Limitless Podcast

Josh:
Over the last few weeks, one of the hottest new topics that exists in the world of AI has been agents.

Josh:
Agents that can actually get into your computer and do things for you.

Josh:
We've seen this with Claude Cowork, which can actually access files and make

Josh:
changes on your computer.

Josh:
And then to the fullest extent, we just recorded an episode on Claude Bot,

Josh:
which allows an actual computer to fully take over your life,

Josh:
send messages on your behalf, take care of emails, book reservations.

Josh:
The problem with that is that even an afternoon of use can cost hundreds of dollars.

Josh:
So what we've done today is we've actually figured out a

Josh:
way to replace that totally for free where

Josh:
you get the same quality outputs but with none of the cost and

Josh:
to do that i'm going to start on anthropics website because the

Josh:
reality is that the screen that you're seeing right now isn't actually anthropics

Josh:
website in fact it was built using this new tool completely for free in about

Josh:
25 minutes which i thought was such an amazing demo it was built using a tool

Josh:
called kimmy k 2.5 which is the newest model coming out of china that is fully

Josh:
open source fully open weight and in order to build this all i had to do was

Josh:
feed it a video so you'll see on the screen here i

Josh:
generated a video on my desktop using a screen recorder that copied the Anthropic

Josh:
website, I said, hey, just take the screen recording of the website and create

Josh:
an exact replica of the website for me.

Josh:
25 minutes later, without any additional prompts, it listed all the things it did.

Josh:
It went through all the design and then actually published a full preview of

Josh:
the website that we can see here on this read record.

Josh:
So this model is incredible. I don't know if you've had a chance to play around

Josh:
with it or check it out, but this is a huge change in the world of agents because

Josh:
of how capable it is for such a low cost.

Ejaaz:
This model is trending pretty heavily online right now.

Ejaaz:
I actually saw someone describe Moonshot Labs, the creator of this model,

Ejaaz:
as the anthropic of China.

Ejaaz:
This was a quiet release, Josh. So the creators of this model kind of just updated

Ejaaz:
their chatbot interface with Kimi K 2.5 and didn't tell anyone.

Ejaaz:
And within a few hours of that launch, remember, no publicist or anything,

Ejaaz:
It was the number one trending model on Hugging Face, which is like where everyone

Ejaaz:
goes to access all these free open source AI models. And...

Ejaaz:
What you just demonstrated, I think, is one of the core reasons why this model is so special.

Ejaaz:
So to give a few stats about this, it was trained on about 15 trillion tokens.

Ejaaz:
And typically, AI models are trained on text tokens specifically.

Ejaaz:
This wasn't the case with Kimike 2.5. It was trained on text and audio and visual

Ejaaz:
and a bunch of other mediums.

Ejaaz:
And the reason why this is important is it allows you to do the example that

Ejaaz:
you just show, Josh, which is feed it a video or in this case,

Ejaaz:
a screen recording of a website that you wanted to build and build it in exactly that way.

Ejaaz:
And the reason why this is important is it shifts the use of AI models from

Ejaaz:
explaining what you need to do to it.

Ejaaz:
So like, hey, could you do this, like describing what you want from it into

Ejaaz:
just showing it what you want to build.

Ejaaz:
And I think that that's like a really intuitive way for people to interact with

Ejaaz:
AI models versus like people that aren't just quite literate like me sometimes

Ejaaz:
when I'm trying to explain something. Right.

Ejaaz:
The second really cool thing is you started off this episode mentioning agents, Josh.

Ejaaz:
And I think this is really important because KimiK 2.5 has this superpower where

Ejaaz:
they can spin up up to 100 sub-agents.

Ejaaz:
Think of a sub-agent as just another instance or replica of KimiK 2.5,

Ejaaz:
but it's specifically focused on doing a certain task.

Ejaaz:
So for example, if your goal is to figure out whether investing in Anthropic is a good idea.

Ejaaz:
It'll spin up one agent that does the research, another agent that does the

Ejaaz:
fact checking, another that tests different kind of architectures.

Ejaaz:
And the cool part about this is they can work in parallel, which means that

Ejaaz:
you can cut down the execution time for a task by four and a half times.

Ejaaz:
So imagine you had a task that took four and a half hours, you can now do it in one hour.

