AI Passes 'Go'

I have a copy of the movie Pi, and the soundtrack. I watch the movie at least once a year, and have a number of the tunes from the soundtrack on the memory stick in my car's audio system.
One of my all-time 20 favorite movies, and likewise one of my favorite music albums.

FWIW, fans of 'Breaking Bad' may recognize the actor (Mark Margolis) who played Sol Robeson, as the wheelchair-bound uncle (Tio Salamanca) of the character Tuco in 'Breaking Bad'. He is reprising the Tio role for the prequel series 'Better Call Saul'.

Hmm. I will have to look into that movie and see what if it's something I would care for but to be honest pretty much every movie thatI have ever watched that had anything to do with mathematics or had a numerical value in its title was by my standards a total waste of my time.

23 with Jim Carry. WTF was that about?

Good Will hunting. Hey! A Robin Williams and Matt Damian movie! Cripes that was hard to sit through give their reputations as actors in my books.

A beautiful mind. A Russell Crow movie how could that go wrong. WTF? 2 hours and 15 minutes of watching a disturbed delusional math professor go on about things he largely imagined were real but weren't which by my estimation means that most of what he thought was mathematics was probably all imagined nonsense too.

From what I can see of PI the guy eventually drills a hole in his head which to be fair yea I can totally see where someone with mathematical obsessions needs that. I've been around a college level mathematic department staff enough times to get the very strong suspicions that most of them needed a fair amount of brain augmentations with a drill as well to get them in touch with reality.

I liked Pi--it's surreal and weird and deals with numerology and paranoia more than pure math. A Beautiful Mind inspired me to read the real bio of John Nash (didn't finish it), and I learned that he never suffered from visual hallucinations as depicted in the film--only auditory. That's pretty liberal cinematic license if you ask me.

Go is an incredible game. it takes only minutes to learn and a lifetime to get a handle on. That a computer as finally been created that can work its way through the vast number of permutations per move in a reasonable amount of time is the only thing this actually demonstrates. After all, a computer does not produce strategy as such. It simply evaluates all possible moves and out comes and picks the one with the best numeric value.

In my mind this does not demonstrate an advancement in AI but an advancement in computational speed.

I think the notability of recent AI breakthroughs like Watson and AlphaGo is that they combine very fast computation, as you mention, with higher degrees of machine learning so that mistakes are not repeated and the success of past moves dictates future moves. To me that's a pretty strategic component.

I do understand your suggestion. I still have to go back to the way computers work and look at your statement as simply a function of larger capacity memory and better addressing systems and faster processing and memory recall. A bad move would be given, for simplicities sake a negative operand so that when the processor is reviewing its memory for that particular move/situation it recalls the negative outcome and moves on to the next one.

What you suggest would simply be a larger memory, (vast) and a very good catalog and recall system functioning at high speeds. A pretty expensive option really. Instead I would posit that the system is functioning much more simply. Instead of carrying a vast library of previous games in memory I would go with the more direct and better suited to high speed computing approach and have it identify each potential placement, evaluate potential response and counter point to X number of moves out and select the one with the highest numerical probability of success. I would have to see the computer actually lay a trap for an opponent or push a bad position before I would consider that machine as "thinking". I believe that was what the small statement about poker was meant to illustrate. Machines still do not understand that a losing move, properly executed, can win because there is, as yet, no way to quanitfy the human response accurately.

Or so my thinking goes.

Just another point of view, but I fail to see much difference here.

How does that differ from human trial and error learning?

Isn't our brain just a high powered organic processing unit and memory storage?

The primary difference as I see it is the lack of emotional effects on the decision making processes. Decisions are less personal and more logical.

AI becoming more n more popular.
Regards,
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