ICNCE 2026

Abstract: This talk explores our success and failures with neuromorphic language models and their deployment on Intel Loihi 2. We have achieved the first billion parameter LLMs running on neuromorphic hardware at 2-watts, moving state-of-the-art reasoning from the datacenter to the edge. We have spent a painful amount of time working out when neuromorphic LLMs do and don't make sense, and our findings have flipped some of our assumptions about how sparsity should be used in these models.

Bio: Jason Eshraghian is an Assistant Professor and Fulbright Scholar in the Department of Electrical and Computer Engineering at the University of California, Santa Cruz. He is the developer of snnTorch, a Python library with over 500,000 downloads for training spiking neural networks. He is a dual-appointed IEEE CAS and EMBS Distinguished Lecturer, an Associate Editor of APL Machine Learning, the Chair of the IEEE Neural Systems and Applications Technical Committee, has been the recipient of seven IEEE Best Paper Awards, a Scientific Advisory Board Member of BrainChip, and leads the Neuromorphic Agents Team at Conscium.