We've already got an algorithm that's theoretically capable of passing the turing test. Neural Networks, afterall they're based on our own neurons.

Will it be able truely to pass the turing test? Not for quite some time.

The qualitative difference between sentience and computational power is the ability to learn.

-- Kwon J. Ekstrom

The thing I think we're missing in current AI is goals and barriers to those goals. Some sort of incentive in the bot's programming to do something, anything, other than respond when the other person types, combined with blocks that would require the AI to develop more than just a 1-2 approach to things. The ability to know whether something is a block or not is also essential. This would not only make it more efficient at attaining the goals assigned to it, it would also make it go through the side-topics that humans have to in order to really learn something. Humans can not only learn that 1+2=3, but also the rest of addition, and that 1+2=3 is the same process as 5+26=31, and that this is actually both signifigant and useful for doing other problems.

Assign the goal of language and knowledge, and the bot could eventually see that in order to learn how to speak, it has to pursue topics the person it is talking to mentions. Assign it avoiding being killed, and number of kills in a FPS, and a bot could learn to learn where the powerups are, when to use which guns, and maybe even some more advanced tactics.

I was not discussing the graphics - which as you say while advanced are evolutionary. I was referring to the AI.

In wolfenstein you had bad guys that basically walked towards you and shot. That was pretty much it.

In UT you have bots that will work together as a team, wait in ambush, find and use different weapons, etc, etc.

Yes it's a controlled environment - but so long as you don't try and talk to them you cannot tell the difference between a bot player and a human player much of the time.

Obviously conversation is a harder goal to achieve - but people are making progress towards it.

I agree that a true AI (Machine Sentience) is a good way off yet. On the other hand convincing AI (Turing Test in set situations - for example a convincing peasant in a fantasy world) is not.

To my knowledge I do not believe that what is currently termed "neuronal networks" has been proven to be theoretically able to pass the Turing Test - especially since a mathematical description of the Turing Test does not exist (if I am wrong here, ignore the rest of my post, please).

Also, neuronal network models, and even more so, neuronal networks used in production systems, are definitly not based on our own neurons. True, some ideas behind them might stem from a study of them, but they are so different in behaviour that "oversimplified" does not even come close to it. And even approximating the behaviour of even a single neuron more than just in a broad way is currently beyond the state of the art.

That the only difference between sentience and computational power is the ability to learn, I believe, is very, very wrong. There already are systems that can infere from facts and learn from mistakes - but is an expert or fuzzy logic system sentient?

What neuronal networks, expert systems and all other synthetic systems currently lack and what is an integral part of sentience, is reflection upon their own state, i.e. the ability to extract information about themselves. No neuronal network can tell you, e.g., what it "looks for" when it classifies images.