Please, show me a chimp or a housefly knowing chess.towforce wrote: ↑Sat Oct 19, 2019 8:03 amWhat does "GPU" mean in this context?corres wrote: ↑Sat Oct 19, 2019 7:16 amThe GPU (more exactly the NN) evaluation contain the result of the many millions games played during self learning. Enhancing the number of played games and the measure of NN we can gain engines playing better and better games.
It is pity but bigger NN needs more powerful hardware.
For solving specific problems, a big NN can be worse than a small one. When a human has done a task enough times, they can do it quickly without conscious thought because fast NN pathways for doing that task get built. However, chimps have much smaller brains than us, but they can still learn simple video games, and when they do, they can easily beat humans because their reaction times are MASSIVELY faster than ours.
More tasks where monkeys outperform humans: the matching pennies game (link), and willingness to change tactics (link).
Going even more extreme, a housefly has complex behaviours in terms of flight control (including landing), walking on six legs, feeding, mating and living life before it can fly (among others), but has a brain size of only around 100,000 neurons (the human brain has around 100,000,000,000 neurons). This shows that good behaviour for solving some complex problems can be encoded in a more simple algorithm than you'd expect.
This would be the exact evidence for your minimalistic idea.
Btw. NN is such a "black box" what has non-linear connection between its input and its output.
So it is not an ideal object for a linear math.