> Useful for what is the question.

Useful for distillation. Any employee at a frontier AI lab will tell you this. This is known in the industry, and it's an open secret that some US labs (OpenAI) distill on the others. Again - don't just make up stuff for a political agenda.

> specifically designed to be useless for distillation purposes

No, it's designed to give feedback to the user, in a way that minimizes its value for distilling. It's still valuable, and so there's a good chance that they'll remove it entirely as a result.

> it would certainly be highly ironic if this summary was in fact "even more valuable" for that purpose as you are claiming!

I did not claim that. Read my comment again:

> The output of a reasoning model is immensely valuable even without the sanitized summary of the reasoning process - that Anthropic's service does expose to you, making it even more valuable.

Because apparently I have to spell it out:

The output of a reasoning model is valuable, even if it didn't have the reasoning summary. Anthropic's models have a reasoning summary. The reasoning summary makes the output more valuable than if it didn't have a reasoning summary. It does not make it more valuable than having the full reasoning.

> Useful for distillation

Here's the thing: no-doubt a summary, if it at least reflects some of the logic connecting response to request, is better than nothing, so this can still be useful additional training data, but a model trained on it would be learning to generate these summaries, not the original withheld reasoning, so "distillation" seems an intentionally emotionally-wrought way of describing it (the "summary" is generated by a different smaller model - not the one the rest of the response came from).

It does bring up an interesting point though - RL training in general results in "cargo-cult" reasoning - you train a model to follow the steps (mistakes and all - Karpathy) that got to a result, without understanding why they worked. If this training on summaries works just as well as training on detailed reasoning, then it just highlights how having a few breadcrumbs to follow/regurgitate is all that it takes.

At the end of the day, without having internal logits or original reasoning traces, "distillation" (which suggests one model being derived from another) just seems a very manipulative way of describing this. OK, so it's a terms of service violation - a customer is using Anthropic model outputs to help create something that competes with Anthropic, but that's it. They are not copying Anthropic - they are, one assumes, using other models to generate cheap training data that they would otherwise have to pay people to generate.

This is why people are calling out the hypocrisy - Anthropic are apple-pie American innovators when they appropriate other people's copyright data for training, but Kimi are evil communists when (we assume) they use data generated by Anthropic (not even copyright protected) to help train their own.