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AI Experts In High Demand
An anonymous reader writes: The field of artificial intelligence is getting hotter by the moment as Google, Facebook, Amazon, Microsoft and other tech companies snap up experts and pour funding into university research. Commercial uses for AI are still limited. Predictive text and Siri, the iPhone's voice-recognition feature, are early manifestations. But AI's potential has exploded as the cost of computing power drops and as the ability to collect and process data soars. Big tech companies like Facebook and Google now vacuum up the huge amount of data that needs to be processed to help machines make "intelligent" decisions. The relationship between tech giants and academia can be difficult to navigate. Some faculty members complain tech companies aren't doing enough in the many collaborative efforts now under way. One big gripe: Companies aren't willing to share the vast data they are able to collect.
Getting a job with AI is still limited. Companies don't trust it. Spooky sounding tech scares managers and business decision makers. Better off calling it a statistic driven predictor
... the companies are actually willing to look beyond H1B visa holders and low wages. If they're not yet ready to pay what a real expert costs, they're not really in high demand.
It's a series of complex rules with some pattern recognition, it's not fucking AI.
*explains how cognition in human brain works*
And what do you think you are? The more I learn about machine learning, the more impressed I am with natural neural networks and the incredible sophistication of the layered methods which are being applied to achieve complex behaviors.
Also:
http://www.artificial-intelligence.com/comic/7
It's a series of complex rules with some pattern recognition
That is also a pretty good description of what a brain does.
That's a pretty-good description of what an *adult* brain does, but it's not a good description of intelligence - artificial or otherwise. Your adult brain learned the rules from its environment with no assumptions about what those rules were.
Try writing an algorithm that can learn to play either chess or checkers, depending on what game it sees.
Make that same algorithm be able to play asteroids, or drive a car, or OCR.
Make that same algorithm be able to recognize a tune ("row row row your boat") even if it's played in a different key, at a different speed, with variations in tempo, and even variations in key.
Any time you know beforehand what the rules are you are not simulating intelligence - you are simulating the *results* of intelligence. You are just writing down whatever it is that the intelligence in your head has decided.
The intelligence never makes it into the program - it stays in your head.
Uh, the term 'expert systems' predates 'AI'.
Nope. The term "artificial intelligence" was coined in 1955 by John McCarthy. Edward Feigenbaum is considered to be the father of expert systems, and first published a paper about them in 1977.
Irony: Agile development has too much intertia to be abandoned now.