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An opinion piece by an ex-Googler, talking, among other things, about how corporate culture is creeping into Google. I've highlighted some snippets which I've found eerily familiar :)

I was so shocked not to see Dario in the authors list!

still practically as an ACT paper ... the first author was the first RF of the team and the one who suggested Dario ...

Yeah I've figured it out from his CV at the end of the article after posting :)

Positioning via accumulated accelerometer data used to stabilize cold trapped atoms. Current systems are not very reliable for submarines, which cannot use GPS underwater. To create the supersensitive quantum accelerometers, Stansfield's team was inspired by the Nobel-prizewinning discovery that lasers can trap and cool a cloud of atoms placed in a vacuum to a fraction of a degree above absolute zero. Once chilled, the atoms achieve a quantum state that is easily perturbed by an outside force - and another laser beam can then be used to track them. This looks out for any changes caused by a perturbation, which are then used to calculate the size of the outside force.

Typically, we send rovers to our planetary neighbors one at a time -- but what if we sent a small team of smaller, less impressive robots instead? That's the idea NASA is exploring at Kennedy Space Center with Swarmies: a quartet of four autonomous robots designed to work together to complete a single mission.

I still think, the lizards have evolved at an unexpectedly high rate and have now taken over the satellite...

NASA validates the EmDrive (http://emdrive.com/) technology for converting electrical energy into thrust. (from the website: "Thrust is produced by the amplification of the radiation pressure of an electromagnetic wave propagated through a resonant waveguide assembly.")

I have to join the skeptics on this one ...

A team from Stanford showing possibility of solar flare prediction using AI techniques and data from the NASA SDO observatory.

Big data analytic systems are reputed to be capable of finding a needle in a universe of haystacks without having to know what a needle looks like. The very best ways to sort large databases of unstructured text is to use a technique called Latent Dirichlet allocation (LDA). Unfortunately, LDA is also inaccurate enough at some tasks that the results of any topic model created with it are essentially meaningless, according to Luis Amaral, a physicist whose specialty is the mathematical analysis of complex systems and networks in the real world and one of the senior researchers on the multidisciplinary team from Northwestern University that wrote the paper. Even for an easy case, big data analysis is proving to be far more complicated than many of the companies selling analysis software want people to believe.

Most of those companies are using outdated algorithms like this LDA and just apply them like retards on those huge datasets. Of course they're going to come out with bad solutions. No amount of data can make up for bad algorithms.

A system of nine quantum bits (qubits) that is robust to errors that would normally destroy a quantum computation has been created by researchers at the University of California, Santa Barbara (UCSB) and Google. The device relies on a quantum error-correction protocol, which the team says could be deployed in practical quantum computers of the future.

The first complete theory of how plasmons produce "hot carriers" has been developed by researchers in the US. The new model could help make this process of producing carriers more efficient, which would be good news for enhancing solar-energy conversion in photovoltaic devices.

I did not read the paper but what is further down written in the article, does not give much hope that this actually gives much more insight than what we had nor that it could be used in any way to improve current PV cells soon: e.g. "To fully exploit these carriers for such applications, researchers need to understand the physical processes behind plasmon-induced hot-carrier generation. Nordlander's team has now developed a simple model that describes how plasmons produce hot carriers in spherical silver nanoparticles and nanoshells. The model describes the conduction electrons in the metal as free particles and then analyses how plasmons excite hot carriers using Fermi's golden rule - a way to calculate how a quantum system transitions from one state into another following a perturbation. The model allows the researchers to calculate how many hot carriers are produced as a function of the light frequency used to excite the metal, as well as the rate at which they are produced. The spectral profile obtained is, to all intents and purposes, the "plasmonic spectrum" of the material. Particle size and hot-carrier lifetimes "Our analyses reveal that particle size and hot-carrier lifetimes are central for determining both the production rate and the energies of the hot carriers," says Nordlander. "Larger particles and shorter lifetimes produce more carriers with lower energies and smaller particles produce fewer carriers, but with higher energies."

Bio-inspired assembly of fluorescent molecules boosts the fluorescence output.

Nice read! It is actually part of the Ariadna PETE study of one of the teams. You can supervise if you want :)

Two research teams have designed an optical gate that can 'switch off' a stream of photons as well as store them ... good news for optical communications as well as future photon-based quantum information systems.

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.

Unfortunately, "make drug discovery faster and much cheaper" actually means "increase profit margin for pharmaceutical companies"...

A common data hub that allows the representation and comparison of data from numerous space missions. "The IMPEx portal offers tools for the visualization and analysis of datasets from different space missions. Furthermore, several computational model databases are feeding into the environment." As they say, with its massive 3D-visualization capabilities it offers the possibility of displaying spacecraft trajectories, planetary ephemerides as well as scientific representations of observational and simulation datasets.

Related to our discussion on crowdfunding from Friday's science coffee. (Another sad example of how Tony Abbott's policy negatively affects the Australian science community... ) A team of astronomers have resorted to raising funds through crowdsourcing to try and save an Australian telescope involved in mapping the Milky Way. The 22-metre diameter Mopra Radio Telescope, based near Coonabarabran in western New South Wales, is slated to be shut down by the end of the year after $110-million was slashed from CSIRO in last year's federal budget.

TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API. TensorFlow was originally developed by researchers and engineers working on the Google Brain Team within Google's Machine Intelligence research organization for the purposes of conducting machine learning and deep neural networks research, but the system is general enough to be applicable in a wide variety of other domains as well.

And the interface even looks a bit less retarded than theano

Engineer Roger Shawyer's controversial EM Drive thruster jets back into relevancy this week, as a team of researchers at NASA's Eagleworks Laboratories recently completed yet another round of testing on the seemingly impossible tech.

I like this just because it will end up on Thijs' desk :D

Interesting that the new comes in... Yahoo Finance :). Another more complete article http://nextbigfuture.com/2015/11/nasa-eagleworks-has-tested-upgraded.html

This is the biggest breakthrough in game AI (and one of the biggest in AI in general) since Deep Blue beat Kasparov in chess: For the first time, a human professional player was defeated in the game of Go. The approach was a combination of tree search and deep neural networks. Very proud of a former colleague on the team at Google Deepmind!

Funny enough, facebook also had a very similar paper around the same time.