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In 2018, Putin approved a national research strategy that stretches to 2024. It calls for more money, extra support for early-career scientists, and some 900 new laboratories, including at least 15 world-class research centres with a focus on mathematics, genomics, materials research and robotics. Last year, the government completed a sweeping evaluation of scientific performance at its universities and institutes; it has vowed to modernize equipment in the 300 institutes that made the top quartile. And it says it wants to strengthen previously neglected areas, including climate and environmental research (see ‘Russia’s climate-science ambitions’).


Some researchers see promise in planned reforms.

A theory of how #AI & #brain recognize things. https://bit.ly/2Qnq3RC “In this article, we proposed a hypothesis that we call Switch Hypothesis for explaining how an ANN as well as a real neural network carry out its functions…” #MachineLearning #DeepLearning #NeuralNetworks


Neuroscience and psychology today has advanced significantly. With the use of neuroimaging methods such as functional magnetic resonance imaging (fMRI) and electroencephalography (EEG), human beings have gradually revealed the secrets behind how our brains perceive, recognize and memorize things. However, if you’d like to have a detailed, neuronal-level elucidation on how brains realize its functions, you should be very disappointed because no one is currently capable of doing so. In other words, although our cerebrums are no longer a pitch-black box, it’s still at least a “gray” box, with a lot of enigmas yet to be explained.

Now, in an important new resource for the scientific community published today in Nature Biotechnology, researchers in the lab of Neville Sanjana, PhD, at the New York Genome Center and New York University have developed a new kind of CRISPR screen technology to target RNA.

The researchers capitalized on a recently characterized CRISPR enzyme called Cas13 that targets RNA instead of DNA. Using Cas13, they engineered an optimized platform for massively-parallel genetic screens at the RNA level in human cells. This screening technology can be used to understand many aspects of RNA regulation and to identify the function of non-coding RNAs, which are RNA molecules that are produced but do not code for proteins.

By targeting thousands of different sites in human RNA transcripts, the researchers developed a machine learning-based predictive model to expedite identification of the most effective Cas13 guide RNAs. The new technology is available to researchers through an interactive website and open-source toolbox to predict guide RNA efficiencies for custom RNA targets and provides pre-designed guide RNAs for all human protein-coding genes.

On March 9, 2016, the worlds of Go and artificial intelligence collided in South Korea for an extraordinary best-of-five-game competition, coined The DeepMind Challenge Match. Hundreds of millions of people around the world watched as a legendary Go master took on an unproven AI challenger for the first time in history.

Directed by Greg Kohs with an original score by Academy Award nominee, Hauschka, AlphaGo chronicles a journey from the halls of Oxford, through the backstreets of Bordeaux, past the coding terminals of DeepMind in London, and ultimately, to the seven-day tournament in Seoul. As the drama unfolds, more questions emerge: What can artificial intelligence reveal about a 3000-year-old game? What can it teach us about humanity?

Cleantech is usually focused on electric cars, batteries, clean electrical generation, and the like. But clean also has a more direct connotation for humans of being free from disease.

Danish company UVD Robotics makes germ-, virus-, and mold-killing ultraviolet robots for hospitals. The product has been in existence for a while, but now it’s signed contracts with Chinese hospitals and is shipping units to that country.