The Computers of Star Trek by Gresh Lois H

Author:Gresh, Lois H. [Gresh, Lois H.]
Language: eng
Format: epub
Tags: Science Fiction
ISBN: 9780465011759
Amazon: 0465011756
Goodreads: 11410467
Publisher: Not Avail
Published: 1999-12-08T08:00:00+00:00

As far back as this 1956 conference, artificial intelligence had two definitions. One was top-down: make decisions in a yes-no, if-then, true-false manner—deduce what’s wrong by elimination. The other was quite different, later to be called bottom-up: in addition to yes-no, if-then, true-false thinking, AI should also use induction and many of the subtle nuances of human thought.

The main problem with the top-down approach is that it requires an enormous database to store all the possible yes-no, if-then, true-false facts a computer would have to consider during deduction. It would take an extremely long time to search that database, and would take an extremely long time to arrive at conclusions. It would have to make its way through mazes upon mazes of logic circuits. This is not at all the way humans think. An astonishing number of thoughts blaze through the human brain all at the same time. In computer lingo, our brains are massive parallel processors.

What top-down AI brings to the table are symbolic methods of representing some of our thought processes in machines. Put more simply, top-down AI codes known human behaviors and thought patterns into computer symbols and instructions.

Perhaps the greatest boost to the top-down philosophy was the defeat of world chess champion, Gary Kasparov, by the IBM supercomputer, Deep Blue. Though not artificially intelligent, Deep Blue used a sophisticated IF-THEN program in a convincing display of machine over man.

Chess, however, is a game with a rigid set of rules. Players have no hidden moves or resources, and every piece is either on a square or not, taken or not, moveable in well-defined ways or not. There are no rules governing every situation in the real world, and we almost never have complete information. Humans use common sense, intuition, humor, and a wide range of emotions to arrive at conclusions. Love, passion, greed, anger: how do you code these into if-then statements?

A great example of top-down thinking is Data’s inability to understand jokes and other human emotions. It takes Data six years to comprehend one of Geordi’s jokes. When O‘Brien is upset, Data asks if he wants a drink, a pillow, or some nice music. Data goes through a long list of “comfort” options, none of which makes sense to O’Brien. This is why the top-down approach is inadequate. We can’t program all possibilities into a computer.

From the very beginning of AI research, there were scientists who questioned the top-down approach. Rather than trying to endow the computer with explicit rules for every conceivable situation, these researchers felt it was more logical to work AI in the other direction—to take a bottom-up approach. That is, figure out how to give a computer a foundation of intrinsic capabilities, then let it learn as a child would, on its own, groping its way through the world, making its own connections and conclusions. After all, the human brain is pretty small and doesn’t weigh much, and is not endowed at birth with a massive database having full archives about the situations it will face.

Download

Copyright Disclaimer:
This site does not store any files on its server. We only index and link to content provided by other sites. Please contact the content providers to delete copyright contents if any and email us, we'll remove relevant links or contents immediately.