Alphago and it's kind are doing some things that we do, for sure. We do utilise pattern recognition and some of the neurological tools we bring to bear on these problems might look a bit like Alphago.

The thing is those are parts of our neurology that have little to do with general intelligence. I think it's becoming clear that they are merely cognitive tools we bring to bear in the service of our higher level general intelligence machinery. In that sense high level Go and Chess players turn themselves into single-task solvers. They're better at bringing that experience and capability to bear in other domains, because they have general intelligence with which to do so, but those specialised capabilities aren't what make them a being with general intelligence. Or if specialising systems are important to general intelligence, it's as just a part of a much broader and more sophisticated set of neurological systems.

I can't agree with you. I know many chess players at master and Grand Master level. Look at Bobby Fischer too. Human specialization does not carry over very well to other tasks, only marginally...

I don't think that's a disagreement, I think you're right. Most of the benefit someone like that would get from their competence in Chess or Go would be incidental ones. In fact I would say your experience confirms my understanding of this, optimizing for a single domain in the way Alphago does or even in the way humans do, has little to do with general intelligence.

Ah, I misread. So we agree then. On the other hand, I would not be surprised if the hippocampus was highly developed in chess players like Bobby Fischer which could translate into better spatial reasoning. Perhaps general intelligence is best trained by variance.... Not targeted training.

You could be right, and for the record I upvoted your comment for the contribution regarding you experience with high level chess players. I think the downvotes you’re getting are regrettable.

I appreciate your sentiment. This field is my focus right now. My bachelors is in BioChemMed but I am doing a master in CS and have finished many courses including the free ones by Hinton, LeCun, and Bengio.

Here is my strongest prediction:

AGI is only possible if the AGI is allowed to cause changes to its inputs.

Current ML needs to be grafted towards attention mechanisms and more boltzmann net / finite/infinite impulse response nets.

> "... if AGI is allowed to cause changes to its inputs."

Could you elaborate on this point ?

Do you mean that the AGI could change the source of inputs, or change the actual content of those inputs (e.g. filtering) or both?

And why do you think this is a critical piece ?

Both. Attention changes the source. Action interacts with the source, modifying it. But the environment will need to respond back. This is reminiscent of reinforcement training but is more traditional NN except where the input is dynamic and evolving with every batch not only in response to the agent but in response to differential equations or cellukar automata / some type of environment evolution. AGI should be able to change the environment in which it inhabits. Attention in some respects is a start - it is essentially equivalent to telling reality to move the page and watching it happen. Until we have attention AND data modification, we will keep getting the specialized NN we are used to.

But in this classification, isn't "general intelligence" just a meta-single-problem-solver, solving the problem of which single purpose solver to bring to bear on this task?

I think I think, but might I just be using a single problem solver that gives the appearance of thinking?

I suspect the way we think in terms of clear symbols and inference isn't actually how we think but a means of providing a post-hoc narrative to ourselves in a linguistic form.

Edit: Which kind of explains the failure of good-old fashioned symbolic AI as it was modelling the wrong thing.

That makes a lot of sense. An internal narrator on events explaining them to the passenger, rather than the driver of said events.

Definitely not my idea though - couldn't find any good references to where I read about that idea.

[NB I worked in good-old-fashioned AI for a number of years]

> AlphaGo didn't learn the rules of Go. It has no idea what those rules are, it's just been trained through trial and error not to break them.

When given a problem it has never seen before it was able to acquire knowledge of the problem and then apply that knowledge as to solve the problem. Thats the definition of learning and intelligence that can generally be applied to any problem.

> I think it's becoming clear that they are merely cognitive tools we bring to bear in the service of our higher level general intelligence machinery.

What are you on about? Cognition and intelligence are the same thing if it's capable of cognition or as you put it applying "cognitive tools" then it's capable of intelligence.

>When given a problem it has never seen before it was able to acquire knowledge of the problem and then apply that knowledge as to solve the problem. Thats the definition of learning and intelligence that can generally be applied to any problem.

It can't be applied to any problem though. Take the example i gave elsewhere of a game where you provide the rules, and as the game progresses the rules change. There are real games that work like this, generally card games where the cards contain the rules, so as more cards come into play the rules change. Alpha Zero cannot play such games, because there isn't even a way to provide it with the rules.

>> I think it's becoming clear that they are merely cognitive tools we bring to bear in the service of our higher level general intelligence machinery. > >What are you on about? Cognition and intelligence are the same thing if it's capable of cognition or as you put it applying "cognitive tools" then it's capable of intelligence.

I'm saying that human minds apply many cognitive tools, and that Alphago is like one of those tools. It's not like the part choosing and deploying those tools, which is the really interesting and smart part of the system.

The human brain consists of a whole plethora of different cognitive mechanisms. Cognition is a broad term of a huge variety of mechanisms, none of which by themselves constitute all of intelligence. A lot of people look at Alphago and say aha, that's intelligence because it does something we do. Yes, but it only does a tiny, specialist fragment of what we do, and not even one of the most interesting parts.

In a Platonic dialogue, they discuss the definition of knowledge as "true belief with an account". You have true beliefs about language, but you don't know it in the Platonic sense if you can't explain it to someone else. Another way I've heard this defined is, you don't know it if you couldn't write the algorithm for it.

By that definition, most people don't have "knowledge" over most things which they believe and act on. And yet, no one accuses them of not possessing "general intelligence".

If an AI shows the same capabilities as the average human being, I would say that is AGI by definition. Regardless of whether it meets the requirement for Platonic Knowledge.

Really most people learn by a mix of the two. It’s going to take you a lot longer to learn chess is you have no clue on the rules.

But on the other hand if you get into rote memorization before you start the game it’s going to slow you down by having no context.

I think people do both. You learn the rules in order to play a game or perform a task, but with practice you end up training a task specific system that "knows" how to do it without thinking about the rules and perhaps without knowing them.