Eric Schmidt DROPS BOMBSHELL: China DOMINATES AI!

China now has two of what appear to be the most powerful models ever made and they're completely open.

So that was Eric Schmidt talking about how China has two of the most powerful models and they are currently open source. And in this video I'm going to dive into a lot of his statements. Now the reason why we're diving into Eric Schmidt is because he is the former CEO of Google and he had a recent talk at Stanford that went pretty viable and his statements on AI seem to be shaking up the entire community. So. So let's take a look at some of his recent comments in this recent interview and I'm going to break them down with a lot of information so you guys can understand exactly where the future of AI is currently headed.

This week there were two libraries from China that were released open source. One is a problem solver that's very powerful, and another one is a large language model that's equal in some cases exceeds the one from Meta that they use every day. It's called llama 3,400 billion. I was shocked when I read this because I had assumed that our, in my conversation with the Chinese that they were two to two to three years late. It looks to me like it's within a year now. So it'd be fair to say it's the US and then China within a year's time. Everyone else is well behind.

So of course one of the models he's talking about is deep seek R1. Now if you weren't familiar with this model, this model actually went completely viral. You can see it's got, you know, 2.8 million views, thousand retweets, 4,000 likes, and essentially this was China's version of 01. They called it R1 Lite Preview. And this one was pretty crazy because O1 was a model that nobody saw coming from OpenAI. I mean, I guess you could have seen it if you dug through the research papers, but the fact that he managed to get a working version that is quite similar to 01 and even surpasses it, when we're actually looking at the benchmarks in certain capabilities, it actually shows us that China are not far behind at all. It, you know, Eric Schmidt basically says that he thought China were two to three years behind, but it seems that in AI currently, they are basically six months to a year behind in terms of AI development. And I mean, if this was a closed source lab, some people could potentially argue that this company is ahead in the sense that they're able to get this deployed faster than Google, faster than X AI and of course faster than anthropic.

So.

So this is something that is truly, truly surprising when we take a look at this entire model space and we do have more benchmarks here. And you can see that the purple bar, the one on the left, is surpassing 01 preview, which is the one that is in the green, which is right next to it. So all this is pretty surprising, I'm.

Not going to lie.

Like definitely. Really, really shocking. And I do want to say that this is something that is so surprising that I am wondering what on earth is going on in terms of the AI space, because this was not an update that I expected, if any, anything, I would have expected that an American company would have been the ones to, you know, race forward with development. But I guess that somehow we're here with open source as well. Now, if you're wondering what he's talking about with the other model, the other model is actually quite popular when it comes to, you know, running models on your computer. And the model that he's referring to is Quinn 2.5. Now Quinn is essentially coming from Alibaba's cloud. So this is Alibaba's, you know, company. And of course they have open source. This model called QIN2.5 72B instruct, and it's a 72 billion private model. So it's not extremely large, but it is really, really good at performing certain tasks. And one of the things that we saw here on the Compass large language model leaderboard was that the Quen2572B instruct actually managed to surpass state of the art models like port 2.5, Sonnet, who and GPT4O. So when we do take a look at this entire development cycle and we're taking a look at how quickly these models are developing, seeing a model that's able to do this is one that is truly, truly surprising considering the fact that it was only a few months ago we had 01 preview and we were like, wow, this is something absolutely amazing. Now it's pretty crazy because when we actually look at AI development, we know that China is facing several restrictions recently. When we look at what TSMC did, they recently closed their door on producing advanced AI chips for China from Monday. You can see it says the world's biggest contract chip maker acts to ensure it is in line with US restrictions on Chinese access to latest processors. And basically they're stating here, and if you don't know who TSMC are, they're basically one of the most important companies in AI. They produce, you know basically all of the chips for Nvidia, they basically produce like I think it's 80% of the world's AI chips. I don't know, it's something pretty crazy. But they're basically suspending production of their most advanced AI chips as Washington continues to impede Beijing's AI ambition. So you can see here that there is certain restrictions on what China is able to do when it comes to getting chips from tsmc. And you can see here that TSMC literally said that they've told Chinese customers that they would no longer manufacture AI chips at advanced process nodes of 7nm or smaller. And basically future supplies of semiconductors to TSMC Chinese customers would need an approval process likely involving Washington. Now this is pretty crazy because of course right now TSMC is doing this thing where they've got this extensive export control system. But the crazy thing about this is that this is not the only company that's facing this. But some people, and we can see here on the leaderboard there's actually this model and if you look at rank seven, which is essentially, I guess you could say probably rank four considering it, we've got this model called Yee Lightning and this is actually by this guy called Kai Fu Lee and, and he's actually working with these restrictions and he's stating that look, whilst yes, previously training runs used to cost billions of dollars, even though there are certain restrictions, companies like his in China are still managing to race ahead.

