MrToadMan

Was it a first version in TypeScript then rewrite to rust situation?

Apart from the fact that elite sports are funded probably at least 10x more than pure mathematics research.

Why should we all need to agree that 'ai can replace us' when 'us' can mean such different things to different people: someone pushing out content on TikTok has a lower bar for accuracy than someone signing off on documents to be submitted for review by a court. I think that's the origin of a lot of discrepancy between viewpoints on AI that gets in the way of talking about the benefits and harms that we can each identify and framing the discussion around how those are changing when these tools are used. There is no inevitability about AI everywhere - we have the agency to decide when it's right to use it and when it's wrong.

To add to that, I don’t think many employers will be happy about their legal exposure to inadequate training and supervision when things go wrong if this is the sort of training people are resorting to. Especially if insurers are excluding coverage for losses arising from the use of generative AI, as seems to be happening.

A more accurate headline would be 'temporarily blocked' given the first line below the heading is 'The page is now back online' and it seems to have been brought back online the same day.

Didn't they say that they launched an effort to evaluate their model on all open Millennium Prize problems, and then narrowed down to Navier-Stokes as the most promising after seeing results on simplified versions of the problems?

Google also spent heavily setting up deals with other platform owners, invested in Chrome and Android to establish Google search as the default option which most users accepted. If integrations of good enough AI features are made within existing platforms most users will probably accept using those and not think too much about whose model is powering it.

People can also ask questions that it is unreasonable to expect people to know on the spot too and after a while the role of the questioner in the meeting can be questioned. :)

Much like his earlier work Westworld which was also scarily prescient for modern times.

> These are highly complicated pieces of equipment. Almost as complicated as living organisms. In some cases, they have been designed by other computers. We don't know exactly how they work.

The competence threshold can vary according to the model's complexity and cost to run, but the broader point remains that having a human operator of greater competence that can evaluate the output and understand potential harms that might result seems to be a valid one. Depending on domain, it can be irresponsible to deploy systems you don't fully understand that could harm others. Responsibly overseeing 37k lines of code a day sounds exhausting.

If only they had access to a world class translation system, they could auto translate between languages effortlessly :)

I guess my point was that I don't see many algo changes in the commit history, which is a shame if this has been lost; library/* files are largely unchanged from the initial commits. But each time the agent runs, it has access to the best solutions found so far and can start from there, often using randomisation, which the agent claims helps it escape local minima e.g. 'simulated annealing as a universal improver'. It would be nice to see how its learnt knowledge performs when applied to unseen problems in a restricted timeframe.

Not as many changes to the files under library as I expected to see. Most changes seemed to be under a single ‘add stuff’ commit. If some of the solvers are randomised, then repeatedly running and recording best solution found will continually improve over time and give the illusion of the agent making algorithmic advancements, won’t it?