106 min listen
#107 - Dr. RAPHAËL MILLIÈRE - Linguistics, Theory of Mind, Grounding
#107 - Dr. RAPHAËL MILLIÈRE - Linguistics, Theory of Mind, Grounding
ratings:
Length:
104 minutes
Released:
Mar 13, 2023
Format:
Podcast episode
Description
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MLST Discord: https://discord.gg/aNPkGUQtc5
Dr. Raphaël Millière is the 2020 Robert A. Burt Presidential Scholar in Society and Neuroscience in the Center for Science and Society, and a Lecturer in the Philosophy Department at Columbia University. His research draws from his expertise in philosophy and cognitive science to explore the implications of recent progress in deep learning for models of human cognition, as well as various issues in ethics and aesthetics. He is also investigating what underlies the capacity to represent oneself as oneself at a fundamental level, in humans and non-human animals; as well as the role that self-representation plays in perception, action, and memory. In a world where technology is rapidly advancing, Dr. Millière is striving to gain a better understanding of how artificial neural networks work, and to establish fair and meaningful comparisons between humans and machines in various domains in order to shed light on the implications of artificial intelligence for our lives.
https://www.raphaelmilliere.com/
https://twitter.com/raphaelmilliere
TOC:
Intro to Raphael - 00:00:00
Intro: Moving Beyond Mimicry in Artificial Intelligence (Raphael Millière) - 00:01:18
Show Kick off - 00:07:10
LLMs - 00:08:37
Semantic Competence/Understanding - 00:18:28
Forming Analogies/JPG Compression Article - 00:30:17
Compositional Generalisation - 00:37:28
Systematicity - 00:47:08
Language of Thought - 00:51:28
Bigbench (Conceptual Combinations) - 00:57:37
Symbol Grounding - 01:11:13
World Models - 01:26:43
Theory of Mind - 01:30:57
YT: https://www.youtube.com/watch?v=fhn6ZtD6XeE
Refs (this is truncated, full list on YT video description):
Moving Beyond Mimicry in Artificial Intelligence (Raphael Millière)
https://nautil.us/moving-beyond-mimicry-in-artificial-intelligence-238504/
On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? ? (Bender et al)
https://dl.acm.org/doi/10.1145/3442188.3445922
ChatGPT Is a Blurry JPEG of the Web (Ted Chiang)
https://www.newyorker.com/tech/annals-of-technology/chatgpt-is-a-blurry-jpeg-of-the-web
The Debate Over Understanding in AI's Large Language Models (Melanie Mitchell)
https://arxiv.org/abs/2210.13966
Talking About Large Language Models (Murray Shanahan)
https://arxiv.org/abs/2212.03551
Climbing towards NLU: On Meaning, Form, and Understanding in the Age of Data (Bender)
https://aclanthology.org/2020.acl-main.463/
The symbol grounding problem (Stevan Harnad)
https://arxiv.org/html/cs/9906002
Why the Abstraction and Reasoning Corpus is interesting and important for AI (Mitchell)
https://aiguide.substack.com/p/why-the-abstraction-and-reasoning
Linguistic relativity (Sapir–Whorf hypothesis)
https://en.wikipedia.org/wiki/Linguistic_relativity
Cooperative principle (Grice's four maxims of conversation - quantity, quality, relation, and manner)
https://en.wikipedia.org/wiki/Cooperative_principle
MLST Discord: https://discord.gg/aNPkGUQtc5
Dr. Raphaël Millière is the 2020 Robert A. Burt Presidential Scholar in Society and Neuroscience in the Center for Science and Society, and a Lecturer in the Philosophy Department at Columbia University. His research draws from his expertise in philosophy and cognitive science to explore the implications of recent progress in deep learning for models of human cognition, as well as various issues in ethics and aesthetics. He is also investigating what underlies the capacity to represent oneself as oneself at a fundamental level, in humans and non-human animals; as well as the role that self-representation plays in perception, action, and memory. In a world where technology is rapidly advancing, Dr. Millière is striving to gain a better understanding of how artificial neural networks work, and to establish fair and meaningful comparisons between humans and machines in various domains in order to shed light on the implications of artificial intelligence for our lives.
https://www.raphaelmilliere.com/
https://twitter.com/raphaelmilliere
TOC:
Intro to Raphael - 00:00:00
Intro: Moving Beyond Mimicry in Artificial Intelligence (Raphael Millière) - 00:01:18
Show Kick off - 00:07:10
LLMs - 00:08:37
Semantic Competence/Understanding - 00:18:28
Forming Analogies/JPG Compression Article - 00:30:17
Compositional Generalisation - 00:37:28
Systematicity - 00:47:08
Language of Thought - 00:51:28
Bigbench (Conceptual Combinations) - 00:57:37
Symbol Grounding - 01:11:13
World Models - 01:26:43
Theory of Mind - 01:30:57
YT: https://www.youtube.com/watch?v=fhn6ZtD6XeE
Refs (this is truncated, full list on YT video description):
Moving Beyond Mimicry in Artificial Intelligence (Raphael Millière)
https://nautil.us/moving-beyond-mimicry-in-artificial-intelligence-238504/
On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? ? (Bender et al)
https://dl.acm.org/doi/10.1145/3442188.3445922
ChatGPT Is a Blurry JPEG of the Web (Ted Chiang)
https://www.newyorker.com/tech/annals-of-technology/chatgpt-is-a-blurry-jpeg-of-the-web
The Debate Over Understanding in AI's Large Language Models (Melanie Mitchell)
https://arxiv.org/abs/2210.13966
Talking About Large Language Models (Murray Shanahan)
https://arxiv.org/abs/2212.03551
Climbing towards NLU: On Meaning, Form, and Understanding in the Age of Data (Bender)
https://aclanthology.org/2020.acl-main.463/
The symbol grounding problem (Stevan Harnad)
https://arxiv.org/html/cs/9906002
Why the Abstraction and Reasoning Corpus is interesting and important for AI (Mitchell)
https://aiguide.substack.com/p/why-the-abstraction-and-reasoning
Linguistic relativity (Sapir–Whorf hypothesis)
https://en.wikipedia.org/wiki/Linguistic_relativity
Cooperative principle (Grice's four maxims of conversation - quantity, quality, relation, and manner)
https://en.wikipedia.org/wiki/Cooperative_principle
Released:
Mar 13, 2023
Format:
Podcast episode
Titles in the series (100)
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