I like this comment because its argument only makes sense if you assume that the entire world's output of books and art did not require a huge amount of resources and expertise to make, nor did it add any value.

It's the most CS-major take ever!

> raining a SOTA model takes a huge amount of resources and expertise

Writing books, building Wikipedia, and answering questions on online forums takes a lot of resources and expertise that scraping didn't. So at the very least, we're already one rung down the "maybe you should've asked" ladder.

I suspect that, in aggregate, all of the informational output of humanity prior to 2020 has taken more resources to produce than the last few years of LLM research.

I don't know man. This reads like "yeah we stole your grain, but making bread is hard."

Probably not as much effort as writing books and creating art the models were trained on.

Still, AFAIK Kimi's architecture (just like that of other LLMs from Chinese labs) is different from those of OpenAI and Anthropic's model in a nontrivial way. So the expertise is still there, and I guess resource use too (although Chinese labs tend to optimize this, thanks to the restrictions they have on GPU use).

EDIT: just wanted to add that resource optimization is usually where the contribution of Chinese labs is, so you shouldn't reaad the above parenthesis as a negative comment.

> training an LLM takes more resources and expertise than distilling from an existing LLM

This is not automatically true. Training and distillation use the same underlying infra and method and there is no intrinsic differences in between.

Yeah, there's a difference. One party spends a bunch of resources doing something illegal and extremely immoral. The other party spends little money doing something legal and morally neutral.

They add value on top of other people’s work, often against licensing, and then commercialize this product, ie profiting from making a product out of other people’s IP.

As an author, that's a genuinely disheartening thing to read.

It took me a year to write a book. It took OpenAI and Anthropic a fraction of a second to ingest it. Do you understand now why I give zero shits if it takes Anthropic a billion to train a model, and Moonshot 10k in API cost to distill it?

Why is it less true for distillation? Everyone technically has access to Fable but Moonshot came up with the model. How can you objectively claim one is adding value while the other is not?

If that is the whole point you need to clarify why this is the case on an objective level.

I would say building a comparable model using any means necessary (just like what Anthropic and OAI did) at a lower cost is actually more valuable to soceity and Monshoot is arguably generating more value with less.

The value of LLM's come from replacing what generated its training data.

If the distilled model is cheaper, then it's just LLM's getting LLM'ed.

You can argue that reverse engineering anything is as hard if not harder than engineering something. I can’t imagine distillation is any different.

>Training a SOTA model takes a huge amount of resources and expertise so the people doing the training are adding a lot of value along the way.

producing the entire body of human knowledge that Silicon Valley companies absorbed like the Borg did not just take more resources but also a fair amount of blood and sweat, certainly more than the LLM so on that front that comparison also seems entirely justified.

I'm sure it takes a lot of time and resources to plan and pull off an epic heist but it is unusual to see people like Thomas Crown being accused of creating value, as they're usually accused of committing theft.