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Exploring the frontiers of Technology and AI
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.