There must be lots of theorems in optimization theory that can be improved w/ more intellectual effort. Unlike video generation if AI is applied to find better algorithms it will have a direct impact on the economy b/c almost every industrial process is using some kind of constraint optimization algorithm including the simplex algorithm & its variations. But it's not flashy & profitable so OpenAI will keep promising AGI by 2030 w/o showing any actual breakthroughs in real world applications.
One of OpenAI's founding team members developed Adam [0] well before it was flashy and profitable. It's not like nobody is out there trying to develop new algorithms.
The reality is that there are some great, mature solvers out there that work well enough for most cases. And while it might be possible to eke out more performance in specific problems, it would be very hard to beat existing solvers in general.
Theoretical developments like this, while interesting on their own, don't really contribute much to day-to-day users of linear programming. A lot of smart people have worked very hard to "optimize the optimizers" from a practical standpoint.
No one thought that theorems in number theory would ever be useful but those theorems are now the foundations of tools like wireguard. Computing the next frame of a snowboarding video is much less valuable than improvements in optimization algorithms that are used daily for optimal transport logistics & energy grid optimization. The promise of AI was solutions to practical problems but what we are getting are frivolous cartoons & 6 second "movie" clips.
