Amica Conference:
Thermodynamic Approaches to Artificial Intelligence

The Amica Conference: Thermodynamic Approaches to Artificial Intelligence seeks to foster interdisciplinary dialogue on the foundational ties between AI and thermodynamics. On the physics side, stochastic thermodynamics has provided a powerful framework for clarifying the relationship between information and energy, while on the AI side, modern generative models—including the diffusion model—have drawn inspiration from thermodynamics and statistical physics. By hosting a small, focused gathering of leading researchers, the conference aims to illuminate emerging methodologies and chart new directions for research at the intersection of statistical physics and machine learning.

Date: 9–11 March 2026
Place: Karuizawa, Japan
Invitation-only
Venue
The venue, DAIKIN AMICA KARUIZAWA, is a comfortable facility in Karuizawa, provided by Daikin Industries, Ltd.
Exterior view of Amica in Karuizawa
Interior view or conference room at Amica
Agenda & Abstracts
A detailed schedule including abstracts is provided as a PDF.
Download Agenda & Abstracts (PDF)
Invited Speakers
SueYeon Chung
Harvard University
Gavin Crooks
Normal Computing
Marco Cuturi
Apple ML Research
Massimiliano Esposito
University of Luxembourg
Christopher Jarzynski
University of Maryland
Daisuke Okanohara
Preferred Networks
Hirosi Ooguri
Caltech / The University of Tokyo
Jascha Sohl-Dickstein
Anthropic
Taiji Suzuki
The University of Tokyo
Max Welling
University of Amsterdam / CuspAI
David Wolpert
Santa Fe Institute
Lenka Zdeborova
EPFL
Special Participants
Makoto Gonokami
President of RIKEN
Ichiro Sakata
The University of Tokyo / RIKEN / DAIKIN
Organizers
The University of Tokyo RIKEN Daikin Industries, Ltd.
Takahiro Sagawa (Chair)
The University of Tokyo
Ryusuke Hamazaki (Co-chair)
RIKEN
Yoshiyuki Kabashima
The University of Tokyo
Masashi Sugiyama
RIKEN / The University of Tokyo
Yuto Ashida
The University of Tokyo
Sosuke Ito
The University of Tokyo
Kyogo Kawaguchi
The University of Tokyo / RIKEN
Asuka Takatsu
The University of Tokyo / RIKEN
Student Participants
Shang-Fu Wei
The University of Tokyo
Satoshi Yoshida
The University of Tokyo