IBM Watson Health has formed a medical imaging collaborative with more than 15 leading healthcare organizations. The goal: To take on some of the most deadly diseases. The collaborative, which includes health systems, academic medical centers, ambulatory radiology providers and imaging technology companies, aims to help doctors address breast, lung, and other cancers; diabetes; eye health; brain disease; and heart disease and related conditions, such as stroke. Watson will mine insights from what IBM calls previously invisible unstructured imaging data and combine it with a broad variety of data from other sources, such as data from electronic health records, radiology and pathology reports, lab results, doctors' progress notes, medical journals, clinical care guidelines and published outcomes studies. As the work of the collaborative evolves, Watson's rationale and insights will evolve, informed by the latest combined thinking of the participating organizations.

Sometimes you just want to buy a decent, affordable bottle of wine without having to know anything about tannins or smokey overtones. An iPad kiosk called VineSleuth wants to help. When it arrives in grocery store aisles next year, you'll be able to press a button and say what you want in your own words. "I'd like a cheap rosé that's not too sweet to go with a Caesar salad." Sounds simple enough, but understanding natural spoken language, picking out keywords and using them to identify specific wines is complicated.

Since the dawn of manufacturing, designers and engineers have repeatedly run up against limitations to making things. Their ability to execute and capacity to afford bringing their ideas to market were once constrained by the manufacturing facility they had to find--either local or offshore--to build the things they wanted to build. But in a new world of enhanced robotics, factory automation, 3D printing, generative design, and design-make-use convergence, engineers' project limitations will fade away. And it's all because machine learning, computing power, and robots in the workforce are increasingly capable and intelligent. Soon, engineers will be able to design the best thing possible and then hand it to robots to dissect and turn into a series of assembled 3D-printed components.

A car crashes while on autopilot and the driver dies. A hefty security robot at a US shopping mall knocks down and injures a child. Autonomous systems and machines that make their own decisions are here. And more are on the way, such as airborne and ground-based delivery drones. But the way they learn about the world and decide to act is complex and opaque and it is hard to know how often they will get it wrong.

When Tesla CEO Elon Musk revealed his much-hyped master plan for his company this week, very little about it came as a surprise?

There's a small but growing handful of robotics companies trying to make it in the warehouse market with systems that work with humans on order fulfillment. Generally, we're talking about clever wheeled platforms that can autonomously deliver goods from one place to another, while humans continue do the most challenging part: picking items off of shelves. There's a lot of value here, since using robots to move stuff frees up humans to spend more of their time picking. Ideally, however, you'd have the robot doing the picking as well, but this is a very difficult problem in terms of sensing, motion planning, and manipulation. And getting a robot do pick reliably at a speed that could make it a viable human replacement is more difficult still.

Look no further than Google's Tensor Processing Unit (TPU), SoftBank's acquisition of ARM (SoftBank hopes to be a big player in AI), and now a venture-backed startup rolling out a family of "Deep Learning" computers. That startup is Wave Computing, based in Campbell, Calif. The six-year-old company came out of stealth mode Thursday (July 21), revealing its design of a massively parallel dataflow processing architecture called the Wave Dataflow Processing Unit (DPU) for deep learning. Derek Meyer, Wave Computing CEO, told EE Times, "In order to accelerate deep learning, the world needs a new computing architecture." Traditional computer architectures are designed for control flow-oriented applications.

Curious to know what an Australian soldier fighting in WWI had for brekkie? Now you can ask him yourself, along with anything else that comes to mind. The Wizeline bots team has partnered News Corp Australia to launch the AnzacLive chatbot, an innovative way to share history with a modern audience. The chatbot was created to commemorate Anzac Day, which recognizes the anniversary of the first major military action fought by the Australian and New Zealand Army Corps. in WWI -- namely the historic battles of Fromelles and Pozieres in July 1916. How did our bots team create a cross-century AMA? Journals from one of the soldiers, Archie Barwick, have been powered by technology.

MedyMatch Technology Ltd., announced today that it has been ranked in the list of "100 Most Promising BigData Solution Providers" by CIOReview. "The companies selected for our 100 Most Promising BigData Solution Providers 2016 list are an elite group of companies whose products and solutions are changing their respective industries," said Jeevan George, Managing Editor of CIOReview. "We are proud to feature MedyMatch Technology in this edition for its effort in helping organizations to easily and quickly adopt BigData analytics as a core part of their business and accelerate conversion of data into valuable business insights." "It is an honor to be recognized by CIOReview for MedyMatch's achievements in cognitive analytics, artificial intelligence and medical imaging," said Robert Mehler, coFounder & COO. "It is a testament to the accomplishments and capability of our product development team in conjunction with our medical big data clinical partnerships," adds Mehler.

Say you're driving late at night and you start to feel lonely. What if your car, detecting your change of mood through an array of sensors and cameras, suddenly asked how you were feeling? Better yet, what if your car already knew how you were feeling, and offered to cheer you up? This possible future was sketched out by SoftBank founder Masayoshi Son at an event in Tokyo Thursday, according to Reuters. The eccentric tech executive, who recently announced his company's acquisition of chip manufacturer ARM for 34.1 billion, said he is working with Honda to produce a car that can both talk and read a driver's emotions. "Imagine if robots, with their super intelligence, devoted themselves to humans," Son said, according to Reuters.