The Andhra Pradesh Government and SAP have signed a MoU here on Thursday to set up a start-up accelerator here. The MoU was signed by SAP Director (Start-up Focus Programme) Mayank Mathur and IT Adviser to AP Government J.A. Chowdary. Mathur said that SAP would strive to create the right kind of eco system in Vizag for the flourishing of start-ups and to develop entrepreneurial spirit among the young. "We will launch the operations initially under our experts based at Bengaluru within a month. They will be visiting Vizag periodically," he said.

A panel of Venture Capitalists from throughout the Bay Area come together to discuss how Artificial Intelligence is catching the eyes of investors across the globe. Panelists discuss the growth of the field and the recent shift in investment from different types of disruptive technologies to AI specifically.

Conventional collaborative filtering techniques treat a top-n recommendations problem as a task of generating a list of the most relevant items. This formulation, however, disregards an opposite - avoiding recommendations with completely irrelevant items. Due to that bias, standard algorithms, as well as commonly used evaluation metrics, become insensitive to negative feedback. In order to resolve this problem we propose to treat user feedback as a categorical variable and model it with users and items in a ternary way. We employ a third-order tensor factorization technique and implement a higher order folding-in method to support online recommendations. The method is equally sensitive to entire spectrum of user ratings and is able to accurately predict relevant items even from a negative only feedback. Our method may partially eliminate the need for complicated rating elicitation process as it provides means for personalized recommendations from the very beginning of an interaction with a recommender system. We also propose a modification of standard metrics which helps to reveal unwanted biases and account for sensitivity to a negative feedback. Our model achieves state-of-the-art quality in standard recommendation tasks while significantly outperforming other methods in the cold-start "no-positive-feedback" scenarios.

With the increase in adoption of Electric Vehicles (EVs), proper utilization of the charging infrastructure is an emerging challenge for service providers. Overstaying of an EV after a charging event is a key contributor to low utilization. Since overstaying is easily detectable by monitoring the power drawn from the charger, managing this problem primarily involves designing an appropriate "penalty" during the overstaying period. Higher penalties do discourage overstaying; however, due to uncertainty in parking duration, less people would find such penalties acceptable, leading to decreased utilization (and revenue). To analyze this central trade-off, we develop a novel framework that integrates models for realistic user behavior into queueing dynamics to locate the optimal penalty from the points of view of utilization and revenue, for different values of the external charging demand. Next, when the model parameters are unknown, we show how an online learning algorithm, such as UCB, can be adapted to learn the optimal penalty. Our experimental validation, based on charging data from London, shows that an appropriate penalty can increase both utilization and revenue while significantly reducing overstaying.

With the general availability of the "Knights Landing" Xeon Phi many core processors from Intel last month, some of the largest supercomputing labs on the planet are getting their first taste of what the future style of high performance computing could look like for the rest of us. We are not suggesting that the Xeon Phi processor will be the only compute engine that will be deployed to run traditional simulation and modeling applications as well as data analytics, graph processing, and deep learning algorithms. But we are suggesting that this style of compute engine – it is more than a processor since it includes high bandwidth memory and fabric interconnect adapters on a single package – is what the future looks like. And that goes for Knights family processors and co-processors as well as the "Pascal" and "Volta" accelerators made by Nvidia, the Sparc64-XIfx and ARM chips that will be used in the used in the Post-K system in Japan made by Fujitsu, the Matrix2000 DSP accelerator being created by China for one of its pre-exascale systems, or the CPU-GPU hybrids based on its "Zen" Opterons that AMD is cooking up for supercomputing systems in the United States and, with licensing partners, in China. During the recent ISC16 supercomputing conference in Frankfurt, Germany, Intel gathered up the executives in charge of some of the largest supercomputing facilities on the planet who are also – not coincidentally, but absolutely intentionally – also early adopters of the Knights Landing Xeon Phi and, in some cases, the Omni-Path interconnect that is a kicker to Intel's True Scale InfiniBand networking.

Japan is famously wary of immigration, fearing that foreign workers will undermine job security and upset familiar ways of life. But there is one kind of industrious interloper that is greeted more enthusiastically in Japan than in any other country. Robots or "immigrants from the future", as my colleague Oliver Morton calls them, are unusually well assimilated into Japanese society. Japan's obsession with robots is well documented. Foreign journalists seem to like Japan's affection for robots almost as much as Japan likes robots.

The story first turned up in mid-May: Foxconn, Apple's favorite manufacturer, was replacing 60,000 of its workers with robots. Everyone from the BBC to Apple fan sites soon reported the ground-shifting news. There was just one problem: It was mostly false. Last weekend, a Foxconn spokesperson told Chinese media that the company hadn't laid off anyone, much less replaced them with automation. That part of the story came from overly enthusiastic bureaucrats in Kunshan, a manufacturing town keen to promote itself as a hub for innovation.

The sight of flying umbrellas, changing altitude with a fluttering rhythm, looks more like an animated Disney scene than graduate work by a student engineer. "I wanted to push the envelope of coordinating drones in the sky," says the project's creator Alan Kwan, a student in MIT's "ACT" (Art, Culture and Technology) program. He wanted his drones to act almost alive, "not like things to be controlled by an algorithm," he says, "but flying creatures that take on a synchronous life." A Hong Kong native, Kwan, 25, has explored scientific art before. He won an award for his Beating Clock project, a reanimated pig heart that keeps time.

Four small rotors to take off and land, one big engine to fly through the sky. Could crowds design the drone of the future? European aviation giant Airbus and Arizona-based open-source manufacturing company Local Motors held a contest for designers across the world to create a new drone concept. This morning, they announced all the winners. Check out the Zelator, by Alexey Medvedev of Omsk, Russia, which won first place in the Airbus Main Prize.

It is the nature of humankind to constantly strive toward innovation and bring forth new inventions. Creativity, imagination and conscious reflection are distinguishing features of the human brain which cannot be copied by machines. However, the use of neuronal networks in machines such as AlphaGO is a prime example that demonstrates the extraordinary speed of development in the area of artificial intelligence (AI). The research and development relevant to AI represents a truly remarkable achievement in human culture. In the years ahead intelligent computers will improve the quality of life: They will diagnose illnesses, recommend therapies, protect the environment, support education and transform the way we work.