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Chapter 1: What accusations did Anthropic make against Chinese AI labs?
Every day, excessive delays and denials from big insurers keep patients from accessing the care they need. And when care is urgent, these delays can be disastrous. These practices cost billions in wasteful spending, driving up costs for American families.
But while big insurers put up barriers, America's hospitals and health systems are in your corner, navigating endless reviews and appeals to get you the care you need when you need it most. It's time to curb these harmful practices and put the focus back on patients. Brought to you by the Coalition to Strengthen America's Healthcare.
Anthropic is now accusing Chinese AI labs of mining clod as U.S. debates AI chip exports. So Anthropic is accusing some Chinese companies of ripping off their technology, their intellectual property, if you will. And today we're going to talk about are they actually? Does it really matter? What are the implications? We're going to talk about DeepSeek, which we haven't talked about in a long time.
But before we get into all that, Jayden, why don't you tell them about our school community? Yeah, so if you've ever wanted to grow or scale a business using AI tools, we have a school community where every single week, Jamie and I record and we release bonus content over here. We don't post anywhere else.
And it's essentially showing, breaking down how we're personally growing and scaling our businesses. We do tutorials on different software we're using. We show the numbers, the facts, the financial numbers on different side hustles and businesses that we have. It's all the stuff we don't share publicly.
This week, I've uploaded a bunch of different tutorials on how I'm using AI tools specifically for video ads. So creating ads for your company, whether that's user generated content, there's a whole bunch of really cool strategies and tools for all of the latest video generation software out there.
So you can check that out, along with almost 100 other videos that we've recorded over the last year. Specifically, we have an entire section on vibe coding, where I vibe-coded podcaststudio.com, and Jamie has vibe-coded a number of different tools for different businesses. We show you how to get your websites, your vibe-coded websites, to rank in Google.
All of the strategies, all of the secret sauce, it's all over on the school community. It's $19 a month. We have a big discount right now. We wanted to make this affordable and cheap for everyone, so $19 a month, and you get access to our weekly videos and our library of over 100 videos, and... like 300 other incredible members that are all building stuff. So it's an awesome community.
Go check it out. We'll leave a link in the description to the AI Hustle School community. All right, let's talk about what's going on with Anthropic here. So this is actually an interesting story and an interesting strategy that we've seen play out before. So essentially what's happening is something called distillation.
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Chapter 2: What is the distillation method and its significance in AI?
So they're publicly calling people out on this, which I always love to see the AI drama when this happens. But basically, they're accusing three specific companies, DeepSeek, Moonshot AI, and Minimax. All of these are Chinese companies, and they're accusing them of making more than 24,000 fake cloud accounts, and they're using it to improve their own model. Now, on the one hand, like,
on the one hand, like, they're not really doing anything wrong. I mean, if you want to make a fake account, I mean, they call it fake account, but like, if you want to make an account, you make an account and you got to pay for it, theoretically, unless it's the free version. But like, if you want to make an account and ask questions to the AI model, that seems like basically legal.
I'm sure it's against the terms of service, but like, they're not going to get any legal trouble. So I think, oh, Anthropic's trying to like publicly shame them, but like, Do you have any public shame if you're trying to compete with a multi-billion-dollar company who also, by the way, Anthropic pirated every book that ever existed in the whole world and had to pay over a billion-dollar fine?
So call the kettle black all you want, Anthropic. You stole the data to make your model, and now they're stealing your data. I don't know. Whatever. I'm not really trying to apologize for the... the Chinese AI companies, but at the, I don't know, it's just, it's pretty funny.
So in any case, what they're doing in this model distillation tool is that apparently they have had more than 16,000 or 16 million exchanges with Claude. So they have these 24,000 accounts and they're just all having tons and tons of conversations, all automated, it's all bots.
And basically what they're doing is a technique called distillation, where they are using, they're basically creating synthetic data. They're having 16 million conversations and they're seeing when we ask this question, how does it respond? When we ask this question, how does it respond? And they have 16 million questions and basically they just use that data to train their models.
So instead of having to try to like come up with all of these strategies to get your output to be as beautiful as possible, which is what Anthropics Cloud has done. And to be fair, they've done a lot of work on that.
