On this episode, we’re joined by Andrew Feldman, Founder and CEO of Cerebras Systems. Andrew and the Cerebras team are responsible for building the largest-ever computer chip and the fastest AI-specific processor in the industry.

We discuss:

- The advantages of using large chips for AI work.

- Cerebras Systems’ process for building chips optimized for AI.

- Why traditional GPUs aren’t the optimal machines for AI work.

- Why efficiently distributing computing resources is a significant challenge for AI work.

- How much faster Cerebras Systems’ machines are than other processors on the market.

- Reasons why some ML-specific chip companies fail and what Cerebras does differently.

- Unique challenges for chip makers and hardware companies.

- Cooling and heat-transfer techniques for Cerebras machines.

- How Cerebras approaches building chips that will fit the needs of customers for years to come.

- Why the strategic vision for what data to collect for ML needs more discussion.

Resources:

Andrew Feldman - https://www.linkedin.com/in/andrewdfeldman/

Cerebras Systems - https://www.linkedin.com/company/cerebras-systems/

Cerebras Systems | Website - https://www.cerebras.net/

Thanks for listening to the Gradient Dissent podcast, brought to you by Weights & Biases. If you enjoyed this episode, please leave a review to help get the word out about the show. And be sure to subscribe so you never miss another insightful conversation.

#OCR #DeepLearning #AI #Modeling #ML