A Google artificial intelligence program has beaten the European champion of the board game Go. The Chinese game is viewed as a much tougher challenge than chess for computers because there are many more ways a Go match can play out. The tech company's DeepMind division said its software had beaten its human rival five games to nil. One independent expert called it a breakthrough for AI with potentially far-reaching consequences. The achievement was announced to coincide with the publication of a paper, in the scientific journal Nature, detailing the techniques used.

It's a good trait to have for this particular demo. He's showing Tech Insider the capabilities of Hound, a free voice assistant app that's being released publicly for iPhone and Android on Tuesday. "What is the population and capital for Japan and China and their areas in square miles and square kilometers and also tell me how many people live in India and what is the area code for Germany, France, and Italy," Mohajer breathlessly says into his Android phone. If you were to ask Siri or Google Now even half of that query, you'd get nothing in return. Mohajer is pulling out the stops to show off the power of Hound, a voice recognition assistant his company SoundHound has been quietly building for the last 9 years.

Whenever I read articles about data science I feel like there is some important aspect missing: evaluating the performance and quality of a machine learning model. There is always a neat problem at hand that gets solved and the process of data acquisition, handling and model creation is discussed, but the evaluation aspect too often is very brief. But I truly believe it's the most important fact, when building a new model. Consequently, the first post on this blog will deal with a pretty useful evaluation technique: lift analysis. Machine learning covers a wide variety of problems like regression and clustering.

Vivek Wadhwa is an academic, entrepreneur, and author who holds appointments at Stanford, Duke, and Singularity University. For the past century, the price and performance of computing has been on an exponential curve. And, as futurist Ray Kurzweil observed, once any technology becomes an information technology, its development follows the same curve, so we are seeing exponential advances in technologies such as sensors, networks, artificial intelligence, and robotics. The convergence of these technologies is making amazing things possible. Yes, with every good there is a bad; wonderful things will become possible, but with them we will also create new problems for mankind. Here are six of the technologies that will make this happen, and the good they will do.

Quantum physics can fly in the face of human intuition--even that of a physicist such as Mario Krenn at the University of Vienna. This counterintuitive quality makes it difficult for researchers to design experiments to explore the field. Now, to avoid intuitive pitfalls, Krenn and his colleagues have devised a computer program to automatically design new quantum experiments that they would not have thought of themselves. The way that all known particles behave can be explained with quantum physics. A major feature of this branch of physics is that the world becomes a vague, bizarre place at its very smallest levels. For example, atoms and other basic building blocks of the universe can exist in states of flux known as superpositions, meaning they can seemingly be located in two or more places at the same time, or spin in opposite directions simultaneously; and with the phenomenon of quantum entanglement, two or more objects can get connected such that what happens to one instantaneously affects whatever is linked to it, no matter how far apart they are in the universe.

Over three jam packed days, and over one hundred speakers, Interaction 16 explored interaction design of many flavors. Over the years the conversation has evolved, and as Josh Seidan put it, we are no longer asking'What is interaction design?' The discipline is evolving and growing more confident in its place in the world of AI, data, conversational UI as well as web and app work. The overall conference theme was the future of interaction design, and that came through strongly. Topics like data, self-driving cars, conversational UI, algorithms all got plenty of attention.

I have voraciously read endless pro and con scenarios about artificial intelligence since first writing about it years ago. At this point, there is no doubt that concerns about the dangers of runaway AI raised by Elon Musk, Stephen Hawking, Bill Gates, Bill Joy and others are genuine. There also is no doubt whatsoever that the new organizations aimed at mitigating the dangers -- OpenAI, The Future of Life Institute, Machine Intelligence Research Institute and others -- are extremely important developments. Clearly, no sane person or organization wants to see, let alone encounter, runaway AI. However, a base problem is that no one knows where the actual crossover point -- the edge or tipping point -- exists, and thus we mortals are unlikely to be able to prevent it from occurring. Said differently, there is a very high probability that we will misjudge where that crossover point is and will thus go beyond the key threshold.

Sony has announced the closure of the UK's Evolution Studios. The Cheshire-based video games development house dates back to 1999, and had most recently worked on the troubled PlayStation title Driveclub. Sony has confirmed that there will be at least some compulsory redundancies as a consequence of its decision. The announcement closely follows Microsoft's announcement of plans to close another British developer, Lionhead Studios. Sony said that its decision had followed a review of its European operations.

Global technology leaders and senior executives from around the world spoke on a range of topics, including Digital India, Smart Cities, Make in India, Skill India and cutting-edge technologies like artificial intelligence, machine learning, 3D printing, drones, robotics, robotic surgeries and genomics, at the two-day EmTech India 2016 event, held in New Delhi on 18 and 19 March. The event was organized by Mint and MIT Technology Review, published by the Massachusetts Institute of Technology (MIT). The speakers included R.S. Sharma, chairman of the Telecom Regulatory Authority of India; John Chambers, executive chairman of Cisco Systems Inc. and chairman of the US-India Business Council; Una-May O'Reilly, principal research scientist, AnyScale Learning For All Group, MIT Computer Science and Artificial Intelligence Laboratory; and Harsh Mariwala, chairman of Marico Ltd. The full list can be accessed here. Here are edited excerpts from their speeches and discussions that followed. John Chambers, executive chairman of Cisco Systems Inc and Chairman of US-India Business Council (USIBC), reiterated the reason for his bullishness on India in a chat with Mint's R. Sukumar, on the first day of EmTech India 2016. When most of us here read the India narrative, it is not uniformly positive. Yet, you are amazingly bullish on the country. What do you see that others don't? Sometimes when you see what is happening in other countries and other businesses around the world from the outside, you are able to gather data very quickly, and then you can connect the dots on the market transitions. I am very bullish on the country for that very simple reason--follow and connect the dots on transitions. The transition to digitization will be the biggest technology change ever. I don't go into a country unless the leader, he or she, really understands this. Second, I don't go to a country that does not have sustainable differentiation capabilities.

In the airy, loft-like Microsoft Research lab in New York City, five computer scientists are spending their days trying to get a Minecraft character to climb a hill. That may seem like a pretty simple job for some of the brightest minds in the field, until you consider this: The team is trying to train an artificial intelligence agent to learn how to do things like climb to the highest point in the virtual world, using the same types of resources a human has when she learns a new task. That means that the agent starts out knowing nothing at all about its environment or even what it is supposed to accomplish. It needs to understand its surroundings and figure out what's important – going uphill – and what isn't, such as whether it's light or dark. It needs to endure a lot of trial and error, including regularly falling into rivers and lava pits.