Modelling Human Intelligence
...human intelligence modelling
traditional AI - model a single thougt, model logic, not intelligence
expert systems- model a large amount of knowledge, automate capabilities of eliminating solution states available as solution to a problem, not intelligence
neural networks- reduce the concept of intelligence to the most basic of actions in the brain, neurons firing, that too statiscally defined , not model for intelligence, ultimately deterministic determined by mathematical equtions, cannt hope to model ture thought
need for human modelling, is plausible to consider that we will be able to achieve human brain like speed 10^17 flops, but until computers capable of modeling human thought, their contribution to total amount of intelligence on earth remains vanishingly small, if however hey do become capable of thought, the advantages that accrue to them will lead to tremendous leaps, the most significant being the fact that they can modify their own architecture leading to growth in intellignece that cannot be experienced by human population. also if they are capable of human thought ,the hardware that they will be capabling of designing will accrue direct advantages to them, leading to exponential growth in capabilty as each achievement speeds the advent of the next.
The academic purpose of modern prehuman AI is to write programs that demonstrate some aspect of human thought - to hold a mirror up to the brain. The commercial purpose of prehuman AI is to automate tasks too boring, too fast, or too expensive for humans. It's possible to dispute whether an academic implementation actually captures an aspect of human intelligence, or whether a commercial application performs a task that deserves to be called "intelligent".
Right now the amount of networked silicon computing power on the planet is slightly above the power of a human brain. The power of a...
View Full Essay
