DeepMind and its partners in the research, London's Moorfields Eye Hospital and the University College London Institute of Ophthalmology, said they plan prospective clinical trials of the technology in 2019. If those trials are successful, DeepMind said it would seek to create a regulator-approved product that Moorfields could roll out across the U.K. It said the product would be free for an initial five-year period. The software would be the first time a DeepMind AI algorithm using machine learning has ended up in a healthcare product. Alphabet has several initiatives aimed at using artificial intelligence to improve healthcare. Earlier this year, Verily, an Alphabet company that says its goal is to extend human lifespans, teamed up with AI experts from Alphabet's Google, to develop an algorithm that could spot a range of cardiovascular issues from a different kind of retinal image.

It aims to promote and develop friendly AI in a way to benefit humanity as a whole. It aims to "freely collaborate" by making its patents and research open to the public.

To put that into perspective, experts at OpenAI recently developed Dactyl, a robotic hand that could handle objects. This is a task that any human child learns to perform subconsciously at an early age. But it took Dactyl 6,144 CPUs and 8 GPUs and about one hundred years' worth of experience to develop the same skills. While it is a fascinating achievement, it also highlights the stark differences between narrow AI and the way the human brain works.

Even more impressive, it can explain its choices. Explain yourself: The black box has long been a challenge in artificial intelligence. This refers to the tendency of algorithms to spit out results without explaining what went into them--and it can make weeding out bias difficult. The news: In a paper released in Nature Medicine yesterday, DeepMind researchers described an AI system that can identify more than 50 diseases, refer them to a specialist, and, most important, indicate which portion of a medical scan prompted the diagnosis. Why it matters: Explainability is crucial if AI is to see increased use in medicine.

Machine-learning technology has been used to identify signs of eye disease and recommend how patients should be referred for treatment. The breakthrough is the result of a partnership between researchers at London's Moorfields Eye Hospital NHS Foundation Trust, DeepMind Health and the University College London Institute of Ophthalmology. The collaboration is looking at whether artificial intelligence (AI) technology can aid clinicians when it comes to improving care for patients. Founded in 2010, DeepMind was acquired by Google in 2014 and is now part of the Alphabet Group. Based in London, it undertakes research in AI.

For engineers at the Elon Musk-founded nonprofit OpenAI, this presented both a challenge and an opportunity. How could their researchers use artificial intelligence to teach a robot to manipulate objects as artfully as a human? Usually, when teaching an AI to control a physical robot, scientists tend to come up against the same problems. Training is often done using reinforcement learning; a method where the AI learns through a process of trial and error. But this requires a lot of time, usually amounting to years of experience.

DeepMind's AlphaGo Zero algorithm beat the best Go player in the world by training entirely by self-play. It played against itself repeatedly, getting better over time with no human gameplay input. AlphaGo Zero was a remarkable moment in AI history, a moment that will always be remembered. Move 37 in particular is worthy of many philosophical debates. You'll see what I mean and get a technical overview of its neural components (code animations) in this video.

Tech industry insiders regularly herald AI as the solution to all of our problems, included those posed by health care. London-based DeepMind, owned by Google's parent company, Alphabet, focuses heavily on the specifics of using artificial intelligence in health care, and on Monday it released a study showing the progress it's made in using AI to diagnose eye conditions. Published in the science journal Nature, the study reports that DeepMind, in partnership with Moorfields Eye Hospital in London, has trained its algorithms to detect over 50 sight-threatening conditions to the same accuracy as expert clinicians. In a project that began two years ago, DeepMind trained its machine learning algorithms using thousands of historic and fully anonymized eye scans to identify diseases that could lead to sight loss. According to the study, the system can now do so with 94 percent accuracy, and the hope is that it could eventually be used to transform how eye exams are conducted around the world.

When Pearse Keane started using optical coherence tomography (OCT) scanners to peer to the back of a person's eye in Los Angeles a decade ago, the machines were relatively crude. "The devices were lower resolution, they had much slower image acquisition speeds," says Keane, a consultant ophthalmic surgeon at Moorfields Eye Hospital and researcher at University College, London. From 2007, Keane spent two years studying scans from OCT machines learning to diagnose eye conditions in patients and pick out the minute details which make up sight-threatening diseases. "It was very time consuming, laborious work," Keane says. OCT scans use light to quickly create high resolution, 3D images of the back of the eye.

Artificial intelligence is now as good as human doctors at spotting early signs of blindness, a new collaboration between DeepMind and the NHS has shown. The new a system can spot 50 eye problems including as age-related macular degeneration and diabetic eye disease with 94 per cent accuracy and even provide a diagnosis for the one in four cases when experts cannot reach a consensus. Doctors are hopeful that it will speed up treatment for people who can wait up to 16 weeks for tests, according to charities, because of current shortages in the NHS. To develop the algorithm, programmers at DeepMind were given access to thousands of eye-scans from Moorfields Eye Hospital which they used to train their system to spot dozens of diseases over 18 months. Dr Pearse Keane, consultant ophthalmologist at Moorfields said: "The AI technology we're developing is designed to prioritise patients who need to be seen and treated urgently by a doctor or eye care professional.