New York: A novel machine learning technique could help soldiers to learn 13 times faster than conventional methods as well as help save lives, say researchers, including one of Indian-origin. Using a low-cost, lightweight hardware and implementing collaborative filtering -- a well-known machine learning technique -- the team found that soldiers are able to decipher hints of information faster and more quickly deploy solutions, such as recognising threats like a vehicle-borne improvised explosive device, or potential danger zones from aerial war zone images. This technique could eventually become part of a suite of tools embedded on the next generation combat vehicle, offering cognitive services and devices for warfighters in distributed coalition environments, said Rajgopal Kannan, a researcher, from the US Army Research Laboratory. This work is part of Army's larger focus on artificial intelligence and machine learning research initiatives pursued to help to gain a strategic advantage and ensure warfighter superiority with applications such as on-field adaptive processing and tactical computing, he said. The paper on this new research won the best-paper award at the 26th ACM/SIGDA International Symposium on Field Programmable Gate Arrays in Monterey, California in February.

New York: A novel machine learning technique could help soldiers to learn 13 times faster than conventional methods as well as help save lives, say researchers, including one of Indian-origin. Using a low-cost, lightweight hardware and implementing collaborative filtering -- a well-known machine learning technique -- the team found that soldiers are able to decipher hints of information faster and more quickly deploy solutions, such as recognising threats like a vehicle-borne improvised explosive device, or potential danger zones from aerial war zone images. This technique could eventually become part of a suite of tools embedded on the next generation combat vehicle, offering cognitive services and devices for warfighters in distributed coalition environments, said Rajgopal Kannan, a researcher, from the US Army Research Laboratory. This work is part of Army's larger focus on artificial intelligence and machine learning research initiatives pursued to help to gain a strategic advantage and ensure warfighter superiority with applications such as on-field adaptive processing and tactical computing, he said. The paper on this new research won the best-paper award at the 26th ACM/SIGDA International Symposium on Field Programmable Gate Arrays in Monterey, California in February.

Ah, now we get to the tricky bit. To give advanced robots with AI capabilities citizenship, responsibility, and a bank account, a ton of laws have to change. Because it's super complicated (and a whole other article in itself), let's assume that we've overcome all of those huge, complex issues. Usually, it expires 50-100 years after the author's lifetime… which could be forever with AI. And then when does it technically die?

Recently published by Cambridge University Press, Re-Engineering Humanity explores how artificial intelligence, automated decisionmaking, the increasing use of Big Data are shaping the future of humanity. This excellent interdisciplinary book is co-authored by Professors Evan Selinger and Brett Frischmann, and it critically examines three interrelated questions. Under what circumstances can using technology make us more like simple machines than actualized human beings? Why does the diminution of our human potential matter? What will it take to build a high-tech future that human beings can flourish in?

Michael Krigsman: Artificial intelligence is one of the great buzzwords of our time, but there's substance behind it in some quarters. Today we're talking with somebody who is actually designing AI systems. We are on Episode #257 of CxOTalk. Before we dive in, I want to thank Livestream for providing our video streaming infrastructure. If you go to Livestream.com/CxOTalk, they'll actually give you a discount on their plans.

As a resource-poor nation, Japan's prosperity relies on free trade. Under worldwide protectionism, it can't survive. That's the message Economy, Trade and Industry Minister Hiroshige Seko wants to send as the emergence of protectionism across the globe becomes a worsening headache for export-reliant Japan. "If free trade collapsed, Japan would lose its base to stand on," he said in an exclusive interview with The Japan Times earlier this month. "We have to keep in mind the basic fact that what underpins resource-poor Japan's current wealth is free trade."

Rick Dickinson, the designer of Sinclair computers, has died in the US while receiving treatment for cancer. The British designer, thought to be in his 60s, worked in-house for Sinclair Research and oversaw the creation of its home computers in the 1980s. He was responsible for the boxy look of the ZX80 and ZX81 and the Bauhaus-inspired appearance of the Spectrum. Mr Dickinson also helped to develop the technologies for the UK company's touch-sensitive and rubber keyboards. He was recently linked to a crowd-funded project by Retro Computers to turn the Spectrum into a handheld computer.

Registration is open for #StrataData San Jose. Transcript Cory: [0:00] Are welcome to 2018 folks I'm your host for this big date of your podcast and Thomas along with their beers along for this fun ride. And it's everybody is probably aware machine learning is easily one of the hottest topics topics in Analytics. And big data for not only the back half of 2017 definitely the hottest thing happened in 2018. And I'm sure it's going to stick around for a while and a handful of a sewer students of this big data space in the. The environment where our fans of machine learning think it's a cool Trend and think it's going to have a lot of power we've started poking around and look at it companies. Do an interesting work to accelerate machine learning in the Enterprise and we wandered into these these folks are did a robot and we thought. It sucks you're doing some pretty interesting work simplifying how organizations and frankly aspiring data scientist can leverage machine learning in real life and such a real life unicorn. West Side at least it is pictures of very robust Big Data mustache his name is dr. Greg: [1:21] Hey thanks for having me although I'm I'm sad to report that my mustache did not survive the Christmas holidays that's what the New Year's resolution. Cory: [1:31] I have to assume I have to assume by casually you mean that it got taken off as you were trying to eat a turkey leg and it got pulled off that's the only acceptable answer.

The times they are a-changin': in 2016, widescale commercial application of artificial intelligence was still a faraway high-tech dream. The ChinaBang Awards did not even have a specialized category for this technology. In the same year, ChinaBang gave out awards to three best AI products, giving a glimpse of the potential that was about to unravel. Here are the five winners of the 7th ChinaBang Awards in the category of Best AI. SenseTime is the most valuable artificial intelligence startup in the world.

Teaching computers to read, think and communicate like humans is a daunting task, but it's one that Dr. Geoff Gordon embraces with enthusiasm and optimism. Moving from an academic role at Carnegie Mellon University, to a new role as Research Director of the Microsoft Research Lab in Montreal, Dr. Gordon embodies the current trend toward partnership between academia and industry as we enter what many believe will be a new era of progress in machine learning and artificial intelligence. Today, Dr. Gordon gives us a brief history of AI, including his assessment of why we might see a break in the weather-pattern of AI winters, talks about how collaboration is essential to innovation in machine learning, shares his vision of the mindset it takes to tackle the biggest questions in AI, and reveals his life-long quest to make computers less… well, less computer-like. Geoff Gordon: You cannot know ahead of time exactly what's going to come out, because if you knew, it wouldn't be research. You don't expect your payoffs to be measured in months or even necessarily a couple of years. But it could be that the things you're doing now pay off ten years later. And so, Microsoft has decided that MSR is in it for the long-term, and that changes the type of research that you can do, right? You can afford to make big bets. Host: You're listening to the Microsoft Research Podcast, a show that brings you closer to the cutting-edge of technology research and the scientists behind it. Teaching computers to read, think and communicate like humans is a daunting task, but it's one that Dr. Geoff Gordon embraces with enthusiasm and optimism. Moving from an academic role at Carnegie Mellon University to a new role as research director of the Microsoft Research Lab in Montreal, Dr. Gordon embodies the current trend toward the partnership between academia and industry, as we enter what many believe will be a new era of progress in machine learning and artificial intelligence. Today, Dr. Gordon gives us a brief history of AI, including his assessment of why we might see a break in the weather pattern of AI winters, talks about how collaboration is essential to innovation and machine learning, shares his vision of the mindset it takes to tackle the biggest questions in AI, and reveals his life-long quest to make computers less… well, less computer-like. Host: Geoff Gordon, thanks for coming all the way from Montreal to join us in the studio today.