Chips revolution: Cerebras talk on accelerating the future of machine learning

On behalf of our partner Cerebras, the EPFL Alumni cordially invite you to join us on Zoom on Wednesday March 2, from 18:00 to 19:00 (UTC+1) to learn more about Cerebras' activities through their presentation "Thinking Outside the Die: Architecting the Machine Learning Accelerator of the Future". The Cerebras team will be available until 19:30 to answer your questions and discuss further their activities or career opportunities.

Jean-Philippe Fricker: Co-founder and Chief System Architect at Cerebras Systems. He holds a MS in Electrical Engineering from EPFL.
Sean Lie: Co-founder and Chief Hardware Architect at Cerebras Systems. He holds a BS and MEng in Electrical Engineering and Computer Science from MIT.

Free registration here

About Cerebras:
Cerebras Systems is an American artificial intelligence company that builds computer systems for complex artificial intelligence deep learning applications. It was co-founded in 2015 by EPFL alumnus Jean-Philippe Fricker and four colleagues. In November 2021, Cerebras announced that it had raised an additional $250 million in Series F funding, valuing the company at over $4 billion.

Conference:
The compute and memory demands from state-of-the-art neural networks have increased several orders of magnitude in just the last couple of years, and there’s no end in sight. Traditional forms of scaling chip performance are necessary but far from sufficient to run the machine learning models of the future.

In this talk, we will explore the fundamental properties of neural networks and why they are not well served by traditional architectures. We will examine how co-design can relax the traditional boundaries between technologies and enable designs specialized for neural networks with new architectural capabilities and performance. We will explore this rich new design space using the Cerebras architecture as a case study, highlighting design principles and tradeoffs that enable the machine learning models of the future.