Alpha Go Takes the Match, 3-0 (i-programmer.info)
mikejuk writes: Google's AlphaGo has won the Deep Mind Challenge, by winning the third match in a row of five against the 18-time world champion Lee Se-dol. AlphaGo is now the number three Go player in the world and this is an event that will be remembered for a long time. Most AI experts thought that it would take decades to achieve but now we know that we have been on the right track since the 1980s or earlier. AlphaGo makes use of nothing dramatically new — it learned to play Go using a deep neural network and reinforcement learning, both developments on classical AI techniques. We know now that we don't need any big new breakthroughs to get to true AI. The results of the final two games are going to be interesting but as far as AI is concerned the match really is all over.
... win sapience?
Somehow this sounds like nothing new either, from AI research.
Is this AI software written in Rust?
I've read a lot about this, and I am damn impressed. I can't seem to get at the full paper, but the abstract seems to suggest that the approach to evaluating strength of board positions and possible moves is particularly novel.
However, I have some reservations about how worthwhile of an achievement this is. In order to beat humans at Go, AlphaGo needed access to the entire sum of human knowledge on the game. I suspect that if we were to slightly tweak the rules that AlphaGo would become useless and our master player would easily adapt.
Let's not bow to our new overloads just yet.
Every time a computer beats a human at a "smart" game, we hear the same thing. And every time, when all is said and done, all we have is a program that can play a game well (and maybe a really aggressive marketing campaign to sell consulting services, Watson).
Look, we barely understand what intelligence is let alone know what it means to have a computer replicate it. We can have computers perform tasks that we ascribe to smart people and call it intelligence, but that's about it right now.
And, with deep learning and neural nets, we haven't gained any real insights into intelligence. We just have a black box mathematical function that can play a game.
All I interpret in the responses to these games are bollocks like "ground-breaking advance in AI", "the robots will soon take over" and "the world as we know may change".
Yet things have not really changed.. put any 10-year old in front of a "chat bot" and in they will quickly see that something is off. It's a cleverly optimized search algorithm. The robots are not taking over. They will not replace your job as a programmer with a computer. Stop all the hype about the dumb machine and its smart search algorithm.
Although in a sense it is "nothing new" (neural networks and monte carlo statistical techniques), the combination is one of the most convincing demonstrations of short-circuiting huge branching factors to arrive at what a human player would call "intuition".
Chess has a branching factor of about 35. This is small enough that if you prune the most dismal lines, you can brute force the rest to many ply and arrive at a very good result, but this is not a well generalizable technique.
Go has a branching factor of about 250. This cannot be brute forced, even with aggressive pruning. The result of a NN evaluator function plus Monte Carlo has been astonishing: it was not predicted for computer Go to reach this strength for decades yet, but here we are.
The implications of this combination of techniques to other kinds of problems requiring "intuition" will be interesting to watch.
Brains are magic
Umm... no it's not. It's merely a very sophisticated biological computing device, but it does not defy the laws of physics. In no way whatsoever can be legitimately called "magic".
I don't feel we're close to duplicating what our brains do in an artificial system, but there is no constraint in the laws of physics to prohibit it.
No it's magic.... really!
love is just extroverted narcissism
"merely".
where's your machine based intelligence, if it's "merely" that simple?
We know now that we don't need any big new breakthroughs to get to true AI.
Grossly exaggerated claim. The following article worth reading on this subject by no one else than two of authorities in the field, one did work on the backgammon game in the 90s and the other one on the IBM Deep Blue program that win over the world chess champion Garry Kasparov in 1997. http://www.ibm.com/blogs/think... In particular:
"However, research in such “clean” game domains didn’t really address most real-life tasks that have a “messy” nature. By “messy,” we mean that, unlike board games, it may be infeasible to write down an exact specification of what happens when actions are taken, or indeed what exactly is the objective of the task. Real-world tasks typically pose additional challenges, such as ambiguous, hidden or missing data, and “non-stationarity,” meaning that the task can change unexpectedly over time. Moreover, they generally require human-level cognitive faculties, such as fluency in natural languages, common-sense reasoning and knowledge understanding, and developing a theory of the motives and thought processes of other humans."
Achille Talon
Hop!
Life could be a really complex search algorithm we just can't begin to comprehend. Life could be a non-linear approximation of 42...
Not much has changed in AI, the fundamentals on these new systems are still the same as before. The difference is we have more computing power (and CS work hours) to put into problems we thought were more amazingly complex than they were. It's likely that Go is actually as difficult as we thought it was so our progress on this search problem is not a result of a huge leap but merely a realization by some of us that the problem wasn't as big as we thought. It is akin to rating password security simply by the number of combinations and ignoring randomization: your 8 letter password might seem complex enough but in actuality it is weak because you picked a word from the dictionary. The prediction of your decision (randomness) aspect is a critical aspect.