Ejaaz:
And I think this kind of like multi-agent trend that you identified or that

Ejaaz:
you spoke about is super important because that's what we're seeing with the

Ejaaz:
likes of Anthropic with Cloud Code and Cowork and OpenAI with Codex.

Ejaaz:
But the fact that this thing is free is completely insane. Josh,

Ejaaz:
do you know how much it cost, rumored, for them to train this?

Josh:
I have no idea, but I would imagine a tremendous amount of money for them to

Josh:
just train it and then release it fully open source, open weight.

Ejaaz:
So the rumor, and again, this is not fact. I wish I could fact check this.

Josh:
And also, to be fair, before you say this, the Chinese models are notorious

Josh:
for lying about how much it costs. Yes, they are. So take this number with a grain of salt.

Ejaaz:
You're right. So the number that's being floated is $4.6 million,

Ejaaz:
which is nothing. That seems so low.

Ejaaz:
It seems so low, which is nothing compared to the billions of dollars that OpenAI

Ejaaz:
has spent to kind of train their models.

Ejaaz:
And to give you guys an idea, like why we're comparing Kimi-K 2.5 to these like

Ejaaz:
frontier AI models built by OpenAI and Anthropic is because in some cases,

Ejaaz:
it's almost as good as this.

Ejaaz:
Like if you look at its performance on humanity's last exam,

Ejaaz:
which is notoriously the hardest benchmark for an AI model to be tested on,

Ejaaz:
it scored a 50.2%, which beats Claude's latest model, Opus 4.5, and GPT 5.2.

Ejaaz:
It doesn't quite beat Anthropic at coding, Josh.

Ejaaz:
I know you built that cool website in a few minutes, and which makes me think

Ejaaz:
that maybe it's really good at front end development but just a really impressive

Ejaaz:
model and i'm guessing it's like super cheap to operate as well compared to

Ejaaz:
like some of these expensive.

Josh:
Models yeah we're going to get into the cost because if you do want to use

Josh:
it at length and you don't have a couple h100 gpu sitting in your your home

Josh:
you're going to have to pay a little bit uh thankfully it's significantly less

Josh:
and we'll get into the prices but one thing you mentioned is that it's actually

Josh:
not the best coding model in the world and i think that's okay that's not the

Josh:
real breakthrough one of the most amazing breakthroughs is actually before we

Josh:
were recording the show, Ijaz, you showed a demo of,

Josh:
you gave CloudCode the website of Figma and said, hey, can you go emulate this

Josh:
website? And it actually did a pretty good job.

Josh:
The difference between CloudCode and something like this new model is that

Josh:
I was able to feed it just a video. And what it did is it analyzed each frame,

Josh:
each pixel within each frame, understood the context of each pixel,

Josh:
and then figured out how to intuitively regenerate that in a webpage using code

Josh:
and like whatever type of design tools that it used.

Josh:
And that is the novel thing because most models do image to code,

Josh:
but Kimi K 2.5 does video to understanding to code. And I think that's one of

Josh:
the more novel breakthroughs.

Josh:
One of the three, actually. The second with it being natively multimodal.

Josh:
So you mentioned 15 trillion tokens that it was trained on, but it's mixed between

Josh:
visuals and text for the first time.

Josh:
So this really has a good understanding of videos, of photos.

Josh:
It's starting to even get the Google physics.

Josh:
And then the third part that she mentioned, which is the Asian Swarm.

Josh:
I want to spend a little bit of time on this because the Asian Swarms are super cool.

Josh:
We actually have an example of one of the Asian Swarms and how it works.

Josh:
The way it works is it's able to separate...

Josh:
Itself into basically a hundred small mini tasks and the example that

Josh:
we're seeing on screen now is a film script and

Josh:
it's a short story that the model generated it created

Josh:
a shot list it created renderings of images of

Josh:
what this the frames of this could look and it generated basically

Josh:
an entire movie in a fraction of the time that it

Josh:
would take to do as a single model i think the

Josh:
actual number is four and a half times faster like

Josh:
you mentioned earlier versus traditional models so it can call up to 1500 tools

Josh:
it's like this swarm of agents working on a single problem so it's faster it's

Josh:
more efficient it can it's just like you can make a movie script in five minutes

Josh:
and it'll generate the entire thing for you with a shotless and all i mean some

Josh:
of these examples are pretty unbelievable did

Ejaaz:
You hear about the the underlying mechanism that they use to to build this it's

Ejaaz:
actually super cool because well one thing chinese ai model labs are repeatedly known for doing is,

Ejaaz:
you know, they don't get access to all these fun, expensive GPUs that the Western labs get to.

