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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 :-)
Thijs Versloot

Computer as smart as a 4-year-old? Researchers IQ test new artificial intelligence system - 0 views

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    Artificial and natural knowledge researchers at the University of Illinois at Chicago have IQ-tested one of the best available artificial intelligence systems to see how intelligent it really is. Turns out it's about as smart as the average 4-year-old, they will report July 17 at the U.S. Artificial Intelligence Conference in Bellevue, Wash.
ESA ACT

Alife XI - 0 views

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    Artificial life investigates the fundamental properties of living systems through simulating and synthesizing biological entities and processes in artificial media.
ESA ACT

Models of eel cells suggest electrifying possibilities - 0 views

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    Artificial cells could be built that not only replicate the electrical behavior of electric eel cells but in fact improve on them. Artificial versions of the eel's electricity generating cells could be developed as a power source for medical implants and
johannessimon81

Enzymes grow artificial DNA - Synthetic strands with different backbones replicate and ... - 0 views

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    Scientists have developed artificial genetic molecules with different structural backbones (XNA, TNA) and/ or a different nucleic acid alphabet. (from April 2012)
zoervleis

One Hundred Year Study on Artificial Intelligence (AI100) | - 1 views

shared by zoervleis on 06 Sep 16 - No Cached
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    "The One Hundred Year Study on Artificial Intelligence, launched in the fall of 2014, is a long-term investigation of the field of Artificial Intelligence (AI) and its influences on people, their communities, and society." (...) "The report is designed to address four intended audiences. For the general public, it aims to provide an accessible, scientifically and technologically accurate portrayal of the current state of AI and its potential. For industry, the report describes relevant technologies and legal and ethical challenges, and may help guide resource allocation. The report is also directed to local, national, and international governments to help them better plan for AI in governance. Finally, the report can help AI researchers, as well as their institutions and funders, to set priorities and consider the ethical and legal issues raised by AI research and its applications."
jcunha

The world's first demonstration of spintronics-based artificial intelligence - 2 views

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    Researchers at Tohoku University have, for the first time, successfully demonstrated the basic operation of spintronics-based artificial neural network.
Tom Gheysens

Computing with silicon neurons: Scientists use artificial nerve cells to classify diffe... - 1 views

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    Scientists in Germany are using artificial nerve cells to classify different types of data. These silicon 'neurons' could recognize handwritten numbers, or distinguish plant species based on their flowers.
Tobias Seidl

Self-assembled artificial cilia - PNAS - 1 views

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    Cilia are hairs driven by molecular motors. They are found in monocellular organisms, etc. If we can build such things artificially, we have micro-pumps etc. Any space usability?
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    carlo's distributed actuator study originally considered cilia as well as peristaltic motion if i remember right. i suppose you might still think about debris transport for digging applications. Originally there was an idea for thermal transport aswell which, it turns out, was bollocks.
Joris _

The Origin of Artificial Species: Creating Artificial Personalities - 0 views

  • The first artificial creature to receive the genomic personality is Rity, a dog-like software character that lives in a virtual 3D world in a PC
  • In Rity, internal states such as motivation, homeostasis and emotion change according to the incoming perception
  • The internal control architecture processes incoming sensor information, calculates each value of internal states as its response, and sends the calculated values to the behavior selection module to generate a proper behavior.
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    they have found Christina's dog !!
evo ata

Future Human Evolution - 1 views

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    Scientific and speculative articles about the future of human evolution regarding to artificial intelligence, genetic engineering, transhumanism, nanotechnology, space colonization, time travel, life extension and human enhancement
nikolas smyrlakis

Artificial meat grown in laboratory - UPI.com - 3 views

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    bioengineers did it in the Netherlands - hope sodexho doesn't find out soon !!
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    geee... I want to see how they "exercise" it :)
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    "If it feels and tastes like meat, people will buy it.", sounds like the normal dutch mentality on food. it feels and tastes smth like it
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    aaah! completely crazy these dutch. What's wrong with killing cows and pigs...
Thijs Versloot

Artificially-intelligent Robot Scientist 'Eve' could boost search for new drugs - 4 views

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    Eve, an artificially-intelligent 'robot scientist' could make drug discovery faster and much cheaper, say researchers writing in the Royal Society journal Interface. The team has demonstrated the success of the approach as Eve discovered that a compound shown to have anti-cancer properties might also be used in the fight against malaria.
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    Unfortunately, "make drug discovery faster and much cheaper" actually means "increase profit margin for pharmaceutical companies"...
Nina Nadine Ridder

Scientists teach bacterium a new trick for artificial photosynthesis - 1 views

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    Berkeley Lab researchers are using M. thermoacetica to perform photosynthesis - despite being non-photosynthetic - and also to synthesize semiconductor nanoparticles in a hybrid artificial photosynthesis system for converting sunlight into valuable chemical products.
jaihobah

Quantum Artificial Life in an IBM Quantum Computer - 6 views

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    I tried reading the abstract and my eyes glazed over at the buzzword density. Is this hot doo doo or a meaningful result?
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    wow, quantum, artificial life, biomimetic, quantum supremacy .... quantum machine learning, and quantum artificial intelligence and, wait for it ...... quantum complexity. All in one abstract is this the new champion?
jcunha

Accelerated search for materials with targeted properties by adaptive design - 0 views

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    There has been much recent interest in accelerating materials discovery. High-throughput calculations and combinatorial experiments have been the approaches of choice to narrow the search space. The emphasis has largely been on feature or descriptor selection or the use of regression tools, such as least squares, to predict properties. The regression studies have been hampered by small data sets, large model or prediction uncertainties and extrapolation to a vast unexplored chemical space with little or no experimental feedback to validate the predictions. Thus, they are prone to be suboptimal. Here an adaptive design approach is used that provides a robust, guided basis for the selection of the next material for experimental measurements by using uncertainties and maximizing the 'expected improvement' from the best-so-far material in an iterative loop with feedback from experiments. It balances the goal of searching materials likely to have the best property (exploitation) with the need to explore parts of the search space with fewer sampling points and greater uncertainty.
jcunha

Superfast light source made from artificial atom - 0 views

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    A new more efficient type of single photon light source consisting of a quantum dot reproduces 1954 Robert Dicke theoretical proposal. Applications in quantum communications directly on the target. "All light sources work by absorbing energy - for example, from an electric current - and emit energy as light. But the energy can also be lost as heat and it is therefore important that the light sources emit the light as quickly as possible, before the energy is lost as heat."
jcunha

Electronic synapses that can learn signal the coming of the first real artificial brain - 0 views

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    A nice quartz article about research in neuromorphic hardware in micro/nanotech out there and future vision of the field.
santecarloni

'Designer' graphene makes its debut - physicsworld.com - 1 views

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    Researchers in the US have created the first artificial samples of graphene with electronic properties that can be controlled in a way not possible in the natural form of the material.
santecarloni

Tilting 'nanocups' double optical frequencies - physicsworld.com - 0 views

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    A new type of structure for converting red light into blue has been unveiled by researchers in the US. Known as frequency doubling or second-harmonic generation (SHG), the conversion involves "nanocups", which are tiny, artificially designed 3D structures. SHG is used in light sources and in metrology applications - and the researchers believe that the new structures could be adapted to achieve frequency doubling in parts of the electromagnetic spectrum where it is currently not possible.
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