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.