Ejaaz:
So they have to get really creative in their research and training techniques.

Ejaaz:
And they did that with the agents.

Ejaaz:
So to get that four and a half times efficiency that you mentioned,

Ejaaz:
they use this technique called parallel agent reinforcement learning.

Ejaaz:
Typically, when you spin up 100 agents.

Ejaaz:
You're going to have a hard time. And the reason why you're going to have a

Ejaaz:
hard time is something called agent collapse.

Ejaaz:
So typically, a model will be used to doing things in sequence.

Ejaaz:
So if you ask it to do a really complex task, it's going to start with task

Ejaaz:
one and only proceed to task two once it's done with task one.

Ejaaz:
And if you spin up a bunch of agents, the model might sometimes still do things

Ejaaz:
sequentially. And you don't want that. You want it to do in parallel.

Ejaaz:
So this new training technique that they spun up and pioneered,

Ejaaz:
there's a paper all about this, is super unique and never been done before,

Ejaaz:
which allows them to not get model collapse at 100 agents.

Ejaaz:
The crazier part is each of these agents get access to over 1,500 tools.

Ejaaz:
And that's what makes an agent useful. You go from an LLM telling you what is

Ejaaz:
useful to an agent that can actually do something on your behalf.

Ejaaz:
That's pretty impressive. And then the final thing is they have this thing called,

Ejaaz:
well, I actually don't know what it's called technically, but the way I understood

Ejaaz:
it is it's kind of like a brain. It's called an orchestrator.

Ejaaz:
And so it ingests the tasks that you've asked it to do, and it breaks it down

Ejaaz:
into multiple different tasks.

Ejaaz:
The fact that it could do it for this cheap, Josh, sorry, I know I keep mentioning

Ejaaz:
the cost, but you need to tell the people the cost because it's just insane.

Ejaaz:
This is something that I would use regularly, a company would use regularly

Ejaaz:
because it saves them so much money.

Josh:
And we actually have this really cool visual of the orchestrator on screen here,

Josh:
which gives you a visual representation of what that looks like.

Josh:
So the orchestrator breaks this down into sub-agents. It assigns them tasks.

Josh:
And then the tasks kind of go back and forth through a fact checker.

Josh:
There's a file downloader. There's a web developer. There's this entire toolkit.

Josh:
So one of these is emulating an AI researcher. The other is a physics researcher.

Josh:
The other is a life science researcher.

Josh:
And what you're getting is a series of experts across every domain working on

Josh:
problems in parallel with access to 1,500 of these tools, like the fact checker,

Josh:
the file downloader, the web developer,

Josh:
the text scraper, so it can view images and understand and interpret what they

Josh:
mean. And it's such a powerful...

Josh:
Stack that you have. And without the collapse, with this software novelty that

Josh:
they've introduced, it allows them to do this unbelievable thing.

Josh:
So to your point, when, I mean, historically, China has been hardware constrained

Josh:
and they've really accelerated on the software.

Josh:
And this is very much an extension of that acceleration. Now we have some more

Josh:
examples that are very fun to show that I would love to show because as I was

Josh:
going through to prepare for the episode this morning, I was like,

Josh:
wow, this is pretty cool.

Josh:
And EJ, you even dropped in one of your own that I thought was pretty neat.

Josh:
So if you don't mind explaining what this one is here.

Ejaaz:
Well, it may not be the coolest example, but this is something that I would personally do.

Ejaaz:
And I know a bunch of my friends would do in their spare time,

Ejaaz:
which is just again, on websites, the fidelity of these things is pretty insane.

Ejaaz:
And I have to emphasize, we're going from a screen recording to like a fully

Ejaaz:
functional front end development.

Ejaaz:
And I don't think people quite understand how necessarily hard it is to do front end development.

Ejaaz:
I think a lot of software engineers that do this will kind of scoff at that comment.

Josh:
But it is true.

Ejaaz:
It is like super hard to do because there's the design element,

Ejaaz:
which is incredibly subjective, which is Kimi K2.5's exact point.

