Some of the world's fastest computers employ Nvidia's graphics processor for computer vision, deep learning and scientific calculations, and a new GPU will supercharge these applications. The Tesla P100 that plugs into the PCI-Express slots of supercomputers will speed up tasks like economic forecasting and weather modeling. The GPU is also targeted at servers, and will play a big role in helping self-driving cars, robots and drones identify objects. Further reading: Nvidia's beastly Pascal GPU is packed with cutting-edge tech and 15 billion transistors Deep-learning systems with the GPUs in data centers will improve cloud-based image recognition, classification, natural language processing and speech recognition. One system with Tesla P100 chips is Nvidia's DGX-1, which can be purchased for 129,000.

Consumers want a more interesting relationship with the brands they use, and think highly of virtual techniques promised by evolving technologies – especially on the more personal mobile level – says a report from the DMA. According to the study, half (48%) of respondents expressed an interest in artificial intelligence (AI) approaches to engagement, such as chatbots or virtual assistants. But this increased dramatically for younger age groups, rising to 79% for 16-24 year olds, 76% for those aged 25-34 and 62% of those aged 35-44. More than half (54%) of Gen Y/Millennial age groups (28% of the total sample) are interested in a service that detected how they were feeling and sent them surprise offers/deals based on their mood. "Current engagement methods often seem clumsy, like'brand stalking', where items follow a consumer around on web banners. Instead, consumer data could be used in virtual or artificial intelligence systems. One example could be chatbots, giving brands a better way to use their data and consumers a more meaningful interaction," said Rachel Aldighieri, DMA MD.

HPE Haven OnDemand is a platform for building data-rich applications and analytics using text analysis, speech recognition, image analysis, indexing and search APIs. Simply put, developers and businesses use the Haven OnDemand APIs to add advanced capabilities such as natural language processing, machine learning, and predictive analytics to their applications. This talk will focus on HPE Haven OnDemand platform's capabilities of human information analytics and building advanced unstructured text indexes. Includes a live demo of our Rich Media App that was recently featured by Gregory Piatetsky, a top influencer in Big Data and Data Science, on his blog, KDNuggets. You'll walk away with a better understanding of our platform offerings, how to set up a Haven OnDemand account to try our APIs and how to build your own rich media app to: Phong Vu is a Developer Evangelist for Haven OnDemand at Hewlett Packard Enterprise.

I said, and I wrote, that machine learning and predictive analytics were almost the same. Of course, I also put optimization as the queen of all analytics technologies as it yields best business value. What else would you expect from someone who spent nearly 3 decades in working in optimization? No wonder this view became popular in the optimization community... First, let me reassure readers about my mental health: I still think that optimization is best for computing optimal decisions. I started thinking there was an issue when I met customers willing to use machine learning to solve all the business problems they have.

We are using intelligent machines for everything from self-driving cars to online searches. But how about leveraging artificial intelligence, or AI, to save lives? "A momentous change in health care is under way," says Suchi Saria, an associate professor in computational biology at Johns Hopkins, with startups harnessing the recent explosion of electronic health data to help doctors make critical decisions and extend care to patients between appointments. Here are five ways that machine learning is poised to bring new rigor to medicine. Developing pharmaceuticals can take decades.

By releasing Haven-on-Demand APIs on Microsoft Azure, HPE is following in the footsteps of IBM. Big Blue made its Watson API's available on BlueMix a while ago. Furthermore, it recently announced a collaboration with Twilio, a cloud communications platform for developers, as part of which it introduced two new offerings: IBM Watson Message Sentiment and IBM Watson Message Insights, pre-integrated with Twilio's APIs. This signaled IBM's willingness to make Watson APIs accessible to a wider community of developers, beyond BlueMix. This is also what HPE is doing by making Haven-on-Demand available on Microsoft Azure.

Tekstum provides real-time scientific analysis of the opinions and feelings that readers are expressing online. Using a state-of-the-art algorithm built with big data and artificial intelligence, the company promises to revolutionise how publishers market, and how customers search for and buy books, by synthesising, analysing and visualising readers' moment-to-moment emotions and experiences. Spanish founder and CEO Marc Santandreu worked for international publishing companies such as Author Solutions and Regió7. Lauren Romeo (PhD in Computational Linguistics) is the Lead Scientist, pioneering the Natural Language Processing research and development of the engine, while Juanjo Fernandez is the engineer responsible for the development of the software. Every year the number of new books in the market grows exponentially, generating huge amounts of data at ever-faster rates.

It's well known that we in the tech sector love our acronyms. We also like re-badging stuff.What was once ASP (application service provision) morphed into SaaS (software as a service) and then became part of the cloud computing eco-system. And so it is at the moment with AI (artificial intelligence). There have been a number of pronouncements recently, particularly from private practice firms, about their adoption of AI. But is the truth more weighted towards the "artificial" than the "intelligence"?

Trust greases the wheels of the sharing economy, paving the way for transactions to take place between total strangers. But figuring out who is trustworthy and who is not remains a sticky bottleneck for digital businesses wanting to scale faster. Meanwhile the consequences for customers when startups screw up these risk calculations can be very unpleasant indeed. The traditional route to assessing risk is to run a full background check on an individual -- a process that can be time consuming and expensive, given it can involve sending an actual person to an actual courthouses to parse actual paper records. Which is why, in recent years as sharing economy businesses have been gunning to scale up, other entrepreneurs have spotted an opportunity to step in to offer online services for verifying identity and screening for unsavory behavior, to try to steal a march on more established but slower paced background checkers.

As the driverless car gets closer to reality, so too does the dilemma of how to insure the car and its owner. The auto insurance industry faces upheaval in the next 25 years as the migration to autonomous safety features -- and ultimately a self-driving car -- shifts more of a car's accident risk from the driver to the vehicle, analysts said. The number of accidents is expected to drop sharply because currently more than 90% of accidents are caused by driver error. The U.S. market for personal auto insurance policies, which currently generates 200 billion in premiums a year, could shrink substantially, some experts predict. "There are going to be dramatic changes," said Joe Schneider, a managing director at KPMG who's part of the accounting firm's task force studying the issue.