In TensorFlow, during the training process of the models, the parameters are maintained in the memory as variables. When a variable is created, you can use a tensor defined as a parameter of the function as an initial value, which can be a constant or a random value.

In this special guest feature, Dave O'Flanagan, CEO and co-founder of Boxever, outlines how airlines are leveraging big data and predictive capabilities to transform how they engage with customers. Dave is the CEO and co-founder of Boxever, a data science and omni-channel personalization platform for travel companies. The subprime financial crisis revealed that our data is only as good as our ability to analyze and understand it. AI will be necessary to helping prevent the next crisis before it happens. Marco Scirea, a PhD student at the IT University of Copenhagen, won the best paper award at the EvoMUSART conference for his research on music composition using artificial intelligence.

Picture the scenario - a sentient machine is "living" in the US in the year 2050 and starts browsing through the US constitution. Having read it, it decides that it wants the opportunity to vote. Oh, and it also wants the right to procreate. Pretty basic human rights that it feels it should have now it has human-level intelligence. "Do you give it the right to vote or the right to procreate because you can't do both?" asks Ryan Calo, a law professor at the University of Washington.

In a span of two and a half hours, Microsoft packed a lot into the opening keynote of its Build 2016 conference. But it was the last video shown that seem to have the biggest impact on many of the viewers at home: the introduction of an AI that helps one of its blind developers "see." At the very end of its keynote, Microsoft CEO Satya Nadella reiterated that he wants technology to enhance the ways humans communicate. Though the many chat bots he introduced earlier seems technologically "smart," the framework behind it still needs the help of developers to continue improving on what has already been built. Some of the biggest names in tech are coming to TNW Conference in Amsterdam this May.

Artificial intelligence (A.I. as many refer to it) is quickly becoming our reality. And even though its technology is all around us, many of us don't understand what that technology is. The "misconception" about artificial intelligence, is that it's a "robot," says Tim Urban, whose stick-figure-filled explainer on the technology has been read by more than 4 million people on his website, Wait But Why. The robot, however, is merely the "container" for the artificial intelligence, Urban told Olivia Stern for "Sunday TODAY with Willie Geist." "The A.I. is the software inside the container. The A.I. is, in particular, software that can make decisions."

PRINCETON, NEW JERSEY – Last month, AlphaGo, a computer program specially designed to play the game go, caused shock waves among aficionados when it defeated Lee Sidol, one of the world's top-ranked professional players, winning a five-game tournament by a score of 4-1. Why, you may ask, is that news? Twenty years have passed since the IBM computer Deep Blue defeated world chess champion Garry Kasparov, and we all know computers have improved since then. But Deep Blue won through sheer computing power, using its ability to calculate the outcomes of more moves to a deeper level than even a world champion can. Go is played on a far larger board (19 by 19 squares, compared to eight by eight for chess) and has more possible moves than there are atoms in the universe, so raw computing power was unlikely to beat a human with a strong intuitive sense of the best moves.

Nasa has announced that it has found evidence of flowing water on Mars. Scientists have long speculated that Recurring Slope Lineae -- or dark patches -- on Mars were made up of briny water but the new findings prove that those patches are caused by liquid water, which it has established by finding hydrated salts. Several hundred camped outside the London store in Covent Garden. The 6s will have new features like a vastly improved camera and a pressure-sensitive "3D Touch" display

Twenty years have passed since the IBM computer Deep Blue defeated world chess champion Garry Kasparov, and we all know computers have improved since then. But Deep Blue won through sheer computing power, using its ability to calculate the outcomes of more moves to a deeper level than even a world champion can. Go is played on a far larger board (19 by 19 squares, compared to 8x8 for chess) and has more possible moves than there are atoms in the universe, so raw computing power was unlikely to beat a human with a strong intuitive sense of the best moves. Instead, AlphaGo was designed to win by playing a huge number of games against other programs and adopting the strategies that proved successful. You could say that AlphaGo evolved to be the best Go player in the world, achieving in only two years what natural selection took millions of years to accomplish.

GE's electronic work instructions with the Google Glass by Novotek: Novotek combined GE's electronic work instructions with the Google Glass wearable computing device, and was demonstrated to Summit attendees in the Technology Fair. Novotek, is the largest European distributor for GE's Intelligent Platforms business and it has been awarded the Scanautomatic Prize for Innovation at Scanautomatic 2014 in Gothenburg, Sweden in October. Novotek has since 1986 worked with integration of IT and automation systems in the process and production industry. Novotek mainly supplies world-leading products and solutions from GE in the Nordics and Benelux. A work process management solution, GE's Proficy Workflow software provides users with interactive, step-by-step task instructions and captures process, traceability and quality data across systems to reduce errors, waste and delays.

In magnetoencephalography (MEG) the conventional approach to source reconstruction is to solve the underdetermined inverse problem independently over time and space. Here we present how the conventional approach can be extended by regularizing the solution in space and time by a Gaussian process (Gaussian random field) model. Assuming a separable covariance function in space and time, the computational complexity of the proposed model becomes (without any further assumptions or restrictions) $\mathcal{O}(t^3 + n^3 + m^2n)$, where $t$ is the number of time steps, $m$ is the number of sources, and $n$ is the number of sensors. We apply the method to both simulated and empirical data, and demonstrate the efficiency and generality of our Bayesian source reconstruction approach which subsumes various classical approaches in the literature.