Andrew Feldman, co-founder and CEO of Cerebras, joins us this week to discuss the Wafer Scale Engine, or WSE, an AI chip that is 50 times larger than the largest chips produced by Nvidia and Intel. This radical design has raised a lot of eyebrows and it is already being heralded as the biggest breakthrough in semi-conductor technology in decades. Andrew helps us unpack why AI work needs chips this large, how Cerebras was able to leapfrog industry incumbents, and what why the Wafer Scale Engine is the ideal AI training accelerator. Join us on this podcast as we talk with Andrew about some of the biggest hurdles that his team encountered on this market shifting journey.
Key Points From This Episode:
- A high-level description of the chip Cerebras has created and what makes it different.
- Why this size and level of the chip has eluded companies far larger than Cerebras.
- The path to the Wafer Scale Engine, starting with the founding of Cerebras.
- Understanding the system architecture of the Wafer Scale Engine.
- The relationship between Cerebras and TSMC, their fabrication partner.
- Choices that were ultimately made around size and particularly memory.
- Getting past the challenge of bottlenecks and bringing data onto a chip this size.
- Reasons startups like Cerebras are able to do things more cheaply than larger competitors.
- Examples of the power that this Wafer Scale Engine offers through its incredible flexibility
- Cerebras’ go-to-market strategy and Andrew’s thoughts on the size of the training market.
“Our guys are not afraid of invention and I think sometimes that’s not the incentive structure at large companies.” — @CerebrasSystems [0:07:01]
“We set out to be extraordinarily ambitious and that was in the system design, that was in the chip design and architecture. That was at every stage of our thinking.” — @CerebrasSystems [0:14:13]
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