AI with AI
Episode 3.2: Newton & the 3-Body Problem
Andy and Dave discuss the AI-related supplemental report to the President’s Budget Request. The California governor signs a bill banning facial recognition use by the state’s law enforcement agencies. The 2019 Association of the US Army meeting focuses on AI. A DoD panel discussion explores the Promise and Risk of the AI Revolution. And the 3rd Annual DoD AI Industry Day will be 13 November in Silver Spring, MD. Researchers at the University of Edinburgh, the University of Cambridge, and Leiden University announce using a deep neural network to solve the chaotic 3-body problem, providing accurate solutions up to 100 million times faster than a state-of-the-art solver. Research from MIT uses a convolutional neural network to recover or recreate probable ensembles of dimensionally collapsed information (such as a video collapsing to one single image). Kate Crawford and Meredith Whittaker take a look at 2019 and the Growing Pushback Against Harmful AI. Air University Press releases AI, China, Russia, and the Global Order, edited by Nicholas Wright, with contributions from numerous authors, including Elsa Kania and Sam Bendett. Michael Stumborg from CNA pens a response to the National Security Commission’s request for ideas, on AI’s Long Data Tail. Deisenroth, Faisal, and Ong make their Mathematics for Machine Learning available. Melanie Mitchell pens AI: A Guide for Thinking Humans. An article in the New Yorker by John Seabrook examines the role of AI/ML in writing, with The Next Word. And the Allen Institute for AI updates its Semantic Scholar with now more than 175 million scientific papers across even more fields of research.