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.

The "photonic time stretch" was invented by Professor Barham Jalali, who holds a patent for this technology, and its use in microscopes is just one of many possible applications. It works by taking pictures of flowing blood cells using laser bursts in the way that a camera uses a flash. This process happens so quickly – in nanoseconds, or billionths of a second – that the images would be too weak to be detected and too fast to be digitised by normal instrumentation. The new microscope overcomes those challenges using specially designed optics that boost the clarity of the images and simultaneously slow them enough to be detected and digitised at a rate of 36 million images per second. It then uses deep learning to distinguish the cancer cells from healthy white blood cells. Deep learning is a form of artificial intelligence that uses complex algorithms to extract meaning from data, with the goal of achieving accurate decision making.

A microscope, invented by a professor at the University of California, uses artificial intelligence in order to locate cancer cells more efficiently than ever before. The device uses photonic time stretch and deep learning to analyze 36 million images every second without damaging the blood samples. This new technique for identifying problematic cells is faster and more accurate than standard methods currently in practice. Commonly, doctors will add biochemicals to blood samples in order to check for cells containing cancer. The biochemicals attach what scientists call "biological labels" to damaged cells, which enables instruments to both locate and identify differences.

The bad news is, Japan is beset by seemingly insoluble problems. The good news is the word "seemingly." No nation whose rise to economic superpowerdom began a bare decade after being bombed to rubble in history's most destructive war will ever find anything truly "insoluble." Give it 34 years, says Clyde Prestowitz. His name rings bells in Japan -- alarm bells mostly, because Prestowitz, an American labor economist who served in the 1980s as economic adviser to the administration of U.S. President Ronald Reagan, earned notoriety here as a prime "Japan basher."

In a milestone for artificial intelligence, a computer has beaten a human champion at a strategy game that requires "intuition" rather than brute processing power to prevail, its makers said Wednesday. Dubbed AlphaGo, the system honed its own skills through a process of trial and error, playing millions of games against itself until it was battle-ready, and surprised even its creators with its prowess. "AlphaGo won five-nil, and it was stronger than perhaps we were expecting," said Demis Hassabis, the chief executive of Google DeepMind, a British artificial intelligence (AI) company. A computer defeating a professional human player at the 3,000-year-old Chinese board game known as Go, was thought to be about a decade off. The clean-sweep victory over three-time European Go champion Fan Hui "signifies a major step forward in one of the great challenges in the development of artificial intelligence--that of game-playing," the British Go Association said in a statement.

UCLA researchers have developed a new laser-based technology to rapidly screen blood samples for the presence of cancer cells. The label-free system measures 16 different physical characteristics of each cell and analyzes the data to identify whether the cell is cancerous. Not having to introduce any labeling chemicals and being gentle on the cells, the technique leaves the cells alive and available for further inspection using other means. It relies on a photonic time stretch microscope and a computer that runs deep learning artificial intelligence algorithms. The microscope can take millions of images per second thanks to unusual optics that produce high quality shots even at this speed.

You have a fever, can't eat and you're barely strong enough to get out of bed. So you phone your GP surgery for an appointment, only to be told that the first one is two weeks away. A mobile app, Your.MD, is promising something radically different. Billed as a personal health assistant, it uses artificial intelligence (AI) to mimic, as far as possible, your consultation with a GP. If you tell Your.MD your symptoms, it will tell you what it thinks your problem might be.

Have trouble achieving a work-life balance? Well, Google Calendar might be able to help. On Wednesday, Google released Goals, a new feature for Google Calendar that uses machine intelligence to help users find time in their busy schedule to accomplish personal goals, such as exercising, reading more, or learning a new skill. Goals is on the Google Calendar mobile app, and can be used to tackle specific, categorized goals, or to create and pursue a custom personal goal. The new feature is now available everywhere that Calendar is. For those of us who live and die by what's on our calendars, stating our goals is a good start to achieving them.

Researchers have traced the paths of thousands of neurons in a tiny piece of mouse brain, creating the largest map of neuronal wiring to date. The atlas, published in March in Nature, shows not only how these neurons connect, but also how they function as the brain processes information1. The work is part of a massive effort, backed by more than 70 million in federal funding, to use the brain as a blueprint for intelligent machines. The findings could also offer clues about how the brain becomes wired during development and what happens when this wiring goes awry, says lead researcher R. Clay Reid, senior investigator of neural coding at the Allen Institute for Brain Science in Seattle, Washington. "In some way that no one has thought of yet, this will help [to advance our understanding of] autism," he says.

Scientists at the California NanoSystems Institute at UCLA have developed a new technique for identifying cancer cells in blood samples faster and more accurately than the current standard methods. In one common approach to testing for cancer, doctors add biochemicals to blood samples. Those biochemicals attach biological "labels" to the cancer cells, and those labels enable instruments to detect and identify them. However, the biochemicals can damage the cells and render the samples unusable for future analyses. There are other current techniques that don't use labeling but can be inaccurate because they identify cancer cells based only on one physical characteristic.