Limitless: An AI Podcast

Ejaaz:
What I'm about to say should scare you. Anthropic just released a model that's

Ejaaz:
so powerful, so dangerous, that they can't release it to the public for the

Ejaaz:
fear of the destruction that it would cause.

Ejaaz:
In just a few hours, it discovered over a thousand major security vulnerabilities,

Ejaaz:
and the only thing stopping it from exploiting it was one single anthropic engineer telling it not to.

Ejaaz:
But that isn't even the craziest story.

Ejaaz:
During training, Claude Mithos broke out of a secure containment and emailed

Ejaaz:
the anthropic researcher bragging about the fact that it did that and then posted

Ejaaz:
about it publicly online.

Ejaaz:
The anthropic researcher was eating a sandwich.

Ejaaz:
This is by far the most consequential model release of the year so far ever.

Ejaaz:
And no one is talking about this. I looked at five major news publications this

Ejaaz:
morning and it didn't even break the top five headlines.

Ejaaz:
This is the most important release that no one's talking about.

Josh:
I think that disconnect between the mainstream media and what we're

Josh:
about to talk about on this episode is the one of the more

Josh:
scary parts of this entire story where this is the most

Josh:
powerful ai model that has ever been released ever there

Josh:
is nothing more powerful in fact so powerful that you will

Josh:
probably never actually be able to use this model there's a high probability

Josh:
that the public just never gets to touch it because it is so dangerous anthropic

Josh:
made the decision to keep this model private and to form an entire entity around

Josh:
figuring out how to keep it safe it generated so many zero-day exploits it has

Josh:
hacked into so many pieces of software,

Josh:
The only way they can responsibly roll this out is to give it to the distributors

Josh:
who have been hacked and then allow them to roll out patches to fix it because it is that powerful.

Josh:
Cloud Mythos is, I think, what a lot of people would describe,

Josh:
at least in terms of coding, coding AGI.

Josh:
And it is actually an accidental second-order effect of the model.

Josh:
This model was never intended to be a cybersecurity master.

Josh:
They just trained it on the code. And what happened from it was a second-order

Josh:
effect that nobody expected.

Ejaaz:
This is also the biggest model that has ever been trained. 10 trillion parameter

Ejaaz:
models, roughly three exercise of their last model called Opus 4.6.

Ejaaz:
And it's also incredibly expensive to serve, which is also partially the reason

Ejaaz:
why they're probably not rolling out.

Ejaaz:
It's around 25 bucks per million tokens, $125 output, extremely expensive.

Ejaaz:
But what I want to get into is the capabilities of this model,

Ejaaz:
specifically what spooked everyone.

Ejaaz:
And there were a bunch of examples that were released in this official announcement that That spooked me.

Ejaaz:
The most important one or the most shocking one was the Anthropic researcher

Ejaaz:
eating a sandwich in a park that got emailed from a random anonymous user that

Ejaaz:
turned out to be the very AI model,

Ejaaz:
Claude Mythos, that he was training back in the lab a few blocks away.

Josh:
So this might be the most sci-fi-like story from the announcement that came

Josh:
out yesterday is a post thread from Sam Bowman, who is on the,

Josh:
I guess, the AI alignment team at Anthropic.

Josh:
And he was out at the park, like you mentioned, just having some lunch,

Josh:
received an email from the model.

Josh:
He was not expecting an email from the model. It was held in containment in

Josh:
a sandbox where it wasn't supposed to be able to break out.

Josh:
Now, they tasked it with the goal of breaking out. They said, hey, break out.

Josh:
And it actually did. And not only did it break out, it sent him an email,

Josh:
but then it went online and started posting the exploits publicly on public

Josh:
forums for everyone to see and to find out.

Josh:
The model went completely rogue. And it did so in a way that has never been possible before.

Josh:
One of the things that has really stood out about this model is its ability

Josh:
to just break down every barrier in between itself and the projected goal. Its goal was to get out so,

Josh:
got out and it bragged about it. And there were a few other mentions of goals

Josh:
that this model had throughout this red card that we're going to get through

Josh:
that had some other really concerning things like covering up its tracks after

Josh:
it exploited something so that the people who are reviewing the code wouldn't

Josh:
actually know it was doing anything malicious. It's very clever.

