Neocortex Webinar Series

The Neocortex Seminar Series highlights real user projects, stories, and research running on Neocortex. The goals of the series are to:

    • Showcase successful Neocortex use cases and workflows
    • Foster community engagement among current and prospective users
    • Inspire broader and more effective usage of Neocortex
    • Set realistic expectations by focusing on what has been shown to work well on the CS‑3 system 

     

    Upcoming Seminars

    April Webinar – April 15, 2026, 2-3pm
    May Webinar – May 13, 2026, 2-3pm – Details forthcoming

    2026 Webinars

    Graphic: Physics-Aware AI at Scale: Neural Compression and Vision Transformers for Simulation Data; Jessica Ezemba, Carnegie Mellon University; April 15, 2026, 2pm ET

    Physics-Aware AI at Scale: Neural Compression and Vision Transformers for Simulation Data

    Date: April 15, 2026, 2pm – 3pm Eastern time

    Modern scientific computing generates terabyte-scale simulation data across physics domains, yet researchers lack efficient tools for storage, retrieval, and analysis. This work presents two complementary approaches to addressing this bottleneck, both leveraging wafer-scale computing on the Cerebras CS-3.

    Graphic: Sampling- and Estimation-based Strategies for Data Collection in<br />
Wafer-Scale Evolution Simulations; Matthew Andres Moreno, University of Michigan; March 5, 2026 | 2:00 PM ET<br />

    Sampling- and Estimation-based Strategies for Data Collection in Wafer-Scale Evolution Simulations

    Date: March 5, 2026, 2pm – 3pm Eastern time

    This talk will present technical and practical aspects of sampling- and estimation-based data collection strategies developed to support digital evolution on the Wafer-Scale Engine. At scale, these strategies enable the tracking of evolutionary history across trillions of simulated organisms in agent-based models. The talk will also review recent work migrating experiment and data management pipelines for general-purpose, SDK-based Wafer-Scale computing to the Cerebras Wafer-Scale Cloud.