Originally posted by CrikeyMagnet
One might argue that we, as humans, are a basic implementation of Google. Perhaps slightly more advanced... and that could be the reason that some of the arguments look familiar. We don't like to think about how reflexive we are, and how many of our actions are conditioned... but really, a lot of them are.

Originally posted by petrus4
They're a couple of textual databases with a (possibly weighted) randomisation algorithm, a voice synthesis program, and a graphical subsystem strung together. That's literally all.

I am prepared to state catagorically that strong (digital/mechanical, at least) artificial intelligence does not exist; and also that it most likely never will. If you're going to call this AI, you'll want to call literally any database lookup system that has ever been written AI, as well.

The responses are generated via pure text matching. Sometimes there are wildcards or regexes used, and because of that, the results can *look* a little emergent and like true intelligence, but that is all it is. A complete illusion. What you're essentially looking at here, is a couple of very basic implementations of something like Google, bouncing search results back and forth between each other. Each result is generated by an entirely dumb, static (or mildly fuzzy in the case of a regex, as stated) search pattern.

Nothing to see here, folks. Nothing at all. Move along.

An artificial neural network (ANN), usually called neural network (NN), is a mathematical model or computational model that is inspired by the structure and/or functional aspects of biological neural networks. A neural network consists of an interconnected group of artificial neurons, and it processes information using a connectionist approach to computation. In most cases an ANN is an adaptive system that changes its structure based on external or internal information that flows through the network during the learning phase. Modern neural networks are non-linear statistical data modeling tools. They are usually used to model complex relationships between inputs and outputs or to find patterns in data.