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No it's far beyond average human code, and it's trained in RL environments on synthetic data etc now. The average human can't solve a millenium problem in mathematics but the LLMs are able to now. Anything with a verifiable output can be RLed on to make llms superhuman it seems, and the average human is not as persistent and thorough as e.g. gpt 6.1 sol at checking every edge case and hunting for bugs because that behavior is something that's just trained into the model. Frontier models perform farm above the average human at the categories of tasks they are RLed on like code and math.
> The average human can't solve a millenium problem in mathematics but the LLMs are able to now.

I think comparing the resources they spent at it would be a more apt comparison.

AKA if you tasked 150 mathematics departments to only focus about that problem, and stop doing things like teaching and researching anything else, you might get close to the amount of resources that these companies put into solving the problem to get a press release.