It is a fascinating experiment that brings together Google's artificial intelligence division and one of the world's leading centres for the treatment of eye conditions. But the research project that has seen Moorfields Hospital hand over retinal scans to DeepMind has already proved controversial - and, for me, it all feels rather close to home. For the past 10 years, I have been a regular visitor to Moorfields, where I receive excellent treatment for a longstanding condition. This includes having pictures taken of the back of my eye, and it seems likely that these photos may be among those handed to DeepMind. This is for a project that aims to work out whether machine-learning technology can give doctors a better understanding of eye disease.

Accelerating the race to autonomous cars, NVIDIA today launched NVIDIA DRIVE PX 2 – the world's most powerful engine for in-vehicle artificial intelligence. NVIDIA DRIVE PX 2 allows the automotive industry to use artificial intelligence to tackle the complexities inherent in autonomous driving. It utilizes deep learning on NVIDIA's most advanced GPUs for 360-degree situational awareness around the car, to determine precisely where the car is and to compute a safe, comfortable trajectory. "Drivers deal with an infinitely complex world," said Jen-Hsun Huang, co-founder and CEO, NVIDIA. "Modern artificial intelligence and GPU breakthroughs enable us to finally tackle the daunting challenges of self-driving cars. "NVIDIA's GPU is central to advances in deep learning and supercomputing.

Someone at Google really likes sneakers: The company has just bought a French machine learning startup that taught a computer how to recognize 15,000 different types of them. Paris-based Moodstocks builds image and object recognition software using deep learning techniques, and offered an Android app and visual search API that could recognize certain kinds of object. By analyzing video from a smartphone camera, and correlating it with accelerometer readings to determine how the camera is moving around, the software is able to infer information about the three-dimensional shape of objects in the video, facilitating their recognition. In February 2015 the company demonstrated its ability to identify sneakers through its app. Three months later, after training the software using 15,000 photos of shoes from an online retailer's website, Moodstocks claimed to be able to shop online for all the sneakers on sale in a Macy's store. Google has been introducing elements of machine learning into its existing online services, including Google Translate and Inbox, a next-generation interface for Gmail.

MIT developed a deep learning algorithm capable of assessing physical interactions in videos and the sounds resulting from those interactions. The algorithm was then fed muted video clips of a drumstick hitting various objects and instructed to produce sound effects appropriate for each video. But the visual Turing Test is just one component of fully passing the Turing Test. MIT is currently developing an algorithm for passing the visual Turing Test, which is great for the machine learning community and is definitely a step towards having machines understand the consequences of interacting with different environments.

The Turing Test was designed by Alan Turing as a way of measuring how good a machine is at imitating human behavior. Passing the test means that the difference between a machine and human is imperceptible. In popular culture, the Turing Test is often portrayed as a computer attempting to seem as human as possible to the point where humans mistake it as one of their own. However, this is only one application of the Turing Test, which has different types. For instance, some machines can mimic human sounds while other can visually compete with what a human can do-- which is a large step toward autonomous vehicles.

In a recent issue of Nature Scientific Reports, a multidisciplinary team of UCLA researchers combined a new form of microscopy called photonic time-stretch imaging with deep learning. With this powerful new technique, they were able to capture 36 million video frames per second. Not content with simply developing a new technique, the team then utilized the augmented microscope to determine which strains of algae provide the most lipids for subsequent refining into biofuels. They also were able to detect cancer cells more accurately and in less time than current techniques. Yes, one methodology that tackled both biofuels and cancer.

AlphaGo's uncanny success at the game of Go was taken by many as a death knell for the dominance of the human intellect, but Google researcher David Silver doesn't see it that way. Instead, he sees a world of potential benefits. As one of the lead architects behind Google DeepMind's AlphaGo system, which defeated South Korean Go champion Lee Se-dol 4 games to 1 in March, Silver believes the technology's next role should be to help advance human health. "We'd like to use these technologies to have a positive impact in the real world," he told an audience of A.I. researchers Tuesday at the International Joint Conference on Artificial Intelligence in New York. With more possible board combinations than there are atoms in the universe, Go has long been considered the ultimate challenge for A.I. researchers.

This is a group for anyone interested in Deep Learning technology, employment, or business opportunities. All skills, levels of experience, and professional backgrounds are welcome. I started this group to help people network with one another and move their careers forward. Looking forward to exploring what this technology can do with everybody.

Which authors of this paper are endorsers? Disable MathJax (What is MathJax?)

AlphaGo's uncanny success at the game of Go was taken by many as a death knell for the dominance of the human intellect, but Google researcher David Silver doesn't see it that way. Instead, he sees a world of potential benefits. As one of the lead architects behind Google DeepMind's AlphaGo system, which defeated South Korean Go champion Lee Se-dol 4 games to 1 in March, Silver believes the technology's next role should be to help advance human health. "We'd like to use these technologies to have a positive impact in the real world," he told an audience of AI researchers Tuesday at the International Joint Conference on Artificial Intelligence in New York. With more possible board combinations than there are atoms in the universe, Go has long been considered the ultimate challenge for AI researchers.