alt Hacker News> Well at least it seems pretty implausible to me that a machine learning model trained to reproduce human text can in principle generate something that is significantly above human text production ability.
These are not the only currently-in-use AI models. However, recent news has even this particular category of AI solving multiple previously unsolved Erdős problems.
(Even if they also do stupid things on a frequent basis).
> Well, not really. For large-scale AI models it's almost exclusively some form of gradient-based non-linear optimization. Genetic algorithms (which is just hill-climbing optimization with extra steps) and genetic programming (which is really cool and not well-understood) do not perform all that well in practice and I'm not aware of any notable applications.
I said "standard technique" rather than "best" for a reason ;)
This is proof-of-possibility: natural selection did it, we know how to mimic that, but we don't know enough to be sure we're doing it with a reward function that will actually give us minds like ours on an interesting timescale with a probability high enough to care about.
Machines have solved tons of unsolved problems in mathematics. That's not a proof of intelligence.
If you brute force a solution, we congratulate you on your effort.
If you stumble into a solution, we congratulate you for being lucky (if we can distinguish)
If you find a unique solution that no one else imagined, we congratulate you on your intelligence.
These are categorically different things and the difference matters. It's the whole distinction. Though in the real world success usually requires all three (and more), complicating evaluation.
When we're talking about intelligence you can't distill it to "getting the answer". If you do then I'll direct you at an abacus, a calculator, a watch, or google search if you want to look at super intelligence.
Did what? Gradient descent? If that's the argument, you need to read more