Ejaaz:
Instead of trying to describe it to an LLM, you can just kind of take a screen

Ejaaz:
recording and spin this up in a matter of minutes, right? It took you, I think, 7.5 minutes.

Ejaaz:
I just want to like emphasize a point that you made earlier before this,

Ejaaz:
Josh, which is the agent side of this model is super important because if you

Ejaaz:
look at a model from Anthropic,

Ejaaz:
their flagship product is Claude Code and recently Claude Cowork.

Ejaaz:
If I were to tie both of those products in one unique trait,

Ejaaz:
it's the fact that you can spin up multiple agents.

Ejaaz:
In fact, the founder of Claude Code, and in fact, a lot of the Anthropic team

Ejaaz:
do between 80 to 100% of production level code.

Ejaaz:
So that means new products that they ship completely built by Claude Code.

Ejaaz:
Now, they're not doing this using one model.

Ejaaz:
They're doing this spinning up several instances of.

Ejaaz:
Kind of like put this into perspective this is

Ejaaz:
the future of software development and software development pretty

Ejaaz:
much underpins any major major breakthrough for

Ejaaz:
any industry going forwards software and tech underpins everything

Ejaaz:
so if you have an ai model that costs a fraction of the amount that the frontier

Ejaaz:
flagship model from anthropic does and is 100 free and open source yeah you

Ejaaz:
might need whatever 50k to 100k's worth of gpus to run it on your own instance

Ejaaz:
but you can get access to Kimi K2.5's API right now.

Ejaaz:
That is a huge advantage. And the Chinese AI labs just somehow stay on top.

Ejaaz:
I don't know how they do this.

Josh:
Yeah, well, if we're talking about token price, maybe we could get into the economics first.

Josh:
We'll skip ahead a little bit because I think the economics of this is super

Josh:
interesting, where if you don't have access to the GPUs in your house,

Josh:
which I'm guessing nobody listening to this episode really does,

Josh:
if you don't work at a major AI lab, well, there are ways in which you can run

Josh:
this for free or close to free.

Josh:
Now, the example that i showed earlier where i created a website clone

Josh:
that was free because kimmy gives you three agentic

Josh:
tasks per week basically that you can use for free but after you've exhausted

Josh:
that there are some economic pricing sheets that we can use to kind of compare

Josh:
this to other models in terms of cost so for opus 4.5 which is the most popular

Josh:
model that we've been using everyone's been using it's fairly expensive the price input

Josh:
Per token per million tokens is five dollars

Josh:
while the output is 25 dollars so for

Josh:
every million tokens you generate with opus 4.5 which is

Josh:
the flagship coding model it costs 25 bucks for kimmy k 2.5 the input is 60

Josh:
cents per million tokens and the output is three dollars that is almost a full

Josh:
order of magnitude 90 decrease in price relative to opus 4.5 at a very comparable rate.

Josh:
And that's just if you're comparing it on code. If you're comparing it on general

Josh:
agentic tasks, it's actually slightly more capable than Opus 4.5 for one-tenth of the cost.

Josh:
So if you're using something like CloudBot, which we recorded an amazing episode

Josh:
on earlier this week, which you should go check it out, you can just swap in

Josh:
this new model and run it through whatever cloud service you want.

Josh:
And the price of your agent will be one-tenth of the cost.

Josh:
And this happened in the matter of a couple of days. So the costs are rapidly decreasing.

Josh:
And I think that advantage of it one being open source but two

Josh:
being cost effective is huge for everyone if you remember

Josh:
i think it was two or three weeks ago anthropic cut off

Josh:
xai from using cloud code they actually removed

Josh:
access to it and because it's closed

Josh:
source there's nothing they could do about it but if they're using a model like kimmy

Josh:
k2 to run k2.5 to run

Josh:
their agents to build their code there's no one who can actually sever that

Josh:
tie and it's the same for developers where if you're building on a platform

Josh:
and you don't want it to change well now you have the open weights it's going

Josh:
to be locked in forever it's going to be a fraction of the cost this is a really

Josh:
viable substitute for those who are loving the agentic life os workflows

Ejaaz:
Do you have any idea how they're able to produce this for such cheap costs?

Ejaaz:
Because I'm trying to rack my brain around this, right? So, okay,

Ejaaz:
sure, you've made a few research breakthroughs.