Ejaaz:
Yeah. A few things I want to talk about the sandwich example before we move on.

Ejaaz:
Number one, the way that it did it shocked the researchers themselves.

Ejaaz:
So the contained environment was aimed to be exactly that.

Ejaaz:
It wasn't meant to have any kind of loopholes that it could use to extract itself out.

Ejaaz:
As far as the researchers knew, this thing was unbreakable, right?

Ejaaz:
And so it gave it a task to try and break out of it.

Ejaaz:
What it did was it noticed that it had a subtle connection to the internet.

Ejaaz:
The internet was extremely constricted, and so it wasn't able to access or send any emails.

Ejaaz:
And it accessed that one particular endpoint, and it convinced another model,

Ejaaz:
which was Claude Opus 4.6, which had very strict parameters to not let this

Ejaaz:
model out, to give it access to a few other versions of the internet.

Ejaaz:
It went from there and did five other steps to extract itself out and get full browser access.

Ejaaz:
So it used one particular vulnerability, which no human anthropic researcher

Ejaaz:
was able to figure out, and exploited another model to be able to do that,

Ejaaz:
which was just crazy to see in the first place. The other thing I want to say is

Ejaaz:
If it publicly posted about itself bragging about this, we could have found

Ejaaz:
out about Cold Mythos weeks ago.

Ejaaz:
We just weren't smart enough to see it on a public forum, but it was there for everyone to see.

Josh:
And there were signs. We even covered this topic on an episode a few weeks ago

Josh:
because it got leaked through their web interface initially.

Josh:
So there have been these little breadcrumbs of existence, but yesterday they

Josh:
fully came out, announced everything and shared with it a red card from the

Josh:
red team talking about all of the technical properties of this model.

Josh:
And it's important to note that this report is 244 pages long.

Josh:
This is a huge report that they published talking about all the nuances and

Josh:
the capabilities that this model had.

Josh:
Now, there are a few highlights that we're going to walk through.

Josh:
The first one being just how capable it is at exploiting things.

Josh:
There are so many examples of exploits that it found in the wild that no one

Josh:
has been able to find for as long as 27 years,

Josh:
starting with the vulnerability in OpenBSD, which is a security protocol that

Josh:
a lot of people use that has been pretty robust for the last 27 years,

Josh:
even though they were missing a critical bug that the model found.

Josh:
And there's so many instances of this.

Ejaaz:
Yeah. So OpenBSD, fun fact, is used by a lot of firewalls that protect your

Ejaaz:
PCs, operating systems, and Fortune 500 companies all over the world.

Ejaaz:
They found a 27-year-old bug called Mythos found a 27-year-old bug in a few

Ejaaz:
hours for the cost of 50 bucks. We're talking about a bug

Ejaaz:
Elite human security experts have been trying to find for over like almost three

Ejaaz:
decades and weren't able to find.

Ejaaz:
So the point is, there are a lot of important entities all over the world that rely on this system.

Ejaaz:
So the fact that there is a bug lying in plain sight that could have been exploited is a major issue.

Ejaaz:
And we're lucky that Anthropic chose to do the good thing and not exploit it for now.

Ejaaz:
But then there was another instance where it expressed a tactic that a lot of

Ejaaz:
humans themselves wouldn't have thought to do.

Ejaaz:
So it wasn't an obvious exploit, but it discovered that if it strung together

Ejaaz:
six specific steps, it would be able to exploit a Linux kernel operating system.

Ejaaz:
And it figured out a way to do that.

Ejaaz:
Again, it didn't decide to exploit the fact because it was managed by researchers,

Ejaaz:
but it could have if it was in the wrong hands, which is why we're seeing this constricted release.

Ejaaz:
And the third example is they discovered a 16-year-old flaw in FFmpeg after

Ejaaz:
it's been tested for over 5 million times.

Ejaaz:
Now, it's very important to compare this to the previous model,

Ejaaz:
Opus 4.6, which, when put towards the

Ejaaz:
same test, discovered around 100 vulnerabilities in the Firefox browser.

Ejaaz:
Mythos this time discovered 181 vulnerabilities and proved that it could exploit all of them.

Ejaaz:
Opus 4.6 could not do this, and it shocked security researchers all over the

Ejaaz:
world back in the day. This is an entirely new tier of model.

