Ex Machina's Scientific Advisor - Murray Shanahan

TL;DR

Murray Shanahan, scientific advisor for Ex Machina, recounts his career trajectory from classical AI (logic programming, the frame problem) through computational neuroscience to modern deep reinforcement learning at DeepMind.

Key insights

• Shanahan’s PhD thesis (1980s) focused on using logic programming (Prolog) to speed up queries by caching established relationships; he later abandoned classical AI around the turn of the millennium be
• The “frame problem” – how a system determines what is relevant and ignores the irrelevant – has recurred throughout his career: in symbolic AI, in understanding the brain, and now in deep reinforcemen
• Ex Machina writer/director Alex Garland contacted Shanahan after reading his book Embodiment and the Inner Life; the script was already 95% complete when Shanahan first saw it, and his scientific advi