IBM announced a deal with sports and fitness retailer Under Armour Inc. to use machine learning technology from Watson and showed off an application for diabetic care developed with the supercomputer's data, highlighting the company's effort to expand Watson's capabilities for the health-care industry. IBM and Under Armour released an updated fitness application for Apple Inc.'s iPhones that uses data powered by Watson, IBM Chief Executive Officer Ginni Rometty said Wednesday in a speech at the International Consumer Electronics Show in Las Vegas. Separately, Medtronic Plc CEO Omar Ishrak joined Rometty on stage to unveil a prototype for a diabetes-management app that tests have shown may be capable of predicting hypoglycemic events as early as three hours in advance. The application still needs to go through regulatory review -- it will roll out this summer, Rometty said. The ability to predict the hypoglycemic events is a "breakthrough," she said.

It's hard to deny that technological breakthroughs have benefited modern designers, but it has also become increasingly clear that advances in artificial intelligence could have a big impact on the future of human creativity. Case in point are hyper-personalized programs like Mark Maker, a new prototype that generates logos and refines them based on the user's feedback. Using a genetic algorithm, Mark Maker generates logos based on a random "gene pool"; when logos are "liked" by the user, new logos are then created by borrowing and recombining their traits. Each logo is created by breaking a design in half, so that it contains both a base design and an accent element. The result is a system that "learns" and can create a personalized, visual vernacular for virtually any company, while also hinting at possibly significant changes in the lives of human designers.

The University of Science and Technology of China on Friday officially launched the robot "Jiajia" it invented for interactive experience. HEFEI, April 15 (Xinhua) -- A new interactive robot, named Jia Jia, was unveiled Friday by the University of Science and Technology of China (USTC) in Hefei, capital of east China's Anhui Province. Welcome!" the eye-catching robot said as it greeted the audience at the university's multi-media center. "Don't come too close to me when you are taking a picture. It will make my face look fat," Jia Jia said. Jia Jia was developed by a robot research and development team at the USTC, which also developed the model service robot "Kejia." It took the team three years to research and develop this new-generation interactive robot, which can speak, show micro-expressions, move its lips, and move its body, according to team director Chen Xiaoping. Compared to previous interactive robots, Jia Jia's eyeballs roll naturally and its speech is in sync with its lip movements, in addition to her human-like form, Chen said. Jia Jia can not cry or laugh and these are areas to be developed, Chen added. "We hope to develop the robot so it has deep learning abilities.

As the Internet of Things (IoT) continues its run as one of the most popular technology buzzwords of the year, the discussion has turned from what it is, to how to drive value from it, to the tactical: how to make it work. IoT will produce a treasure trove of big data – data that can help cities predict accidents and crimes, give doctors real-time insight into information from pacemakers or biochips, enable optimized productivity across industries through predictive maintenance on equipment and machinery, create truly smart homes with connected appliances and provide critical communication between self-driving cars. The possibilities that IoT brings to the table are endless. As the rapid expansion of devices and sensors connected to the Internet of Things continues, the sheer volume of data being created by them will increase to a mind-boggling level. This data will hold extremely valuable insight into what's working well or what's not – pointing out conflicts that arise and providing high-value insight into new business risks and opportunities as correlations and associations are made.

The following is a list of current and past, nonclassified notable artificial intelligence projects.

Nathan Benaich of Playfair Capital joins Nick to cover Artificial Intelligence Investing, Part 1.

Artificial intelligence (A.I. as many refer to it) is quickly becoming our reality. And even though its technology is all around us, many of us don't understand what that technology is. The "misconception" about artificial intelligence, is that it's a "robot," says Tim Urban, whose stick-figure-filled explainer on the technology has been read by more than 4 million people on his website, Wait But Why. The robot, however, is merely the "container" for the artificial intelligence, Urban told Olivia Stern for "Sunday TODAY with Willie Geist." "The A.I. is the software inside the container. The A.I. is, in particular, software that can make decisions."

Much of our conception of Artificial Intelligence or AI has been shaped by popular movies: from the homicidal Red Queen of "Resident Evil", to the J.A.R.V.I.S. operating system / virtual butler that provides logistical support to "Iron Man".

Automation and robotisation are becoming more prominent in the media, although the uninitiated might be forgiven for still being in the dark about them. Machine learning is happening right now. Artificial intelligence and machine learning applied to massive amounts of data are being harnessed to automate more and more of the things that, hitherto, we have had to do manually. Right now most of this data is centralized and in the hands of a few key players in Silicon Valley. And this centralization of data, the fuel of machine learning, has also attracted an astounding number of the world's leading machine learning researchers -- the industry's true superstars -- who, in recent years, have been recruited from universities by companies like Facebook, Google and Microsoft.

Funding dollars to Internet of Things startups jumped 31% in the first quarter of this year, compared to Q4'15. That was the second-highest total yet in a quarter. As industrial and business processes are more frequently mediated by the IoT, and IoT-driven analytics solidifies as a category, startups are leveraging machine learning and deep learning to provide predictive insights based on the data collected from wearables and sensors. Just in the last quarter, companies like Tellmeplus, Neura, and Sentenai raised funds to integrate machine learning algorithms with different IoT functions, including data collection, sorting, analyzing, insights, and automation. "A good IoT solution gives you an extraordinarily useful view of your organization's data; a great one allows you to build algorithms that can predict what's next…" – Microsoft IoT blog.