Intelligence in Nature - Jeremy Narby [90]
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P. 125: ARTIFICIAL INTELLIGENCE
Franklin (1995) writes: âAI (Artificial intelligence) is sometimes defined as the art of making machines do things that would otherwise require intelligence if done by a humanâ (p. 11). Kurzweil (1999) writes: âComputers today exceed human intelligence in a broad variety of intelligent yet narrow domains such as playing chess, diagnosing certain medical conditions, buying and selling stocks, and guiding cruise missiles. Yet human intelligence overall remains far more supple and flexible. Computers are still unable to describe the objects on a crowded kitchen table, write a summary of a movie, tie a pair of shoelaces, tell the difference between a dog and a cat (although this feat, I believe, is becoming feasible today with contemporary neural netsâcomputer simulations of human neurons), recognize humor, or perform other subtle tasks in which their human creators excelâ (pp. 2â3). Lanier (2000) writes: âThe first two or three generations of artificial intelligence researchers took it as a given that blind evolution in itself couldnât be the whole of the story, and assumed that there were elements that distinguished human mentation from other earthly processes. For instance, humans were thought by many to build abstract representations of the world in their minds, while the processes of evolution neednât do that. Furthermore, these representations seemed to possess extraordinary qualities like the fearsome and perpetually elusive âcommon sense.â After decades of failed attempts to build similar abstractions in computers, the field of AI gave up, but without admitting it. Surrender was couched as merely a series of tactical retreats. AI these days is often conceived as more of a craft than a branch of science or engineering. A great many practitioners Iâve spoken with lately hope to see software evolve but seem to have sunk to an almost postmodern or cynical lack of concern with understanding how these gizmos might actually workâ¦Finally, there is an empirical point to be made: There has now been over a decade of work worldwide in Darwinian approaches to generating software, and while there have been some fascinating and impressive isolated results, and indeed I enjoy participating in such research, nothing has arisen from the work that would make software in general any betterâ¦So, while I love Darwin, I wonât count on him to write codeâ (p. 170). See Johnson (2001) on artificial life.
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P. 126: THE HUMAN BRAINâS CONSISTENCY AND NATURE
Colburn (1999) writes: âItâs about three pounds of wrinkled, pinkish-gray matter with the consistency of jellyâand yet, in Emily Dickinson