100 billion neurons x 10,000 connections = 1 quadrillion connections firing at 200 Hz. 7 neurotransmitters can be represented by 3 bits of data. So say, 600 quadrillion bits flying around per second. That’s 600 petaflops, roughly. 10 petaflop supercomputers are under construction today so we will be well within the 600 petaflop range in 10 years.

Unless you are a dualist, then you must concede that an artificial brain can be built at least as blackbox, even if we don’t understand how it all works. Cells in mouse hypothalamus have been replaced by silicon chips – we aren’t sure what is being done with the signals sent out of the chips, but they mimic exactly what the cells were doing before they were replaced. The mice function normally.

For 50 years people have made predictions regarding AI, but have not been able to substantiate those claims. Today we are already able to replace neurons with silicon and fully simulate a neocortical cortex column. Rather than trying to create an expert system that can manage millions of rules and somehow look intelligent, we are now copying the structure and function of brains directly.

AI researchers are not so much building an airplane as they are building an artificial bird. Hopefully, the plane will come later, once the bird can fly 30,000 kph

It is interesting how closely the debate, research and execution of AI follows the patterns of the debate between free will and determinism (which could also just as easily be stated: the philosophy of consciousness).

However, my one minor quibble is with your final statement where you speculate that things might reach a state by the year 2020 that would enable effective implementation of AI. I find that statement ironic only in context of the history of AI. About once every 5 or 10 years some expert comes out ans says “We’ll see true AI in 10 to 15 years” – and they’ve been saying that since the 50′s.

I think the difficulties are far greater than anyone connected with the field is able to comprehend. Why else is there such optimism over such a long period of time? Technological advances grant us an even deeper sense of optimism, and why not? We are creating things that people wouldn’t have dreamed possible even 10 years ago. But despite the advances, we’re still at least 10 years away from AI – and we always have been (apparently).

It is my opinion that I will not see true AI in my lifetime (which, hopefully, will be at least another 40 years or so). Despite advances in computer technology (even assuming the advent of quantum computers) we are left with a fundamental gap in the ability of our programing languages to breach the gap between “act in accordance with your programing” (which as a previous commenter said can be very clever indeed) and what humans evaluate as “creativity” or “genius”.

Perhaps I will be deemed to fall into the fold of “mysterianism” which holds that human consciousness is unique and has some magical quality that can never be imbued into computers. I favor a much more simplistic definition: we are not binary.

The complexity of the human brain includes: approximately 100 billion neurons, with each neuron intertwined and connected with upwards of 10,000 other neurons, each one capable of using 7 different known neurotransmitters used in solo or combination to convey specific messages across the network. I’m afraid to even try and calculate the math for how that works out in raw computational power.

As soon as you’re able to develop a computer that can even approach that kind of messaging complexity, then I’ll begin to believe that AI is possible.

This seems to be the crucial question.

Intelligence is the ability to solve problems through mental effort.

Unfortunately this definition undermines the entire field of AI, for several reasons:

1. Computers HAVE NO PROBLEMS. They are neither alive nor self-aware. Therefore the concept of “problem” cannot apply to them. Nevertheless, this is not a significant objection, because we are simply trying to get them to solve OUR problems.

2. Use of the word “Intelligence” in AI is a misnomer. Many of the characteristics commonly understood to constitute human intelligence were trivial problems, solved very early in the development of computers (for example, the ability to do complex math in a very short time with absolute accuracy). Or the ability to generate logical results reliably from indefinitely complex premises. Or the ability to play a passable game of chess (substitute any other game with well defined rules.

On the other hand, we have had very limited success in getting computers to replicate abilities which are trivial for humans, for example the ability to recognize a face, carry on a conversation (pass the Turing Test), or generate a mathematical proof.

The field of “Artificial Intelligence” is largely concerned with human capabilities that are NOT generally considered characteristics of intelligent humans. Instead it attempts to reproduce those things humans do WITHOUT KNOWING HOW. This is the crux of the problem. Any activity that can be expressed as an algorithm can be coded onto a Turing Machine, but in order to produce an algorithm the coder must first understand how to perform the activity. Thus, complex mathematics was easily accomplished on computers, because WE KNOW EXACTLY HOW WE DO IT. Chess was not difficult to program because it has a small set of rules and a well-known set of strategies that lent themselves to algorithmic programming. Facial recognition, on the other hand, is something we do WITHOUT KNOWING HOW. The problem, therefore, is figuring out how we do accomplish an activity before we can tell a machine how to do it. We have made some progress on some of these problems, but we are very far from answering the fundamental questions such as the nature of consciousness. These problems have resisted understanding by philosophers for at least 2500 years, and are not likely to be solved by computer scientists in 50. For this reason I don’t expect human intelligence to be replicated on machines in the foreseeable future, if ever.

This is also why the field of Artificial Intelligence should more correctly be called Artificial Instinct.

I did my PhD research in AI (used Peter Norvig’s book in my graduate studies, by the way). I wrote a program for my dissertation that “learned” by itself, but ultimately I left the field. All of the so-called gains in AI are still a million miles away from the “dull but functional human” There are some things like playing chess that computers do really well. And intelligent humans do those things too. But that in no way means the computer is remotely intelligent.

The whole AI field is nothing but clever programming. Some of those programs are quite clever indeed, but they represent the intelligence of their creators, not the programs. Some programs may appear intelligent in very narrow domains, but they are extremely brittle — they will not be useful at all even on the borders of the domains for which they were designed. I have yet to see a program that has a modicum of intelligence or adaptability outside of a very, very narrow domain. They are more like an idiot savant that can add up sums of large numbers but can’t figure out how to open a door.

People really underestimate the magic of human intelligence, even in the dull but functional humans. Humans are a miracle of adaptability that a computer will never even approach. It isn’t a question of FLOPS or GPUs. We have such an incredibly limited understanding of our own intelligence, how can we have the arrogance to think we can make an intelligence computer?

I think that it will be at least another decade before we’re there…even a super computer can’t match the pure computational power of a human brain.