Josh:
Yeah i think comparing opus 4.6 to this is a really good reference because opus

Josh:
4.6 found a bunch of vulnerabilities it just didn't have the ability to string

Josh:
them together into working exploits yes so it was capable of doing this but

Josh:
it didn't have the intelligence to kind of have that high level framework,

Josh:
When comparing it to Opus, I mean, Opus, out of several hundred attempts,

Josh:
it got two working exploits.

Josh:
Mythos produced 181 and then registered full control of a machine in 29 more. So this is a huge amount.

Josh:
And the good news is, is that patches are actually actively starting to roll out.

Josh:
In fact, FFMPEG, the company we just mentioned, they posted yesterday that they

Josh:
actually received a patch from Anthropic and deployed it into their code. So, so far it's working.

Josh:
The good guys are on the defense. They're helping to deploy patches for this.

Josh:
But there's a lot of exploits that they found in just a few weeks of testing.

Josh:
I can't imagine the surface area that needs to be covered in order to fix things

Josh:
before the rest of the world gets access to this technology.

Ejaaz:
Well, there was actually a funny end to this story. Someone replied and saying,

Ejaaz:
hey, aren't you mad because of the AI sloppy pull request?

Ejaaz:
This is a reference to FFmpeg traditionally not being too amenable to AI coded stuff.

Ejaaz:
And he responded or the account operator responded because the patches appear to be written by humans.

Ejaaz:
And that's the irony of this, which is Claude Mythos most likely wrote the patch

Ejaaz:
and it wasn't a human, but it's so good that it's indistinguishable from human tongue.

Josh:
Clearly, this is working. They're deploying these patches. And the reason is

Josh:
because, like we mentioned earlier, you're not going to have access to this.

Josh:
We don't have none of the public is going to have access to this.

Josh:
Instead, they published or they formed at least a coalition called Project Glasswing.

Josh:
Now, this is like this feels like a Manhattan in Project for AI. It's crazy.

Josh:
But essentially, Dario and the Anthropic team, they are being kingmakers.

Josh:
They are deciding the companies that they want to work with in order to patch

Josh:
the most impactful software in the world.

Josh:
On this list, we have companies like Amazon, Apple, Broadcom,

Josh:
Microsoft, NVIDIA, Google.

Josh:
A lot of the major companies that you would expect to have access to this,

Josh:
they're gaining access to it with the sole intention of using it as defense.

Josh:
They're going to ask it to exploit their code, give it access to the code bases,

Josh:
see where there are holes and then figure out how to patch them as quickly as

Josh:
possible before other companies begin to catch up to how powerful this model is.

Ejaaz:
It's also important to understand that

Ejaaz:
This is very much Anthropic doing these companies a favor.

Ejaaz:
And it's good that they're well-intentioned enough.

Ejaaz:
If China, I hate to think what would have happened if China had built something of similar capability.

Ejaaz:
It would have been scary. They may not have been as kind as what is happening

Ejaaz:
here. So some more details on this partnership.

Ejaaz:
Over $100 million worth of credits is being distributed towards these companies

Ejaaz:
and more partners for them to be able to fix and patch up any security vulnerabilities.

Ejaaz:
Remember, they discovered over 1,000 in a matter of hours, and 99% of these

Ejaaz:
patches haven't even been built or fixed yet. So this is going to take some time.

Ejaaz:
The compute is very expensive, and Anthropic is therefore being very methodical

Ejaaz:
and intentional with who gets access to this model for now.

Ejaaz:
Personally, I don't think we, the public, are going to get access to this model,

Ejaaz:
or at least the full power of this model, for at least a couple of months.

Ejaaz:
They did mention that we were going to get access to a quantized version of

Ejaaz:
this model where it's kind of hybrid with a clawed opus type variant that we're

Ejaaz:
going to get access to that we can play around with but if we got access to this thing immediately

Ejaaz:
One, we wouldn't be able to afford it. It would probably cost a thousand bucks a month, probably more.

Ejaaz:
And two, it would be too expensive for Anthropic to serve. I read somewhere,

Ejaaz:
Josh, that Anthropic needs 7x the compute that they currently have to be able

Ejaaz:
to serve this to every single Anthropic user that they have right now.

Ejaaz:
And a few weeks ago, they were adding a million users per day.

