So, Jaws, I want you to run us through
David:
what we are calling the dopamine section.
David:
So I'm going to read out what are the words here. AI, ASMR, AI agents are redacted.
David:
The girlies are asking GPT for a glow of advice and IQ of AI has jumped 40 points
David:
in one year. Speed run us through all these subjects.
Ejaaz:
Okay, let's hit the first one. So AI ASMR.
Ejaaz:
The point that this video is demonstrating is that both video and sound AI models
Ejaaz:
are getting really, really good.
Ejaaz:
But rather the product of this video is, for those of you who can't see,
Ejaaz:
is a gingerhead Caucasian woman sitting in front of a podcast mic,
Ejaaz:
and she's speaking clearly into it, but she sounds really, really human.
Ejaaz:
And for those of you who have watched ASMR videos, you'll get the idea of what
Ejaaz:
that sounds like in your headphones.
Ejaaz:
And she's basically trolling a bunch of AI researchers.
Ejaaz:
So it's real like nerd fest right now, but she talks about, you know,
Ejaaz:
fine tuning a different data set and all these like nerdy things.
Ejaaz:
But it's just incredibly realistic how like these things are becoming.
Ejaaz:
And I thought that was pretty funny to watch.
Ejaaz:
The next one that's coming up is AI agents are redacted.
Ejaaz:
Now, this is a Carnegie Mellon University company that was started only with AI agents as employees.
Ejaaz:
Now, if you kind of think it went really intelligently and well,
Ejaaz:
because, you know, AI models are incredibly intelligent, you would be wrong.
Ejaaz:
The best performing employee, which was an AI agent, which was Claude specifically,
Ejaaz:
only completed 24% of tasks that was set forth for it.
Ejaaz:
And the tasks that it was given were things that a normal employee working at,
Ejaaz:
your average sized company would do.
Ejaaz:
So reading emails, maybe doing some coding, taking some calls,
Ejaaz:
messaging other employees to say, hey, here's the update from my end.
Ejaaz:
And this simulation ran and basically the takeaway is that we're not,
Ejaaz:
quite there just yet. But, you know, it's a it's a funny observation.
Ejaaz:
And I want to check back in in about six months time when these agents are probably
Ejaaz:
way, way, way more intelligent.
Ejaaz:
The third thing here is, I saw this post the other day, and I kind of like laughed
Ejaaz:
because I think like, my kind of interactions with AI has been kind of similar,
Ejaaz:
but just from a different perspective.
Ejaaz:
But it's titled the girls are using chat GPT for glow up recommendations.
Ejaaz:
And the results are pretty good. So what we see here in the snapshot is this
Ejaaz:
girl asked ChatGPT, how can I improve my appearance? And she just posts a picture of herself.
Ejaaz:
And then ChatGPT gives her an AI edited glow up version of what she could look like
Ejaaz:
with annotations of what she could do to herself, like dye your hair,
Ejaaz:
chocolate brown, use a peachy lipstick and blush and use bronze eyeshadow.
Ejaaz:
And then she did all those things that it suggested and posted her glow up feature there.
Ejaaz:
And it got apparently like a pretty crazy response from people being like,
Ejaaz:
hey, this is like pretty cool or whatever. So I don't know about you,
Ejaaz:
but I'll probably stop looking in the mirror and just start doing this going forwards.
Ejaaz:
And the final point here is the IQ of AI has jumped 40 points in one year.
Ejaaz:
Now, this is basically a measure of the IQ of these different AI models.
Ejaaz:
And if you were to extrapolate this out going forwards, it's basically these
Ejaaz:
things are going to become much smarter than humans on average.
Ejaaz:
And this is an on average take in probably about a year and a half time, right?
Ejaaz:
And whilst this isn't like kind of like a fancy, cool thing to look at,
Ejaaz:
it's just something to keep in mind that these models are getting way more intelligent than you think.
Ejaaz:
And for all the critics that are saying, hey, it doesn't understand the nuance
Ejaaz:
of this, or it just doesn't understand my personality, we're going to reach
Ejaaz:
a point where these AI models and AI agents understand you way better than you
Ejaaz:
understand yourselves.
Ejaaz:
And that should be expected more imminently than it is a far off kind of dream.
David:
Maybe to drive the point at home about how big 40 IQ points are,
David:
10 IQ points is one standard deviation.
David:
Four standard deviations, because of 40 IQ points, means that AI models have
David:
surpassed from going from the bottom 0.003% of the population to the top 99.997% of the population.
David:
That happened this year.
Josh:
In one year.
David:
In one year.
Ejaaz:
Crazy. Wow.
David:
Guys, we covered a ton in this AI rollup. I love these episodes.
David:
I learned a lot from you guys. See, Joss, thank you for helping us put the agenda
David:
together. And Josh, thank you for your takes as always.
Ejaaz:
Awesome.
Josh:
It was a pleasure. Another great week.
David:
Yeah, this is no longer the Bankless Podcast, so I don't know if I have to give
David:
a crypto disclaimer. This is the Limitless Podcast. The future is weird.
David:
The future is risky. And that is why we are doing these episodes to help us
David:
all stay ahead of the curve.
David:
And we are glad you are joining us on this journey into the frontier of technology
David:
and AI. So come back next week.
David:
Subscribe to the podcast if you have not already. Subscribe to the YouTube if
David:
you have not already. make sure to give us a five-star review so we can grow
David:
this podcast and push it to the frontier of podcasts where this podcast deserves
David:
to be limitless nation i guess uh we'll see you in seven days
Ejaaz:
See you guys see you.
Creators and Guests
