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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    2 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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      2 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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          2 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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              2 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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                2 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”.

                  • Zos_Kia@jlai.lu
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                    23 hours ago

                    I’m sorry but no, models are definitely not collapsing. They still have a million issues and are subject to a variety of local optima, but they are not collapsing in any way. It is not known whether this can even happen in large models, and if it can it would require months of active effort to generate the toxic data and fine-tune models on that data. Nobody is gonna spend that kind of money to shoot themselves in the foot.

                • XLE@piefed.social
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                  2 days ago

                  The funny thing is, in order to get it to the dumber model, they have to run people’s queries through a model that selects the appropriate model first. This is resulted in new headaches for AI fans

                  • Zos_Kia@jlai.lu
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                    2 days ago

                    Yeah that’s also something that you have to train for, i’m not super aware of the technicals but model routing is definitely important to the AI companies. I suspect that’s part of why they can pretend that “inference is profitable” as they are already trying to squeeze it down as much as possible.

          • CileTheSane@lemmy.ca
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            2 days ago

            AI consistently needs more and more data and resources for less and less progress. Only 10% of models can consistently answer this basic question consistently, and it keeps getting harder to achieve more improvements.

        • Mirror Giraffe@piefed.social
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          2 days ago

          As someone who’s been using it in my work for the last 2 years, it’s my personal observation that while the models aren’t improving that much anymore, the tooling is getting much much better.

          Before I used gpt for certain easy in concept, tedious to write functions. Today I hardly write any code at all. I review it all and have to make sure it’s consistent and stable but holy has my output speed improved.

          The larger a project is the worse it gets and I often have to wrap up things myself as it shines when there’s less business logic and more scaffolding and predictable things.

          I guess I’ll have to attribute a bunch of the efficiency increase to the fact that I’m more experienced in using these tools. What to use it for and when to give up on it.

          For the record I’ve been a software engineer for 15 years

        • FaceDeer@fedia.io
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          2 days ago

          And yet the best models outdid humans at this “car wash test.” Humans got it right only 71.5% of the time.

          • CileTheSane@lemmy.ca
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            2 days ago

            That 71.5% is still a higher success rate than 48 out of 53 models tested. Only the five 10/10 models and the two 8/10 models outperform the average human. Everything below GPT-5 performs worse than 10,000 people given two buttons and no time to think.