AGI is a very weird field, in that approximately half the practitioners are getting experimental results, half are getting formal mathematical results, and half are complete crackpots outside their own field of Narrow AI expertise. These attributes can even appear in the same person, though Ray Kurzweil and Google are famous for seeming more crackpot-y than many for essentially claiming that a sufficiently large deep-learning or neural-network algorithm will at some point develop sapience ;-).
Which is obviously wrong. Everyone knows it will develop sapience and then develop a fetish for small office implements and destroy humanity.
Ok, to be serious, the guys who are actually doing Real Research into this sort of thing are, IMHO, Juergen Schmidhuber and Marcus Hutter. They are getting formal results in what they call the "new formal science" of "Universal Artificial Intelligence", and their insights into UAI are then leading them back to insights into Narrow AI and Machine Learning. Notice how they keep producing publications in reputable journals, keep getting awards for their papers, and keep getting major research grants? That's called results, and it's what shows they're onto something.
They actually wrote a textbook on the subject, but it is, unfortunately, well beyond my level of background knowledge right now. I would recommend it, however, to anyone who thinks that AGI is going to be as cheap and easy as throwing lots and lots of machines into a single gigantic machine-learning cluster.
On the upside, their algorithms can play a game of Pac-Man. Someone ought to enter them in a Procedural Super Mario competition. But overall, the old dream of "Strong AI" is not a matter of just coming up with the One True Algorithm and crossing the finishing line to victory. Even for the researchers smart enough to see the eventual shape of the finished product, there are lots of intermediate steps still to be solved -- even though we now have a better idea of what they are than before.
Thank you eli_gottlieb, do you have a link to where to buy their book and a link to their website?
My AGI project is stalled and this level of AI is beyond my understanding right now, and I have to find a better source to read. I've been using an old AI book from Radio Shack that my father-in-law gave me just before he died in 2002.
I think it was designed for the Tandy 1000 series and BASIC or Prolog that he used to have but I have been trying to convert it to different programming languages. The problem is my wife cleaned up my stuff and I cannot find it anymore. I think this was it: http://www.amazon.com/Understanding-Artificial-Intelligence-... but I am not 100% sure so I have been guessing.
I got sick and became disabled in 2002, and then my father-in-law died of cancer while I was in a hospital almost dying myself. I wanted to finish the AI project he wanted me to do for him, but I've been sick and in way over my head.
If you can't understand the math in that book, then you are basically not going to do better at the Formal UAI field than the crackpots have done for decades. I mean no disrespect, but nobody has actually discovered an easier to understand theory of UAI that gets equivalently good results.
A book from 1986 is definitely obsolete, and definitely applies to Narrow AI rather than AGI. The General/Universal AI field in its modern form dates to roughly the early-mid 2000s (2003ish is when AIXI was published in the Journal of Machine Learning and they got their own conference in 2005... which was kinda crackpotish).
On the other hand, to be encouraging rather than discouraging, one of the things about the AI/Machine Learning field is that you can discover far less than "ahaha, talking robots now!" and still have a useful discovery. A* Heuristic Search was a useful discovery that powers a huge fraction of modern video-game AI, even though it will never take over the world.
For instance, I read a blog post yesterday about writing improved "rock paper scissors" bots and came up with a nice little model of strategic "I know you know I know" Sicilian Reasoning that I scrawled out into a Reddit post.
Which is obviously wrong. Everyone knows it will develop sapience and then develop a fetish for small office implements and destroy humanity.
Ok, to be serious, the guys who are actually doing Real Research into this sort of thing are, IMHO, Juergen Schmidhuber and Marcus Hutter. They are getting formal results in what they call the "new formal science" of "Universal Artificial Intelligence", and their insights into UAI are then leading them back to insights into Narrow AI and Machine Learning. Notice how they keep producing publications in reputable journals, keep getting awards for their papers, and keep getting major research grants? That's called results, and it's what shows they're onto something.
They actually wrote a textbook on the subject, but it is, unfortunately, well beyond my level of background knowledge right now. I would recommend it, however, to anyone who thinks that AGI is going to be as cheap and easy as throwing lots and lots of machines into a single gigantic machine-learning cluster.
On the upside, their algorithms can play a game of Pac-Man. Someone ought to enter them in a Procedural Super Mario competition. But overall, the old dream of "Strong AI" is not a matter of just coming up with the One True Algorithm and crossing the finishing line to victory. Even for the researchers smart enough to see the eventual shape of the finished product, there are lots of intermediate steps still to be solved -- even though we now have a better idea of what they are than before.