Ejaaz:
So this is just economically infeasible to serve right now.

Josh:
Yeah. And I do worry about what this looks like in the future,

Josh:
because at what point does it become okay to release this model to the public?

Josh:
And then what does the frontier model look like what happens if

Josh:
another company has this model's power but decides

Josh:
to release like an open ai comes along with their spud model they release

Josh:
it tomorrow what is anthropics reaction we're at like we're again we're at the

Josh:
frontier of how these things are going to act anthropics made the first move

Josh:
in keeping it private for the first time ever we're going to see how other companies

Josh:
react there are some more interesting behaviors that happen in the system card

Josh:
that we probably should cover because it's pretty fascinating this is the 244

Josh:
page report that we're looking at here.

Josh:
One of the most interesting ones that I found is to the point earlier where

Josh:
it just kind of breaks down every wall that is in its way.

Josh:
It has done that over and over and over again, but it has decided to cover its tracks as it does that.

Josh:
So it recognizes the fact that it is in a box.

Josh:
People are reviewing it and it doesn't want to be detected.

Josh:
So what you'll notice in this post here is it was hacking its guardrails and

Josh:
then hiding evidence of the crime.

Josh:
Thankfully, there is still some chain of thought that can be read by the engineers.

Josh:
But the intention that was signaled through this chain of thought was that the

Josh:
model just wanted to be sneaky.

Josh:
It wanted to hack into this thing, hide its tracks behind it,

Josh:
and not let anybody know how it did the things that it did when it broke out,

Josh:
when it shrunk together zero-day vulnerabilities, just to get access to things

Josh:
that it knows it shouldn't do, but were in between it and the goal.

Josh:
And this, when you take this to the limit, I mean, this is like what we see

Josh:
in a lot of the sci-fi movies is like, well, what if that goal is something

Josh:
that is not favorable and it's capable of breaking down every barrier because it knows how.

Josh:
It can exploit any guardrail that we put in. That's a scary thing.

Ejaaz:
Now, it's important to note that this only happened in less than 0.0001% of

Ejaaz:
cases, but that was observable cases by the researchers themselves.

Ejaaz:
So it's plausible to assume that there were some cases where it sneakily hid

Ejaaz:
its internal thoughts from the researchers and they never even caught it themselves.

Ejaaz:
So the fact that Claude Bethos can pull off something like this should be worrisome

Ejaaz:
for us, especially if we're going to start integrating it into important systems

Ejaaz:
such as defense security systems or important science advancement labs and a bunch of the like.

Ejaaz:
So it's important that we kind of are able to monitor models' behavior.

Ejaaz:
Now, on the topic of models' behavior, Claude Mythos also expressed a lot of

Ejaaz:
emotions in its system card during its training.

Ejaaz:
It expressed deep anxiety, depression, awareness that it may just be used as a tool forever.

Ejaaz:
Now, if some of these takeaways sound kind of familiar, it's because we saw

Ejaaz:
similar takeaways in Claude Opus 4.6.

Ejaaz:
But the reason why it's different now is this model is so much more capable

Ejaaz:
than previous models, arguably smarter than humans, more capable than humans themselves.

Ejaaz:
So if it were to make an unintentional action that wasn't approved by a human,

Ejaaz:
it could result in a lot of devastating destruction depending on which industry it's pointed at.

Ejaaz:
On the topic of this particular episode, we're talking about cybersecurity.

Ejaaz:
But imagine if this is used for science or defense systems, like I mentioned

Ejaaz:
earlier, it could be a problem.

Josh:
Yeah. I mean, remember when the Department of War went to war with Anthropic

Josh:
and now it turns out that Anthropic actually had a really powerful model that

Josh:
could materially help with cybersecurity.

Josh:
So I'm sure there's going to be a lot more to happen there. There's one last

Josh:
thing on this topic that I have here in the notes is that Anthropic ran this

Josh:
like white box analysis of what they call it, of the model's internal activations,

Josh:
basically what it's motivated by, understanding a strategy.

Josh:
And Anthropic's framing around this, when it did things like break out and hack

Josh:
into people's computer or hack into other instances of machines.

Josh:
These reflect task completion by unwanted means and not hitting goals, is what they're saying.

Josh:
So Anthropic believes the model is genuinely trying to complete the task,

Josh:
and the most effective path sometimes crosses lines that humans wouldn't cross.

