Date: April 13, 2026
Time: 18:00 – 19:30 Israel Time
Speaker: Prof. Jason Eshraghian, University of California, Santa Cruz
Language: English
Abstract
The brain is the perfect place to look for inspiration to develop more efficient neural networks. Inspired by the recurrent dynamics of biological neurons, this talk will present several frontier reasoning LLMs developed in my lab, from software to device deployments. Trained end-to-end in an academic lab on a full production pipeline (data curation, pre-training, to post-training and alignment) these models surpass all leading LLMs from Meta, Google and every other over-resourced company in the ~10-billion parameter regime, despite being ~5x smaller. We have deployed several of our models on neuromorphic hardware at 2-watts, bringing SoTA-level reasoning from the datacenter to the edge.
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.
The webinar is free, but registration is required. The Zoom link will be sent after registration.