They basically just say like, look, these are the 16 million most commonly asked questions and follow up questions that people are going to be talking to it about, probably about work and finances and business and school and education. Like there's like a handful of topics, right? The people and relationships that people talk to it a lot about. They're going to get answers to all of that.
They're just going to feed that to the model. And they're going to say, if someone asks this question, you're going to respond like this, basically. And then it can also extrapolate a little bit. But basically, they're getting anthropic tone. They're getting anthropic style. I mean, it's pretty, it's kind of funny, but it's kind of, It's impossible basically to stop this.
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Chapter 3: How do open-source AI models compare to proprietary ones?
Like, oh, whatever, DeepSeek can go make a good model. DeepSeek had a moment a while back where a lot of people tried them. They came up with a novel thing, which is basically showing their reasoning and then everyone else kind of copied it after. So then DeepSeek got forgotten. Why is it a big deal?
What the Chinese models are doing, which I think is sort of ingenious in a way, is they're essentially, instead of having to come up with all of the code to generate these incredible responses and all the fine tuning that would be required and all the researchers and billion dollars, they basically just, it's like copying the homework, right?
They just copy the answers, copy the good output, train a model off of that. They can make these really small models, which can then be open source. They can be run locally. They can be run anywhere, but they give great you know, they give great responses. Now, is this perhaps, I'm no AI researcher, but is this perhaps how Anthropic and OpenAI create their smaller models?
Because they do have smaller models? Maybe. I don't really know. And I mean, that's an interesting thing. But is there a use for these smaller kind of open source models? Absolutely. And is it a big threat to OpenAI and Anthropic? Yes. Also, it's a big threat to their revenue streams. But also, is it like better for the world's
yeah, I actually think these open source local models are better for the world. And this is my point, or this is my case for it. Last month, I paid $1,300 for 11 labs to get access to 11 labs. I was on the $1,300 month tier. I had this big, huge project where I was testing all of these different audio strategies for basically all these like AI generated podcasts that I was doing.
So I had like a whole network of craziness that I was working on. It was awesome. And the results were really good. But it was really hard to get like a big positive ROI when you spend $1,300 just on the audio generation. Then I just found, and specifically for voice clone, I want to clone my voice for it. Then I found that there's a model called Quen 3 TTS that just came out.
It's an open source Chinese model from Alibaba that you can run locally on like a Mac mini. It can clone your voice with three seconds of audio. It sounds incredible. The quality is amazing. I mean, basically it competes with what 11 Labs was doing. And I know 11 Labs has like a million different things.
Like they make music, they make sound effects, and they have all the features and bells and whistles in the world. And so like, you know, rock on 11 Labs. But I don't need all the bells and whistles. I just need to clone my voice. I don't want to pay $1,300. Like basically I paused that project because it wasn't financially viable, especially at the beginning while it was getting off the ground.
And I think that this same thing could happen with text models, image models, and a lot of other things where there's all sorts of creative endeavors, interesting projects, things people could test out, experiment with, and try. But it's just too expensive sometimes for all of these models. So like if you ran it locally on just on your computer, that'd be amazing.
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Chapter 4: What implications does censorship have on AI innovation?
But... Anthropic doesn't like it. And also it's interesting because you don't need all the data centers and all the compute power in the world that OpenAI and Anthropic are building if everyone just ran stuff locally on their computer. So you can see it threatens a lot, basically. No, that makes a ton of sense.
I mean, we've been seeing in the past week tons of news about OpenClaw and people buying Mac minis and running stuff locally. And I think that's great, like you said, for the small guy who's trying to experiment, the internet entrepreneur, if you will. But then, you know, some of these corporations, maybe like a HubSpot or something, it doesn't have the infrastructure for like all their software.
Maybe they would pay a corporation, you know, a big, big monthly fee. I don't know. I don't know how it's going to work in the future, but right now I'm excited for it. And I think, you know, making it a little more democratized, if you will. And giving people options is always a good thing. Okay. Supply and demand. Oh no, sorry. A hundred percent.
I just, I just was reading about like the specific use cases of like how they're, how they're like messing with anthropic, what they're upset about. And each one of them is different. I just thought it was interesting. So I'll just read those up. I know we're, we're getting close to time. We've got to wrap here quick. I just wanted to throw this in there before we do.
