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
