Google researchers got an eye-scanning algorithm to figure out on its own how to detect a common form of blindness, showing the potential for artificial intelligence to transform medicine remarkably soon. The algorithm can look at retinal images and detect diabetic retinopathy--which affects almost a third of diabetes patients--as well as a highly trained ophthalmologist can. It makes use of the same machine-learning technique that Google uses to label millions of Web images. Diabetic retinopathy is caused by damage to blood vessels in the eye and results in a gradual deterioration of vision. If caught early it can be treated, but a sufferer may experience no symptoms early on, making screening vital.

WebRTC is the future of browser-to-browser communications, and continues to make inroads into the traditional, difficult, plug-in web communications world. WebRTC Summit 2017 New York continues our tradition of delivering the latest and greatest presentations within the world of WebRTC. Topics include voice calling, video chat, P2P file sharing, and use cases that have already leveraged the power and convenience of WebRTC. All major researchers estimate there will be tens of billions devices - computers, smartphones, tablets, and sensors - connected to the Internet by 2020. This number will continue to grow at a rapid pace for the next several decades.

Artificial intelligence captured the world's attention last year when it defeated humanity's champion at the game of Go. It was a landmark event for AI, much like the moment 20 years earlier when IBM's Deep Blue defeated Garry Kasparov at chess in 1997. Starting next week an artificial intelligence system named Libratus, developed by a team at Carnegie Mellon University, will try to establish a new milestone: beating some of the best human players at Heads-Up No-Limit Texas Hold'em poker. While Libratus may one day be listed in the history books alongside Deep Blue and Alpha Go, it's actually attempting to solve a very different kind of problem. Go and chess are perfect-information games: each player knows exactly what moves have been made and what space is left on the board to consider.

Artificial Intelligence, as we see it, is a collection of multiple technologies that enable machines to sense, comprehend and act--and learn, either on their own or to augment human activities. Compelling data reveal a discouraging truth about growth today. There has been a marked decline in the ability of traditional levers of production--capital investment and labor--to propel economic growth. Yet, the numbers tell only part of the story. Artificial intelligence (AI) is a new factor of production and has the potential to introduce new sources of growth, changing how work is done and reinforcing the role of people to drive growth in business.

While robots and computers will probably never completely replace doctors and nurses, machine learning/deep learning and AI are transforming the healthcare industry, improving outcomes, and changing the way doctors think about providing care. Machine learning is improving diagnostics, predicting outcomes, and just beginning to scratch the surface of personalized care. Imagine walking in to see your doctor with an ache or pain. After listening to your symptoms, she inputs them into her computer, which pulls up the latest research she might need to know about how to diagnose and treat your problem. You have an MRI or an xray and a computer helps the radiologist detect any problems that could be too small for a human to see.

"Fake news" vexed the media classes greatly in 2016, but the tech world perfected the art long ago. With "the internet" no longer a credible vehicle for Silicon Valley's wild fantasies and intellectual bullying of other industries – the internet clearly isn't working for people – "AI" has taken its place. Almost everything you read about AI is fake news. The AI coverage comes from a media willing itself into a mind of a three year old child, in order to be impressed. For example, how many human jobs did AI replace in 2016?

In the passing year many breakthroughts of Artificial Intelligence (AI) occurred. But right now the technology industry reaches a new step of evolution: Using Artificial Intelligence - or better Machine Learning (ML) - to advance and enhance Cyber Security. As Ken Levine - an american (video) game developer - mentioned: a human hacker will one day not be able to defeat an AI, because it won't make any mistakes. So why don't use AI to improve the Cyber Security, which is extremely needed in times of the Internet of Things (IoT) and Financial Technology (FinTech)? Google, as one of the big companies in the race of AI, made an experiment in which two Artificial Intelligences had to communicate in a secure way, while a third one had to decrypt what they encrypt.

While "big data" can be a misunderstood buzzword in tech, there's no denying that the recent AI and machine learning push is dependent on the labeling and synthesis of huge amounts of training data. A new trend report by advisory firm Ovum predicts that the big data market--currently at $1.7 billion--will swell to $9.4 billion by 2020. So what do data insiders see happening in the coming year? TechRepublic spoke to several leaders in this field to find out. Here are five big data trends to watch in 2017, from the experts.

Predictions are ultimately a fool's game. While it's certainly possible to make some broad assumptions about the next 12 months in technology (Apple will release a new iPhone! More firms will introduce cloud services!), the fast-changing nature of the industry can quickly wreck even the most seemingly surefire trends. With that in mind, here are some cautious forecasts about the hottest technologies of 2017. Sure, we could be wrong.

Just as Skype revolutionized the way we communicate, and TransferWise found a way to break worn patterns in the financial world, Estonia is about to make a transforming difference in the dynamic field of robotics too. Besides the country being a Mecca for data and tech-driven startups, more and more Estonians, in addition to excelling in code writing and software development, are thrusting their hands deep into the wiring and metal of robots. Imagine a vacuum-cleaner-sized, yellow'turtle' diving elegantly down hundreds of metres to probe ship wrecks, thus gathering valuable data for archaeologists and maybe even finding lost treasures buried somewhere deep under the sea. But this intelligent'turtle' is actually a robot. Equipped with a camera and a searchlight, the relatively cheap and highly manoeuvrable U-CAT (Underwater Curious Archaeology Turtle) locomotion principle is similar to that of the sea turtles of the natural world.