Google-owned DeepMind has expanded its collaboration with the UK's National Health Service (NHS), announcing a research partnership today with Moorfields Eye Hospital NHS Foundation Trust in London -- its second publicly confirmed foray into working with the NHS. But this time the project is being explicitly badged as medical research, and DeepMind will be applying AI machine learning algorithms to the data -- so that's also a first. Although the company has been public about its ambitions to apply AI to health data before now. The Moorfields partnership is focused on two specific sight-loss causing conditions: diabetic retinopathy and age-related macular degeneration (AMD), which DeepMind notes collectively affect more than 625,000 people in the UK and more than 100 million people worldwide. The stated aim is to investigate whether machine learning algorithms can automate the analysis of the digital eye scans that are typically used to diagnose the two conditions.

Google on Wednesday announced a deal to buy Moodstocks, a French startup behind technology that helps smartphones recognize whatever they are aimed at. Moodstocks caught the US technology giant's eye for its work in computer vision and machine learning, as well for accomplishments in enabling smartphones or other mobile devices to recognize images and objects. Google is among Silicon Valley titans investing in ways to get computers to see and understand the world around them the way people do. Machine learning has been woven into an array of Google offerings, such as its free language translation and photo services. "There's a lot more to be done to improve machine vision," Google France tech site lead Vincent Simonet said in a blog post.

Moodstocks caught the US technology giant's eye for its work in computer vision and machine learning, as well for accomplishments in enabling smartphones or other mobile devices to recognise images and objects. Google is among Silicon Valley titans investing in ways to get computers to see and understand the world around them the way people do. Machine learning has been woven into an array of Google offerings, such as its free language translation and photo services. "There's a lot more to be done to improve machine vision," Google France tech site lead Vincent Simonet said in a blog post. "That's where Moodstocks comes in."

Google on Wednesday announced a deal to buy Moodstocks, a French startup behind technology that helps smartphones recognize whatever they are aimed at. Moodstocks caught the US technology giant's eye for its work in computer vision and machine learning, as well for accomplishments in enabling smartphones or other mobile devices to recognize images and objects. Google is among Silicon Valley titans investing in ways to get computers to see and understand the world around them the way people do. Machine learning has been woven into an array of Google offerings, such as its free language translation and photo services. "There's a lot more to be done to improve machine vision," Google France tech site lead Vincent Simonet said in a blog post.

The self-driving robots have already journeyed over 5,000 miles in tests across Greenwich, Milton Keynes and Glastonbury. The company says they have "met over 400,000 people without a single accident." When they're deployed by Just Eat and Pronto, the 4mph robots will operate as a "last-mile" solution, delivering food to customers within a 2-3 mile radius with help from its on-board GPS system and various sensors. When a robot arrives at its destination, customers simply need to type in a code that has been sent to them via the mobile app to open the lid and collect their food. "By launching partnerships with major companies we will enter the next phase in our development," says Ahti Heinla, co-founder, CEO and CTO of Starship Technologies.

Nasa has announced that it has found evidence of flowing water on Mars. Scientists have long speculated that Recurring Slope Lineae -- or dark patches -- on Mars were made up of briny water but the new findings prove that those patches are caused by liquid water, which it has established by finding hydrated salts. Several hundred camped outside the London store in Covent Garden. The 6s will have new features like a vastly improved camera and a pressure-sensitive "3D Touch" display

Machine learning is a hot topic in business. Even data-driven organizations that have spent years developing successful data analysis platforms, with many accurate statistical models in place, are now looking into this decades-old discipline. But how can companies turn hyped opportunities for machine learning into real business value? This report examines the growing momentum of machine learning in the analytics landscape, the challenges machine learning presents to businesses, and examples of how organizations are actively seeking to incorporate modern machine learning techniques into their production data infrastructures. Authors Patrick Hall, Wen Phan, and Katie Whitson look at two companies in depth--one in healthcare and one in finance--that are seeing the real impact of machine learning.

Uber drivers who pay a visit to the company's inspection lot near Mission Bay in San Francisco will be met with a rather strange sight: a five-foot-tall, white, egg-shaped robot wheeling around the lot, on the look-out for trouble. The robot is a K5, a 300-pound security robot made by Silicon Valley start-up Knightscope. Stacy Stephens, Knightscope's VP of marketing, says Uber is a recent customer of the company. The robot has multiple high-definition cameras for 360-degree vision, a thermal camera, a laser rangefinder, a weather sensor, a license-plate recognition camera, four microphones, and person recognition capabilities. Once set up in a geofenced area, "it roams around looking for anomalies," said Stephens.

The Tesla Model S Last week it emerged that a self-driving Tesla car had been involved in a fatal crash in Williston, Florida on May 7. The car was in Autopilot mode when its on-board system failed to recognize a left-turning truck intercepting its path, resulting in the car proceeding underneath the trailer and losing its roof. There are already numerous theories about what happened, the most likely being that the car's cameras could not decipher the pale trailer against the bright Florida sky. Another possibility is that the system registered the trailer as an overhead road sign – Tesla cars are programmed to ignore overhead signs to avoid excessive and unnecessary braking – which could have happened due to the onward view beneath the trailer being clear to cameras. Nonetheless, the crash resulted in the death of 40-year-old Joshua Brown from Ohio and official investigations have begun. Since the incident, Tesla has released a blog post expressing their condolences and outlining the safety procedures all Tesla cars are equipped with.

IBM, Amazon, Facebook and Google are bent on building horizontal platforms around AI, but for Asia, the opportunity to build vertical solutions for startups is the forecasted trend. In an interview with EconomicTimes India, Sanat Rao, partner of IDG Venturs, a venture capital company, said "There is a really big opportunity in sectors such as healthcare and automobiles for AI. Concider a healthcare AI platform that can learn from thousands and even millions of images and can make more accurate diagnosis as it learns."