DailyDirt: Making Computers More Like Humans And Vice Versa
from the urls-we-dig-up dept
As artificial intelligence projects get more advanced, the questions of how to measure general intelligence become increasingly more important. Tests such as beating humans at chess and conversing with people naturally are somewhat crude ways to judge the improvements in silicon-derived cognition. And as many point out, when AI projects do succeed in beating humans at chess (or other intelligent tasks), people move the goal posts and say that chess isn't really an intelligent task or that the computer's approach is fundamentally different from a human's mind. Here are just a few links about humans and computers improving by copying off each other.- Computers playing chess can beat over 99% of the human population at the game (and humans are arguably better at calling a draw). This situation hasn't decreased the popularity of chess, and in fact, it's made humans play more like computers by learning new tricks from chess programs. [url]
- Silicon-based computers are quite energy inefficient as they perform calculations, but how efficient are human brains or other biological computation mechanisms? There are fundamental computational limits for any kind of computer (silicon based or DNA based), but we've only started to quantify the biological limitations. [url]
- Silicon chips designed to mimic the known mechanisms of brain neurons and synapses could create an artificial neural network that processes a multitude of parallel instructions simultaneously. IBM is working on this kind of artificial brain that will require a completely different kind of programming, but it may produce a machine that processes information more like biological systems do (and make more mistakes?). [url]
Filed Under: ai, artificial brain, artificial intelligence, calculations, chess, computational limits, neural networks