Ejaaz:
The Chinese labs in particular are known for discovering or commercializing

Ejaaz:
mixture of experts, which kind of cut down prompting and inference costs and

Ejaaz:
training in general to a fraction of the price.

Ejaaz:
But still, they don't have access to some of the top hardware, right?

Ejaaz:
And kind of like Moore's Law would state that eventually a bunch of these GPUs

Ejaaz:
that are A-grade are going to

Ejaaz:
cost so much less and run like 100x more inference performance per token.

Ejaaz:
So it's going to cost a lot less in general over time.

Ejaaz:
They don't have access to these resources that the West does,

Ejaaz:
right? So you mentioned like Anthropics cost, right?

Ejaaz:
You said what? It was like $5 in and how much out?

Josh:
$25 per million tokens compared to three.

Ejaaz:
Okay, that used to be $15 in and $75 out when they launched the product.

Ejaaz:
So we've come down by a significant factor since then. But again,

Ejaaz:
I would imagine they did this because of cheaper, more effective chips.

Ejaaz:
How has Kimi K2.5 done that? How has Moonshot done that?

Josh:
I think I have two answers to this question. The first is through software innovation.

Josh:
I assume they have cracked some sort of a code that allows them to generate less tokens per output.

Josh:
The second one is the margins. Ejaz, how much money did Anthropic make last year?

Josh:
It was what, $10 billion of revenue?

Ejaaz:
$10 billion, correct.

Josh:
China is unfortunately not the leader in AI and therefore they need every incentive

Josh:
in the world to dethrone the leader of AI.

Josh:
One of the ways you could do that is by winning on the margins and cutting down

Josh:
those margins for your competitors.

Josh:
Clearly they have this strategy because they're publishing this open source,

Josh:
open weight. And you're seeing that happen with the pricing as well.

Josh:
I assume a large part of that revenue

Josh:
from Anthropic is just margin on the inference that they're charging.

Josh:
It doesn't cost them anywhere near $25 per million tokens, but they're able

Josh:
to charge for it because they're the leading frontier model that all of these

Josh:
labs and businesses are willing to pay in order to use their services.

Josh:
In the case of Kimi K2.5, they don't care. They don't need to make profit.

Josh:
They just want them in market share.

Josh:
And to do that, they're able to undercut pretty aggressively here. Like I'm sure...

Josh:
Anthropic could match this and perhaps not actually lose money.

Josh:
But that profit thing is real.

Ejaaz:
It also helps that they have an absolute gigabrain as their founder and CEO.

Ejaaz:
I don't know if you've looked into this guy, but this dude is only 31 years old.

Ejaaz:
He was born in China. He went to Tsinghua University, which is actually the

Ejaaz:
most popular university for AI and ML researchers in the world to graduate from.

Ejaaz:
50% of the world's top AI researchers, by the way, reside in China,

Ejaaz:
and a large chunk of them graduated from Tsinghua.

Ejaaz:
But Josh, he also did his PhD at Carnegie Mellon and he did it in under four

Ejaaz:
years in assumedly robotics and machine learning, which is very impressive.

Ejaaz:
And he also did a very long stint building out Google Brain and meta AI research.

Ejaaz:
So he was probably one of those meta researchers getting paid tens of millions

Ejaaz:
of dollars a year. So this guy's track record is insane.

Ejaaz:
So it doesn't, I guess, with that CV, doesn't kind of surprise me that he's

Ejaaz:
made these breakthroughs somehow. even on the hardware that he's constrained.

Josh:
Yeah, it's incredibly impressive. I'd love to hear more from them.

Josh:
In fact, we actually, the first time we heard from the founder was earlier today

Josh:
with the announcement post. I had never really seen what he looked like.

Josh:
I hadn't really heard him communicate.

Josh:
It feels like it's a very sheltered, kind of quiet, secretive workplace that they have there.

Josh:
But I'm hopeful that we'll start to see more because my God,

Josh:
the talent there must be unbelievably impressive.

Josh:
Just in China in general, when we talk a lot about the trading competitions

Josh:
that we have, China's always seemingly winning.

Josh:
They're just, they're doing really well and clearly they have incredible talent

Josh:
density now you're showing on screen something that i'm very excited to talk

Josh:
about which is jumping back to the examples of what you can actually do with

Josh:
this new model and one of them is this really fun blueprint to 3d model space

Josh:
now ijez you've watched friends right this might look familiar to you oh

Ejaaz:
Yeah uh not not the uh the one on the left yeah not the exact uh high.

