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Any viral licence is a bad license...

I'm pretty confident I'm about to open a can of worms, but mind explaining why? :)

I am less worried about the can of worms ... actually eager to open it ... so why????

Well, the topic GPL vs other open-source licenses (e.g., BSD, MIT, etc.) is old as the internet and it has provided material for long and glorious flame wars. The executive summary is that the GPL license (the one used by Linux) is a license which imposes some restrictions on the way you are allowed to (re)use the code. Specifically, if you re-use or modify GPL code and re-distribute it, you are required to make it available again under the GPL license. It is called "viral" because once you use a bit of GPL code, you are required to make the whole application GPL - so in this sense GPL code replicates like a virus. On the other side of the spectrum, there are the so-called BSD-like licenses which have more relaxed requirements. Usually, the only obligation they impose is to acknowledge somewhere (e.g., in a README file) that you have used some BSD code and who wrote it (this is called "attribution clause"), but they do not require to re-distribute the whole application under the same license. GPL critics usually claim that the license is not really "free" because it does not allow you to do whatever you want with the code without restrictions. GPL proponents claim that the requirements imposed by the GPL are necessary to safeguard the freedom of the code, in order to avoid being able to re-use GPL code without giving anything back to the community (which the BSD license allow: early versions of Microsoft Windows, for instance, had the networking code basically copy-pasted from BSD-licensed versions of Unix). In my opinion (and this point is often brought up in the debates) the division pro/against GPL mirrors somehow the division between anti/pro anarchism. Anarchists claim that the only way to be really free is the absence of laws, while non-anarchist maintain that the only practical way to be free is to have laws (which by definition limit certain freedoms). So you can see how the topic can quickly become inflammatory :) GPL at the current time is used by aro

whoa, the comment got cut off. Anyway, I was just saying that at the present time the GPL license is used by around 65% of open source projects, including the Linux kernel, KDE, Samba, GCC, all the GNU utils, etc. The topic is much deeper than this brief summary, so if you are interested in it, Leopold, we can discuss it at length in another place.

Thanks for the record long comment - am sure that this is longest ever made to an ACT diigo post! On the topic, I would rather lean for the GPL license (which I also advocated for the Marek viewer programme we put on source forge btw), mainly because I don't trust that open source is by nature delivering a better product and thus will prevail but I still would like to succeed, which I am not sure it would if there were mainly BSD like licenses around. ... but clearly, this is an outsider talking :-)

"Java is clearly an example of a money oriented programming (MOP)." Exactly. And for the industry it's the money that matters. Whatever mathematicians think about it.

It is actually a good thing that it is "MOP" (even though I do not agree with this term): that is what makes it inter-operable, light and easy to learn. There is no point in writing fancy codes, if it does not bring anything to the end-user, but only for geeks to discuss incomprehensible things in forums. Anyway, I am pretty sure we can find a Java guy slamming C++ ;)

Personally, I never understood what the point of Java is, given that: 1) I do not know of any developer (maybe Marek?) that uses it for intellectual pleasure/curiosity/fun whatever, given the possibility of choice - this to me speaks loudly on the objective qualities of the language more than any industrial-corporate marketing bullshit (for the record, I argue that Python is more interoperable, lighter and easier to learn than Java - which is why, e.g., Google is using it heavily); 2) I have used a software developed in Java maybe a total of 5 times on any computer/laptop I owned over 15 years. I cannot name of one single Java project that I find necessary or even useful; for my usage of computers, Java could disappear overnight without even noticing. Then of course one can argue as much as one wants about the "industry choosing Java", to which I would counterargue with examples of industry doing stupid things and making absurd choices. But I suppose it would be a kind of pointless discussion, so I'll just stop here :)

"At Google, python is one of the 3 "official languages" alongside with C++ and Java". Java runs everywhere (the byte code itself) that is I think the only reason it became famous. Python, I guess, is more heavy if it were to run on your web browser! I think every language has its pros and cons, but I agree Java is not the answer to everything... Java is used in MATLAB, some web applications, mobile phones apps, ... I would be a bit in trouble if it were to disappear today :(

