Berkeley Lab researchers Vahe Tshitoyan, Anubhav Jain, Leigh Weston, and John Dagdelen used machine learning to analyze 3.3 million abstracts from materials science papers. Sure, computers can be used to play grandmaster-level chess, but can they make scientific discoveries? Researchers at the U.S. Department of Energy's Lawrence Berkeley National Laboratory have shown that an algorithm with no training in materials science can scan the text of millions of papers and uncover new scientific knowledge. A team led by Anubhav Jain, a scientist in Berkeley Lab's Energy Storage & Distributed Resources Division, collected 3.3 million abstracts of published materials science papers and fed them into an algorithm called Word2vec. By analyzing relationships between words the algorithm was able to predict discoveries of new thermoelectric materials years in advance and suggest as-yet unknown materials as candidates for thermoelectric materials.

A.A.A. is a scholar of the Leukemia and Lymphoma Society. This work used the XStream computational resource, which is supported by the National Science Foundation Major Research Instrumentation program (ACI-1429830). This work used the shared FACS facility, which is supported by NIH S10 Shared Instrument Grant (S10RR027431-01). We thank the NIH Tetramer Facility for providing recombinant HLA-DR monomers for the peptide binding experiment. We thank M. Nielsen for providing insights regarding implementation of the NetMHCIIpan algorithm.

The new funding opportunity will distribute approximately $120 million in 2020 to fund planning grants and up to six research institutes focused on advanced research powered by artificial intelligence. The National Science Foundation has announced a new joint federal program to fund research focused on artificial intelligence at colleges, universities and nonprofit or nonacademic organizations focused on educational or research activities. The National Artificial Intelligence Research Institutes program expects to award approximately $120 million in 2020 to fund planning grants and up to six research institutes. The planning track will provide project planning support for up to two years and $500,000 for teams to develop communities and capacity for full institute operations. The institute track will support cooperative agreements between $16 million and $20 million for four to five years.

Five Dutch companies Ahold Delhaize, ING, KLM, NS and Philips aim to further boost the AI ecosystem in the Netherlands by accelerating and promoting the development of AI technology and nurturing AI talent in the country. This effort will add educational capacity, foster the development of the AI community in the Netherlands and reiterate the position of the Netherlands as a competitive and relevant global AI hub. The goal of Kickstart AI, is to bridge the AI gap between the Netherlands and other countries, like the UK, the US and China, that have made notable progress in this area. In order to keep the country's position as a pioneer and inventor of technologies, the Dutch government, companies, organizations and universities have ground to cover in terms of structural investments and availability of global AI talent. The five companies "kickstarting" AI are, for the first time, uniting forces in this kind of joint initiative and taking highly needed decisive action.

Five Dutch companies Ahold Delhaize, ING, KLM, NS and Philips aim to further boost the AI ecosystem in the Netherlands by accelerating and promoting the development of AI technology and nurturing AI talent in the country. This effort will add educational capacity, foster the development of the AI community in the Netherlands and reiterate the position of the Netherlands as a competitive and relevant global AI hub. The goal of Kickstart AI, is to bridge the AI gap between the Netherlands and other countries, like the UK, the US and China, that have made notable progress in this area. In order to keep the country's position as a pioneer and inventor of technologies, the Dutch government, companies, organizations and universities have ground to cover in terms of structural investments and availability of global AI talent. The five companies "kickstarting" AI are, for the first time, uniting forces in this kind of joint initiative and taking highly needed decisive action.

WASHINGTON, D.C.--(BUSINESS WIRE)--At the Association for the United States Army (AUSA) conference today, General Micro Systems (GMS) announced that its new S422-SW and X422 combination has been chosen for two new military development programs. The system pair brings a massive amount of server processing power, 10/40/100 Gigabit networking ports for sensors, and general-purpose graphics processing unit (GPGPU) artificial intelligence (AI) onto the battlefield for the first time in two small "shoebox-sized" rugged chassis designed to survive the harshest conditions where regular rackmount servers cannot. The two programs that selected the S422-SW "Thunder" and X422 "Lightning" combo will deploy it in mobile platforms to move IP-based sensor data instantaneously over multi-sensor LANs into the server and AI processor. Once processed, the server reports out to operators information that can help maneuver a vehicle or UAS in real-time, calculate a fire control solution for a weapon, or identify threats such as stationary IEDs or incoming objects such as projectiles. "The tremendous processing power of this combo makes it a highly attractive option for these two development programs as well as others creating autonomous, self-driving or self-piloting vehicles," said Ben Sharfi, chief architect and CEO, General Micro Systems.

I am the co-founder and CEO of Neurala Inc., a Boston-based company building Artificial Intelligence emulating brain function in software. Neurala's deep learning tech makes robots, drones, cars, consumer electronics, toys and smart devices more useful, engaging and autonomous. Neurala stems out of 10 years of research at Boston University Neuromorphics Lab, where as AI Professor I have pioneered the research and fielding of brain-inspired (also called Deep Learning, or Artificial Neural Networks) algorithms that allow robots and drones to perceive, navigate, interact and learn real-time in complex environments. Over my academic and industrial career, I have lectured and spoken at dozens of events and venues, including TEDx, keynote at Mobile World Congress Drone Summit, NASA, the Pentagon, GTC, InterDrone, Los Alamo National Lab, GE, Air Force Research Labs, HP, iRobot, Samsung, LG, Qualcomm, Huawei, Ericsson, BAE Systems, AI World, Mitsubishi, ABB and Accenture, among many others. My work has been featured in TIME, IEEE Spectrum, Fortune, CNBC, The Boston Globe, Xconomy, The Chicago Tribune, TechCrunch, VentureBeat, Nasdaq, Associated Press and many other media.

We, as humans, have the tendency to anthropomorphize objects around us. That is to say we attribute human characteristics, such as emotions or even intent to non-human things. To do so is literally within our psychological nature. However, it is one thing where a home vacuum, like a Roomba, can be seen as an endearing pet. It is a completely different scenario to give an AI a pronoun (Project Debater is referred to as a "she") and proceed to debate with it as if it were another human with actual stake in the issues being argued about.

Over the past few months, high-profile incidents in the United Kingdom, one of the most surveilled societies in the world, forced people to consider how facial recognition will be used there. Brexit taking up most of the oxygen in the room hasn't made that debate any easier, but in conversations with VentureBeat, three experts from different backgrounds -- Ada Lovelace Institute director Carly Kind, the U.K.'s surveillance camera commissioner Tony Porter, and University of Essex professor Daragh Murray, who studies police use of facial recognition -- all agree that the U.K. needs to find a middle ground. All three agree that years of Brexit debate have stifled necessary reform, and that leaving the European Union could carry consequences for years to come as police and businesses continue experiments with facial recognition in the U.K. They also worry that an inability to take action could lead to calls for a ban or overregulation, or far more dystopian scenarios of facial recognition everywhere. The Terminator's got serious competition for symbolizing the fear of technology trampling human rights. Facial recognition has become a major issue around the globe due both to its deeply personal and pervasive nature as well as advances in AI that now make it work in real time. In democratic societies worldwide, facial recognition is challenging lawmakers to confront how AI will shape society and is redefining attitudes toward artificial intelligence.

Canada is continuing as one of the favorite abroad destinations for foreign students to study and newcomers to relocate from their home nation. Canada's openness to migration and favorable policies to foreign students makes it more favored among overseas students and aspirants. There are more famous universities & colleges in Canada which are immensely presenting world-class education to students and have been creating a higher number of graduates being successful in various fields! It is more clear that pursuing their education in Canada could make global students more successful. There are greater job openings after studying in Canada.