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Thijs Versloot

Turing test success marks milestone in computing history @UniofReading - 2 views

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    The 65 year-old iconic Turing Test was passed for the very first time by supercomputer Eugene Goostman during Turing Test 2014 held at the renowned Royal Society in London on Saturday.
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    Breaking news: humans fail to pass the Turing Test for the very first time! Suprisingly, playing the dumb boy does not only work for humans, but for chatterbots as well.
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    Is there already a drunk version of the Turing test? Anna?
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    Humans have been failing the reverse turing test for years now actually.
Dario Izzo

Miguel Nicolelis Says the Brain Is Not Computable, Bashes Kurzweil's Singularity | MIT ... - 9 views

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    As I said ten years ago and psychoanalysts 100 years ago. Luis I am so sorry :) Also ... now that the commission funded the project blue brain is a rather big hit Btw Nicolelis is a rather credited neuro-scientist
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    nice article; Luzi would agree as well I assume; one aspect not clear to me is the causal relationship it seems to imply between consciousness and randomness ... anybody?
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    This is the same thing Penrose has been saying for ages (and yes, I read the book). IF the human brain proves to be the only conceivable system capable of consciousness/intelligence AND IF we'll forever be limited to the Turing machine type of computation (which is what the "Not Computable" in the article refers to) AND IF the brain indeed is not computable, THEN AI people might need to worry... Because I seriously doubt the first condition will prove to be true, same with the second one, and because I don't really care about the third (brains is not my thing).. I'm not worried.
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    In any case, all AI research is going in the wrong direction: the mainstream is not on how to go beyond Turing machines, rather how to program them well enough ...... and thats not bringing anywhere near the singularity
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    It has not been shown that intelligence is not computable (only some people saying the human brain isn't, which is something different), so I wouldn't go so far as saying the mainstream is going in the wrong direction. But even if that indeed was the case, would it be a problem? If so, well, then someone should quickly go and tell all the people trading in financial markets that they should stop using computers... after all, they're dealing with uncomputable undecidable problems. :) (and research on how to go beyond Turing computation does exist, but how much would you want to devote your research to a non existent machine?)
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    [warning: troll] If you are happy with developing algorithms that serve the financial market ... good for you :) After all they have been proved to be useful for humankind beyond any reasonable doubt.
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    Two comments from me: 1) an apparently credible scientist takes Kurzweil seriously enough to engage with him in polemics... oops 2) what worries me most, I didn't get the retail store pun at the end of article...
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    True, but after Google hired Kurzweil he is de facto being taken seriously ... so I guess Nicolelis reacted to this.
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    Crazy scientist in residence... interesting marketing move, I suppose.
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    Unfortunately, I can't upload my two kids to the cloud to make them sleep, that's why I comment only now :-). But, of course, I MUST add my comment to this discussion. I don't really get what Nicolelis point is, the article is just too short and at a too popular level. But please realize that the question is not just "computable" vs. "non-computable". A system may be computable (we have a collection of rules called "theory" that we can put on a computer and run in a finite time) and still it need not be predictable. Since the lack of predictability pretty obviously applies to the human brain (as it does to any sufficiently complex and nonlinear system) the question whether it is computable or not becomes rather academic. Markram and his fellows may come up with a incredible simulation program of the human brain, this will be rather useless since they cannot solve the initial value problem and even if they could they will be lost in randomness after a short simulation time due to horrible non-linearities... Btw: this is not my idea, it was pointed out by Bohr more than 100 years ago...
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    I guess chaos is what you are referring to. Stuff like the Lorentz attractor. In which case I would say that the point is not to predict one particular brain (in which case you would be right): any initial conditions would be fine as far as any brain gets started :) that is the goal :)
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    Kurzweil talks about downloading your brain to a computer, so he has a specific brain in mind; Markram talks about identifying neural basis of mental diseases, so he has at least pretty specific situations in mind. Chaos is not the only problem, even a perfectly linear brain (which is not a biological brain) is not predictable, since one cannot determine a complete set of initial conditions of a working (viz. living) brain (after having determined about 10% the brain is dead and the data useless). But the situation is even worse: from all we know a brain will only work with a suitable interaction with its environment. So these boundary conditions one has to determine as well. This is already twice impossible. But the situation is worse again: from all we know, the way the brain interacts with its environment at a neural level depends on his history (how this brain learned). So your boundary conditions (that are impossible to determine) depend on your initial conditions (that are impossible to determine). Thus the situation is rather impossible squared than twice impossible. I'm sure Markram will simulate something, but this will rather be the famous Boltzmann brain than a biological one. Boltzman brains work with any initial conditions and any boundary conditions... and are pretty dead!