I personally do not believe in interoperability :)

Well, I bet you'd notice an overnight disappearance of java, because half of the internet would vanish... J2EE technologies are just omnipresent there... I'd rather not even *think* about developing a web application/webservice/web-whatever in standard C++... is it actually possible?? Perhaps with some weird Microsoft solutions... I bet your bank online services are written in Java. Certainly not in PHP+MySQL :) Industry has chosen Java not because of industrial-corporate marketing bullshit, but because of economics... it enables you develop robustly, reliably, error-prone, modular, well integrated etc... software. And the costs? Well, using java technologies you can set-up enterprise-quality web application servers, get a fully featured development environment (which is better than ANY C/C++/whatever development environment I've EVER seen) at the cost of exactly 0 (zero!) USD/GBP/EUR... Since many years now, the central issue in software development is not implementing algorithms, it's building applications. And that's where Java outperforms many other technologies. The final remark, because I may be mistakenly taken for an apostle of Java or something... I love the idea of generic programming, C++ is my favourite programming language (and I used to read Stroustroup before sleep), at leisure time I write programs in Python... But if I were to start a software development company, then, apart from some very niche applications like computer games, it most probably would use Java as main technology.

The solution of thrusting in space.

Thrusting in space is solved already. Maybe you wanted to say something different?

Thrusting until your fuel runs out is solved, in this way one can produce mass from, among others, solar/star energy directly. What I like about this experiment is that we have the technology already to do it, many parts have been designed for inertial confinement fusion.

I am quite certain that it would be more efficient to use the photons directly for thrust instead of converting them into matter. Also, I am a bit puzzled at the asymmetric layout for photon creation. Typically, colliders use two beam of particle with equal but opposite momentum. Because the total momentum for two colliding particles is zero the reaction products are produced more efficiently as a minimum of collision energy is waisted on accelerating the products. I guess in this case the thermal radiation in the cavity is chosen instead of an opposing gamma ray beam to increase the photon density and increase the number of collisions (even if the efficiency decreases because of the asymmetry). However, a danger from using a high temperature cavity might be that a lot of thermionic emission creates lots of free electrons with the cavity. This could reduce the positron yield through recombination and would allow the high energetic photons to loose energy through Compton scattering instead of the Breit-Wheeler pair production.

Well, the main benefit from e-p pair creation might be that one can accelerate these subsequently to higher energies again. I think the photon-photon cross-section is extremely low, such that direct beam-beam interactions are basically not happening (below 1/20.. so basically 0 according to quantum probability :P), in this way, the central line of the hohlraum actually has a very high photon density and if timed correctly maximizes the reaction yield such that it could be measured.

I agree about the reason for the hohlraum - but I also keep my reservations about the drawbacks. About the pair production as fuel: I pretty sure that your energy would be used smarter in using photon (not necessarily high energy photons) for thrust directly instead of putting tons of energy in creating a rest-mass and then accelerating that. If you look at E² = (p c)²+(m0 c)² then putting energy into the mass term will always reduce your maximum value of p.

Q1: For the time being, for what purposes computers are mainly used on-board?

for navigation, control, data handling and so on .... why?

Well, because the point is to identify an application in which such computers would do the job... That could be either an existing application which can be done sufficiently well by such computers or a completely new application which is not already there for instance because of some power consumption constraints... Q2 would be then: for which of these purposes strict determinism of the results is not crucial? As the answer to this may not be obvious, a potential study could address this very issue. For instance one can consider on-board navigation systems with limited accuracy... I may be talking bullshit now, but perhaps in some applications it doesn't matter whether a satellite flies on the exact route but +/-10km to the left/right? ...and so on for the other systems. Another thing is understanding what exactly this probabilistic computing is, and what can be achieved using it (like the result is probabilistic but falls within a defined range of precision), etc. Did they build a complete chip or at least a sub-circiut, or still only logic gates...

