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.
While this reality has become more tangible in recent years through consumer technology, such as Amazon's Alexa or Apple's Siri, the applications of AI software are already widespread, ranging from credit card fraud detection at VISA to payload scheduling operations at NASA to insider trading surveillance on the NASDAQ. Broadly defined as the imitation of human cognition by a machine, recent interest in AI has been driven by advances in machine learning, in which computer algorithms learn from data without human direction.1 Most sophisticated processes that involve some form of prediction generated from a large data set use this type of AI, including image recognition, web-search, speech-to-text language processing, and e-commerce product recommendations.2 AI is increasingly incorporated into devices that consumers keep with them at all times, such as smartphones, and powers consumer technologies on the horizon, such as self-driving cars. And there is anticipation that these advances will continue to accelerate: a recent survey of leading AI researchers predicted that, within the next 10 years, AI will outperform humans in transcribing speech, translating languages, and driving a truck.3
The adversarial vulnerability  of deep neural nets (DNNs) threatens their applicability in security critical tasks, e.g., autonomous cars , robotics , DNN-based malware detection systems [21, 8]. Since the pioneering work by Szegedy et al. , many advanced adversarial attack schemes have been devised to generate imperceptible perturbations to sufficiently fool the DNNs [7, 20, 6, 30, 12, 3]. And not only are adversarial attacks successful in white-box attacks, i.e. when the adversary has access to the DNN parameters, but attacks are also successful in black-box attacks, i.e. it has no access to the parameters. Black-box attacks are successful because one can perturb an image so it misclassifies on one DNN, and the same perturbed image also has a significant chance to be misclassified by another DNN; this is known as transferability of adversarial examples . Due to the transferability of adversarial examples, it is very easy to attack neural nets in a black-box fashion [15, 5]. In fact, there exist universal perturbations that can imperceptibly perturb any image and cause misclassification for any given network . There is much recent research on designing advanced adversarial attacks and defending against adversarial perturbation.
It's hard to remember the days when artificial intelligence seemed like an intangible, futuristic concept. This has been decades in the making, however, and the past 90 years have seen both renaissances and winters for the field of study. At present, AI is launching a persistent infiltration into our personal lives with the rise of self-driving cars and intelligent personal assistants. In the enterprise, we likewise see AI rearing its head in adaptive marketing and cybersecurity. The rise of AI is exciting, but people often throw the term around in an attempt to win buzzword bingo, rather than to accurately reflect technological capabilities.
Drones are flown at a training class in Las Vegas in anticipation of new regulations allowing their commercial use. Drones are flown at a training class in Las Vegas in anticipation of new regulations allowing their commercial use. We are in "one of the most dramatic periods of change in the history of transportation," says Transportation Secretary Anthony Foxx. He was talking about all of it: the self-driving cars, the smart-city movement, the maritime innovations. The Federal Aviation Administration expects some 600,000 drones to be used commercially within a year.