Under the Hood of AI

Join NYU LPE, ACS, and Energy Law to ask the AI-related questions that should be on your mind: Where is artificial intelligence? Is it really worth trillions of dollars? Where are these investments going, and who decides what happens next? Finding solid answers will require taking a closer look at the layers of infrastructure that support large language models: GPUs, data centers, power utilities, and the financial flows funding it all.

Dive under the hood of AI with the authors of some of the best research on AI infrastructure from 2025: Advait Arun (“Bubble or Nothing”) and Eliza Martin (“Extracting Profits from the Public”). They will be joined by Nandan Kumar Jha, an NYU Ph.D. candidate in Electrical & Computing Engineering specializing in LLM systems.

Together they will delve into the AI industry’s explosive demands for computing infrastructure and explore the impacts of this buildout on local communities, natural resources, the financial economy, and the public at large.

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Lunch provided (please if you have any dietary restrictions or accessibility needs). Please register for a ticket to receive the exact room.

This event is open to the public. It will also be livestreamed via Zoom; please for the link.

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Advait Arun is Senior Associate for Capital Markets at the Center for Public Enterprise, in Washington, D.C. Advait is a climate finance and energy infrastructure analyst whose work focuses on identifying and addressing the barriers to mobilizing public and private finance toward the green transition. His project areas center on capital market and energy finance modeling. He formerly worked for the United States Treasury Department’s Office of Sustainable Infrastructure.

Eliza Martin is a former Legal Fellow at Harvard Law School’s Environmental & Energy Law Program. Eliza works on electricity and power sector issues. She received her J.D. from The University of Chicago Law School, where she was a member of the Abrams Environmental Law Clinic and interned for FERC Commissioner Allison Clements. Before attending law school Eliza worked for a member of the Texas House of Representatives and was a Thomas J. Watson Fellow.

Nandan Kumar Jha is a Ph.D. candidate in Electrical and Computer Engineering at New York University, where he researches the mathematical foundations of large language models (LLMs)—how information, geometry, and learning dynamics interact and shape the stability, efficiency, and scaling behavior of LLMs. In particular, his work explores designing and optimizing LLMs while preserving their representational integrity.

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The event cosponsors are the NYU Law & Political Economy Association, the American Constitution Society at NYU Law, and the Energy Committee of NYU Law's Environmental Law Society.

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