Satellites use old CPUs also because with the trend of going for higher power modern CPUs are not very convenient from a system design point of view (TBC)... as a consequence the constraints put on on-board algorithms can be demanding. I agree with you that double precision might just not be necessary for a number of applications (navigation also), but I guess we are not talking about 10km as an absolute value, rather to a relative error that can be tolerated at level of (say) 10^-6. All in all you are right a first study should assess what application this would be useful at all.. and at what precision / power levels

The interest of this can be a high fault tolerance for some math operations, ... which would have for effect to simplify the job of coders! I don't think this is a good idea regarding power consumption for CPU (strictly speaking). The reason we use old chip is just a matter of qualification for space, not power. For instance a LEON Sparc (e.g. use on some platform for ESA) consumes something like 5mW/MHz so it is definitely not were an engineer will look for some power saving considering a usual 10-15kW spacecraft

What about speed then? Seven time faster could allow some real time navigation at higher speed (e.g. velocity of a terminal guidance for an asteroid impactor is limited to 10 km/s ... would a higher velocity be possible with faster processors?) Another issue is the radiation tolerance of the technology ... if the PCMOS are more tolerant to radiation they could get more easily space qualified.....

Or: mathematicians catch up with open-source software developers :)

"Similar open-source techniques could be applied in fields such as [...] computer science, where the raw materials are informational and can be freely shared online." ... or we could reach the point, unthinkable only few years ago, of being able to exchange text messages in almost real time! OMG, think of the possibilities! Seriously, does the author even browse the internet?

I do not agree with you F., you are citing out of context! Sharing messages does not make a collaboration, nor does a forum, .... You need a set of rules and a common objective. This is clearly observable in "some team", where these rules are lacking, making team work inexistent. The additional difficulties here are that it involves people that are almost strangers to each other, and the immateriality of the project. The support they are using (web, wiki) is only secondary. What they achieved is remarkable, disregarding the subject!

I think we will just have to agree to disagree then :) Open source developers have been organizing themselves with emails since the early '90s, and most projects (e.g., the Linux kernel) still do not use anything else today. The Linux kernel mailing list gets around 400 messages per day, and they are managing just fine to scale as the number of contributors increases. I agree that what they achieved is remarkable, but it is more for "what" they achieved than "how". What they did does not remotely qualify as "massively" collaborative: again, many open source projects are managed collaboratively by thousands of people, and many of them are in the multi-million lines of code range. My personal opinion of why in the scientific world these open models are having so many difficulties is that the scientific community today is (globally, of course there are many exceptions) a closed, mostly conservative circle of people who are scared of changes. There is also the fact that the barrier of entry in a scientific community is very high, but I think that this should merely scale down the number of people involved and not change the community "qualitatively". I do not think that many research activities are so much more difficult than, e.g., writing an O(1) scheduler for an Operating System or writing a new balancing tree algorithm for efficiently storing files on a filesystem. Then there is the whole issue of scientific publishing, which, in its current form, is nothing more than a racket. No wonder traditional journals are scared to death by these open-science movements.

here we go ... nice controversy! but maybe too many things mixed up together - open science journals vs traditional journals, conservatism of science community wrt programmers (to me one of the reasons for this might be the average age of both groups, which is probably more than 10 years apart ...) and then using emailing wrt other collaboration tools .... .... will have to look at the paper now more carefully ... (I am surprised to see no comment from José or Marek here :-)

My point about your initial comment is that it is simplistic to infer that emails imply collaborative work. You actually use the word "organize", what does it mean indeed. In the case of Linux, what makes the project work is the rules they set and the management style (hierachy, meritocracy, review). Mailing is just a coordination mean. In collaborations and team work, it is about rules, not only about the technology you use to potentially collaborate. Otherwise, all projects would be successful, and we would noy learn management at school! They did not write they managed the colloboration exclusively because of wikipedia and emails (or other 2.0 technology)! You are missing the part that makes it successful and remarkable as a project. On his blog the guy put a list of 12 rules for this project. None are related to emails, wikipedia, forums ... because that would be lame and your comment would make sense. Following your argumentation, the tools would be sufficient for collaboration. In the ACT, we have plenty of tools, but no team work. QED

