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any of us has knowledge how to use this open source 3D rendering software? -LS I used it, but it was a while ago. Why? - MR

A contribution to why we need the ACT, what science needs to proceed, etc.

A paper on fruit flies and why it is so difficult to kill them. Watch the high speed movies!!!

A new way to move in sand. Which makes me think of the biggest challenge ever: path integration while moving on sand!

open source hardware?why not

If we have so much interest in decision processes, why don't we make a study on it?

has anybody already tried out this? i contains "lotus" and thus has already a handicap in its name but well ... why not check it out

Quantum internet will enable perfectly secure communications, but the technology and means to build the required quantum memories and routers are still many years distant. The proposal here is to store qubits and send them in containers over the oceans. Researchers claim that it is possible to send information at bandwidths measured in teraahertz outperforming the predictions of a quantum router internet. It can be thought in space systems as well. Then the problem is still for how long are we able to store a qubit, without dephasing... PS: As a curiosity, you can find a very interesting book about containers and how in some way they changed our world: Mark Levinson's book 'The Box' http://press.princeton.edu/titles/9383.html Maybe they will do it again

love this one ... it seems to take physicist to explain to the AI crowd what they are actually doing ... Deep learning is a broad set of techniques that uses multiple layers of representation to automatically learn relevant features directly from structured data. Recently, such techniques have yielded record-breaking results on a diverse set of difficult machine learning tasks in computer vision, speech recognition, and natural language processing. Despite the enormous success of deep learning, relatively little is understood theoretically about why these techniques are so successful at feature learning and compression. Here, we show that deep learning is intimately related to one of the most important and successful techniques in theoretical physics, the renormalization group (RG). RG is an iterative coarse-graining scheme that allows for the extraction of relevant features (i.e. operators) as a physical system is examined at different length scales. We construct an exact mapping from the variational renormalization group, first introduced by Kadanoff, and deep learning architectures based on Restricted Boltzmann Machines (RBMs). We illustrate these ideas using the nearest-neighbor Ising Model in one and two-dimensions. Our results suggests that deep learning algorithms may be employing a generalized RG-like scheme to learn relevant features from data.

Wow, this seems like a good idea ... I wonder why we did not have it before .....

Interesting read!

it got some interesting viewpoitns from a game/marketing point of view but to say that Kinect2 was only a marginal improvement over the first one is only true if you think about games. For robots it is a huge step forward!

Why not power an airplane with an ion thruster?

This is an interesting and easily digestible article that sheds some light on why and how (some) insects undergo metamorphosis.

Showing why epycicles worked so well

I would troll the world and do a GR theory using epicycles :)

... related to the new mathematical proof of emergence of structures in random graphs.

Really nice video! Something for the ACT? :-D

Why is it moving so slowly ?

not a surprise though still bad to read ....

On a side note, it's hilarious to read an article on something repeatedly referred to as being secret...

quite self-explanatory described though: "The terrorists apparently would win if Google told you the exact number of times the Federal Bureau of Investigation invoked a secret process to extract data about the media giant's customers. That's why it is unlawful for any record-keeper to disclose it has received a so-called National Security Letter. But under a deal brokered with the President Barack Obama administration, Google on Tuesday published a "range" of times it received National Security Letters demanding it divulge account information to the authorities without warrants. It was the first time a company has ever released data chronicling the volume of National Security Letter requests. National Security Letters allow the government to get detailed information on Americans' finances and communications without oversight from a judge. The FBI has issued hundreds of thousands of NSLs and has even been reprimanded for abusing them. The NSLs are written demands from the FBI that compel internet service providers, credit companies, financial institutions and businesses like Google to hand over confidential records about their customers, such as subscriber information, phone numbers and e-mail addresses, websites visited and more as long as the FBI says the information is "relevant" to an investigation." and ""You'll notice that we're reporting numerical ranges rather than exact numbers. This is to address concerns raised by the FBI, Justice Department and other agencies that releasing exact numbers might reveal information about investigations. We plan to update these figures annually," Richard Salgado, a Google legal director, wrote in a blog post. Salgado was not available for comment. What makes the government's position questionable is that it is required by Congress to disclose the number of times the bureau issues National Security Letters. In 2011, the year with the latest available figures, the FBI issued 16,511 National Sec

And this, kids, is why cloud computing is bad.

ridiculous next frontier for patenting ... mathematics!!!!!

should I take these as an indication of news from the bankers concerning your business case?

this would trigger innovation, and kill mathematics! The world is crazy... imagine a mathematician that will have to pay to use a demonstration for his own demonstration... haha. And the interviewed guy in the article say that this would benefit mathematicians !!! what a joke ! And all the schools that will have to pay billions to Euclid's heirs ! This would kill physics too, and all domains that use mathematics as a tool !