Google has built an AI that is capable of beating human professional players in Go boardgame. What next? Skynet?
>The same had been done with chess decades ago
>It became so mundane and easy to make machines 'beat' humans that people just lost interest in it
>Google afraid no one cares about them anymore and just know them for their search
>W-we have to make something cool!
>Make the same shit that already existed for decades but now for another game.
When I was a retarded piece of shit retard practicing programming I made an AI that played connect 4. It is 'almost' perfect. Where is my fucking article?
Where is everyone's fucking article because anyone with half a brain can make an AI that plays a fucking game.
Playing chess can be made by brute force. Go have a combinatorial explosion that requires a different approach.
In your retarded world there's no difference between cutting a tree branch with a stone axe and CNC laser cutting a pattern in a steel sheet.
>What makes you think the AI wouldn't just get rid of us?
No loss if it kills us, for anyone like myself that have a value as a human being it'd be killing 1000 total morons that serve no purpose on this planet.
But as it's going to be designed by people it'll most likely be an optimizing agent acting in generalized human interests but without the vulnerability of bias and corruption.
It used a search algorithm together with an ANN. But ML is also a part of AI. If you're some popsci faggot crying about your general AI meme you should gtfo of my Taoist Monastry meme image board.
Chess has a combinatorial explosion just like go. It's just a slightly smaller game tree. It's no surprise that top-tier go computers would emerge shortly after top-tier chess computers.
This uses a significantly different approach than say Deep Blue used.
Because every step increases moves exponentially the branching factor is extremely significant. Having 400 moves per turn instead of 100 makes an enormous difference (more than a million more possibilities if you check ten moves and then run some heuristic evaluator).
Not really. Chess positions can be evaluated relatively easily using the material value of pieces, the amount of space each player controls, the pawn structure, etc. Go doesn't have that, and that has nothing to do with combinatorial explosion.
The sad part is that this is still a specific environment which any hardcoded software could be programmed into beating a human in.
But afaik DeepMind is using Machine learning which is quite different to hardcoding a algorithm.
Why don't we use neuron-simulation to create a human-like brain by chance?
Even if one generation needs 30min to be simulated we could simulate 1-2million years (first human appearance up until now) in 114 years and considering that technology improves over time this date will probably get closer to our current time.
It's not a method that guarantees a brain when we reach this point but at least it does something.
We don't actually.
Any moron that things we have a good model of how a neuron functions is mentally retarded.
None of those models are actually correct, they only appear correct because the outputs are "close enough."
You do not.
MIT is doing mad research right now trying to figure out how the internals of the neuron work, turns out there are tons of micro tunnels inside for some reason.
Their function is unknown for now.
Japanese pro player looked through the games and tweeted that Sedol might be having hard time when facing AlphaGo in March.
Well the cool thing is they were able to beat them with thousands less board states that deep blue used to beat kasparov.
That alone is pretty fucking cool. Many problems can be reduced to tree search. Even engineering problems like designing machines and what not
there's much more to computer chess than just bruteforcing
search and evaluation algorithms are still being worked on, it's not like your pc can calculate his way to the checkmate or even winning a piece
The mathematician's perspective:
>Chess and Go are games that terminate in finite time
>Therefore they are deterministic, and if every end-state is evaluated as a win for either player I or player II, for each game one of the two players has a winning strategy obviously calculable in finite time
>Therefore these games are both trivial and trivial to solve
Why do the retards in this thread whose maximum level of mathematical achievement is learning calculus keep pretending that they know better what Google is working on, then, uh... Google itself?
At least spend some time reading up how Google DeepMind works before bashing it, you imbeciles. It uses human-like learning algorithms, derived from models of the human brain and behavior. It's one of the most promising AI systems up to date.
>some dumb guy
was a 5-0 wipeout of a 2-dan professional, mate. Granted, he's just the European champ (king of the kindergarten), but that is still stronger than pretty much all amateur Go players.
This is a huge step up from the previous state of the art! Google claims AlphaGo utterly wipes out all other top Go programs, a feat not seen in computer chess since Deep Thought.
>It's going to beat Lee Sedol
don't count your chickens
Many mistakes were made on both sides, according to strong players. There is a lot of difference between a 2-p and a 9-p world champ.
That in itself isn't new anymore. MCTS has been out for a decade, and many other Go programs have also dabbled with neural networks for evaluation. People are saying this is like the 2005 World Computer Chess Championship, where two unknown programs, one open source, crushed the field of established programs. They took a fresh look at existing ideas and simply implemented them better than anyone had before.
>Go is more intuitive
>Chess is more logic-based
This is just wrong. The mental filter that determines which moves a good chess player even begins to consider is just as intuitive as for Go players and always the result of having played thousands of games. Humans can't just start playing by brute-forcing their way through with logic and reason. It's always about building an intuitive knowledge base. Once you have that, Go positions can be considered just as analytically as chess. There literally is no difference except in the details of the moves.