I support research funding at all levels, and have nothing against mostly theoretical research, but is it really the best use of resources to throw $1 billion at reinforcement learning without any similar investments into addressing mass unemployment and wealth inequality (both of which are well-documented to cause political instability), how existing gender and racial biases are being encoded in our algorithms, and on how to best get this technology into the hands of people working on high impact areas like medicine and agriculture around the world?
Not quite my field, but perhaps such currently intractable, high-impact societal and medical problems do require theoretical breakthroughs after all... I guess I'm just concerned Rachel that --to put it in reinforcement learning terms-- we need both exploration and exploitation.