NeuroMetrix, makers of a pain-relief device called "Quell," are using AI in a simple form already, but it plans to integrate neural networks going forward to increase and improve the product's functions, according to CEO Shai Gozani.
MIT researchers used Bayesian inference, a form of AI, to make computer programs write new programs designed especially for data analysis. The premise is to ease the burden for data scientists who aren't also AI experts themselves.
Qualcomm's president, Cristiano Amon, took some time at the Consumer Electronics Show to discuss how 5G cellular will amaze consumers. He also reflected on how AI processing on smartphones will become more prevalent.
Cars on the road know little about drivers and passengers today -- except maybe whether the person at the wheel is drowsy. Tomorrow's vehicle will have a total awareness of the cabin, claims AI startup Eyeris, using multiple cameras and convolutional neural networks.
Jeff Green, chief executive of advertising industry giant The Trade Desk, says a thoughtful use of AI can free up people do to what humans do best: be creative and connect with other people.
Jensen Huang, fonder and CEO of computer graphics chip maker Nvidia, showed off the achievements of his company’s neural network technology during a press conference Sunday night in Las Vegas at the Consumer Electronics Show. He argues that a combination of deep learning and ray tracing, the simulation of real-world physics, is going to totally transform the computer graphics business.
A slew of recent research finds all kinds of ways to improve neural networks, from compressing the math needed to compute network weights to reducing data bandwidth to contemplating novel distributed computing systems.
Facebook has a whole set of internal tools to try and optimize its neural networks to run on mobile devices. Still, the company finds it difficult to navigate a smartphone market that is byzantine in its complexity, with thousands of different chipsets, most of poor performance, and software stacks that aren't quite up to the job.
Researchers at Google's AI labs created a couple of novel neural networks that can succeed in navigating Web forms, such as an online flight-booking site. Although baby steps at the moment, the program succeeds as well or better than some models trained using human demonstrations of pointing and clicking.
A machine learning researcher at Virginia Tech proposes a way to vet papers in AI by the look of the text and graphics in the document. Is its ability to gauge the "gestalt" of winning research enough to speed up the peer-review process?