U.S. Navy officials are investigating the use of artificial intelligence technologies to automate business processes and decision making on key Navy and joint platforms ranging from navigation and ship control to tactical analysis, sensors, and weapons.
In fact, Turing well understood the need for empirical evidence, proposing what has become known as the Turing Test to determine if a machine was capable of thinking. The test was an adaptation of a Victorian-style competition called the imitation game.
It involves secluding a man and woman from an interrogator who has to guess which is which by asking questions and studying written replies.
Working at the secretive Google X lab, researchers from Google and Stanford connected 1,000 computers, turned them loose on 10 million YouTube stills for three days, and watched as they learned to identify cat faces.
The first Love-lace-question is whether computational concepts can help us understand how human creativity is possible. The second is whether computers (now or in the future) could ever do things which at least appear to be creative.
In 1950, Alan Turing, A British mathematician, proposed a test standard called "Turing Test," with the aim to determine whether a machine had human intelligence.
No matter how complex artificial intelligence systems get, information must be programmed in at this basic level, and with every possible variation. You can imagine why computer codes are really, really long. Some take months or years to write. But when they are finished, some computers can complete hundreds of thousands of tasks in as little as one second
Traditional, or top-down AI continued during this period but new approaches began to emerge that looked at AI from the bottom-up. These approaches were also labeled Neat and Scruffy approaches segregating them into their representative camps.
Many people find such a scientific quest unnerving. It is unnerving. The possibility that some of our most cherished human attributes might be scientifically explained could be seen as a sort of threat.
The history of AI is interesting all by itself. It's a modern-day drama, filled with excitement and anticipation, discovery, and disappointment. From over-promises of early (and later) AI research, to fears of the unknown from the general public, AI's history is worthy of study by itself.
The central scientific goal of AI is to understand the principles that make intelligent behavior possible in natural or artificial systems. This is done by:
-the analysis of natural and artificial agents;
-formulation and testing hypotheses about what it takes to construct intelligent agents; and
-designing, building, and experimenting with computational systems that perform tasks commonly viewed as requiring intelligence.