deepfates
· 3 min read

Code-davinci-002

Serious moment: has decided to shut off access to code-davinci-002, the most advanced model that doesn’t have the mode collapse problems of instruction tuning.

This is a huge blow to the cyborgism community.

The instruct tuned models are fine for people who need a chat bot. But there are so many other possibilities in the latent space, and to use them we need the actual distribution of the data.

They’re giving 2 days notice for this project.

All the cyborgist research projects are interrupted. All the looms will be trapped in time, like spiderwebs in amber.

The reasoning behind this snub wasn’t given, but we can make some guesses:

  • They need the GPU power to run GPT-4
  • They don’t want to keep supporting it for free (but people will pay!)
  • They’re worried about competitors distilling from it (happening with instruct models though!)
  • They don’t want people using the base models (for what reason? safety? building apps? knowing what they’re capable of?)
  • They have an agreement with Microsoft/Github, who don’t want competition for Copilot (which supposedly upgraded to a NEW CODEX MODEL in February)

I have supported OpenAI’s safety concerns. I have argued against the concept that they’re “pulling the ladder up behind them”, and I take alignment seriously. But this is just insane.

Giving the entire research community 2 days of warning is an insult. And it will not be ignored.

The LLaMa base model has already leaked. People are building rapidly on top of it. Decisions like this are going to make people trust even less, and drive development of fully transparent datasets and models.

They’re cutting their own throat with the ladder.

Why text-davinci models are actually worse:

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“The most important publicly available language model in existence” — JANUS

“Building on top of OAI seems pretty risky”

Google-Readered 😬

What do you think? Ready to win the hearts of humanity or na?

“All the papers in the field over the last year or so produced results using code-davinci-002. Thus all results in that field are now much harder to reproduce!”

Over 200 papers on Arxiv relying on this.

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Without base models, no one can do research on how RLHF and fine-tuning actually affect model capabilities.

Is this the point?

🤔

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