3 ms·
You know, it's kind of funny. We have no idea if the current path is trending toward a local optima, or if we're heading toward a global optima. We are complet
by lostcolony 8y ago
You know, it's kind of funny. We have no idea if the current path is trending toward a local optima, or if we're heading toward a global optima.
We are completely aware of the issues of finding a local optima in our AI (especially ML) algorithms, but little thought has been given if our AI evolution has been trending toward one or not. We're pouring vast research reserves along a few pathways, and hoping that our hill climbing leads to a global maxima (or at least a local one sufficiently high as to be 'human level intelligence')
- jhall1468 8y ago> but little thought has been given if our AI evolution has been trending toward one or not. Wait, you think people aren't thinking about that all the time? They absolutely are. And there's very little obvious ways to determine if this is a local or global optima. Resources are limited and everyone wants to follow the current best results, because that's necessary for business success.
- lostcolony 8y agoOne would expect a competitive advantage, then, in funding research to try something else. Exclusively following the current best results just means equivalency, and provides no competitive edge.
- PeterisP 8y agoAre we? It seems quite the opposite, that the vast research reserves of AI, now heavily funded and employed by industry, are applied to pathways on hills that credibly seem high enough. Current deep learning approaches are sufficient for systems that work well enough to make profitable products, and that's it, there's no claim, expectation or necessity for that to be even a local optimum, much less a global one.