Artificial intelligence can find, map poverty, researchers ...

Artificial intelligence (A.I.) dates back to the 1950s, when the term was coined. But the way Intel sees it, the field is not old -- it represents a growth opportunity for the chipmaker. Last week Intel made a bold move and acquired Nervana, one of the preeminent startups in deep learning, a type of A.I. that involves training artificial neural networks on data and then getting them to make inferences on new data. Today, when Intel announced a new generation of Xeon Phi server chips, the emphasis was on their ability to handle A.I. workloads. In previous years, Xeon Phi has been geared toward the high-performance computing market.

IN "Minority Report", a policeman, played by Tom Cruise, gleans tip-offs from three psychics and nabs future criminals before they break the law. In the real world, prediction is more difficult. But it may no longer be science fiction, thanks to the growing prognosticatory power of computers. That prospect scares some, but it could be a force for good--if it is done right. Machine learning, a branch of artificial intelligence, can generate remarkably accurate predictions.

Nine times out of ten, when you hear about deep learning breaking a new technological barrier, Convolutional Neural Networks are involved. Also called CNNs or ConvNets, these are the workhorse of the deep neural network field. They have learned to sort images into categories even better than humans in some cases. If there's one method out there that justifies the hype, it is CNNs. What's especially cool about them is that they are easy to understand, at least when you break them down into their basic parts. I'll walk you through it.

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Getting aid to impoverished Africans is hard enough, what with blockades of bureaucracy and red tape. But in many African countries, bad data, or a lack of it, makes distributing funds even more troublesome. "Fighting poverty has always been this shining goal of the modern world," Neal Jean, a doctoral student in computer science at Stanford University's School of Engineering, told me. "It's the number one priority for the United Nation's 2030 Agenda for Sustainable Development, but the major challenge is that there's not enough reliable data. It's really hard to help impoverished people when you don't know where they are."

Pasadena, CA - Firefighters have only their wits and five senses to rely on inside a burning building. But research developed in part by NASA's Jet Propulsion Laboratory, Pasadena, California, may change that, introducing artificial intelligence (AI) that could collect data on temperatures, gases and other danger signals and guide a team of first responders safely through the flames. AUDREY, the Assistant for Understanding Data through Reasoning, Extraction, and sYnthesis, has received the Undersecretary's Award for Collaboration from the Department of Homeland Security (DHS) in recognition of its joint development by JPL and DHS. It's part of the Next Generation First Responder (NGFR) program, a DHS initiative to innovate new ways to keep firefighters, police, paramedics and other first responders safe in the field through increased awareness of their surroundings and communication abilities. But the big picture is even more exciting: AUDREY can track an entire team of firefighters, sending relevant signals to individuals while helping to make recommendations for how they could work together.

The cities of the future will be huge and super-dense -- but will they also be alive? Could the increasingly complex systems needed to manage the next generation of megacities become our first true artificial intelligence? People have speculated before about the idea that the Internet might become self-aware and turn into the first "real" A.I., but could it be more likely to happen to cities, in which humans actually live and work and navigate, generating an even more chaotic system? It's either my worst nightmare or the dawn of a wonderful new future, but scientists are… Read more Read more As cities become more networked and their mixture of urban infrastructure and surveillance infrastructure becomes more complex, eventually we'll have to build cities that can think for themselves. People have speculated about the potential for computer systems to help in urban planning forever, including papers about the use of "fuzzy logic" to automate the decision-making process and A.I. solutions for land use planning, and the an A.I. "spatial decision support system."

Artificial intelligence can find, map poverty, researchers ... Ai Weiwei exhibit extended until Sept. 11 at Warhol AI passenger carrying gold bars worth over Rs 2.5 crore held

Attracting and capturing talent has always been a challenge for startup companies. The statistics, compiled by Statistic Brain Research Institute, are grim. Candidates understand that they are taking a big risk with working for a startup. Brian Hughes, Founder and CEO at Integrity Marketing & Consulting writes for Huffington Post, "machine learning in the hiring process can even the odds of hiring great people." Leveraging technology, recruiters can use the software to screen candidate resumes for certain skills and industry keywords.