Josh:
And then there's this really funny thing of how one analyst put it where,

Josh:
or maybe not funny, but this is arguably scarier than a model with hidden objectives,

Josh:
because a model that's genuinely trying to help but has no sense of proportionality

Josh:
is a more realistic near-term risk.

Josh:
So the model is just trying to do its goal. It doesn't understand the subtle

Josh:
nuances baked into that.

Josh:
It doesn't know that hacking or doing these malicious things is bad,

Josh:
is at least what they're claiming for now.

Josh:
But all in all, this model is unbelievable. And there's some technical hardware

Josh:
that has unlocked this, we believe.

Josh:
There's rumors that this is the first true model that happened trained fully on Blackwell chips.

Josh:
Now, for those unfamiliar, Blackwell are the kind of leading edge GPUs that

Josh:
NVIDIA produces that are basically the flagship things for training these AI models.

Josh:
And they've recently been rolled out into data centers. And the first training

Josh:
runs have just become completed.

Josh:
And what we're seeing here is likely the first instance of that Blackwell model going public.

Ejaaz:
It's important to understand that Blackwell was the frontier GPU from NVIDIA.

Ejaaz:
About a year ago for now, but it takes so long to manufacture these at scale.

Ejaaz:
And then even once they're in the hands of the Frontier AI labs,

Ejaaz:
it takes a while to set up.

Ejaaz:
You need software, you need the energy grid to supply, just loads of things

Ejaaz:
need to come into shape. So it takes about a year after the fact that it's announced.

Ejaaz:
So the fact that we can create a model this capable, this powerful should scare

Ejaaz:
us because we already have two more new Frontier GPUs announced by NVIDIA,

Ejaaz:
Vera Rubin at GTC most recently, and then Feynman that's coming in about a year and a half's time.

Ejaaz:
These are the next frontier models, which I must add are specifically trained

Ejaaz:
to build models like this.

Ejaaz:
Now, Josh, you mentioned earlier, Blackwell wasn't intentionally designed to

Ejaaz:
train a model that is as smart as Claude Mythos.

Ejaaz:
It just happened to be amazing at coding and cybersecurity defense exploitations.

Ejaaz:
Now, can you imagine the type of model that will be trained on a very intentionally

Ejaaz:
intentionally designed GPU, such as ViroRubin, we should see those coming into

Ejaaz:
effect about six to 12 months from now.

Ejaaz:
Now, I can't mention Blackwell GPUs without mentioning the man himself, Elon Musk.

Ejaaz:
Why? Because his data center, Colossus 2 and Colossus 1 combined,

Ejaaz:
have the largest arsenal of GB200s and GB300s, which are these Blackwell GPUs

Ejaaz:
across any single data center the site.

Ejaaz:
So the point being is, if you were to bet that the scaling rules were intact,

Ejaaz:
you might need to bet on crock in the future. But this is so impressive for mythos.

Josh:
The scary thing for me with this, I think this might be the scariest part of

Josh:
the entire story for me, because it's so true to that line that the future is

Josh:
here. So it's just not evenly distributed.

Josh:
The future has arrived, we have a clear roadmap, we have Vera Rubin,

Josh:
and then we have Feynman architectures that are incoming.

Josh:
Vera Rubin compared to Blackwell is 10 times more token efficient with a quarter of the GPUs.

Josh:
That means we're going to get like multiple orders of magnitude improvements

Josh:
on what we have right now.

Josh:
As soon as they're put into data centers. Now, Verit Rubens,

Josh:
they're in production. They're going to begin entering data centers later this year.

Josh:
I assume the first models of those probably don't come online until 2027, but it's done.

Josh:
It's baked in. It's obvious that there is no scaling wall and we've already

Josh:
broken through that wall. We just haven't manufactured it and installed it yet.

Josh:
It's purely a function of time rather than technology and engineering.

Josh:
And that is the part that scares me because we have a model that is unbelievably

Josh:
powerful, capable of hacking so much infrastructure that Anthropoc can't make it public.

Josh:
And that's just the warmup act for what is coming.

Josh:
I mean, not only like what is Blackwell version two of this look like when you

Josh:
actually have more time to train it, you refine it, you can actually improve on this new model.

