Deep neural networks and other modern machine learning models are often susceptible to adversarial attacks. Indeed, an adversary may often be able to change a model's prediction through a small, directed perturbation of the model's input - an issue in safety-critical applications. Adversarially robust machine learning is usually based on a minmax optimisation problem that minimises the machine learning loss under maximisation-based adversarial attacks. In this work, we study adversaries that determine their attack using a Bayesian statistical approach rather than maximisation. The resulting Bayesian adversarial robustness problem is a relaxation of the usual minmax problem. To solve this problem, we propose Abram - a continuous-time particle system that shall approximate the gradient flow corresponding to the underlying learning problem. We show that Abram approximates a McKean-Vlasov process and justify the use of Abram by giving assumptions under which the McKean-Vlasov process finds the minimiser of the Bayesian adversarial robustness problem. We discuss two ways to discretise Abram and show its suitability in benchmark adversarial deep learning experiments.

Founder and CEO of tech platform Gloo Scott Beck tells'Fox & Friends Weekend' that God'allowed' AI to exist and have its convergence with faith. We tend to view progress as (1) inevitable, (2) necessary, and (3) good for everyone. It is inevitable, in part, because we must have new ideas and tools at our disposal to address emerging challenges. Progress is necessary because without it we may become incapable of surviving (or being comfortable) in a broken world. It is good for everyone because its fruits make it easier to survive in the systems we have created. We, and we assume everyone else, are better off than we would be if forced to deal with the struggles of previous eras.

For example, Fetch AI, an AI and digital economics company, recently announced the appointment of Marcin Abram who them as a Machine Learning Scientist. Abram completed his PhD in Theoretical Physics in 2016 and his doctoral research explored topics on coherence and emergent behaviour in quantum systems. Another key appointment was of Dr Sebastian Seung was by Samsung Electronics to bolster the AI R&D and bring a revolutionary business impact. An eminent computational neuroscientist, Dr Seung originally studied theoretical physics at Harvard. He has worked as a researcher at Bell Labs and a professor at the Massachusetts Institute of Technology (MIT).

TED program represents the Army's first successful The Gulf War confirmed that the Abrams tank epitomizes lethality and survivability on today's battlefield. Logistically, however, the negative corollary is that the Abrams is expensive to operate, support, and maintain. Central to these costs is the maintenance of its turbine engine. Maintenance on the Abrams engine is accomplished at three levels: (1) organizational, (2) direct support, and (3) depot. Depot is usually in the United States.

In the two-plus months since the creation of open-source drivers for Microsoft's Kinect made it possible to hack the popular motion controller, the device has been used as a sophisticated piano, to add voice control to popular video games, to create 3D renderings of a car's path, and even for a demo of soft-core porn. Indeed, the open-source tools have snatched control of the device from Microsoft's proprietary hands, and each new day sees the emergence of some new kind of Kinect hack. But as the community of techies investing time in these types of imaginative--and unauthorized--works grows and each new hack pushes the envelope a little more, it's natural to wonder just how far hackers can go. What are, in other words, the outer limits of Kinect hacking? "I truly believe that those who [say] that the sky is the limit [have] limited imagination," said Kristoffer Risanger, the founder of a site called Kinect Hacks that aggregates the latest efforts by the fledging community to do things with the device that Microsoft never intended.