In Game Two, the Google machine made a move that no human ever would. As the world looked on, the move so perfectly demonstrated the enormously powerful and rather mysterious talents of modern artificial intelligence. But in Game Four, the human made a move that no machine would ever expect. And it was beautiful too. Indeed, it was just as beautiful as the move from the Google machine--no less and no more.

Last year it was a Chinese speaking girlfriend and now it's an American teenage girl. Microsoft has launched its latest chat bot aimed at 18 to 24 year olds to improve their understanding of conversational language among young people online. Tay, like most teens, can be found hanging out on popular social sites and will engage users with witty, playful conversation, the firm claims. Microsoft has launched its latest chat bot aimed at 18 to 24 year olds to improve their understanding of conversational language among young people online. This chat bot is the brainchild of Microsoft's Technology and Research and Bing teams, and can be found interacting with users on Twitter, KIK and GroupMe.

Demiurge Technologies AG, a Swiss startup that works on artificial intelligence, says it's interested in acquiring Boston Dynamics, the Waltham robot maker put on the auction block last week by Alphabet Inc., parent company of Google. "We are pursuing an acquisition of Boston Dynamics to develop a new Robot Operating System (ROS) based on Demiurge's next generation of deep neural networks exclusively for physical mobile robots," said a statement issued by Demiurge. Little more is known about Demiurge. According to information on the company's website, it was launched last May with 9.5 million in angel and venture funding. Investors include Vantone Holdings and Hongdao Capital.

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If you were in charge of Google's robotics division and you had all those robotics companies at your disposal, what would you do? What kinds of robots would you build and for what markets? Many declined to comment, citing ties to Alphabet. Others said they didn't have a good answer (as one Japanese robotics executive put it, "I know exactly what I want to do with my robot business. Sorry, but I have no idea about Google.")

SAN FRANCISCO--(BUSINESS WIRE)--Executives previously from IBM Watson, GE Digital, Infosys, and MicroStrategy announced today that they have joined forces with TPG Growth to launch Noodle Analytics, Inc. (Noodle.ai), the Enterprise Artificial Intelligence company. Enterprise AI represents a major step forward in merging human learning and machine learning, all fueled by big data. Enterprise AI solutions combine world-class expertise in human-centered design, business process engineering, and artificial intelligence technologies. Today's artificial intelligence technologies include machine learning, predictive data analytics, and data science. "Over the next three to five years, artificial intelligence technologies and big data will be the most significant competitive differentiators in business. We are excited to be a pioneer in Enterprise Artificial Intelligence, offering timely, valuable, and affordable solutions to clients. We have the right team, an optimized business model, and the right partners to create extraordinary value," says Stephen Pratt, CEO of Noodle.ai.

A computer program has beaten a master Go player 3-0 in a best-of-five competition, in what is seen as a landmark moment for artificial intelligence. Google's AlphaGo program was playing against Lee Se-dol in Seoul, in South Korea. Lee Se-dol is one of the game's greatest modern players Mr Lee had been confident he would win before the competition started. The Chinese board game is considered to be a much more complex challenge for a computer than chess. "AlphaGo played consistently from beginning to the end while Lee, as he is only human, showed some mental vulnerability," one of Lee's former coaches, Kwon Kap-Yong, told the AFP news agency.

Are we looking for an algorithm that "If we all die, it would keep trading"? Should we be worried that electronic trading is mushrooming like airplane traffic, while we are not paying that much attention? Today, I'll look for AI pigments of incremental changes in algorithmic trading, first on Wall Street and then outside, in the Fintech startup world. I am not including the HFT space because it is a particular space driven by speed and merits a separate post because of its politically sensitive angle (Michael Lewis's babe). Renaissance Tech and Two Sigma, are probably the most recognizable names in old fashioned quant trading space.

It's a weird feeling, cruising around Silicon Valley in a car driven by no one. I am in the back seat of one of Google's self-driving cars – a converted Lexus SUV with lasers, radar and low-res cameras strapped to the roof and fenders – as it maneuvers the streets of Mountain View, California, not far from Google's headquarters. I grew up about five miles from here and remember riding around on these same streets on a Schwinn Sting-Ray. Now, I am riding an algorithm, you might say – a mathematical equation, which, written as computer code, controls the Lexus. The car does not feel dangerous, nor does it feel like it is being driven by a human. It rolls to a full stop at stop signs (something no Californian ever does), veers too far away from a delivery van, taps the brakes for no apparent reason as we pass a line of parked cars. I wonder if the flaw is in me, not the car: Is it reacting to something I can't see? The car is capable of detecting the motion of a cat, or a car crossing the street hundreds of yards away in any direction, day or night (snow and fog can be another matter). "It sees much better than a human being," Dmitri Dolgov, the lead software engineer for Google's self-driving-car project, says proudly. He is sitting behind the wheel, his hands on his lap. As we stop at the intersection, waiting for a left turn, I glance over at a laptop in the passenger seat that provides a real-time look at how the car interprets its surroundings. On it, I see a gridlike world of colorful objects – cars, trucks, bicyclists, pedestrians – drifting by in a video-game-like tableau. Each sensor offers a different view – the lasers provide three-dimensional depth, the cameras identify road signs, turn signals, colors and lights. The computer in the back processes all this information in real time, gauging the speed of oncoming traffic, making a judgment about when it is OK to make a left turn.

In March 2001, futurist Ray Kurzweil published an essay arguing that humans found it hard to comprehend their own future. It was clear from history, he argued, that technological change is exponential -- even though most of us are unable to see it -- and that in a few decades, the world would be unrecognizably different. "We won't experience 100 years of progress in the 21st century -- it will be more like 20,000 years of progress (at today's rate)," he wrote, in'The Law of Accelerating Returns'. Fifteen years on, Kurzweil is a director of engineering at Google and his essay has acquired a cult following among futurists. Some of its predictions are outlandish or over-hyped -- but technology experts say that its basic tenets often hold.