Eye On A.I.
#165 Andy Hock: Will AI Revolutionize How We Do Business?
Episode guests
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Quick takeaways
- Cerebras Systems has developed a wafer-scale engine designed specifically for AI workloads, offering advantages in terms of memory bandwidth and communication bandwidth compared to clusters of small GPUs.
- Cerebras Systems has developed innovative cooling and power solutions for its wafer-scale engine, allowing it to be packaged in a dorm room refrigerator-sized device and cooled by facility air or water in data center environments.
Deep dives
Revolutionary Chip Architecture for Scaling AI Workloads
Cerebrous Systems has developed a wafer-scale engine, a square silicon chip that is the largest in the industry. This chip is designed specifically for AI workloads and can handle sparse, tensor-based linear algebra operations. It offers advantages in terms of memory bandwidth and communication bandwidth compared to clusters of small GPUs. The chip is being used to train large foundation models, including GPT models, and can run the whole model on a single machine. With its simple programming model, it eliminates the need for complex parallel programming and offers significantly faster training times. Cerebrous Systems is working towards making its chip accessible in both on-premises and cloud environments, with the goal of democratizing access to high-performance AI compute.
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