Episode 22 March 23, 2018 Larry Lewis, Director of CNAs Center for Autonomy and AI, again sits in for Dave this week.
Research from the Stanford makes an empirical examination of bias and generalization in deep generative models, and Andy notes striking similarities to previously reported experiments in cognitive psychology.
In other stories, Andy and Dave discuss the AI-generated portrait that sold at a Christies auction for 432,500.
Government invests in its people and funds AI university courses with 115.Andy and Dave conclude with a discussion of why fruit flies are so awesome.Crifasi provides a fictional peek into a combat scenario involving.Next, Andy and Dave discuss a few adversarial attack-related topics: a single-pixel attack for fooling deep neural network (DNN) image classifiers; an Adversarial Robustness Toolbox from IBM Research Ireland, which provides an open-source software library to help researchers in defending DNN against adversarial attacks; and.And in the silliness of the week, a robot appears at a UK parliamentary meeting and talks to MPs about the future of AI in the classroom.Yaneer Bar-Yam makes a 2003 work, Dynamics of Complex Systems, available.Sparrow, Rob, Ethics as a source of law: the Martens Clause and autonomous weapons, icrc Blog, November 14 2017.
Dept of Defense drone spending for FY19 with FY18.
After a brief discussion on protein folding, they discuss the "AI Index which seeks to measure the evolution and advances in AI over time.OpeanAI, Berkley and Edinburgh research looks at curiosity-driven learning across 54 benchmark environments (including video games and physics engine simulations, showing that agents learn to play many Atari games without using any rewards, rally-making behavior emerging in two-player Pong, and others.They also discuss the introduction of probabilistic models to AI as a way for AI to "embrace uncertainty" and make better decisions (or perhaps doubt whether or not humans should spa ribeauvillé casino remain alive).Researchers create a memristor-based hybrid analog-digital computing platform to demonstrate deep-Q reinforcement learning.The group also discusses developments in the Russian civilian AI sector, as well as Russias intent to publish a civilian AI Roadmap by mid-year.Google Brain examines how well ImageNet architectures transfers to other tasks.PD uses geant casino vals pres le puy 43 three pioneering capabilities: data-driven speech writing and delivery, listening comprehension, and the ability to model human dilemmas.Darpa announces the Automating Scientific Knowledge Extraction (aske) project, with the lofty goal of building an AI tool that can automatically generate, test, and refine its own scientific hypotheses.Research casino jeux d argent en france from MIT, McGill and Masdar IST defines and visualizes skill sets required for various occupations, and how these contribute to a growing disparity between high- and low-wage occupations.Individual talks Zachary Lipton, Carnegie Mellon University: Troubling Trends in ML Scholarship Yann LeCun, Facebook AI Research/New York University: The Epistemology of Deep Learning Joelle Pineau, Facebook/McGill University: Reproducible, Reusable, and Robust Reinforcement Learning Shai Shalev-Shwartz, Hebrew University of Jerusalem: Surrogates Michael Collins, Google Research/Columbia.