Mathilde Marcolli writes: "What is it about all of these famous and less famous, invariably hard, Big Problems™? There is an undeniable sense in which these questions are interesting. Typically they are because, in the process of thinking about a particularly hard question, a lot of new mathematics gets developed that advances the field as a whole. The Riemann hypothesis is currently unsolved (at the time of this writing), but many people, in the process of thinking about the problem, have developed a very significant amount of very interesting mathematics. That is certainly a valuable goal.…
We have got to acknowledge that most of the advanc advances in AI came out of algorithm advances not just the raw hardware. Now if most advances came from algorithms and computer science and programming tell me that their army of AI researchers is not their fundamental advantage.
However, we are actually absolutely doing this. It's just the great works are kernels of operating systems, the browser, the um lots of the software platforms, the phones, the um the incredible advances in uh silicon lithography
Going all in on AI is not the highest return-on-investment strategy if you care about human flourishing, even if AI might lead to rapid scientific advances.
So, we could be fooled into thinking like, "Oh, technology's going to go on forever, we're always going to find new advances." As opposed to sometimes things just flatten out for a long time. So, you have to be careful about that bias that we have living in this time of great acceleration.
Above I dismissed the notion that technological advances should make the market more efficient in all but the short-term sense. Here, I argue it likely goes the other way at longer horizons. And, IMHO, this is the best of my three hypotheses.
Despite these advances, contemporary physical and evolutionary-history-based approaches produce predictions that are far short of experimental accuracy in the majority of cases in which a close homologue has not been solved experimentally and this has limited their utility for many biological applications.
Clearly something other than the current type of healthcare advances will be needed to crack through the natural human lifespan ceiling-it'll take some deeper recoding of the human genome.
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