It's a device that brings to mind the bodyless hand, Thing, from The Addams Family: a human-like robotic hand, engineered by scientists at the University of Washington, that can learn on its own as it handles a specific task. The hand has five fingers, tendons, joints, over a hundred sensors, and is capable of moving faster than its human counterpart. In a video the university released, the hand can be seen delicately rotating a tube full of coffee beans-- an activity that the robot can improve iteratively, the university said. "Hand manipulation is one of the hardest problems that roboticists have to solve," Vikash Kumar, a doctoral student at the University of Washington and the lead author on a new paper about the robot hand, said in a statement. "A lot of robots today have pretty capable arms but the hand is as simple as a suction cup or maybe a claw or a gripper."

The application that the TPUs are specific to is TensorFlow and neural networks in particular. One of the big bottlenecks here is the huge computing power it takes to train and even use such big deep neural networks. Google now has a short cut. It claims that using TPUs is an order of magnitude better-optimized for performance per watt than other approaches. This is vague, but it is also claimed to have moved the technology about seven years into the future - or three generations of Moore's law.

From self-driving cars to robot lorries, autonomous vehicles are the future of road transportation. But who's in pole position, who's stuck in the pit lane and how far away is the starting grid? Autonomous vehicles are already on our roads. At the cutting edge there are self-driving cars being tested in pilot programmes, and they are proving perfectly capable of motoring alongside human drivers. But beyond robotic cars, many high-end vehicles available today are already practically capable of driving themselves either under the guise of passenger safety or driver convenience.

Now it wants to go to a yet smaller wavelength and add machine learning to the back end of its sensors said Wim van Thillo, program director for perceptive systems at IMEC, speaking at the IMEC Technology Forum. Van Thillo said his group is already working on a 140GHz chip. At this frequency the wavelength is 2.2mm and his group is aiming for more than 4GHz of bandwidth from a chip measuring 1 square millimeter, he added. The advantages will include higher distance and angular resolution at lower power in a much smaller system size with the radar able to include the antenna-on-chip. In addition to angle and distance the radar is able to provide speed information via a mini-doppler effect.

The secret to Viv is the system actually writes it's own code. In contrast to any other similar system, It is a profound and monumental giant leap forward. The structure of the Voice First world is held together by Intelligent Agents. Intelligent Agents use AI (Artificial Intelligence) and ML (Machine Learning) to decode volition and intent from an analyzed phrase or sentence. The AI in most current generation systems like Siri, Echo and Cortana focuses on speaker independent word recognition and to some extent the intent of predefined words or phrases that have a hard coded connection to a domain expertise.

Too many custom distributions with various versions of the 20 or so tools that make up Apache Big Data. To be able to move between HDP, CDH, IBM, Pivotal and MapR seemless would be awesome. For now HDP, Pivotal and IBM are part of the ODPi. Structured Data: Connecting Modern Relational Database and Hadoop is always an architectural challenge that requires decisions, EnterpriseDB (Postgresql) has an interesting article on that. Semistructured Data: Using Apache NIFI with Tesseract for OCR: HP and Google have been fine-tuning Tesseract for awhile to handle OCR.

Siri seemed pretty futuristic when Apple first released the voice activated virtual assistant. But with Google, Facebook, Amazon and a slew of promising startups pushing the limits of interactive interfaces, the original app for making your phone talk back to you is seeming like a bit of a relic. Leading thinkers in the world of tech are a little concerned. Influential Apple developer Marco Arment wrote in a blog post over the weekend that Apple was falling so far behind in developing artificial intelligence interfaces, the company could fall off the map like Blackberry did. The concern could soon be--and Apple surely hopes already is--irrelevant.

The true value of the Internet of Things is when it is used in conjunction with autonomous devices and machine learning, according to SAS' chief analytics officer for Australia and New Zealand, Evan Stubbs. Speaking at the SAS Analytics Insights event in Sydney yesterday, he said that IoT is just a small part of the "bigger revolution that's going on", which includes big data, analytics, machine learning and automation. "The Internet of Things in isolation is really boring at the end of the day," he said. "The exciting thing about the Internet of Things is the fact that it can create an entire army of autonomous devices linked to a central intelligence that can make decisions for us. "So the fact that your toaster has an IP address – who cares?

There is a difference between knowledge and understanding. Knowledge typically comes down to knowing facts while understanding is the application of knowledge to the mastery of systems. You can know a lot while understanding very little. Just as an example, IBM's Watson artificial intelligence system that defeated the TV Jeopardy champs a few years ago knew all there was to know about Jeopardy questions but didn't really understand anything. Ask Watson to apply to removing your appendix its knowledge of hundreds of medical questions and you'd be disappointed and probably dead.

The first wave of robots taking over human jobs is upon us. Apple Inc. AAPL, 1.76% supplier Foxconn Technology Co. 2354, -0.41% has replaced 60,000 human workers with robots in a single factory, according to a report in the South China Morning Post, initially published over the weekend. This is part of a massive reduction in headcount across the entire Kunshan region in China's Jiangsu province, in which many Taiwanese manufacturers base their Chinese operations. Roughly 600 companies are reportedly looking to reduce headcount with robots, as part of an effort to accelerate growth and reduce costs, according to the Chinese newspaper, which cited data from the Kunshan government. Last year, 35 Taiwanese companies, including Foxconn, spent a total of 4 billion yuan ( 610 million) on artificial intelligence as part of this initiative, according to the report.