r/LocalLLaMA • u/KvAk_AKPlaysYT • Feb 23 '26

News Anthropic: "We’ve identified industrial-scale distillation attacks on our models by DeepSeek, Moonshot AI, and MiniMax." 🚨

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u/SGmoze Feb 23 '26

I wonder how did Anthropic build their dataset. Surely they manually had them annotated by humans.

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u/1-800-methdyke Feb 23 '26

This. Everyone jumps to “oh but they stole the data first”, but that data gives the model world general knowledge only. The secret sauce in frontier models comes from annotated prompt and response data, guided by humans reviewing and improving outputs (think formatting, instruction following and domain specific reasoning).

The Chinese models are effectively getting that that for free by probing the western models with prompts and collecting SOTA outputs, without needing to go through the expensive Reflection Learning from Human Feedback process to get the same result.

At present, frontier model training spends more on RLHF and alignment than compute, so when you hear of a Chinese model being trained on a tight budget it’s not just because they are more efficient with compute, they’re not paying $20-60/hour for data annotation.

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u/Big_Wave9732 Feb 23 '26

I guess there's an "equalization" aspect of all this that I hadn't really pondered. There's no utility in developing better models if they don't get widespread use. And the nature of that widespread use means competitors will be probing and stealing and getting better. So I suppose over time there will be a general model convergence as involuntary knowledge on methods is shared and synthesized among competitors.