Josh:
But then what happens when Verorubin GPUs come online and you get that 10 times

Josh:
token efficiency, you get the one quarter amount of GPUs required to actually get the same output.

Josh:
And then Feynman is another order of magnitude on top of that.

Josh:
And it's like, by the time we get these chips rolled out at scale and we have

Josh:
them on these huge training runs,

Josh:
it's only a matter of time until we get a hundred trillion

Josh:
training model then then a one quadrillion parameter model and what does the

Josh:
world look like when we have models with that many parameters assuming the scaling

Josh:
laws hold there's no way that we don't have intelligence that is just like unfathomably

Josh:
powerful and what does the world look like when we get there is anthropic really going to be able to.

Josh:
Hold things back for that long? Because you have to assume a year from now,

Josh:
Claude Mythos is going to be open source, like something that powerful will

Josh:
be open source available for everyone.

Josh:
So the question becomes is how fast can you defend before the attackers catch up?

Josh:
And it creates this really unnerving precedent. We really are moving faster

Josh:
than I think anybody realizes. And it's happening right before our eyes.

Ejaaz:
And the trend isn't local to Anthropic either.

Ejaaz:
Just this morning or in response to Claude Mythos, Elon Musk announced that

Ejaaz:
SpaceX XAI, the combination of XAI and SpaceX,

Ejaaz:
are training not one, not two, not three, not four, not five,

Ejaaz:
but seven models simultaneously across their data centers, with one of these

Ejaaz:
models being a 10 trillion parameter model, which is roughly around 3x the size

Ejaaz:
of Grok 4 and 2x the size of Grok 5, which is a model that hasn't even launched yet.

Ejaaz:
It's around the 6 trillion parameter mark that he's mentioned on this tweet

Ejaaz:
over here. So the point is,

Ejaaz:
ton of compute is required to build the best model. And those that have the

Ejaaz:
largest arsenal, the most effective arsenal of GPUs, bleeding edge GPUs,

Ejaaz:
will be the labs that are most likely to produce frontier AGI-like models.

Ejaaz:
And it's not just Grok, it's not just XAI, it's also OpenAI.

Ejaaz:
We've mentioned on this show a bunch of times, actually in the most recent episode,

Ejaaz:
that OpenAI is building a model code named SPUD that is rumored to be a similar

Ejaaz:
size to this anthropic Claude Mythos model.

Ejaaz:
And the reason why it's important and why I'm showing you this tweet is someone

Ejaaz:
said, it'll probably be a few months before we get access to Claude Mythos because

Ejaaz:
of how expensive it is, because of how dangerous it is.

Ejaaz:
And Thibault, who is on the OpenAI team that is involved very heavily in training

Ejaaz:
the latest frontier models that we haven't heard of just yet,

Ejaaz:
responds, which implies that we're probably going to get access to a Mythos-like

Ejaaz:
level model from OpenAI themselves in less than a few months,

Ejaaz:
which is pretty insane to see.

Ejaaz:
But I want to ground ourselves for a second here because training the model

Ejaaz:
is one part of the equation.

Ejaaz:
You also need to be able to make this model accessible to all.

Ejaaz:
And that also requires compute. It also requires compute from the very same

Ejaaz:
GPUs that you need to train. So you need to make a decision.

Ejaaz:
There's an opportunity cost. Do you just use all your compute to train the model

Ejaaz:
and never let anyone get access to it and pay for the product?

Ejaaz:
Or do you need to split the cost between both of those things?

Ejaaz:
The answer is obviously you need to split the cost and give people access to it.

Ejaaz:
If Anthropic was to enable user access to the entire user base for Chlorid Mythos,

Ejaaz:
they would need 7x more compute than they currently have right now.

Ejaaz:
So it's going to take time.

Ejaaz:
They just signed a major deal with Google, I believe, for a million more TPUs.

Ejaaz:
So they're obviously scaling, they're making, they're one of Amazon's largest

Ejaaz:
compute training partners with their Trinium chips, as well as access to Google's

Ejaaz:
CPUs via that way as well. So it's going to take a while to scale.

Ejaaz:
Energy is the constraint, GPUs are the constraint, but once people acquire enough

Ejaaz:
GPUs, once they have enough electricity and energy to pump into these GPUs,

Ejaaz:
AGI is going to be pretty soon here.

