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Claude 4

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Re: Claude 4

#61
Is this really worthy of a claude 4 label? Was there a new pre-training run? Cause this feels like 3.8... only swe went up significantly, and that as we all understand by now is done by cramming on specific post training data and doesn't generalize to intelligence. The agentic tooluse didn't improve and this says to me that it's not really smarter.

Re: Claude 4

#62

Sooo... it can play Pokemon. Feels like they had to throw that in after Google IO yesterday. But the real question is now can it beat the game including the Elite Four and the Champion. That was pretty impressive for the new Gemini model.

Right, but on the other hand... how is it even useful? Let's say it can beat the game, so what? So it can (kind of) summarise or write my emails - which is something I neither want nor need, they produce mountains of sloppy code, which I would have to end up fixing, and finally they can play a game? Where is the killer app? The gaming approach was exactly the premise of the original AI efforts in the 1960s, that teaching computers to play chess and other 'brainy' games will somehow lead to development of real AI. It ended as we know in the AI nuclear winter.

Re: Claude 4

#63
post #46

I'm curious what are others priors when reading benchmark scores. Obviously with immense funding at stakes, companies have every incentive to game the benchmarks, and the loss of goodwill from gaming the system doesn't appear to have much consequences. Obviously trying the model for your use cases more and more lets you narrow in on actually utility, but I'm wondering how others interpret reported benchmarks these da…

Hasn't it been proven many times that all those companies cheat on benchmarks?

I personally couldn't care less about them, especially when we've seen many times that the public's perception is absolutely not tied to the benchmarks (Llama 4, the recent OpenAI model that flopped, etc.).

Re: Claude 4

#64
post #13

I'll look at it when this shows up on https://aider.chat/docs/leaderboards/ I feel like keeping up with all the models is a full time job so I just use this instead and hopefully get 90% of the benefit I would by manually testing out every model.

Are these just leetcode exercises? What I would like to see is an independent benchmark based on real tasks in codebases of varying size.

Aider is not just leetcode exercises I think? livecodebench is leetcode exercises though.

Re: Claude 4

#65

“GitHub says Claude Sonnet 4 soars in agentic scenarios and will introduce it as the base model for the new coding agent in GitHub Copilot.” Maybe this model will push the “Assign to CoPilot” closer to the dream of having package upgrades and other mostly-mechanical stuff handled automatically. This tech could lead to a huge revival of older projects as the maintenance burden falls.

Anyone see news of when it’s planned to go live in copilot?

Re: Claude 4

#66

“GitHub says Claude Sonnet 4 soars in agentic scenarios and will introduce it as the base model for the new coding agent in GitHub Copilot.” Maybe this model will push the “Assign to CoPilot” closer to the dream of having package upgrades and other mostly-mechanical stuff handled automatically. This tech could lead to a huge revival of older projects as the maintenance burden falls.

That's kind of my benchmark for whether or not these models are useful. I've got a project that needs some extensive refactoring to get working again. Mostly upgrading packages, but also it will require updating the code to some new language semantics that didn't exist when it was written. So far, current AI models can make essentially zero progress on this task. I'll keep trying until they can!

Re: Claude 4

#67
It’s been hard to keep up with the evolution in LLMs. SOTA models basically change every other week, and each of them has its own quirks.

Differences in features, personality, output formatting, UI, safety filters… make it nearly impossible to migrate workflows between distinct LLMs. Even models of the same family exhibit strikingly different behaviors in response to the same prompt.

Still, having to find each model’s strengths and weaknesses on my own is certainly much better than not seeing any progress in the field. I just hope that, eventually, LLM providers converge on a similar set of features and behaviors for their models.

Re: Claude 4

#68
post #46

I'm curious what are others priors when reading benchmark scores. Obviously with immense funding at stakes, companies have every incentive to game the benchmarks, and the loss of goodwill from gaming the system doesn't appear to have much consequences. Obviously trying the model for your use cases more and more lets you narrow in on actually utility, but I'm wondering how others interpret reported benchmarks these da…

People's interpretation of benchmarks will largely depend on whether they believe they will be better or worse off by GenAI taking over SWE jobs. Think you'd need someone outside the industry to weigh in to have a real, unbiased view.

Re: Claude 4

#69
This is starting to get ridiculous. I am busy with life and have hundreds of tabs unread including one [1] about Claude 3.7 Sonnet and Claude Code and Gemini 2.5 Pro. And before any of that Claude 4 is out. And all the stuff Google announced during IO yday.

So will Claude 4.5 come out in a few months and 5.0 before the end of the year?

At this point is it even worth following anything about AI / LLM?

[1] https://news.ycombinator.com/item?id=43163011

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