Andy and Dave discuss the latest in AI news and research, starting with a publication from the UK’s National Cyber Security Centre, providing a set of security principles for developers implementing machine learning models. Gartner publishes the 2022 update to its “AI Hype Cycle,” which qualitatively plots the position of various AI efforts along the “hype cycle.” PromptBase opens its doors, promising to provide users with better “prompts” for text-to-image generators (such as DALL-E) to generate “optimal images.” Researchers explore the properties of vanadium dioxide (VO2), which demonstrates volatile memory-like behavior under certain conditions. MetaAI announces a nascent ability to decode speech from a person’s brain activity, without surgery (using EEG and MEG). Unitree Robotics, a Chinese tech company, is producing its Aliengo robotic dog, which can carry up to 11 pounds and perform other actions. Researchers at the University of Geneva demonstrate that transformers can build world models with fewer samples, for example, able to generate “pixel perfect” predictions of Pong after 120 games of training. DeepMind AI demonstrates the ability to teach a team of agents to play soccer by controlling at the level of joint torques and combine it with longer-term goal-directed behavior, where the agents demonstrate jostling for the ball and other behaviors. Researchers at Urbana-Champaign and MIT demonstrate a Composable Diffusion model to tweak and improve the output of text-to-image transformers. Google Research publishes results on AudioLM, which generates “natural and coherent continuations” given short prompts. And Michael Cohen, Marcus Hutter, and Michael Osborne published a paper in AI Magazine, arguing that dire predictions about the threat of advanced AI may not have gone far enough in their warnings, offering a series of assumptions on which their arguments depend.
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