bryan0

on iOS I still get badge notifications from unknown senders. I don't think there's a way to turn this off for some reason?

In other news, 30-year-old chess engine outperforms frontier llms in chess

I guess I wasn’t clear, but using manim to make videos is not the hard part. The hard part is making them engaging and enlightening, and whatever else you want to attribute to 3b1b videos which make them a joy to watch and learn from.

the key word in OP's description is "good". If AI can create videos as engaging and enlightening as 3b1b, then we hit AGI.

> Why not pay taxes and let us, the people decide how to use it instead?

Maybe because the current administration has no interest in doing this and Anthropic doesn't want to wait for this cluster-f of a situation to sort itself out. Even if the current admin was for progressive taxation it might take them years to sort through all the bureaucracy to use this money effectively which might be much too late.

But in theory I think you're right.

I think here the question is what is the goal? If the goal of the code is to learn and teach, then understandability is critical. If the goal to efficiently produce useful software, then that is not necessarily the case, because the end-users could not care less if the code is understandable. They just want it to work. And maybe understandability and "working" are correlated, but not necessarily.

fair points but i disagree. LLMs are very good about explaining and summarizing complicated material. You can test this today with any modern LLM about any topic or paper you like. One thing that makes them so powerful is that they can customize their explanation to the specific querier.

Today, to explain and communicate these math proofs, it makes sense that a human working with an LLM would be the most effective at human explanation. However, given LLMs current abilities with explanation, it seems reasonable that LLMs will become equal to human experts in explanation. Again part of their power is that they can scale to 1-on-1 explanations for the particular audience which humans cannot do.

> "it's not X it's Y" construct.

I agree this is annoying, but this is not a fundamental feature of LLMs, this is "tick" of current models, like the em-dash. There have been countless of these "ticks" that have been refined and this process will continue.