#83 Dr. ANDREW LAMPINEN (Deepmind) - Natural Language, Symbols and Grounding [NEURIPS2022 UNPLUGGED]

First in our unplugged series live from #NeurIPS2022 We discuss natural language understanding, symbol meaning and grounding and Chomsky with Dr. Andrew Lampinen from DeepMind.  We recorded a LOT of material from NeurIPS, keep an eye out for the uploads.  YT version: https://youtu.be/46A-BcBbMnA References [Paul Cisek] Beyond the computer metaphor: Behaviour as interaction https://philpapers.org/rec/CISBTC Linguistic Competence (Chomsky reference) https://en.wikipedia.org/wiki/Linguistic_competence [Andrew Lampinen] Can language models handle recursively nested grammatical structures? A case study on comparing models and humans https://arxiv.org/abs/2210.15303 [Fodor et al] Connectionism and Cognitive Architecture: A Critical Analysis https://ruccs.rutgers.edu/images/personal-zenon-pylyshyn/proseminars/Proseminar13/ConnectionistArchitecture.pdf [Melanie Mitchell et al] The Debate Over Understanding in AI's Large Language Models https://arxiv.org/abs/2210.13966 [Gary Marcus] GPT-3, Bloviator: OpenAI’s language generator has no idea what it’s talking about https://www.technologyreview.com/2020/08/22/1007539/gpt3-openai-language-generator-artificial-intelligence-ai-opinion/ [Bender et al] On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? https://dl.acm.org/doi/10.1145/3442188.3445922 [Adam Santoro, Andrew Lampinen et al] Symbolic Behaviour in Artificial Intelligence https://arxiv.org/abs/2102.03406 [Ishita Dasgupta, Lampinen et al] Language models show human-like content effects on reasoning https://arxiv.org/abs/2207.07051 REACT - Synergizing Reasoning and Acting in Language Models https://arxiv.org/pdf/2210.03629.pdf https://ai.googleblog.com/2022/11/react-synergizing-reasoning-and-acting.html [Fabian Paischer] HELM - History Compression via Language Models in Reinforcement Learning https://ml-jku.github.io/blog/2022/helm/ https://arxiv.org/abs/2205.12258 [Laura Ruis] Large language models are not zero-shot communicators https://arxiv.org/pdf/2210.14986.pdf [Kumar] Using natural language and program abstractions to instill human inductive biases in machines https://arxiv.org/pdf/2205.11558.pdf Juho Kim https://juhokim.com/

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Welcome! We engage in fascinating discussions with pre-eminent figures in the AI field. Our flagship show covers current affairs in AI, cognitive science, neuroscience and philosophy of mind with in-depth analysis. Our approach is unrivalled in terms of scope and rigour – we believe in intellectual diversity in AI, and we touch on all of the main ideas in the field with the hype surgically removed. MLST is run by Tim Scarfe, Ph.D (https://www.linkedin.com/in/ecsquizor/) and features regular appearances from MIT Doctor of Philosophy Keith Duggar (https://www.linkedin.com/in/dr-keith-duggar/).