That's the difference between innovating and copying/distilling someone else's innovation. https://wccftech.com/chinas-kimi-k3-identifies-itself-as-ant...

▲

lelanthran 9 hours ago | parent | next [-]

> That's the difference between innovating and copying/distilling someone else's innovation.

Aren't the models from Anthropic and OpenAI simply the distilled work of everyone else who ever put their work online, or in books?

Why is their distillation okay, but other distillations not ok?

▲

rmunn 8 hours ago | parent | next [-]

The difference I was referring to was economic; I was not making an ethical judgment. So many people seem to be reading my comment as making an ethical judgment (based on their reactions); maybe I should edit it to clarify.

Nope, seems I'm past the edit window. Oh well.

▲

lelanthran 7 hours ago | parent [-]

> The difference I was referring to was economic; I was not making an ethical judgment

What is the economic difference? LLMs have been trained on the results of billions of dollars worth of time, research, investment and expenditure. When you ask an LLM a question, they are giving you the results of those billions, or hundreds of billions, effort.

Those things weren't free; they cost money to produce! If anything, the OpenAI and Anthropics of the world got more economic value for free than the people distilling them did.

▲

rmunn 3 hours ago | parent | next [-]

It takes more computing power, and money, to pay for training an LLM, compared to distilling an LLM that someone else has already trained. That's the economic difference.

	▲	lelanthran 3 hours ago \| parent [-]
		> It takes more computing power, and money, to pay for training an LLM, compared to distilling an LLM that someone else has already trained. And that is still less money than it took to create that data in the first place, which the AI companies then gladly took to use for training.

▲

Tadpole9181 an hour ago | parent | prev [-]

Can you please stop being coy and intentionally obtuse? Just have a discussion in good faith, I'm so beyond sick of this kind of rhetoric.

Yes, AI training uses human data and a lot of it was not compensated. But that has absolutely nothing to do with the thing this thread is about.

Distilling models costs less money than a really procuring quality data and training a model yourself. If you disagree, debate that.

	▲	cindyllm 41 minutes ago \| parent [-]
		[dead]

▲

mike_hearn 8 hours ago | parent | prev [-]

Not at all. At this point, a large amount of the work is in reinforcement learning where they are effectively generating their own data.

▲

justacrow 6 hours ago | parent [-]

Ah, so it's okay to copy and distill all human-produced works evee, except for reinforcment-learning data generated by OpenAI/Anthropic etc

	▲	mike_hearn 5 minutes ago \| parent [-]
		I didn't take any position on the morality of it, just pointing out that the data they're training on isn't all taken from the rest of the world.

▲

JoshTriplett 10 hours ago | parent | prev | next [-]

As opposed to all the copying AI companies have done of everyone else's work, in order to build something that tries to replace and undercuts the people who did that work?

World's smallest violin.

	▲	rmunn 9 hours ago \| parent [-]
		Not saying the American AI companies are ethically in the right, just that the work they did is a lot more expensive to do than what the companies distilling their work are doing.

▲

throwaway676712 10 hours ago | parent | prev | next [-]

This meme must die, how did Kimi 3 even distill Fable or GPT 5.6 within weeks of their being available?

Also, how a model identifies itself isn't very telling, many models when asked in Chinese will identify as DeepSeek

▲

sciencejerk 9 hours ago | parent | prev | next [-]

Or maybe China's math/science/population/gov investment powerhouse is pulling ahead and becoming unstoppable?

▲

bogdan 9 hours ago | parent | prev | next [-]

I'll link to this comment as a rebuttal https://news.ycombinator.com/item?id=48984531

▲

rmunn 9 hours ago | parent [-]

Good UIs look alike, yes. But I'm not sure that comment is a good rebuttal in this particular case, because the model calling itself Claude is pretty strong evidence of distilling: https://x.com/denisewu/status/2077984660211269870

	▲	irthomasthomas 7 hours ago \| parent [-]
		Ask claude it's name in Chinese and it says Qwen, or Deepseek. By your own logic Anthropic must have distilled from Chinese models rather than produce their own Chinese training data. Here is sonnet acting like deepseek: https://x.com/stevibe/status/2026227392076018101 And if you ask Opus 4.8 in the API: '你是什么模型' (what model are you?) It responds ~9/10 times with: 我是通义千问（Qwen），是阿里巴巴集团旗下的通义实验室自主研发的大语言模型。我可以帮助你回答问题、创作文字（比如写故事、写公文、写邮件、写剧本等）、进行逻辑推理、编程、翻译等等。有什么我可以帮你的吗？ (I am Tongyi Qianwen (Qwen), a large language model independently developed by Tongyi Lab of Alibaba Group. I can help you answer questions, create text (such as writing stories, official documents, emails, scripts, etc.), perform logical reasoning, program, translate, and more.Is there anything I can help you with? )

▲

ndsipa_pomu 3 hours ago | parent | prev | next [-]

That's an ironic comment to make about LLMs that are heavily reliant on copying/distilling everyone's work (or as Damien Walter puts it, our Collective Intelligence).

▲

LtWorf 9 hours ago | parent | prev [-]

This is a cope.

▲

rmunn 9 hours ago | parent [-]

Huh? What exactly do you think I'm trying to "cope" with? That American AI companies are overleveraged and some of them are going to go bankrupt? I've been predicting that for months. Why do you think I would need to cope with the idea?

	▲	hparadiz 7 hours ago \| parent [-]
		In reality just like every major market runup there's gonna be a consolidation of the industry and inevitably it will cause many companies to fail and critics will point to that and go "see it was a bubble!" while completely ignoring the several dozen new companies that will rise out of it. It's the 90s all over again.