AI with AI
Episode 4.24: The Earth Dies Dreaming
Andy and Dave discuss the latest in AI news, including a letter from the National Transportation Safety Board that asks the National Highway Traffic Safety Administration to regulate more strictly autonomous vehicles and driver assistance technologies; of note, the letter also uses Tesla as an example, stating that the company is using its customers to beta test its full self-driving technology on public roads. KMPG surveys business leaders on a variety of AI-related topics and finds that, among other things, many more leaders have the perception that AI tech is moving out too quickly. Researchers at Aston University announce a three-year study to explore the utility of human brain stem cells grown on a microchip, a so-called Neu-ChiP. Researchers from Norway and Australia unveil DyRET, a quadruped robot that can adapt its morphology (such as growing taller or shorter) as it encounters different environments. And Japanese researchers describe a decoded neurofeedback (DecNef) method, which uses fMRI to visualize brain activity and then calculate the similarity between real-time brain activity and brain activity patterns corresponding to specific pre-established memory and mental states. Microsoft’s PowerPoint has a Presenter Coach that will listen and watch your presentation and give you pointers on speech patterns, pacing, attention, body language, and other attributes. The two main research items both involve AI agents playing in the Atari Learning Environment (57 games from Atari’s library), and both with groundbreaking results in different ways: Uber AI and OpenAI use a model-free approach in Go-Explore, which uses a concept of “first return (to previous states), and then explore; GoogleAI use a world model approach with DreamerV2, which learns behaviors inside a separately trained world model (they also recommend a “clipped record mean” to aggregate scores across the various games). The survey of the week looks at Deepfakes Generation & Detection. Marjorie McShane and Sergei Nirenburg publish Linguistics for the Age of AI, arguing that researchers must place linguistics front and center for machines to achieve human-level language understanding, with big data and stats approaches as contributing methods. And in the video of the week, Steven Gouveia has produced a documentary on The Age of AI.