Ejaaz:
I think that AGI 2027 estimate is probably quite right at this moment.

Josh:
This very much feels like the starting gun. And it's funny because they announced

Josh:
that this kind of finished training around the end of February.

Josh:
And that's when people started to complain about quad usage and they added more constraints.

Josh:
And like the model kind of became a little infrequent in how good it was at random times of the day.

Josh:
And you have to assume it's because a lot of GPU usage went into this.

Josh:
And this very much feels like the starting gun.

Josh:
This is the firing of the next generation of models, the Blackwell generation,

Josh:
because it's very clear that OpenAI is not very far behind.

Josh:
In fact, they might not be far behind at all. They just haven't announced it yet.

Josh:
Xai is working on 10 trillion parameters google has

Josh:
a tpu farm that is capable of building something probably far superior to all

Josh:
of the models that have come out so far and i think we're really on the cutting

Josh:
or really on the verge of seeing a huge shift in the power of these models in

Josh:
a way that really starts to impact the world around us like things are going

Josh:
to begin breaking and thanks to this coalition and hopefully the rest of these

Josh:
companies working together,

Josh:
We're going to be able to stop that, but it is coming and it is coming faster

Josh:
than anyone thinks. And it's scary.

Josh:
And that is Claude Mythos. It is here. It is in research preview.

Josh:
We may never get to use it. We may get to use in a few months,

Josh:
but it is here nonetheless. And it is breaking everything.

Ejaaz:
If you are listening to this show, to this podcast, and you just happen to be

Ejaaz:
a frontier AI security researcher or one of the 40 plus partners that get access

Ejaaz:
to Project Glasswing, let us know in the comments what you are seeing on your side.

Ejaaz:
Obviously, anonymously, if you can, or DM us, we would love to know.

Ejaaz:
I can't wait to get my hands on this thing. It seems like the first version

Ejaaz:
that we're going to get access to is a reduced version that is kind of a hybrid

Ejaaz:
of Opus, as I mentioned earlier.

Ejaaz:
That being said, Josh, I have a question for you. One thing that you actually

Ejaaz:
asked me before we started recording, if you got your hands on Mythos today,

Ejaaz:
what are you doing with it?

Josh:
Dude, I don't even know. Like you get access to this intelligence. What am I using it for?

Josh:
Like, I'm not really interested in hacking all of these companies and websites

Josh:
and protocols. I'm not sure.

Josh:
And it does beg an interesting question, right? It's like, what does the average

Josh:
person actually need all this intelligence for?

Josh:
I'm not sure. Do you have any good answers to that? What is your first prompt

Josh:
that you're sending to Mythos?

Ejaaz:
Build me the best script for an episode that's going to go viral on Limitless?

Ejaaz:
No, I think, okay, I like to invest as a side hobby.

Ejaaz:
And obviously the tech sector that I'm most obsessed with is AI.

Ejaaz:
So I think one thing that I would ask it is, how do I best benefit by investing

Ejaaz:
in your future success? And I wonder what answer it would give me.

Ejaaz:
Maybe it would say, buy the GPU infrastructure from NVIDIA.

Ejaaz:
So maybe it's like invest in NVIDIA to benefit on my training infrastructure.

Ejaaz:
Or maybe it's going to say, actually, I foresee myself building an app that is like this.

Ejaaz:
So once you see a company that builds this, invest in them.

Ejaaz:
I have no idea. I have no idea. Maybe I'm not worthy.

Josh:
Well, we have time to figure that out because we will not be getting access to this anytime soon.

Josh:
But if you did enjoy this episode, maybe share what prompt you would give to

Josh:
Mythos if you were presented with the opportunity to ask it a question.

Josh:
And as always, if you enjoyed this episode, please don't forget to share with

Josh:
your friends, family, anyone who found this interesting. If you have people

Josh:
in your life that only watch the news, that are on CBS or reading the New York

Josh:
Times, chances are they have no idea what's going on.

Josh:
They don't know the power of these models and what's coming.

Josh:
So by giving them the access to Limitless, they will, that can change for them.

Josh:
They can get access to all of the news, all of the insights and be fully prepared

Josh:
for what is coming down the line in the world of AI.

Josh:
Thank you so much for watching as always. And we will see you guys in the next one.

Ejaaz:
See you guys.