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.
Announced at the Consumer Electronics Show (CES) in Las Vegas, BelleFox (www.bellefox.ai) is poised to revolutionize how families interact in this constantly connected world. The BelleFox Wi-Fi router is a unique technology that delivers not only reliability and fast speeds, but a host of features to help parents see and understand their children's online behavior -- and even to learn more about who their children are as individuals. The system uses Big Data and AI (artificial intelligence) to deliver its powerful, useful insights. "Children today are online natives, which can be extremely stressful for parents," stated Lily Li, co-founder of BelleFox. "Until now, family Wi-Fi systems simply offered ways to limit children's time and access to specific sites.
Just over five years ago, IBM's Watson supercomputer crushed opponents in the televised quiz show Jeopardy. It was hard to foresee then, but artificial intelligence is now permeating our daily lives. Since then, IBM has expanded the Watson brand to a cognitive computing package with hardware and software used to diagnose diseases, explore for oil and gas, run scientific computing models, and allow cars to drive autonomously. The company has now announced new AI hardware and software packages. The original Watson used advanced algorithms and natural language interfaces to find and narrate answers.
Serving more than a billion people a day, Facebook has its work cut out for it when providing customized news feeds. That is where the social network giant takes advantage of deep learning to serve up the most relevant news to its vast user base. Facebook is challenged with finding the best personalized content, Andrew Tulloch, Facebook software engineer, said at the company's recent @scale conference in Silicon Valley. "Over the past year, more and more, we've been applying deep learning techniques to a bunch of these underlying machine learning models that power what stories you see." Applying such concepts as neural networks, deep learning is used in production in event prediction, machine translation models, natural language understanding, and computer vision services. Event prediction, in particular, is one of the largest machine learning problems at Facebook, which must serve the top couple of stories out of thousands of possibilities for users, all in a few hundred milliseconds.
Using deep learning techniques, a group of researchers has trained a computer to recognise events in videos on YouTube -- even the ones the software has never seen before like riding a horse, baking cookies or eating at a restaurant. Researchers from Disney Research and Shanghai's Fudan University used both scene and object features from the video and enabled link between these visual elements and each type of event to be automatically determined by a machine-learning architecture known as neural network. "Notably, this approach not only works better than other methods in recognising events in videos, but is significantly better at identifying events that the computer programme has never or rarely encountered previously," said Leonid Sigal, senior research scientist at Disney Research. Automated techniques are essential for indexing, searching and analysing the incredible amount of video being created and uploaded daily to the Internet. "With multiple hours of video being uploaded to YouTube every second, there is no way to describe all of that content manually.