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    Say one has an accurate model of a brain. It may be the case that the initial and boundary conditions do not matter that much in order for the brain to function an exhibit macro-characteristics useful to make science. Again, if it is not one particular brain you are targeting, but the 'brain' as a general entity this would make sense if one has an accurate model (also to identify the neural basis of mental diseases). But in my opinion, the construction of such a model of the brain is impossible using a reductionist approach (that is taking the naive approach of putting together some artificial neurons and connecting them in a huge net). That is why both Kurzweil and Markram are doomed to fail.
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    I think that in principle some kind of artificial brain should be feasible. But making a brain by just throwing together a myriad of neurons is probably as promising as throwing together some copper pipes and a heap of silica and expecting it to make calculations for you. Like in the biological system, I suspect, an artificial brain would have to grow from a small tiny functional unit by adding neurons and complexity slowly and in a way that in a stable way increases the "usefulness"/fitness. Apparently our brain's usefulness has to do with interpreting inputs of our sensors to the world and steering the body making sure that those sensors, the brain and the rest of the body are still alive 10 seconds from now (thereby changing the world -> sensor inputs -> ...). So the artificial brain might need sensors and a body to affect the "world" creating a much larger feedback loop than the brain itself. One might argue that the complexity of the sensor inputs is the reason why the brain needs to be so complex in the first place. I never quite see from these "artificial brain" proposals in how far they are trying to simulate the whole system and not just the brain. Anyone? Or are they trying to simulate the human brain after it has been removed from the body? That might be somewhat easier I guess...
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    Johannes: "I never quite see from these "artificial brain" proposals in how far they are trying to simulate the whole system and not just the brain." In Artificial Life the whole environment+bodies&brains is simulated. You have also the whole embodied cognition movement that basically advocates for just that: no true intelligence until you model the system in its entirety. And from that you then have people building robotic bodies, and getting their "brains" to learn from scratch how to control them, and through the bodies, the environment. Right now, this is obviously closer to the complexity of insect brains, than human ones. (my take on this is: yes, go ahead and build robots, if the intelligence you want to get in the end is to be displayed in interactions with the real physical world...) It's easy to dismiss Markram's Blue Brain for all their clever marketing pronouncements that they're building a human-level consciousness on a computer, but from what I read of the project, they seem to be developing a platfrom onto which any scientist can plug in their model of a detail of a detail of .... of the human brain, and get it to run together with everyone else's models of other tiny parts of the brain. This is not the same as getting the artificial brain to interact with the real world, but it's a big step in enabling scientists to study their own models on more realistic settings, in which the models' outputs get to effect many other systems, and throuh them feed back into its future inputs. So Blue Brain's biggest contribution might be in making model evaluation in neuroscience less wrong, and that doesn't seem like a bad thing. At some point the reductionist approach needs to start moving in the other direction.
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    @ Dario: absolutely agree, the reductionist approach is the main mistake. My point: if you take the reductionsit approach, then you will face the initial and boundary value problem. If one tries a non-reductionist approach, this problem may be much weaker. But off the record: there exists a non-reductionist theory of the brain, it's called psychology... @ Johannes: also agree, the only way the reductionist approach could eventually be successful is to actually grow the brain. Start with essentially one neuron and grow the whole complexity. But if you want to do this, bring up a kid! A brain without body might be easier? Why do you expect that a brain detached from its complete input/output system actually still works. I'm pretty sure it does not!
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    @Luzi: That was exactly my point :-)
Marcus Maertens

Enigma hero Alan Turing should be pardoned, leading scientists claim - Telegraph - 0 views

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    Stephen Hawking is also in for that
santecarloni

Magic: the Gathering is Turing Complete - 1 views

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    so happy that the times of ACT magic are over ... or are they?
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    of course not !!!! :) The ACT Magic nights are alive and well, and getting crazier all the time. And I'm happy to say, no blood has been spilled yet... though at times we've come close :).
ESA ACT

Sustainability of Human Progress - 0 views

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    from the guy recipient of Turing awar 1971 (DI)
ESA ACT

