"The dataset contains practically all actions of all
players of the MMOG Pardus since the game went online in
2004 [18]. Pardus is an open-ended online game with a world-
wide player base of currently more than 370,000 people. Play-
ers live in a virtual, futuristic universe in which they interact
with others in a multitude of ways to achieve their self-posed
goals [22]. Most players engage in various economic activities
typically with the (self-posed) goal to accumulate wealth and
status. Social and economical decisions of players are often
strongly influenced and driven by social factors such as friend-
ship, cooperation, and conflict."
quite impressive ...
Short GRBS are formed when neutron stars (in a binary system) slam into one another. On the other hand, long GRBs are a result of massive stars going supernova. Stars end their lives in violent explosions, typically leaving behind remnants like neutron stars.
Some bacteria can influence the weather. Up high in the sky where clouds form, water droplets condense and ice crystal grow around tiny particles. Typically these particles are dust, pollen, or even soot from a wildfire. But recently scientists have begun to realize that some of these little particles are alive - they are bacteria evolved to create ice or water droplets around themselves.
old but might be worth a discussion
We finally have an understanding of how Mars transformed from a once habitable, Earth-like planet, into the dry world we see today. NASA researchers have just announced that Mars' once rich atmosphere was stripped away by solar winds in the early days of the Solar System, causing the planet to dry out.
I used the law in some slides :-)!
This sentence is more or less the summary "The end of Moore's law is not a technical issue, it is an economic issue,".
As Moore's himself recognized last year, the Moore's law itself is a pretty wild extrapolation of one exponential growth when there were only 5 experimental points. It is remarkable however how the semiconductor industry grabbed this and made every single effort to make it true. This effort was rewarded by turning semiconductor industry into one of the most important industries worldwide. Now these are challenging times indeed, and "when tide is gone, we realize who was swimming naked"...
The "law" is one of the most successful concrete predictions of the technological future... Still very impressive and a lot more long-lived than Moore had probably ever dreamed of :)
Love this type of friday afternoon research questions. There is also a now famous scene in the movie Clerks discussing the loss of independent contractors lives as the Death Star was being build.. https://www.youtube.com/watch?v=iQdDRrcAOjA
Quoted from one of the authors in a separate interview: "We know that the spin states of atomic nuclei associated with semiconductor defects have excellent quantum properties at room temperature," said Awschalom, Liew Family Professor in Molecular Engineering and a senior scientist at Argonne National Laboratory. "They are coherent, long-lived and controllable with photonics and electronics. Given these quantum 'pieces,' creating entangled quantum states seemed like an attainable goal."
Bringing the quantum world to the macroscopic scale could see some interesting applications in sensors, or generally entanglement-enhanced applications.
They were previously working on the same concept in N-V centers in diamond (as a semiconductor). Here the advantage is that SiC could in principle be integrated with Si or Ge. Anyway its all about controlling coherence.
In the next 10 years some breakthroughs are expected in the field of semiconductor spintronics, but quantum computing in this way lies still in the horizon
Research in active-matter systems is a growing field in biology. It consists in using theoretical statistical physics in living systems such as molecule colonies to deduce macroscopic properties. The aim and hope is to understand how cells divide, take shape and move on these systems.
Being a crossing field between physics and biology "The pot of gold is at the interface but you have to push both fields to their limits." one can read
Maybe we should discuss about this active matter one of these days?
"These are the hallmarks of systems that physicists call active matter, which have become a major subject of research in the past few years. Examples abound in the natural world - among them the leaderless but coherent flocking of birds and the flowing, structure-forming cytoskeletons of cells. They are increasingly being made in the laboratory: investigators have synthesized active matter using both biological building blocks such as microtubules, and synthetic components including micrometre-scale, light-sensitive plastic 'swimmers' that form structures when someone turns on a lamp. Production of peer-reviewed papers with 'active matter' in the title or abstract has increased from less than 10 per year a decade ago to almost 70 last year, and several international workshops have been held on the topic in the past year."
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
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?
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.
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
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?)
[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.
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...
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...
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 :)
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!
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.
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...
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.
@ 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!