> Algorithmic mitigation is being explored, but scientists describe it as “embryonic” — potentially demanding computing power that rivals the science processing itself.

It sounds like this would work? Just be more costly, at least in the short term.

> Engineering fixes are the real answer

What is the fix and tradeoff? The article doesn't seem to cover it at all.

> The accidental static bleeding from onboard hardware, coupling through satellite structures and radiating across frequencies nobody authorized.

> The numbers tell the story bluntly:

I wouldn't waste too much compute trying to parse it, lots of LLM tells in the article. Pangram puts it at 100% AI.

You can still do all that. The only thing going is that in some cases the human isn't going to be able to claim that they made the key insights that first solved the problem.

A lot of this would be public funding. If AI is reducing the need for mathematicians in an area it makes sense to fund it less and fund something else that isn't solved.

Surely it is. Ask it to keep a list of all the promising sub paths, reprompt the collections of agents again on these after the main problem has been addressed. Or even release a list of them and let others investigate.

I feel like most of the latest big Chinese lab models are good enough now. If I had to pick a difference it feels like sol goes further towards 1 shotting things and needs less babysitting. But if I am actively prompting and reading the results can get just as far on a lesser model.

They really can't in the open model space. Look at any current open model you would want to use on open router, there will be 20 or more options.

I think that is fine, certain things are becoming less important to learn and certain things more important. With the pace of change it is likely to continue shifting.

I really don't see how anything but social skills are rising in prominence. Perhaps twenty years from now everything will depend on your connections as any "hard" problems will be readily solved by AI (seeing as few problems are ever really novel).

Nothing stopping kids from asking AI to give you responses like this, it is more than capable. There is always going to be the temptation to take short cuts though.

Can just pass it a context, cancel the context, and handle for it in the goroutine.

Some of the pre-ai decline in questions might just be that they had filled out of alot of the question space. What might be more interesting is the traffic graph as it would be possible to have a decline in questions but still have traffic rising to the existing ones.

Today I'd expect even when someone is googling and a question is relevant that most people will just read the AI overview.