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Anthropic has already been burned before on this. DeepSeek was trained on million of conversations with Claude. And DeepSeek created thousands of free accounts to burn all this compute at their expense.
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And they're hilariously pissy about it for a megacorp that did the same with the entire Internet and every library book they could get their hands on.
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Anthropic's claim was that Deepseek collected ~150k conversations.

https://www.anthropic.com/news/detecting-and-preventing-dist...

I think the extent of distillation by Deepseek specifically is overstated. For comparison, Minimax collected over 13m 'exchanges', which starts to sound a lot more like large-scale distillation.

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If that's all it took to make Deepseek so good, I'll gladly ship High-Flyer all my personal 150k claude/chatgpt conversations in exchange for Deepseek 5 (and a rack of B200s or Ascend chips)
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Ah, dang it. My college professors warned me about this: the Wikipedia page I read the other day is wrong!
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Did you read a Wikipedia page, or did you read a LLM-generated summary? When I looked this number up yesterday the LLM summary claimed it was millions, but I opened the Anthropic post I was looking for and verified it was indeed just 150,000. Are you sure you weren't just being lazy and trusting the summary?
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I said what I meant:

https://en.wikipedia.org/wiki/DeepSeek

> In February 2026, Anthropic accused DeepSeek of using thousands of fraudulent accounts to generate millions of conversations with Claude to train its own large language models.[57]

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They don't want someone to piggyback Anthropic's Mythos to make their own Mythos with less effort than it cost Anthropic.
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Ironic, given they piggybacked on the entirety of human knowledge and massive amounts of GPL'd software and repeatedly say they want to replace people with a tool.

And now they say that's fine so long as people are entertained.

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Pulling up the ladder behind you is a tradition as old as time.
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That I can understand. It’s Anthropic’s right to choose their customers.

But silent degradation for use cases including “distributed training” as one of their examples is going to catch up a lot of proper use cases. Not everyone in AI or ML is trying to build frontier LLMs. Heck, most probably aren’t.

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So they are lying then when they say it's for safety reasons.

I think if they want to behave anti competitively they should be honest about it and we should absolutely call them on it. Perhaps even regulators should.

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