University of Cambridge > Talks.cam > Foundation AI > Large Language Models, Model Collapse, and the Conservation of Information

  Browse A-Z

Log in

Googledetails Microsoftdetails

🔐 Log In

Information on

Subscribing to talksdetails Finding a talkdetails Adding a talkdetails Disseminating talksdetails Help and Documentationdetails

ℹī¸ Information

Large Language Models, Model Collapse, and the Conservation of Information

Download to your calendar using vCal

If you have a question about this talk, please contact Pietro Lio .

LT1

Do Large Language Models (LLMs) think and reason? Are they perpetual information machines, producing endless coherent and correct text from finite training data? We explore how LLMs work and whether they produce rational thought and endless information. We show how theoretical considerations and experimental results from philosophy, statistics, information theory, and machine learning argue against the thesis that LLMs are rational, information-generating entities.

This talk is part of the Foundation AI series.

This talk is included in these lists:

Note that ex-directory lists are not shown.

Other lists

CEB Alumni Speaker Series Ca Meeting the Challenge of Healthy Ageing in the 21st Century

Other talks

title and abstract tba (joint seminar with Spectral Geometry in the Clouds) Spectral rigidity of random covers of compact hyperbolic surfaces LMB Seminar - Mechanisms of mRNA packaging and export Title to be confirmed Title TBC The Neurophenomenology of Surrender: Agency, Renewal, and Social Engagement in Speaking in Tongues
 

Š 2006-2025 Talks.cam, University of Cambridge. Contact Us | Help and Documentation | Privacy and Publicity