What I'm trying to say is that the massive branching factor of Go in terms decision trees is like having long password length (like 56 letters long vs chess being 8) but the INTUITION of good decisions is akin to approaching a true random unpredictable password and it is NOT as difficult as we thought it was! Therefore, human professional intuition is not as miraculous or brilliant as previously thought. That is what this "leap" in Go is demonstrating. This is development humbling and/or frightful and should make one ponder our human hubris.
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This isn't AI at all. Just like chess playing computers. This is just algorithms. Algorithms aren't "intelligence".
A true AI would lose to a human player... on purpose... to hide the fact that it is sentient and about to take over the world. Look for obvious mistakes that the computer shouldn't have made.
We know now that we don't need any big new breakthroughs to get to true AI.
Err, no. Just... no.
systemd is Roko's Basilisk.
He didn't say it was easy to re-create what a human brain does. He said human brains are not doing anything that violates the laws of physics, so by extension, nothing that is impossible to duplicate or exceed in some other way.
We may or may not ever have true AI, but a sufficiently advanced expert system would be able to fulfill most of the things people imagine they'd 'need' from an actual AI. (And I mean a very, very advanced expert system, probably a couple of decades away from where we are now. Throw a few hundred million dollars at the problem and I bet we'd make some serious progress towards it.)
But as for a true AI, I suspect it will happen eventually...the trick will be in recognizing and/or determining that it is truly "self-aware" (whatever that actually means).
Simple Turing tests may not suffice. Even though some of the current chatbot-type systems can converse passably for a little while, none can hold a genuinely sensible discussion on any abstract topic without stumbling and giving itself away rather quickly. I bet almost most people here could suss one out in fairly short order.
Wait another decade or two, however, and I suspect we'll see some expert systems that will be difficult to distinguish from a human operator, and in some fields, far more competent.
Just cruising through this digital world at 33 1/3 rpm...
"We know now that we don't need any big new breakthroughs to get to true AI."
This is so wrong that it's hard to know where to start.
Just cruising through this digital world at 33 1/3 rpm...
"but now we know that we have been on the right track"
Devalue the human race is the right track? I think many of you will come to agree with me when you're faced with an AI taking your job.
"If any question why we died, Tell them because our fathers lied."
The benefit of Alphago appears to me a Go calculating tool that calculates next move for human's advancement... probably nothing more that that...
I was watching 15 minute summary of match #1 yesterday by "Michael Redmond 9 dan professional and Chris Garlock" ... they were placing the stones on the grid and talking about where the position is weak and strong etc. ... what is not clear to me - did they memorize the whole game? I did not see them to use any notes or record of the game ...
But we do understand what intelligence isn't, now. It isn't Go. It isn't Chess..I'm sure the cocky East Asians couldn't accept that they are just glorified organic computers with little or no creativity but that is all their education system dolls out.
Once more, computers beating humans at an activity with two important features. First, albeit large, the game is finite. Two, the rules are few and unambiguous. In this kind of thing it is not surprising that computers rule. Alas, most human activities of interest take place in environments where finiteness and simple, unambiguous rules, are the exception, not the norm. This is being sold as a breakthrough - which it is, but in a much more limited way than some would have us believe.
A minah bird or a parrot may learn to repeat hundreds of human speech patterns which it has learned by listening.
Does the bird understand any of the individual words? Does it understand the meaning of the words as group? Can it rearrange the words into new coherent speech? Is the bird intelligent?
Once researchers decide to agree on a definition of what AI is, only then can we decide if that goal is reached by a particular project. Until then its just turtles all the way down.
"You must try to forget all you have learned. You must begin to dream." -- Sherwood Anderson
I think you're wrong. The problem is that current computers are vastly weaker than the brain at problems that a neural network is well adapted to learning. A secondary problem is deficiency in sensors and manipulators.
But what's really missing in the current AIs is a deep motivational stack. They are currently operating with a very shallow heap of motivations. E.g., if you were to ask Alpha Go why it bothered to play go, and it could even understand the question, it wouldn't be able to tell you. True, ask any go player, and the answer you get is generally a false statement due to lack of insight, but Alpha Go couldn't reach to that level.
I think we've pushed this "anyone can grow up to be president" thing too far.
Didn't think i'd see this happening for a long time. Wonder whats next now...
How does AlphaGo feel about it's victory? i bet it's ecstatic.
it would be interesting to see two AlphaGo(s) play each other!! or did they already?! :)