GPT-Rosalind-6 System Card Addendum

(deploymentsafety.openai.com)

26 points | by gmays 2 hours ago

8 comments

  • fakwandi_priv 19 minutes ago
    Slightly off-topic to this model card but has anyone noticed changes to GPT6 Astra about a week after 6.1 came out?

    I feel like 6 Astra just turned a lot lazier during planning and strangely enough claude has become a lot more assertive with Opus 5.5 while it used to be very lazy.

    It’s really obvious during planning, it used to be that claude would just give a best effort guess and handwave things but now it will actually write small tests, launch playwright to test a hypothetical and even look things up in github during a question. This was something codex’s models were really good at.

    I’ve read so many stories about people claiming models getting nerfed after a new release and now it seems I can finally join them.

    • margalabargala 10 minutes ago
      I imagine this is basically not at all due to actual model changes.

      If you use Codex, Claude Code, etc, those are being constantly updated. That sort of behavior would be highly harness dependent.

  • Alifatisk 39 minutes ago
    > GPT-Rosalind-6 uses the same weights as GPT-6 Astra, our flagship reasoning model.

    Didn’t Sol-6.1 top Astra? Or is it maybe that Astra is still a larger model and therefore can comprehend deeper complexity better in the long run?

    • pizza234 21 minutes ago
      > Didn’t Sol-6.1 top Astra

      No, Astra is still smarter (https://artificialanalysis.ai/models/?models=gpt-6-astra%2Cg...).

    • lnkdinsuxs 22 minutes ago
      > Didn’t Sol-6.1 top Astra?

      On specific coding skewed benchmarks yes.

      But Astra is in a different league when it comes to doing research and investigative tasks that require exploration.

      For my usecases, Astra is pareto frontier - it dominates Fable 5.1 on cost. Fable 5.1 is a phenomenal model but Astra is cheaper and uses way less tokens and steps to produce similar output.

    • kingkongjaffa 36 minutes ago
      I thought the same.

      My assumption is Astra is the biggest model in terms of param size and has the most intellectual horsepower.

      But Sol-6.1 is more instruction tuned to perform better on the average use cases for most users, so it benchmarks better and feels better to use.

    • Starlevel004 23 minutes ago
      It's widely suspected that sol 6.1 is a slightly detuned version of astra 6
      • lnkdinsuxs 20 minutes ago
        > It's widely suspected that sol 6.1 is a slightly detuned version of astra 6

        My feel is it's the opposite of a "detune".

        Sol 6.1 is likely a distillation that's highly instruction tuned and designed to perform better on benchmarks.

        • Starlevel004 13 minutes ago
          Sol 6.1 is incredibly incredibly slow, 20t/s slow (vs the ~70-80 of Terra 6.1 and Luna 6). It wouldn't be so much slower if it was just a distillation, surely? There's something else going on there.
          • lostmsu 11 minutes ago
            But is it slower than Astra?
  • kingjimmy 29 minutes ago
    OpenAI naming scheme makes no sense. I get naming is hard but atleast keep it consistent.
    • whafro 27 minutes ago
      I felt like I had a read on it right away – it's a 6[.0]-series model, and not named after space since it's specialist model, and I assumed it was named after Rosalind Franklin. Looks like the docs back that up, that it's based on Astra, which is not [yet?] at 6.1.
    • varispeed 23 minutes ago
      Probably AI came up with the naming scheme ;-P Maybe they used Gemini for that or copilot.
  • zb3 9 minutes ago
    > We review applicants’ proposed uses, security controls and governance practices before granting access.

    For-profit corporations shouldn't have this power, this is not democracy.

  • theplumber 45 minutes ago
    It’s clear to me that open source will rule at the end of the day as everyone wants AI and nobody can rely on U.S crop/gov anymore.
  • hmokiguess 55 minutes ago
  • lifeisloving 28 minutes ago
    Last I checked machine learning wasnt the bottleneck for drug discovery and where it fits in the research process was largely solved 5+ years ago.. Weren't there already a ton of ML based drug discovery startups that went out of business, or got aquired, not because they werent useful but because they produced more candidates than the industry could use.

    I dont think I want researchers offloading their thinking to some specialty model after seeing what its done to me and my colleagues in software, it certainly isn't making anyone more competent.

    It really only enables people to be able to do less novel and lower quality work faster.

    OpenAI and Anthropic creating these platforms seems mostly just to create narratives around AI that its going to lead to cures for disease, which it wont, but plenty of normies assume it will cure cancer now. Also a bunch tech oligarchs who are equally convinced or 'one-shot' they're going to live forever because of language models lol.

    Promises of the Fountain of Youth continue to be a time tested tools for snake oil salesmen.

  • chairhairair 19 minutes ago
    You’d be a fool to use an OpenAI product with any proprietary data.
    • vindex10 12 minutes ago
      can you elaborate?