Screenshot of this question was making the rounds last week. But this article covers testing against all the well-known models out there.

Also includes outtakes on the ‘reasoning’ models.

  • realitista@lemmus.org
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    6 days ago

    You’re getting downvoted but it’s true. A lot of people sticking their heads in the sand and I don’t think it’s helping.

    • FaceDeer@fedia.io
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      6 days ago

      Yeah, “AI is getting pretty good” is a very unpopular opinion in these parts. Popularity doesn’t change the results though.

        • MangoCats@feddit.it
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          6 days ago

          It’s overhyped in many areas, but it is undeniably improving. The real question is: will it “snowball” by improving itself in a positive feedback loop? If it does, how much snow covered slope is in front of it for it to roll down?

            • kescusay@lemmy.world
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              6 days ago

              It’s already happening. GPT 5.2 is noticeably worse than previous versions.

              It’s called model collapse.

              • Zos_Kia@jlai.lu
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                6 days ago

                To clarify : model collapse is a hypothetical phenomenon that has only been observed in toy models under extreme circumstances. This is not related in any way to what is happening at OpenAI.

                OpenAI made a bunch of choices in their product design which basically boil down to “what if we used a cheaper, dumber model to reply to you once in a while”.

                • MangoCats@feddit.it
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                  2 days ago

                  I feel that a lot of what is improving in the recent batch of model releases is the vetting of their training data - basically the opposite of model collapse.

                  Nothing requires an LLM to train on the entire internet.

                  • Zos_Kia@jlai.lu
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                    2 days ago

                    That’s an excellent point! On that topic I recently listened to an interview of the founder of EleutherAI, who focuses on training small language models. She said they were able to train a 1B parameters reasoning model with 50K Wikipedia articles and carefully curated RL traces. The thing could run in your smartphone and is at parity with much larger models trained on trillions of tokens.

                    She also scoffed at Common Crawl and said it contained mostly cookies and porn. She had a kind of attitude like “no wonder the big labs need to slurp trillions of tokens when the tokens are such low quality”. Very interesting approach, if you understand french I can only recommend the interview.