Top-down vs bottom-up AI

The top-down approach seeks to replicate intelligence by analyzing cognition independent of the biological structure of the brain, in terms of the processing of symbolswhence the symbolic label. The bottom-up approach, on the other hand, involves creating artificial neural networks in imitation of the brains structurewhence

is a large experiment in symbolic AI. The project began in 1984 under the auspices of the Microelectronics and Computer Technology Corporation, a consortium of computer, semiconductor, and electronics manufacturers. In 1995 Douglas Lenat, the CYC project director, spun off the project as Cycorp, Inc., based in Austin, Texas. The

The most common top-down approach to fabrication involves lithographic patterning techniques using short-wavelength optical sources. A key advantage of the top-down approachas developed in the fabrication of integrated circuitsis that the parts are both patterned and built in place, so that no assembly

research, especially with the fields top-down approach to problem solving. The top-down approach, which dominated the field at that time, presupposes that a computer must first be supplied with an internal representation of the essential features of the world in which it operatesan immensely difficult framework problem for all but