Breakthroughs in technology are typically attributed to a single lone genius, but research led by DeepMind scientist Thore Graepel suggests the full power of AI will be unleashed through a collective approach of multi-agents. The UCL machine learning professor helped create AlphaGo, which pursued an individual strategy called competitive self-play to become the first computer program to defeat a human professional Go player in 2015. He's since turned his focus from competition to cooperation, using deep reinforcement learning to understand how teamwork develops among self-interested agents, whether they're computer programmes or human social dilemmas. "We believe that this kind of model is a powerful baseline to study these kinds of social dilemmas in more detail," said Graepel at the AI for Social Good symposium at the Turing Institute. His work forms part of DeepMind's ambitious mission "to solve intelligence".

Every relationship has The Moment. Not the moment when you take your partner home to mom or when you finally compromise on the correct number of pillows to have on your bed. I mean The Moment when your potential boo reveals that they own an All Lives Matter shirt or that they sincerely believe that 9/11 was an inside job. Entering into this growing cohort of dating silos is Trump.dating, a new service that gives "like-minded Americans a chance to meet without the awkwardness that comes with the first conversation about politics." No longer will you have to swipe left on profile after profile that includes "proud liberal" or "no Trump supporters"--you now have your own digital mixer!

Byron Reese: This is Voices in AI, brought to you by Gigaom. Today I'm excited that our guest is Marie des Jardins. She is an Associate Dean for Engineering and Information Technology as well as a professor of Computer Science at the University of Maryland, Baltimore County. She got her undergrad degree from Harvard, and a Ph.D. in computer science from Berkeley, and she's been involved in the National Conference of the Association for the Advancement of Artificial Intelligence for over 12 years. Welcome to the show, Marie.

On this episode of Business Insanity Talk Radio, we first talk about how my first guest discovered how artificial intelligence paired with behavioral science helps businesses build high-performing teams. We also discuss other applications for A.I. in business. Then, we talk to a small business owner who is using Fulfillment by Amazon to operate and grow their business. Plus, I show you how to get your small business unstuck. Finally, we'll discuss how small business owners can prepare for the holiday rush and survive the holiday season.

There may be a way to predict which jobs are most vulnerable to being taken over by machines, says a new research paper. Two researchers from the Massachusetts Institute of Technology and Carnegie Mellon University say machine learning will not spell the "end of work" for humans, but will have considerable impacts on the economy and the way people work. They have created a set of 21 questions that evaluate how suitable a task might be for machine learning based on what they know about machine learning systems' current and future capabilities. They published their paper Thursday in the journal Science. Managers should be able to use the rubric to evaluate the tasks performed in every job in their organization, while policymakers can use the list to determine which occupations are most likely to be affected by automation, said the paper's co-author, Erik Brynjolfsson, in an interview with CNBC.

New workplace trends such as automation, AI, and the gig economy are generating a need for policies that create jobs and work that is more fulfilling. This summer, the UK government published a long-awaited independent review of employment practices in the modern economy, led by Matthew Taylor, chief executive of the London-based Royal Society for the encouragement of Arts, Manufactures and Commerce (RSA). His review and policy recommendations addressed questions about automation in the workplace, the influence of the so-called gig economy, and the need to create better work. Taylor sat down recently with James Manyika, chairman of the McKinsey Global Institute, whose recent research agenda has tackled many of the same and similar topics (notably the future of work, independent work, automation, and declining productivity). What follows are edited highlights of their conversation. It begins with Taylor outlining the scope of the UK report. Matthew Taylor: We've been exploring three questions. One is who's being exploited, how they're being exploited, and what might we do about it. Second, an understanding of the incentives that are driving changes in the labor market.

It's been 2018 for 17 days now and CES is wrapping up another great show in Las Vegas. It's clearly become a global stage for innovation; Over 4000 exhibitors coming from all around the world to showcase their gadgets. This year Startupbootcamp joined CES with four alumni – Monument, Thread in Motion, Domotz and LiateR supported by one of our Managing Directors, Raph Crouan, Startupbootcamp IoT. They unveiled new product features and made some exciting announcements. We caught up with Ercan, Co-Founder at Monument and Kadir, CEO and Co-Founder at Thread In Motion to get some insights into the fair.

Tom Davenport, a professor at Babson College near Boston, a Fellow of the MIT Initiative on the Digital Economy, a co-founder of the International Institute for Analytics, and a senior advisor to Deloitte's analytics practice, shares his views on AI and analytics in an interview with TCS. He is co-authored the 2016 book'Only Humans Need Apply: Winners and Losers in the Age of Smart Machines.' Davenport, the man responsible for making big data and analytics a topic of boardroom discussions, explains his views on the connection between analytics and artificial intelligence, automation and augmentation, opportunities arising from cognitive technologies, and how companies should address AI's impact on jobs. Davenport argues that the largest and most sophisticated branch of AI today is machine learning. While asserting that AI is primarily based on big data and analytics, Davenport believes any company that would skip analytics and go straight to AI is less likely to be successful. He explains that every industry has major opportunities from cognitive technologies and AI.

Robots swarming in 2018 Winter Olympics in PyeongChang to serve visitors, athletes and delegates with food, drinks and directions show South Korea's automaton way of hosting the Winter Olympic Games for the first time, with the country deciding to deploy at least 12 kinds of robots presented here in a list below: Korea Advanced Institute of Science and Technology's (Kaist's) Hubo robot is the first unit deployed by the country for the event. In December last year, the humanoid carried the Olympic torch, clearing a path for itself through a makeshift wall, set up as an obstacle, to hand the torch to a Kaist professor. In 2015, the humanoid had won Kaist a prize of $2 million by not falling off in order to complete simple tasks like opening doors. The robot also features a Bumble Bee-like ability to switch back and forth from a walking biped to a wheeled machine. The second robot deployment FX-2, that carried the professor who received the Olympic torch from the humanoid, is an eight-foot-tall human-operated robot weighing more than 600 pounds with a price tag close to $1 million.

Pedro Domingos is a professor of computer science at the University of Washington. He is a winner of the SIGKDD Innovation Award, the highest honor in data science. A fellow of the Association for the Advancement of Artificial Intelligence, he lives near Seattle. Domingos' core argument is that machine learning needs an unifying theorem, not unlike the Standard Model in physics or the Central Dogma in biology. He takes readers through a historical tour of artificial intelligence and machine learning and breaks down the five main schools of machine learning (below).