One of the scientists responsible for AlphaGo, the Google DeepMind software that trounced one of the world's best Go players recently, says the same approach can produce a surprisingly competent poker bot. Unlike board games such as Go or chess, poker is a game of "imperfect information," and for this reason it has proved even more resistant to computerization than Go. Gameplay in poker involves devising a strategy based on the cards you have in your hand and a guess as to what's in your opponents' hands. Poker players try to read the behavior of others at the table using a combination of statistics and more subtle behavioral cues. Because of this, building an effective poker bot using machine learning may be significant for real-world applications of AI.

BIO: Theophano Mitsa holds a Ph.D. degree in EE from the U. of Rochester and is the author of 47 publications, 11 U.S. patents and the book (CRC Press, 2010) "Temporal Data Mining". She has diverse academic and industrial experience, having served as a faculty member at the Universities of Iowa and Massachusetts and a Senior Software Engineer at GE HealthCare and Abiomed. Dr. Mitsa has received research awards from NSF, the Whitaker Foundation and HP. She is also a Fulbright scholar and the winner of the University of Rochester Eastman Medal. She is currently an independent Machine Learning and Analytics consultant.

Microsoft today announced updates to its portfolio of machine learning tools. Until now they have fallen under the Project Oxford name, but now they are being rebranded to Microsoft Cognitive Services. In total there are 22 APIs available in Cognitive Services now, said Microsoft senior program manager lead Cornelia Carapcea. And now there are prices for the new services, along with application programming interfaces (APIs) made available from Microsoft's Bing search division. Developers can still try out these services for free.

Machine learning just can't be left out of major tech keynotes and conferences these days. And while Tay continues to be a topic of funny discussions rather than the serious ones it was intended to be, Microsoft is announcing a few updates to its suite of Machine learning tools. First up, is the rebranding. If you are a developer, and a hard-core one at that, you'd remember Microsoft's machine tools being tabbed under something called'Project Oxford'. However, it isn't just the re-christening which is happening here.

Machine Learning algorithms powered by intelligent applications serve useful functions in our daily lives in ways we may not even be aware of. For instance, predictive analytics allow businesses to retain key customers, help assembly lines and buildings to run more efficiently, and help us find movies that we are likely to find intriguing. The ML field has gained tremendous traction and respect over the last decade, prompting Harvard Business Review to name the Data Scientist the sexiest job of the 21st century. To encourage new ML applications and foster a vibrant online community, we thrilled to launch Cortana Intelligence Competitions, a gamification feature of Cortana Intelligence Suite, as well as our first competition Decoding Brain Signals. This platform provides an intuitive and fun environment to hone users' data science and analytics expertise, and our first competition will allow you to have the chance to contribute to the important field of neuroscience to win prizes and recognition.

AlphaGo handily beat 18-time world Go champion Lee Sedol 4-1, and in doing so taught us several interesting lessons about where AI research is today, and where it is headed. One fascinating thing about AlphaGo is the unusual way it was designed. The software combined deep learning--the hottest AI technique out there today--with a much older, and far less fashionable, approach. Deep learning involves using very large simulated neural networks, and usually it eschews logic or symbol manipulation of the kind pioneered by the likes of Marvin Minksy and John McCarthy. But AlphaGo combines deep learning with something called tree-search, a technique invented by one of Minksy's contemporaries and colleagues, Claude Shannon.

Slowly but surely, artificial intelligence (AI) is advancing. Where it stands in comparison to human intelligence is difficult to say because people excel across a broad set of intellectual tasks, while AI tends to be narrowly focused. But machines keep getting better at tasks like sifting through vast quantities of data, understanding natural language, and recognizing objects in images. Over the weekend, scientists from a Silicon Valley company called MetaMind described their efforts to advance the state of the art in a research paper, "Dynamic Memory Networks for Visual and Textual Question Answering." The paper explains improvements in memory and input modules for a system called a dynamic memory network (DMN), a general architecture for answering questions about text and images.

One week ago, we reported that Microsoft's first foray into Twitter chat "artificial intelligence" did not quite work as expected: once unleashed into the wild, the chat robot named "Tay" proceeded to have a spectacular implosion, and in the span of just a few hours upon interacting with the broader Twitter population, was transformed from a polite teenage girl impersonator into an all out sociopath, unleash ingtweets covering everything from racist outbursts, N-words, conspiracy theories, genocide, incest, Obama-slurs, and even outright Nazism. "The AI chatbot Tay is a machine learning project, designed for human engagement. It is as much a social and cultural experiment, as it is technical. Unfortunately, within the first 24 hours of coming online, we became aware of a coordinated effort by some users to abuse Tay's commenting skills to have Tay respond in inappropriate ways. As a result, we have taken Tay offline and are making adjustments."

Ben Narasin was an entrepreneur for 25 years, a seed investor for 8 and is now a VC as a General Partner at Canvas Ventures. When I heard Ray Kurzweil present the concept of the singularity to a small group at TED, the idea that computing power advances would ultimately allow thinking machines to advance beyond humans' ability to advance them, and eventually allow us to "upload" our own consciousness into an eternal ether, I was so smitten I committed to living long enough to live forever. I even practiced caloric restriction for several years. Although many things can improve life expectancy, caloric restriction is the only one to have been proven to extend life span -- and every life-extending drug experiment attempts to duplicate its effects. Over time, I came to realize that while the parts of Kurzweil's concept will likely happen for machines, it won't happen for me.

The Pentagon's No. 2 civilian official said Wednesday that the Defense Department is concerned that adversary nations could empower advanced weapons systems to act on their own, noting that while the United States will not give them the authority to kill autonomously, other countries might. Deputy Defense Secretary Robert O. Work said the Pentagon hasn't "fully figured out" the issue of autonomous machines, but continues to examine it. The U.S. military has built a force that relies heavily on the decision-making skills of its troops, but "authoritarian regimes" may find weapons that can act independently more attractive because doing so would consolidate the ability to take action among a handful of leaders, he said. "We will not delegate lethal authority to a machine to make a decision," Work said. "The only time we will… delegate a machine authority is in things that go faster than human reaction time, like cyber or electronic warfare."