Emerging technology has the potential to add efficiency and effectiveness to healthcare, according to Eric Topol, MD. Capabilities such as artificial intelligence, polygenic risk scores and digital health technology can equip physicians to improve and reduce the cost of care, while enabling them to better connect with patients, said Topol, the founder and director of The Scripps Research Institute. Much of care today is not based on provable facts, Topol noted at Liberation 2019, the annual meeting of Medecision, in Frisco, Texas. He cited an article by Hannah Fry, MD, published last month in The New Yorker, which detailed research that found that, of every 1,000 people taking statins for heart conditions over five years, only 18 will avoid a major heart attack or stroke. "Patients and clinicians exist in a world of insufficient data," Topol said.

I always felt that our modern society was becoming more and more lackadaisical with our privacy and data. No-one really seemed to care about privacy or how their data was being used. Then came along the EU's GDPR regulation and to some degree things changed. I think the thing that changed was that we began to realise there was some value in our data, that that value could be greater to others than we thought, and actually, protecting that data wasn't the primary concern of the people we were sharing it with. But did it change our behaviour?

TechRepublic's Macy Bayern spoke with Tatiana Mejia, director of product marketing at Adobe Sensei, at Mobile World Congress 2019 in Los Angeles about the benefits and uses of artificial intelligence (AI) and machine learning. The following is an edited transcript of the interview. Tatiana Mejia: AI and machine learning is making a difference across the entire journey. When you think about creating, delivering, and optimizing content and then learning from it, understanding what your users' experience is. "What is in this asset? What is in this video? How do I make these tweaks quickly?" "How do I create a different viewpoint on a video?"

Conversational AI tools or chatbots have come a long way from error-prone level-1 support to becoming a widely used tool in banks' automation and AI strategies. Today, chatbots in banking are being used by Wells Fargo, Capital One Bank of America, HDFC Bank, HSBC, CBA, and many other leading global banks. The contribution of these chatbots is noteworthy. Consider this: Bank of America's chatbot Erica has served over 35 million customers, and HDFC's EVA engages in over 20,000 conversations every day. The overall impact and growing importance of intelligent chatbots can be understood if we look at the report from Gartner, which suggests that by 2020, customers will prefer to resolve 85% of their problems with an enterprise without interacting with support staff.

LOS ALAMOS, N.M., Oct. 22, 2019--A probabilistic artificial intelligence computer model developed at Los Alamos National Laboratory provided the most accurate state, national and regional forecasts of the flu in 2018, beating 23 other teams in the Centers for Disease Control and Prevention's FluSight Challenge. The CDC announced the results last week. "Accurately forecasting diseases is similar to weather forecasting in that you need to feed computer models large amounts of data so they can'learn' trends," said Dave Osthus, a statistician at Los Alamos and developer of the computer model, Dante. "But it's very different because disease spread depends on daily choices humans make in their behavior--such as travel, hand-washing, riding public transportation, interacting with the healthcare system, among other things. Those are very difficult to predict."

Detecting fake news is getting more difficult as more false information pours onto the internet ... [ ] every day, and from very influential sources. New papers from MIT explore how current methods are failing, and bring new weapons to the fight against fake news. Now is the time to make facts great again. "Fake news," the 2017 Collins word of the year, poses a serious threat to the values of honesty, truth, and accountability--values that purveyors of falsified information don't seem to hold too closely. Apart from the most obvious dangers of spreading false information (erosion of trust, political or national hostility, widespread uncertainty) the prevalence of AI systems on social media mean that unverified claims and slanderous falsehoods are picked up and distributed at eye-watering speeds.

Professor Bostrom spoke about AI and its safety on the sidelines of Russia's main event in the field of technological entrepreneurship - the annual Open Innovations forum - held by Skolkovo's Innovation Center. Sputnik: In what area can we expect to see "unicorns" in the future? Nick Bostrom: They can crop up in any part of the economy really, as long as the sector has a certain size that could bring new innovations and new ideas that would be successful enough to become worth a billion. Nick Bostrom: I think the highly salient areas which are sort of big ambitions tech things on the Internet. But a lot of other parts of the economy that also are quite large and have less of a public profile.

SAN FRANCISCO, Oct. 24, 2019 (GLOBE NEWSWIRE) -- MICRON INSIGHT -- Micron Technology, Inc. (MU), today announced a powerful new set of high-performance hardware and software tools for deep learning applications with the acquisition of FWDNXT, a software and hardware startup. When combined with advanced Micron memory, FWDNXT's (pronounced "forward next") artificial intelligence (AI) hardware and software technology enables Micron to explore deep learning solutions required for data analytics, particularly in IoT and edge computing. With this acquisition, Micron is integrating compute, memory, tools and software into a comprehensive AI development platform. This platform in turn provides the key building blocks required to explore innovative memory optimized for AI workloads. "FWDNXT is an architecture designed to create fast-time-to-market edge AI solutions through an extremely easy to use software framework with broad modeling support and flexibility," said Micron Executive Vice President and Chief Business Officer Sumit Sadana.

If there is one application of Machine Learning that is known to be particularly useful and often successful, that is classification. Classification is the task of assigning a given entry to a single class (e.g. Usually, each entry to be processed is represented numerically as a vector of numbers, which can encode high-level features (e.g. the length of the tail, the presence of stripes or spots, etc.) or low-level ones (e.g. the value of each pixel in an image). Over the years, a lot of different classifiers have been explored by the community, the most popular ones being artificial neural networks, decision trees, support -vector machines, or other algorithms such as k-means clustering. In this article I will focus on neural networks, but the argument can be adapted to other types of classifiers.

BlackBerry CTO Charles Eagan says no security passwords is the dream. This may sound strange coming from a technologist whose company has invested billions in security and recently opened a new lab and business unit focused solely on research and development in the cybersecurity space. But he makes a compelling argument. "Passwords are painful and not that effective, and multi-factor authentication just makes it more complicated to compromise," Eagan told SDxCentral. "People do things to avoid having to remember passwords, or they take shortcuts. Our real vision is: we want more security with less friction. We would love it if you never had to use a password, and you had more security at the same time."