the question on the ACT team work is one that is coming back continuously and it always so far has boiled down to the question of how much there need and should be a team project to which everybody inthe team contributes in his / her way or how much we should leave smaller, flexible teams within the team form and progress, more following a bottom-up initiative than imposing one from top-down. At this very moment, there are at least 4 to 5 teams with their own tools and mechanisms which are active and operating within the team. - but hey, if there is a real will for one larger project of the team to which all or most members want to contribute, lets go for it .... but in my view, it should be on a convince rather than oblige basis ...

It is, though, indicative that some of the team member do not see all the collaboration and team work happening around them. We always leave the small and agile sub-teams to form and organize themselves spontaneously, but clearly this method leaves out some people (be it for their own personal attitude or be it for pure chance) For those cases which we could think to provide the possibility to participate in an alternative, more structured, team work where we actually manage the hierachy, meritocracy and perform the project review (to use Joris words).

I am, and was, involved in "collaboration" but I can say from experience that we are mostly a sum of individuals. In the end, it is always one or two individuals doing the job, and other waiting. Sometimes even, some people don't do what they are supposed to do, so nothing happens ... this could not be defined as team work. Don't get me wrong, this is the dynamic of the team and I am OK with it ... in the end it is less work for me :) team = 3 members or more. I am personally not looking for a 15 member team work, and it is not what I meant. Anyway, this is not exactly the subject of the paper.

My opinion about this is that a research team, like the ACT, is a group of _people_ and not only brains. What I mean is that people have feelings, hate, anger, envy, sympathy, love, etc about the others. Unfortunately(?), this could lead to situations, where, in theory, a group of brains could work together, but not the same group of people. As far as I am concerned, this happened many times during my ACT period. And this is happening now with me in Delft, where I have the chance to be in an even more international group than the ACT. I do efficient collaborations with those people who are "close" to me not only in scientific interest, but also in some private sense. And I have people around me who have interesting topics and they might need my help and knowledge, but somehow, it just does not work. Simply lack of sympathy. You know what I mean, don't you? About the article: there is nothing new, indeed. However, why it worked: only brains and not the people worked together on a very specific problem. Plus maybe they were motivated by the idea of e-collaboration. No revolution.

Joris, maybe I made myself not clear enough, but my point was only tangentially related to the tools. Indeed, it is the original article mention of "development of new online tools" which prompted my reply about emails. Let me try to say it more clearly: my point is that what they accomplished is nothing new methodologically (i.e., online collaboration of a loosely knit group of people), it is something that has been done countless times before. Do you think that now that it is mathematicians who are doing it makes it somehow special or different? Personally, I don't. You should come over to some mailing lists of mathematical open-source software (e.g., SAGE, Pari, ...), there's plenty of online collaborative research going on there :) I also disagree that, as you say, "in the case of Linux, what makes the project work is the rules they set and the management style (hierachy, meritocracy, review)". First of all I think the main engine of any collaboration like this is the objective, i.e., wanting to get something done. Rules emerge from self-organization later on, and they may be completely different from project to project, ranging from almost anarchy to BDFL (benevolent dictator for life) style. Given this kind of variety that can be observed in open-source projects today, I am very skeptical that any kind of management rule can be said to be universal (and I am pretty sure that the overwhelming majority of project organizers never went to any "management school"). Then there is the social aspect that Tamas mentions above. From my personal experience, communities that put technical merit above everything else tend to remain very small and generally become irrelevant. The ability to work and collaborate with others is the main asset the a participant of a community can bring. I've seen many times on the Linux kernel mailing list contributions deemed "technically superior" being disregarded and not considered for inclusion in the kernel because it was clear that

