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A Layman’s Guide to Artificial Intelligence
Part One: Introduction to Neural Networks.

If you’re an executive making software purchasing decisions, you may have been asked to evaluate an artificial intelligence solution for your business. (This would be especially true if you’re one of my clients.) This paper is intended to be briefing on the current state of this art, and to separate fact from science fiction regarding a topic that is much more often discussed than it is understood.

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“Probability Points the Other Way”   I was just a child when it started. I really didn't understand any of it. All I remember was Mother gathering all of us and hurrying us to the lightship. I asked why and she didn't answer. Then workers grabbed me a put me in one of those liquid-filled pods that was supposed to protect me. They closed the lid and it was dark. I was just a child.  I really didn't understand any of it.   I wish that I knew then that I would never see Mother again. I wish that I had known then that the World was about to end.  :Cydonian Tablet 295a2  Louis stopped reading the translation screen, “It looks like this one’s another biography, Henry,” he said into his helmet radio as his thickly gloved hands removed the millimeter thin stone tablet from the scanner, carefully putting it back on the dust covered shelf with the others. READ MORE>>

The Two Spirals Problem Solved Using a simple four-layer MLP and standard backprop (You're going to say I cheated.) While the Two-Spirals Problem may be (or actually, may not be) a valuable benchmark for neural network researchers working on new architectures, I believe that it much more valuable, and to a much larger number of people (those working on applied NN solutions), as an example of THE WRONG WAY to present data to a neural network. This paper is intended as a primer on how to evaluate, and manipulate, your dataset prior to building a neural network to improve or even guarantee your results.