Zero one AI now has is the third best model modeling company in the world, ranking number six in models measured by LMSIS and UC Berkeley. But the most amazing thing, I think the thing that shocks my friends in Silicon Valley is not just our performance but that we train the model with only $3 million. And GPT4 was trained by 80 to 100 million and GPT5 is rumored to be trained by about a billion dollars. So it is not the case. We believe in scaling law, but when you do excellent detailed engineering, it is not the case. You have to spend a billion dollars to train a great as a company in China, first we have limited access to GPUs due to the US regulations and secondly, the Chinese companies are not valued what American companies are. I mean we're valued at a fraction of the equivalent American company. So when we have less money and difficulty to get GPUs, I truly believe that necessity is the mother of innovation. So when we only have 2,000 GPUs, well, the team has to figure out how to use it. I as the CEO have to figure out how to prioritize it. And then not only do we have to make training fast, we have to make inference fast.

Now, of course, it isn't just Eric Schmidt saying this. I'm sure you guys remember the video I recently made where I discussed the fact that Congress is basically pushing ahead for a Manhattan style AGI product. You can see here that the Congress recommends that, you know, in order to stay ahead of other countries, they're basically stating that, look, they need to start providing these kind of things for current US Companies and ensure that that they managed to get AGI under wraps before other countries managed to get to it first. And of course, in that video I spoke about how in the article they're talking about China is racing towards AGI and it's critical that we take them extremely seriously. So one of the big things that people are talking right now is of course, with the models like Deepseek, the one that's currently doing better than OpenAI 01 Preview, a lot of people are wondering, why are these models open source? And if this trend continues, what are going to be the kind of problems that we will face in the future? Future? And that's what they actually talk about in this podcast. They're basically talking about that, look, it's probably not even China that's going to do anything wrong with this kind of technology, but malicious actors out there. When you're able to just have a system that manages to ace these benchmarks like future models will, what are they going to be able to do? And this is where we see Eric Schmidt talk about this.

And we're obviously, you and I are not in China and I don't know why China made a decision to release them, but surely evil groups and so forth will start to use those. Now, maybe they don't speak Chinese or what have you, or maybe the Chinese just discount the risk. But there's a real risk of proliferation of systems in the hands of terrorism. And the proliferation is not going to occur by misusing Microsoft or Google or what have you. It's going to be by making their own servers in the dark web. And an example, a worry that we all have, is exfiltration of the models. I'll give you an example. Google or Microsoft or OpenAI spends $200 million or something to build one of these models. They're very powerful. And then some evil actor manages to exfiltrate it out of those companies and put it on the dark web. We have no theory of what to do when that occurs.

And then of course this is where we actually see Connor Leahy talk about this. And this is a guy that's focused on AI safety and he actually talks about how open source AI is going to be a really big issue.

AI is a problem as big or bigger than nukes. If you just build bigger and bigger bombs and anyone is allowed to own bombs, eventually everything blows up. That's just a fact about physics. Like, like this is not an ideological statement. So like there's a reason that nuclear bombs are not allowed to be produced or owned by private individuals and Hot take. I think this is good. I think it's actually great. I don't think that the blueprints of the F22 fighter jet should be open sourced. I don't like, I come from an open source background which is very libertarian, very accelerationist and when I got into it, you know, I got into it from like, you know, like Linux and like you make software like free and open and like secure so you can like help people and all this kind of stuff. What I found quickly is that a lot of the people, not everyone of course, but like a lot of people open source don't really care about making people's lives better. They just want to be allowed to do whatever they want and they don't want anyone getting in their way. So I remember when for like the first deep fakes generators started like being created and like the first like voice cloning software and I was like, hey, that's kind of up. Like maybe we shouldn't open source that and people are like, what are you against free speech? It's open source, so it's good. And I just think that's a very childish view of reality.