The Center for Philosophy of Science at the University of Pittsburgh
invites you to join us for our 65th Annual Lecture Series Talks. All
lectures will be held in room 1008 in the Cathedral of Learning (10th
Floor) at 3:30pm EDT.  If you can't join us in person  please visit our
live stream on YouTube at
https://www.youtube.com/channel/UCrRp47ZMXD7NXO3a9Gyh2sg.

The Annual Lecture Series, the Center’s oldest program, was established in
1960, the year when Adolf Grünbaum founded the Center. Each year the series
consists of six lectures, about three quarters of which are given by
philosophers, historians, and scientists from other universities.



*Thomas Ryckman*

Stanford University

Friday, September 27  @ 3:30 pm - 6:00 pm EDT

*Title: Niels Bohr: Transcendental Physicist*

*Abstract:*

While it would be unwarranted to label Bohr as “neo-Kantian” or indeed
adherent of any philosophical school, his understanding of quantum theory
crucially employs an intricate transcendental argument. Bohr deemed the
quantum postulate, or “wholeness” of interaction between agency of
measurement and atomic system, to call into question a core epistemological
distinction between subject and object familiar in the concept of
‘observation’ from everyday life and classical physics. Re-conceptualizing
that distinction led to redefinition of the term ‘phenomenon’, a
corresponding non-representationalist account of the wave function, and to
situating the notion of objectivity within “conditions of the possibility
of unambiguous communication”.



*Colin Klein*

Australian National University

Friday, October 11th  @ 3:30 pm - 6:00 pm EDT

*Title: Transformers, Representational Structure, and the Language of
Thought*

*Abstract:*

Transformers are an extraordinarily powerful computational architecture,
applicable across a range of domains. They are, notably,  the computational
foundation of contemporary Large Language Models (LLMs).  LLMs’ facility
with language have led many to draw analogies between LLMs and human
cognitive processing. Drawing out the consequences of what seems like an
innocuous step—the need for positional encoding of the input to LLMs—I
argue that transformers are broad precisely because they have so little
built-in representational structure. This naturally raises questions about
the need for structured representations and what (if any) advantage they
might have over mere representation of structure. I develop this in
particular in the context of the contemporary revival of the Language of
Thought hypothesis.



*Melanie Mitchell*

Santa Fe Institute



Friday, November 22nd  @ 3:30 pm - 6:00 pm EDT



*Title: AI’s Challenge of Understanding the World*

*Abstract:*

I will survey a debate in the artificial intelligence (AI) research
community on the extent to which current AI systems can be said to
“understand” language and the physical and social situations language
encodes. I will describe arguments that have been made for and against such
understanding, hypothesize about what humanlike understanding entails, and
discuss what methods can be used to fairly evaluate understanding in AI
systems.


*A reception with light refreshments will follow each Talk in 1008 lounge
from 5-6pm.*

All lectures will be live streamed on YouTube at
https://www.youtube.com/channel/UCrRp47ZMXD7NXO3a9Gyh2sg.