As G.E., Oracle, Salesforce.com and others push their A.I. products, it remains unclear whether potential customers understand how they will profit.

Photographic cues have helped systems like Microsoft's Emotion API detect human feelings with decent accuracy, but a new research project from MIT's Computers Science and Artificial Intelligence lab can interpret emotions with a greater degree of accuracy, using only wireless radio signals. Researchers at CSAIL have created a device they call the EQ-Radio, which can pick up emotions including excitement, sadness, anger and happiness with around 87 percent accuracy in tests thus far. The research is significant because it doesn't actually require any on-body sensors, either, even though it's detecting subtle cues from the subject including breathing patterns and heart rhythm. And since it requires nothing worn by the user, and avoids the accuracy pitfalls of something like camera-based facial recognition software, its creators believe it could be the ideal tech for companies looking to build some kind of emotional intelligence into their products. MIT professor Dina Katabi led the development of the EQ-Radio, and suggests that it could be used in varying ways across the entertainment, consumer advertising and healthcare verticals. You could, for instance, use it in smart TVs to more accurately gauge viewer response to ads and programming; or you could build it into a smart home hub to trigger automated actions with connected devices like stereos and lighting, adjusting the mood of you home to counter or augment your emotions.

Who says machine learning can't be fun? A crew of us from SAS went to San Francisco for the recent KDD conference, which bills itself as "a premier interdisciplinary conference, [which] brings together researchers and practitioners from data science, data mining, knowledge discovery, large-scale data analytics, and big data." We brought these buttons with us, and they were a huge hit! But we weren't at KDD just to have fun, of course. We came to learn and share, in our booth and in many other ways.

Today, Microsoft announced an audacious new goal: its researchers will attempt to "solve" cancer by treating the disease group as information processing systems that can be modeled and reasoned, and then use sophisticated analysis tools to better understand and treat cancer. "At Microsoft's research labs around the world, computer scientists, programmers, engineers and other experts are trying to use computer science to solve one of the most complex and deadly challenges humans face: Cancer." Microsoft's Allison Linn writes in a new post to Microsoft Stories. "And, for the most part, they are doing so with algorithms and computers instead of test tubes and beakers." Yes, Microsoft's research labs are hard at work on tough computer science problems too.

Is there a program out there that's easy to set up that I could run on my unremarkable desktop PC to watch it try a simple game for a few hours and see how much it learns? I'd love to watch the evolution of a program as it learns something like Pacman on its own.

"The question of whether a computer can think is no more interesting than the question of whether a submarine can swim." Many articles about chatbots focus on their use of A.I. and argue that recent advances in artificial intelligence are making bots viable in a way that they had't been until now. Unfortunately, this argument is not only misguided, it is actually damaging to those who are trying to make and sell useful bots. Artificial intelligence is literally the type of intelligence that makes a computer indistinguishable from a human. The concept is based on the ideas of Alan Turing. One could make the argument that Alan Turing did more to win World War II than any other individual.

Many of the big players in IT are taking an interest in artificial intelligence nowadays. A.I. has already become a part of our daily lives and has the potential to penetrate further to fulfill our day-to-day needs. It is apparent from the existing tools that A.I. has a significant role to play in the areas of business and marketing. Here are some of the best A.I.-based tools that can benefit small and medium business. Gluru acts like a personal assistant that will keep a watch on your calendar, track meetings and events, and give you a daily digest of your deadlines, to-dos, and appointments.

For some, mentioning artificial intelligence conjures up clichés like Skynet and humanity's demise at the hands of our kitchen appliances gone wild. The reality is that, in one form or another, the demands of our evolutionary continuum have created a need for machines in the past and as we move forward, there will be a need to make them smarter. Necessity is said to be the mother of invention and has often helped us combat the unpredictable and sometimes violent forces of nature. In this regard, technology has held our hand since the beginning. From the discovery of fire to the miracle of flight, technology has helped humanity realise greatness.

There are three central challenges that have plagued past efforts to use artificial intelligence in medicine: the label problem, the deployment problem, and fear around regulation. With tools like Apple's ResearchKit and Google Fit, we can collect health data at scale; with deep learning, we can translate large volumes of raw data into insights that help both clinicians and patients take real actions. These annotations, called labels, are essential to make techniques like deep learning work. These two things enable outside-in approaches to healthcare: build up a user base outside the core of the healthcare system (e.g., outside the EMR), but take on risk for core problems within the healthcare system, such as re-hospitalizations.

Researchers at Uppsala University have used computer modeling to study how brain tumors arise. Instead of almost exclusively using different biological models, like cells, today large-scale statistical analyses are increasingly used to understand tumor diseases and find new therapies. In the study the researchers used aSICS to interpret data from brain tumors and they could identify a new mechanism behind mesenchymal glioblastoma, an extra aggressive brain tumor type. "According to the computer model, mesenchymal glioblastoma is partly caused by alterations in a gene called Annexin A2.