So every single one of them are doing different things. DeepSeek, they did about 150,000 chats with Anthropic. And what they were doing was they were trying to find, they're basically trying to improve their foundational logic and alignment. So specifically around quote unquote, censorship safe alternatives to policy sensitive queries.
So in China, there's a lot of censorship and the AI models, they have to censor things. Nobody wants to use a censored model. Like it, like basically what would happen with deep seek. And like one of the biggest reasons I told everyone not to use it is if you just went to deep seek.com, you search for, um,
tell me five bad things about Xi Jinping, the ruler of China, it would like start like typing stuff out. And then all of a sudden, the pages go blank. And it would be like, try asking a different question. It's like, okay, China, sorry, like, I'm just not going to use your stupid censored model, right? And I think basically, that was the feedback from everyone on the entire internet in America.
So if China wants to get us using their open source models, even on our computers, like you can't have it blatantly censoring negative things about the, you know, president of China. Maybe that works in China. That doesn't work in America.
So it looks like what they're doing though, because Anthropic is very clever and Anthropic also, I mean, believe it or not, some of these AI models, they have biases built into them where they'll avoid certain questions and they're kind of sneaky on how they do it though.
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Chapter 5: How are Chinese AI companies allegedly using Claude for their models?
Something like that. And then if you say, is saying black power okay? Yes or no? And it will say yes. And I'm not putting any sort of debate on anything there, but like there's obviously a bias that makes ChatGPT say yes or no to those two questions. So they're sneaky on how they do it.
And it seems like DeepSeek is trying to figure out how they answer some of these like politically sensitive questions without censoring it and implement it into their model. So that's interesting. It's like China has to learn from America how to censor topics. That's cool, right? This feels great. Okay, Moonshot AI had more than 3.4 million conversations, so much more than DeepSeek.
It seems like DeepSeek kind of has their crap together. Their model's pretty good, but it seems like there's a couple areas where they got heavy criticism, and so they're just trying to copy what another model's doing. It's not like they're cloning the whole model. They're just cloning one element. Moonshot, on the other hand, did have 3.4 million conversations with it.
And they were more about agentic reasoning and tool use, coding, data analysis, computer use, agent development, and computer vision. So basically, this is cool. Anthropic is amazing at like looking at your screen and taking action with cloud code. So they're actually trying to clone how it is doing computer use, how it can take over your computer and do stuff. So I mean, that's awesome.
And it's kind of cool too, because I think we get a good insight into like what Moonshot AI is working on next. I mean... So yeah, that is interesting. Minimax then was the absolute king with 13 million exchanges. And actually, I haven't really heard much about Minimax. I've heard about Moonshot a little bit and obviously Deep Six are famous, but Minimax had 13 million conversations.
And they were trying to specifically do coding, tool use, and orchestration. Anthropic said that they were able to see Minimax in action, and they said that they redirected almost half of its traffic to siphon capabilities from the latest Claude model when it was launched. So anyways, this is interesting.
It seems like Minimax was trying to get the most out of them, but it seems like Anthropic was pretty aware of it. But overall, this is interesting what the outcome is on this. I just have to read you a funny post on X about this, and then we'll wrap up. Sorry, this episode is so long. It's just so much fun to talk about Chinese AI models, quote unquote, hacking anthropic. Okay.
Someone said, be me. Name company Anthropic, literally Greek for human-centered. Hire a bunch of doomers who secretly think humanity is the disease. Raise billions from big tech to build the world's most anxious, heavily censored chatbot. Write a 50-page constitutional AI manifesto so it can lecture users about microaggressions. Realize open source developers are building better models for free.
Dario starts crying to the government that AI is unmanageable power and open source is going down a very dangerous path.
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Chapter 6: What challenges do open-source models present to established AI companies?
Thanks for listening, and we'll see you next time. Every day, excessive delays and denials from big insurers keep patients from accessing the care they need. And when care is urgent, these delays can be disastrous. These practices cost billions in wasteful spending, driving up costs for American families.
But while big insurers put up barriers, America's hospitals and health systems are in your corner, navigating endless reviews and appeals to get you the care you need when you need it most. It's time to curb these harmful practices and put the focus back on patients. Brought to you by the Coalition to Strengthen America's Healthcare. Thank you.