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> That's when A.I. starts advancing itself and needs humans in the loop no more. You got to put the environment back in the loop though, it needs a source of d
by visarga 1y ago
> That's when A.I. starts advancing itself and needs humans in the loop no more.
You got to put the environment back in the loop though, it needs a source of discovery and validity feedback for ideas. For math and code is easy, for self driving cars doable but not easy, for business ideas - how would we test them without wasting money? It varies field by field, some allow automated testing, others are slow, expensive and rate limited to test.
- jaggederest 1y agoSimulation is the answer. You just need a model that's decent at economics to independently judge the outcome, unless the model itself is smart enough. Then it becomes a self-reinforcing training environment. Now, depending on how good your simulation is, it may or may not be useful, but still, that's how you do it. Something like https://en.wikipedia.org/wiki/MuZero https://en.wikipedia.org/wiki/MuZero
- drbojingle 1y agoElectric dreams. Simulation of what?
- staplers 1y agodoable but not easy, for business ideas That requires a lot of human psychology and advanced hard economic theory (not the fluffy academic kind). With human controlled monetary supply and most high-level business requiring illegal and immoral exploitation of law and humans in general, it's not a path machines can realistically go down or even want machines treading down. Think scams and pure resource extraction. They won't consider many impacts outside of bottom line.
- enknee1 1y agoSimulated environment suggests the possibility of alignment during training but real time, real world, data streams are better. But the larger point stands: you don't need an environment to explore the abstraction landscape prescribed by systems thinking. You only need the environment at the human interface.