alt Hacker News> distillation: why exactly is it bad? After all, what are large language models but the distillation of all of the knowledge on the open Internet, scraped by the frontier labs and distilled into the models that are themselves being distilled? Who is exactly being wronged here? ... The U.S. should pass a law that (1) makes explicit that collecting data for training models is fair use, and (2) bars terms of service that forbid distillation
Sounds great to me; live by the sword, die by the sword.
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Forbidding distillation is like forbidding using a compiler to make another(perhaps better, more efficient) compiler.
Yup, fair's fair. Anything else stinks of 'rules for thee but not for me' (a maxim the frontier labs seem worryingly happy to apply, on several counts).
I am immediately sold on this.
Sorry, OpenAI & Anthropic.
Why would reading copyrighted material ever be an issue anyway? Wouldn't copyright law only apply to what you create and publish using the model? Training on every comic book should already be perfectly legal, as long as you accessed them legally, right? But publishing your own Batman comic using that training is copyright infringement.
What I'm saying is, doesn't the law already cover 1?
> distillation: why exactly is it bad?
Felony contempt of business model.
Government cannot exactly "bar" terms of service. ToS isn't law. The most they can do is say they're unwilling to enforce them.
ToS is just conditions that you agree to in order to use a private service that is provided at-will. I can have a private coffee shop where the terms of service are that you must wear red to enter, and if you're not wearing red, you are not welcome on my property.
So it would be upto OpenAI and Anthropic to enforce them on their own terms (by banning accounts and IPs).
The distillation explanation is classic American exceptionalism: No one could possibly do anything unless they were copying American leaders (where "American" means a bunch of Chinese, Canadian, Europeans and Indians working in the US).
It's also a bit of securities defensiveness. Pretending that you really do have a super moat, people just keep swimming in it so you just need to add more alligators.
It's farcical. Anyone who has worked on large models knows that the premise that an almost-Fable model was trained with distillation is beyond ridiculous. It's theoretically possible if they spent tens of billions of dollars on API calls, but it isn't the magic that somehow these people keep convincing people it is.
Previously Anthropic has reported on some Chinese firms doing chicken-shit level of API calls, that at most would be doing some Q and A or final fine tuning. The notion that they're training these models via it is fantastically ignorant nonsense that only very ill-informed and gullible people fall for.
Don’t know much about how distillation works so please enlighten me here.
> what are large language models but the distillation of all of the knowledge on the open Internet, scraped by the frontier labs and distilled into the models
If it’s as easy as that why do they choose to distill another model and not distill the knowledge on the open Internet from scratch?
Making an LLM from raw data is value-add.
Distillation is just value extract.
It's soft, and I'm not sure what the answer should be ... but I think that there is a difference.
I think we start by recognizing that ... and then try to figure it out from there.
'The Internet' may be a public good, maybe we make them pay a tax for that, but that's different than distillation.
Seems only fair that if LLMs can use copyrighted data for training then they should be able to use cannot-be-copyrighted output of other LLMs.
But barring the terms of service from forbidding distillation seems like a tough sell. OpenAI shouldn't be allowed to decide what types of customers it wants and doesn't want?