The Morning After: Monday, November 7, 2016


While you were weekending, you might have missed Roku's cheap, entry-level video streamer, our first 24 hours with Olympus' intriguing new camera and Samsung's attempts to hype up its next smartphone way in advance. What's going on this week? Well, there's a certain election happening on Tuesday... The time is now for cheap set-top boxesReview: Roku's new $30 player is more intriguing than its high-end siblings The Roku Express is a streaming marvel thanks to its low price. If you can live with some speed issues, it's perfect for bringing streaming video to screens all over your house -- and could well be your first set-top box.

Google I/O: Android N goes beta and here's what's new


Also: Google plays social catch-up (again) with Allo, Duo, revamped digital assistant Google unveils Google Home, takes aim at Amazon Echo Google I/O keynote: By the numbers CNET: Android Wear 2.0 coming this fall with smarter messaging, smarter fitness and better battery life Android is focusing on performance, low latency and a system UI that can be used for virtual reality. Android's just in time runtime enables apps to be installed 75 percent faster than the previous version and cuts their size by 50 percent. Android has also added Google Play Security Testing, an App Security Improvement Program as well as a safe browsing. Google also added two new window modes, picture in picture and split screen.

Google I/O 2016 Preview: Machine Learning, Virtual Reality And Android N - ARC


Google, as it normally does, has organized I/O around three distinct categories: development, monetization and the future. The conference will have 190 sessions for developers to learn how to make fast and efficient Web apps, optimize Android development and learn about the tools and features that will progressively make the Internet a more intelligent place. The biggest news on the machine learning front at Google I/O will be around Project Tango, a machine vision framework that allows smartphones to sees what is in front of them and let software react to it. ARC will be at Google I/O 2016 covering everything that matters to people who build software for a living and people who make a living with software.

The hottest new technologies are coming to cars


Many of these advancements are being driven by the interest in what's called ADAS (Advanced Driver Assistance Systems), the technology that will eventually lead to self-driving cars. The multiple cameras, LIDAR and other sensors being integrated into new models serve as inputs to sophisticated neural networks that are running inside the car. From more sophisticated entertainment features to better displays to more reliable connectivity, tech performance has largely overtaken driving performance for many modern buyers. USA TODAY columnist Bob O'Donnell is president and chief analyst of TECHnalysis Research, a market research and consulting firm that provides strategic consulting and market research services to the technology industry and professional financial community.

Gamasutra: Kain Shin's Blog - Optimizing AI for The Magic Circle


HAZARD AVOIDANCE Creatures avoid zap walls unless they have lightning rod. So having another human manually place hint volumes around hazards and set its data properly was not an option we wanted to explore. The cost of this startup evaluation was negligible compared to the noticeable performance gain in areas away from the lava river in Overworld. OPTIMIZATIONS NOT DONE Some potential optimizations were considered, but ultimately not done... Cliff Edge Detection In addition to avoiding hazards, creatures avoid cliff edges, which also involve multiple raycasts.

MIT researchers build energy-friendly chip to perform powerful AI tasks


A team of US researchers has built an energy-friendly chip that can perform powerful artificial intelligence (AI) tasks, enabling future mobile devices to implement "neural networks" modelled on the human brain. It is 10 times as efficient as a mobile GPU (Graphics Processing Unit) so it could enable mobile devices to run powerful AI algorithms locally rather than uploading data to the internet for processing. With powerful AI algorithms on board, networked devices could make important decisions locally, entrusting only their conclusions, rather than raw personal data, to the internet. At the conference, the MIT researchers used "Eyeriss" to implement a neural network that performs an image-recognition task.