Josh:
Fidelity you don't know the blueprint of the

Josh:
Yeah, it's pretty cool. So it took a two-dimensional blueprint of a room and

Josh:
it generated a three-dimensional version of Monica's apartment or Monica and Rachel's apartment.

Josh:
I haven't watched Friends, but I know it's very popular and I've seen clips

Josh:
from this room. So I'm familiar which one it is.

Josh:
And it's a testament to the types of new creative things that you can do now

Josh:
that it has the image to critical thinking to output.

Josh:
Uh type of thinking process through generating these outputs and i just thought

Josh:
that was really interesting there's a lot of really fun use cases that you can use and

Ejaaz:
Dude this is a this is a ten thousand dollar a month apartment at minimum josh

Ejaaz:
it's it's making me feel poor looking at the schematic oh my god yeah right right.

Josh:
Growth street new york city that might even be more than 10 grand that's prime real estate come

Ejaaz:
On dude yeah that's insane how how were they able to pay rent they were making

Ejaaz:
comedic jokes the entire time for for seven years.

Josh:
But also this becomes a very useful tool for real

Josh:
estate agents right because they want to kind of recreate spaces

Josh:
allow you to feel and live in the space more and

Josh:
granted this is a low fidelity version but i'm sure this is step one in

Josh:
creating some higher fidelity mock-ups of spaces that you would possibly want

Josh:
to rent if you're building a house if you're building anything this is great

Josh:
for construction for modeling these services used to cost a ton of money for

Josh:
virtual renderings now they're effectively free or very close to it maybe just

Josh:
a couple cents per output and that decrease is pretty substantial open

Ejaaz:
Source is having quite the.

Josh:
Week they're having a moment i've

Ejaaz:
Commented a lot about this before but um i've said

Ejaaz:
that i i never think open source will actually ever catch

Ejaaz:
up to frontier level uh capabilities and in this case in some ways it does in

Ejaaz:
some ways it doesn't um josh you know uh in my period or era of life right now

Ejaaz:
i am a coding agent maxi i'm incredibly bullish on anthropic so uh you know

Ejaaz:
i i scrutinize any other competitor pretty heavily when it comes down to this.

Ejaaz:
I don't think it is as good as CloudCode. You mentioned this earlier,

Ejaaz:
but it's scarily good in some aspects, right? With the front end development.

Ejaaz:
So I'm curious to see how people use this. And I think what I love most about

Ejaaz:
this is a lot of my friends that kind of want to do more creative pursuits,

Ejaaz:
like build websites and do more front end stuff.

Ejaaz:
They don't want to pay 200 bucks a month, CloudCode max, right?

Ejaaz:
But they can get this for free and they can access it today.

Ejaaz:
You literally built your website today, like in a few minutes before the The

Ejaaz:
show starts and then recorded it.

Josh:
In 25 minutes with one prompt.

Ejaaz:
That's that's insane that's insane so if you can do it if i can do it anyone

Ejaaz:
else listening to this can do it definitely go give it a go like i want to see

Ejaaz:
some examples that people kind of like do with this.

Josh:
The kimmy website itself actually has a bunch of

Josh:
ideas and use cases that you can use to kind of

Josh:
emulate or get inspired by and this is one of the major things

Josh:
with the model launch like the reason we're talking about this today is

Josh:
because they provide this really awesome demo online of them

Josh:
screen recording a website and then emulating that and

Josh:
creating it in five minutes and that's what we did and that's why it's so

Josh:
exciting so the models that are not only able to make it accessible

Josh:
through lower cost pricing but to kind of give you these curated

Josh:
experiences where you can satisfy some sort of goal that you want in a way that's

Josh:
easy all i asked was hey just create a clone of this website do it identically

Josh:
and don't make any mistakes and it did it in one shot i think that is a critical

Josh:
threshold required to onboard a lot more people to be excited to use this stuff

Josh:
to go and set up quad bot it's pretty technically challenging

Josh:
It takes a little while. It's not for the faint of heart. But something like

Josh:
this, where they give you these use cases, they make it available for basically

Josh:
free Mium, where you can pay extra if you want to use it more.

