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Microsoft researchers detect lung-cancer risks in web search logs - Next at Microsoft

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Smoking cigarettes is the leading cause of lung cancer, the most common cause of cancer death in the world. But nearly 20 percent of lung-cancer diagnoses are made in people who are non-smokers. That means in addition to smoking, geographic, demographic and genetic factors play a role in the devastating disease. A project from Microsoft's research labs is exploring the feasibility of using anonymized web search data to learn more about lung-cancer risk factors and provide early warning to people who are candidates for disease screening. The findings, published Thursday in JAMA Oncology, extend research that team members published last June on the feasibility of using the text of questions people ask search engines to predict diagnoses of pancreatic cancer.


As machine learning breakthroughs abound, researchers look to democratize benefits - Next at Microsoft

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When Robert Schapire started studying theoretical machine learning in graduate school three decades ago, the field was so obscure that what is today a major international conference was just a tiny workshop, so small that even graduate students were routinely excluded. But it has become one of the hottest fields in computer science, turning once-obscure academic gatherings like the upcoming Annual Conference on Neural Information Processing Systems in Barcelona, Spain, into a sold-out affair attended by thousands of computer scientists from top corporations and academic institutions. "It's been really something to see this field develop, and to see things that seemed impossible become possible in my lifetime," said Schapire, a principal researcher in Microsoft's New York City research lab whose machine learning research is widely used in the field. The NIPS conference, which starts Monday, is so popular because machine learning has quickly become an indispensable tool for developing technology that consumers and businesses want, need and love. Machine learning is the basis for technology that can translate speech in real time, help doctors read radiology scans and even recognize emotions on people's faces.


Paradigm Shift in Parenting By Leveraging Artificial Intelligence

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The deep penetration of internet among users in India has paved way for digitization. Digital platforms are leveraging new age technologies such as AI to make lives easier and enriching. Parenting too has joined the digital/ AI bandwagon. Today there are several apps that have implemented AI to help parents nurture and groom their children. This was a much needed revolution in assisting parents to understand the needs and psychology of their children. It guides them throughout the parental journey and helps in develop a mutual understanding that results in healthy relationships within the family.


5 Best AI-Powered Chatbot Apps

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The Telegraph has proclaimed: "The end of apps is here…" TechCrunch, Mashable, VentureBeat, and others also shared their belief that mobile applications as we know them are a dying breed. But how did mobile apps become endangered? Recently, IO's creators changed the app's name to Luka and added several little helpers, meaning it's now in charge of 12 other bots: Foodie (for restaurant recommendations), Weather, Wiki, Video, Gif, Pic, News, Founders, Search, Calculator, Quiz, and QuestHero. As of July 2016, Luka had around 5,000 downloads on App Store, with a monthly income of less than $5,000 (according to Sensor Tower). Nevertheless, having announced the recent close of a $4.42 million Series A funding round, Luka's creators are more than optimistic about the app's future.


Interview with Flowcast CTO: AI / Machine Learning in Fintech

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I'd love to talk more about Flowcast, but I'm still not able to shake the image of you making a robotic submarine run by San Diego poolside (laughs). As a STEM enthusiast, I have been in awe of IBM Watson's capabilities. And I feel it's an honor to be talking to someone who has contributed to its capabilities. Winnie: Flowcast came about with my friend and co-founder Ken So. We met back when I was at MIT and he was doing his MBA at Berkeley.


Tips for Beginner Machine Learning/Data Scientists Feeling Overwhelmed

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I think that having a so much great resources available can sometimes be both a blessing and a curse. It's great that we have so many tools and sources of information to choose from, but to make best use of it -- and our time -- it is really important to actually "choose" and keep "focused." I don't want to say that many resources are "redundant," since "redundant" has a somewhat negative ring to it. However, there are many different books, tools, and courses that cover essentially the same thing, although, the scope and style may be a bit different. So, instead of adding everything that we stumble upon to our reading lists, I'd say that it makes more sense to be absolutely clear about personal goals first ("What skills do I need to learn to solve problem X?," "Do I really to learn this new, shiny tool X instead of Y?").


Three key trends for 2017 - The Advisor

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This piece, written by MWD Advisors' lead analysts Angela Ashenden, Neil Ward-Dutton and Craig Wentworth, provides an overview of the key trends we see organisations facing in 2017 (and beyond). If you're in a technology leadership role, you should be exploring how these trends will impact the ways you plan, design, deliver and support services and capabilities. At MWD Advisors, our research program is focused, at a high level, on how digital technology changes work. The core of our scope of research is the systems and platforms organisations use to share knowledge, make decisions and co-ordinate work; we look at how new technologies are changing the picture, and what distinguishes successful organisations that reap the benefits of new technologies from those that struggle to drive meaningful change. The three trends we outline below are fundamentally changing the relationship between technology and business.


Artificial intelligence and Big Data to manage your wealth: robo-advisers

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It is done by various possible people such as investment managers, wealth managers, financial advisers and even accountants. Since just a few years a range of new fintechs hit the market with so-called robo-advisers or automated financial advice tools. They have been popping up (and keep popping up) in no time and some already even dissapeared. It will be hard for robo-adviser startups to scale; differentiating their services is key. Robo-advisers, essentially software tools driven by artificial intelligence and crunching loads of data, are predicted to be an important growing category of fintech.


Gartner Reveals Top Predictions for IT Organizations and Users in 2017 and Beyond

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ORLANDO, Fla., October 18, 2016 View All Press Releases Gartner Reveals Top Predictions for IT Organizations and Users in 2017 and Beyond Analysts Explore the Digital Future at Gartner Symposium/ITxpo 2016, October 16-20 in Orlando Gartner, Inc. today revealed its top predictions for 2017 and beyond. Gartner's top predictions for 2017 examine three fundamental effects of continued digital innovation: experience and engagement, business innovation, and the secondary effects that result from increased digital capabilities. "Gartner's top strategic predictions continue to offer a provocative look at what might happen in some of the most critical areas of technology evolution. At the core of future outcomes is the notion of digital disruption, which has moved from an infrequent inconvenience to a consistent stream of change that is redefining markets and entire industries," said Daryl Plummer, managing vice president, chief of research and Gartner Fellow. "Last year, we said digital changes were coming fast. This year the acceleration continues and may cause secondary effects that have wide-ranging impact on people and technology."


How a researcher used big data to beat her own ovarian cancer

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Academic scientists devote their lives to research, often toiling away on problems that few people outside their discipline fully understand. Perhaps some are driven by pure curiosity or competition, while others have a personal interest in the topic at hand. For Shirley Pepke, a genomics researcher based in Los Angeles, the urgency to find answers comes from her own instinct for survival. Since 2014, she has been working on a tool capable of tailoring ovarian cancer treatment to each patient using genomics data and a machine learning algorithm. The first subject in this DIY precision medicine project was Pepke herself, who was diagnosed with stage IIIC ovarian cancer in September 2013.