Uber has acquired Geometric Intelligence, a two-year-old artificial intelligence startup that vows to surpass the deep learning systems under development at internet giants like Google and Facebook. But as this tiny AI lab slips into Uber's increasingly vast and ambitious operation, the startup is still tight-lipped on what its technology actually looks like. Founded by New York University psychologist Gary Marcus and University of Cambridge professor of information engineering Zoubin Ghahramani, Geometric Intelligence spans thirteen other researchers culled from across the academic world. Fourteen of the startup's fifteen employees will move to San Francisco, where Uber is based, serving as the central AI lab for the ride-hailing company. Ghahramani, the mathematician most responsible for the startup's core technology, will remain at Cambridge while spending half his time working for Uber.
Intel CEO Brian Krzanich, BMW CEO Harald Krueger, and Mobileye CTO and cofounder Amnon Shashua pose after a press conference in Munich on July 1, 2016. Intel started making lots of noise about the autonomous car market last year. But it's a long slog getting into a market like automotive, where it can take years to get designed into a vehicle. On Monday, the chip giant announced it would just buy its way into the market with a $15.3 billion acquisition of Mobileye, a leading provider of advanced driver assistant systems based in Israel. A massive consolidation spree is sweeping the semiconductor industry.
Today at the Frankfurt motor show, one of the biggest and most prestigious motor shows in the world, Sheryl Sandberg, COO of Facebook, spoke before German Chancellor Angela Merkel. Now what is Facebook and most importantly, Sheryl Sandberg doing at an automotive industry event? The obvious answer that comes to mind when one relates Facebook and the car industry is the billions of advertising dollars the industry spends on marketing and advertising. However, that does not seem to be Facebook's game plan, as highlighted by Sheryl and shown at their pavilion. Facebook seems to have a strategy of leveraging its capabilities in social marketing, AR & VR and interestingly, who would have thought of it, leveraging its advanced AI and deep learning capabilities to support the development of autonomous vehicles.
End-to-end learning has recently emerged as a promising technique to tackle the problem of autonomous driving. Existing works show that learning a navigation policy from raw sensor data may reduce the system's reliance on external sensing systems, (e.g. GPS), and/or outperform traditional methods based on state estimation and planning. However, existing end-to-end methods generally trade off performance for safety, hindering their diffusion to real-life applications. For example, when confronted with an input which is radically different from the training data, end-to-end autonomous driving systems are likely to fail, compromising the safety of the vehicle. To detect such failure cases, this work proposes a general framework for uncertainty estimation which enables a policy trained end-to-end to predict not only action commands, but also a confidence about its own predictions. In contrast to previous works, our framework can be applied to any existing neural network and task, without the need to change the network's architecture or loss, or to train the network. In order to do so, we generate confidence levels by forward propagation of input and model uncertainties using Bayesian inference. We test our framework on the task of steering angle regression for an autonomous car, and compare our approach to existing methods with both qualitative and quantitative results on a real dataset. Finally, we show an interesting by-product of our framework: robustness against adversarial attacks.
The Consumer Electronics Show, one of the world's tentpole technology shows, is a flashy vehicle for the engineering underneath. In the world of chipsets, the show was dominated by Nvidia, one of many companies seeking to power the artificial intelligence in next-generation cars and image processors. There were also plenty of opportunities for component manufacturers to find places in the flashy new cars and fleets that dominated some of the show floors. Chipmakers and sensor manufacturers are also keeping an eye on what customers want in the automotive space. Just seven states – Nevada, California, Florida, Michigan, Hawaii, Washington, and Tennessee -- and the District of Columbia have passed bills related to autonomous driving.