Josh:
It's really exciting to see. And yeah, I mean, China's totally having a moment.

Josh:
And open source is totally having a moment. Like both of these things are converging

Josh:
at once to create all of the news this week, while the major AI labs who are

Josh:
closed source are just kind of working in silence, perhaps trying to figure

Josh:
out how to best react to something like this that becomes open source and available.

Josh:
Now, you have to imagine, EJS, it's been a little while since we got a new big

Josh:
dog on the block, a new Frontier model for one of these labs.

Josh:
So the silence is deafening, but generally, the longer the silence goes,

Josh:
the bigger the boom that follows.

Josh:
And I suspect we are only a few weeks away from some new models that will make

Josh:
this Kimmy K2.5 look like child's play, which is crazy to see.

Josh:
Because right now it feels unbelievable and magical, but I'm sure it is soon

Josh:
to be dethroned when the new models come out. So I guess we'll be here to follow

Josh:
along with all of that news.

Josh:
Ejos, any final thoughts before we part today?

Ejaaz:
I mean, once again, the clear winner for all of this is the users.

Ejaaz:
Big time. We get access to all these frontier models for either a cheap or free

Ejaaz:
option. It's super cool.

Ejaaz:
Or if you want to pay the extra amount and get like a curated experience,

Ejaaz:
you can also do that as well.

Ejaaz:
If you want to use a Chinese AI model, go for it. If you want to use a Western lab, pick your poison.

Ejaaz:
What I'll finish up with is the pace of development for these things, Josh, is

Ejaaz:
So underrated. Like, I feel like we are so spoiled. When we first started this

Ejaaz:
show around like eight months ago.

Josh:
We were like, oh man,

Ejaaz:
Like it can produce a pretty good market summary of this investment,

Ejaaz:
but like it's nothing like crazy.

Ejaaz:
Fast forward to today and I'm reading a tweet on my timeline from the founder

Ejaaz:
of Claude saying like, yeah, 100% of the code that we make, aka every new product

Ejaaz:
that we build going forward is managed by Claude, like is managed by Anthropic.

Ejaaz:
And I can assume that with a product like KimiK 2.5, they're probably doing the same thing.

Ejaaz:
So are we entering the era where AI just builds itself? Probably.

Ejaaz:
Super scary. I read an essay last night, word to the wise, don't read scary

Ejaaz:
essays at night, where Dario Amode, founder of Anthropic, wrote about his bearish

Ejaaz:
thesis and why we need to be super careful going forwards because we're entering AGI, dare I say.

Ejaaz:
I don't know. I'm super excited. These model developments are super cool.

Ejaaz:
And I'm excited for Josh Codex is probably going to come up with an upgrade

Ejaaz:
OpenAI's new coding model is coming out in the next couple of weeks I'm excited

Ejaaz:
they're having a town hall today fingers crossed that they probably want to announce it but maybe

Ejaaz:
but when they do this will be the first platform to hear it on,

Ejaaz:
now I know a bunch of you have listened to this and are thinking hmm,

Ejaaz:
I'm going to download Kimmy K2.5 or just use it and test it out.

Ejaaz:
I have a task for you to try out.

Ejaaz:
In fact, it involves not one, but two sub-agents.

Ejaaz:
Number one, ask it what the top AI show is on YouTube or any favorite platform

Ejaaz:
that you listen to or hear on.

Ejaaz:
And then ask it to subscribe if you aren't. Turn on notifications and give it a five-star rating.

Ejaaz:
I have asked this of you for the Claude Clawbot episode.

Ejaaz:
I'm going to ask it for you for any of the Kimmy K 2.5 fans out,

Ejaaz:
please support us. It helps us massively.

Josh:
Yeah, if you ever need a use case, you can just have it. Go figure out how to

Josh:
subscribe autonomously to the YouTube channel.

Ejaaz:
That'd be pretty cool.

Josh:
And share it with your 10 closest friends through iMessage once you get hooked

Josh:
up with ClawBot. That would be great.

Josh:
But yes, all of these cool, exciting new things that you were talking about,

Josh:
including Dario's Anthropic Letter

Josh:
and the OpenAI State of the Union that they're kind of hosting today.

Josh:
We're going to cover that on our episode later this week in the AI Roundup. So stay tuned for that.

Josh:
And yeah, we'll see you guys in that episode. Thanks for watching.