In this episode, co-hosts Calum Chace and David Wood explore a number of recent developments in AI - developments that are rapidly changing what counts as "state of the art" in AI.00.05: Short recap of previous episodes00.20: A couple of Geoff Hinton stories02.27: Today's subject: the state of AI today02.53: Search03.35: Games03.58: Translation04.33: Maps05.33: Making the world understandable. Increasingly07.00: Transformers. Attention is all you need08.00: Masked language models08.18: GPT-2 and GPT-308.54: Parameters and synapses10.15: Foundation models produce much of the content on the internet10.40: Data is even more important than size11.45: Brittleness and transfer learning13.15: Do machines understand?14.05: Human understanding and stochastic parrots15.27: Chatbots16.22: Tay embarrasses Microsoft16.53: Blenderbot17.19: Far from AGI. LaMDA and Blaise Lemoine18.26: The value of anthropomorphising19.53: Automation20.25: Robotic Process Automation (RPA)20.55: Drug discovery21.45: New antibiotics. Discovering Halicin23.50: AI drug discovery as practiced by Insilico, Exscientia and others25.33: Eroom's Law26.34: AlphaFold. How 200m proteins fold28.30: Towards a complete model of the cell29.19: Analysis30.04: Air traffic controllers use only 10% of the data available to them30.36: Transfer learning can mitigate the escalating demand for compute power31.18: Next up: the short-term future of AIAudio engineering by Alexander Chace.Music: Spike Protein, by Koi Discovery, available under CC0 1.0 Public Domain DeclarationFor more about the podcast hosts, see https://calumchace.com/ and https://dw2blog.com/