Andy and Dave discuss the latest in AI and autonomy news and research, including an announcement that the Federal Trade Commission is exploring rules for cracking down on harmful commercial surveillance and lax data security, with the public having an opportunity to share input during a virtual public form on 8 September 2022. The Electronic Privacy Information Center (EPIC), with help from Caroline Kraczon, releases The State of State AI Policy, a catalog of AI-related bills that states and local governments have passed, introduced or failed during the 2021-2022 legislative season. In robotics, Xiaomi introduces CyberOne, a 5-foot 9-inch robot that can identify “85 types of environmental sounds and 45 classifications of human emotions.” Meanwhile at a recent Russian arms fair, Army-2022, a developer showed off a robot dog with a rocket-propelled grenade strapped to its back. NIST updates its AI Risk Management Framework to the second draft, making it available for review and comment. DARPA launches the SocialCyber project, a hybrid-AI project aimed at helping to protect the integrity of open-source code. BigScience launches BLOOM (BigScience Large Open-science Open-access Multilingual Language Model), a “bigger than GPT-3” multilanguage (46) model that a group of over 1,000 AI researchers has created, that anyone can download and tinker with it for free. Researchers at MIT develop artificial synapses that shuttle protons, resulting in synapses 10,000 times faster than biological ones. China’s Comprehensive National Science Center claims that it has developed “mind-reading AI” capable of measuring loyalty to the Chinese Communist Party. Researchers at the University of Sydney demonstrate that human brains are better at identifying deepfakes than people, by examining results directly from neural activity. Researchers at the University of Glasgow combine AI with human vision to see around corners, reconstructing 16x16-pixel images of simple objects that the observer could not directly see. GoogleAI publishes research on Minerva, using language models to solve quantitative reasoning problems, and dramatically increasing the SotA. Researchers from MIT, Columbia, Harvard, and Waterloo publish work on a neural network that solves, explains, and generates university math problems “at a human level.” CSET makes available the Country Activity Tracker for AI, an interactive tool on tech competitiveness and collaboration. And a group of researchers at Merced’s Cognitive and Information Sciences Program make available Neural Networks in Cognitive Science. https://www.cna.org/our-media/podcasts/ai-with-ai