Loebner Prize Home Page - 0 views

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    The Loebner Prize for artificial intelligence is the first formal instantiation of a Turing Test.
Dario Izzo

Bold title ..... - 3 views

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    I got a fever. And the only prescription is more cat faces! ...../\_/\ ...(=^_^) ..\\(___) The article sounds quite interesting, though. I think the idea of a "fake" agent that tries to trick the classifier while both co-evolve is nice as it allows the classifier to first cope with the lower order complexity of the problem. As the fake agent mimics the real agent better and better the classifier has time to add complexity to itself instead of trying to do it all at once. It would be interesting if this is later reflected in the neural nets structure, i.e. having core regions that deal with lower order approximation / classification and peripheral regions (added at a later stage) that deal with nuances as they become apparent. Also this approach will develop not just a classifier for agent behavior but at the same time a model of the same. The later may be useful in itself and might in same cases be the actual goal of the "researcher". I suspect, however, that the problem of producing / evolving the "fake agent" model might in most case be at least as hard as producing a working classifier...
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    This paper from 2014 seems discribe something pretty similar (except for not using physical robots, etc...): https://papers.nips.cc/paper/5423-generative-adversarial-nets.pdf
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    Yes, this IS basically adversarial learning. Except the generator part instead of being a neural net is some kind of swarm parametrization. I just love how they rebranded it, though. :))
Luís F. Simões

Evolution of AI Interplanetary Trajectories Reaches Human-Competitive Levels - Slashdot - 4 views

  • "It's not the Turing test just yet, but in one more domain, AI is becoming increasingly competitive with humans. This time around, it's in interplanetary trajectory optimization. From the European Space Agency comes the news that researchers from its Advanced Concepts Team have recently won the Gold 'Humies' award for their use of Evolutionary Algorithms to design a spacecraft's trajectory for exploring the Galilean moons of Jupiter (Io, Europa, Ganymede and Callisto). The problem addressed in the awarded article (PDF) was put forward by NASA/JPL in the latest edition of the Global Trajectory Optimization Competition. The team from ESA was able to automatically evolve a solution that outperforms all the entries submitted to the competition by human experts from across the world. Interestingly, as noted in the presentation to the award's jury (PDF), the team conducted their work on top of open-source tools (PaGMO / PyGMO and PyKEP)."
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    We made it to Slashdot's frontpage !!! :)
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    Congratulations, gentlemen!
Thijs Versloot

Does your iPhone have free will? #arXiv - 3 views

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    If you've ever found your iPhone taking control of your life, there may be a good reason. It may think it has free will. That may not be quite as far-fetched as it sounds. Today, one leading scientist outlines a 'Turing Test' for free will and says that while simple devices such as thermostats cannot pass, more complex ones like iPhones might.
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    An interesting paper about how you should *NOT* think about free will...
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    I must say that the fact that the outcome of a thought process is not evident to myself in advance sounds like a more plausible explanation than 'free will' being the product of quantum mechanics. The later would not only produce unpredictable decisions but probably also irrational ones...
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    Even if it were the product of quantum mechanics, it's still the result of external interference and not the result of 'free' will. It doesn't matter if the external input is deterministic or random, it's still external and it's not "YOU" that decided stuff.
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    I don't know the inventor of that nonsense that the free will should be the result of QM. It's about the only point I agree with the author of the paper: QM is not necessary and doesn't help. What I meant: all these thought experiments done by typical ultra-naive realists (or ultra-naive physicalists, if you prefer) that cultivate the university departments of physics, computer science etc. are put the cart before the horse. First one has to clarify the role of physical theories and its concepts (e.g. causality) and then one can start to ask how "free will" could perhaps be seen in these theories. More than 200 years ago there existed a famous philosopher named Kant who had some interesting thoughts about this. But authors like Lloyd behave as if he never existed, in fact is view of the world is even pre-Platonic!
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    Henry Kissinger How I'm missing yer And wishing you were here
Francesco Biscani

Why three buses come at once, and how to avoid it - physics-math - 29 October 2009 - Ne... - 4 views

  • Now systems complexity researchers Carlos Gershenson and Luis Pineda of the National Autonomous University of Mexico have devised a mathematical model that shows how the problem might be prevented
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    This is from Carlos, the guy who gave a science coffee talk a couple of months ago.
Ma Ru

The human Turing machine: a neural framework for mental programs - 2 views

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    From the alternative computing series...
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