LLM’s seem very good at solving mathematical problems of which there is an enormous amount of exisiting work/attempts in their training data. This is an amazing capability, but does not convince me that these models are «thinking» or «reasoning» in the way a human does. A human mathematician could in theory categorize/discover an entirely new field of mathematics tomorrow, based purely on their «human intelligence»,…
The Navier–Stokes Millennium Prize Problem
201–210 of 234 posts
Re: The Navier–Stokes Millennium Prize Problem
#202> ... we heard rumors that two Millennium Prize problems had been resolved. Inspired by these rumors ... I've observed this exact effect last week. I made a discovery regarding a stepwise performance improvement in a codebase. I shared the benchmark results with a peer and within 12 hours they replicated the same. We had both been looking for this for years. I think giving someone hope that an answer exists might as…
I have a similar story, but perhaps even stranger. I work for a startup. We often bring a wooden arcade with us to conferences as a marketing gimmick. The arcade runs a single side-scrolling video game. You're running from a monster and dodging obstacles. The goal is to survive as long as possible, and your result is measured in meters. There are always a few competitive guys who spend the entire conference taking tu…
There's little reason to aim for a score a lot higher than the current best; and when getting close to the score you're aiming for, it's easy to get agitated and make a mistake.
And if you do beat the high score, you're likely to loosen your attention right after that, and it's even annoying to keep going for much more.
Re: The Navier–Stokes Millennium Prize Problem
#203> The discovery is somewhat overshadowed by accusations of skulduggery from Tristan Buckmaster [...] I think you should not say that. Buckmaster did only state his version of events and was very clear on that he did not make any accusations at all. To quote from his statement pdf: > I am not accusing anyone of anything.
Re: The Navier–Stokes Millennium Prize Problem
#204I really should get up to speed with LEAN, I know AI can probably write it better than me but I'd like to grasp it better still...
Re: The Navier–Stokes Millennium Prize Problem
#205I run a small SaaS[1], like so many others, that uses AI to generate and optimize SQL. Getting this to perform optimally has been a lot of work and now I wonder if OpenAI is outright stealing this knowledge, which without a doubt is highly valuable to them. [1]: https://www.sqlai.ai
Re: The Navier–Stokes Millennium Prize Problem
#206I keep looking for a technical article to appear on HN discussing literally anything about the mathematical result--- Not fluff, not marketing, actual content. Instead, all I read on HN about N.-S. is human soap opera, told from every possible angle. In 100 years we won't care about the soap opera. The N.-S. result itself will still matter. Someone, anyone, please, submit articles on the result itself.
Re: The Navier–Stokes Millennium Prize Problem
#207I run a small SaaS[1], like so many others, that uses AI to generate and optimize SQL. Getting this to perform optimally has been a lot of work and now I wonder if OpenAI is outright stealing this knowledge, which without a doubt is highly valuable to them. [1]: https://www.sqlai.ai
It's extremely unlikely that there is anything interesting or novel in the optimisation of a small SaaS SQL
Re: The Navier–Stokes Millennium Prize Problem
#208> While unlikely, we cannot rule out that de-identified data derived from their usage of our products helped improve our models AKA everything you send to them (and I bet it's the same for any other lab) will be used, no matter what are the TOS, the law or what they publicly say.
Put down the pitchfork. It's a toggle in their settings.
Users data is just too precious to ignore.
Re: The Navier–Stokes Millennium Prize Problem
#209Re: The Navier–Stokes Millennium Prize Problem
#210LLM’s seem very good at solving mathematical problems of which there is an enormous amount of exisiting work/attempts in their training data. This is an amazing capability, but does not convince me that these models are «thinking» or «reasoning» in the way a human does. A human mathematician could in theory categorize/discover an entirely new field of mathematics tomorrow, based purely on their «human intelligence»,…
The kind of humans who invent entire fields of science on their own come by a few times a generation. It’s fine to say AI isn’t anywhere as close to them in intelligence, but instead is comparable to the “average” mathematician who is building on the work done by others and taking it a bit further.