hey, just catched up the discussion. For me what is very new is mainly the framework where this collaborative (open) work is applied. I haven't seen this kind of working openly in any other field of academic research (except for the Boinc type project which are very different, because relying on non specialists for the work to be done). This raise several problems, and mainly the one of the credit, which has not really been solved as I read in the wiki (is an article is written, who writes it, what are the names on the paper). They chose to refer to the project, and not to the individual researchers, as a temporary solution... It is not so surprising for me that this type of work has been first done in the domain of mathematics. Perhaps I have an ideal view of this community but it seems that the result obtained is more important than who obtained it... In many areas of research this is not the case, and one reason is how the research is financed. To obtain money you need to have (scientific) credit, and to have credit you need to have papers with your name on it... so this model of research does not fit in my opinion with the way research is governed. Anyway we had a discussion on the Ariadnet on how to use it, and one idea was to do this kind of collaborative research; idea that was quickly abandoned...

I don't really see much the problem with giving credit. It is not the first time a group of researchers collectively take credit for a result under a group umbrella, e.g., see Nicolas Bourbaki: http://en.wikipedia.org/wiki/Bourbaki Again, if the research process is completely transparent and publicly accessible there's no way to fake contributions or to give undue credit, and one could cite without problems a group paper in his/her CV, research grant application, etc.

Well my point was more that it could be a problem with how the actual system works. Let say you want a grant or a position, then the jury will count the number of papers with you as a first author, and the other papers (at least in France)... and look at the impact factor of these journals. Then you would have to set up a rule for classifying the authors (endless and pointless discussions), and give an impact factor to the group...?

could we just use genetic algorithms to evolve these shapes and layouts? :P

> Not sure if the skycrane is really necessary but it is certainly cool. I think apart from coolness using a skycrane helps keep the rotating knives away from the recipient...

Honest question, are we ever going to see this in practice? I mean besides some niche application somewhere, isn't it fundamentally flawed or do I need to keep my window opened on the 3rd floor without a balcony when I ordered something from DX? Its pretty cool yes, but practical?

Package delivery is indeed more complicated than it may seem at first sight, although solutions are possible for instance by restricting delivery to distribution centers. What we really need of course is some really efficient and robust AI to navigate without any problems in urban areas : ) The hybrid is interesting since it combines the advantage of a Vertical Takeoff and Landing (and hover), and a wing for more efficient forward flight. Challenges lie in the control of the vehicle under any angle and all that this entails also for higher levels of control. Our lab has first used this concept a few years ago for the DARPA UAVforge challenge, and we had two hybrids in our entry last year for the IMAV 2013 (for some shaky images: https://www.youtube.com/watch?v=Z7XgRK7pMoU ).

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...

True, but after Google hired Kurzweil he is de facto being taken seriously ... so I guess Nicolelis reacted to this.

Crazy scientist in residence... interesting marketing move, I suppose.

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.

we... the article is a bit overblown in my view ... except maybe the last paragraphs: "The collision between universe's is a variation on this theme. "The "colliding universe" scenario can be realized as a simple extension of our earlier experiments simulating the spacetime geometry in the vicinity of big bang," he says. He simulates an expanding universe using concetric rings of gold separated by a dielectric. "When the two concentric ring ("universe") patterns touch each other ("collide"), a Minkowski domain wall is created, in which the metallic stripes touch each other at a small angle," he says. Being able to recreate these exotic events in the lab is certainly interesting but it is beginning to lose its novelty. The problem is that this work is not telling us anything we didn't know--the universe behaves the same way inside a metamaterial as it does outside. What Smolyaninov needs is a way of using his exotic materials to do something interesting. In other words, he needs a killer app. Any ideas? "

Seems to be very good, I am going to make one account for me.

Ugh... no operator overloading, no efficient generic programming and no lambda expressions... Only time will tell, but I don't understand who the intended audience is: I think that Python guys won't care about the (supposedly) increased performance (and you can interface C/C++ with Python easily) and that C++ programmers (I mean, the hardcore serious C++ Boost-like programmers, no the Java-like whiners :P) won't have their beloved templates pried from their cold dead hands with ease.

yeah though I think especially operator overloading is not going to be a main problem, it is as with the JS library though quite thinkable that lots of users will switch or use it (or being put to use it...) because it is done by Google