CHM Live | The Great Chatbot Debate: Do LLMs Really Understand?

Описание: [Recorded March 25, 2025]
Chatbots based on large language models (LLMs), like ChatGPT, answer sophisticated questions, pass professional exams, analyze texts, generate everything from poems to computer programs, and more. But is there genuine understanding behind what LLMs can do? Do they really understand our world? Or, are they a triumph of mathematics and masses of data and calculations simulating true understanding?

Join CHM, in partnership with IEEE Spectrum, for a fundamental debate on the nature of today’s AI: Do LLMs demonstrate genuine understanding, the “sparks” of true intelligence, or are they “stochastic parrots,” lacking understanding and meaning?

FEATURED PARTICIPANTS
Speaker
Emily M. Bender
Professor of Linguistics, University of Washington

Emily M. Bender is a professor of linguistics and director of the Computational Linguistics Laboratory at the University of Washington, where she also serves as faculty director of the CLMS program, and adjunct professor at the School of Computer Science and Engineering and the Information School. Known for her critical perspectives on AI language models, notably coauthoring the paper "On the Dangers of Stochastic Parrots," Bender is also the author of the forthcoming book, The AI Con: How to Fight Big Tech's Hype and Create the Future We Want.


Speaker
Sébastien Bubeck
Member of Technical Staff, OpenAI

Sébastien Bubeck is a member of the technical staff at OpenAI. Previously, he served as VP, AI and distinguished scientist at Microsoft, where he spent a decade at Microsoft Research. Prior to that, he was an assistant professor at Princeton University. Bubeck's 2023 paper, "Sparks of Artificial General Intelligence: Early experiments with GPT-4," drove widespread discussion and debate about the evolution of AI both in the scientific community and mainstream media like the New York Times and Wired. Bubeck has been recognized with best paper awards at a number of conferences, and he is the author of the book Convex Optimization: Algorithms and Complexity.


Moderator
Eliza Strickland
Senior Editor, IEEE Spectrum

Eliza Strickland is a senior editor at IEEE Spectrum, where she covers artificial intelligence, biomedical technology, and other advanced technologies. In addition to her writing and editing work, she also hosts podcasts, creates radio segments, and moderates talks at events such as SXSW. Prior to joining IEEE Spectrum in 2011, she oversaw a daily science blog for Discover magazine and wrote for outlets including Wired, The New York Times, Sierra, and Foreign Policy. Strickland received her master’s degree in journalism from Columbia University.

Catalog Number: 300000014
Acquisition Number: 2025.0036