Inside Story of Building the World’s Largest AI Inference Chip

Discover how Cerebras is challenging NVIDIA with a fundamentally different approach to AI hardware and large-scale inference.

In this episode of Startup Project, Nataraj sits down with Andrew Feldman, co-founder and CEO of Cerebras Systems, to discuss how the company built a wafer-scale AI chip from first principles. Andrew shares the origin story of Cerebras, why they chose to rethink chip architecture entirely, and how system-level design decisions unlock new performance for modern AI workloads.

The conversation explores:

• Why inference is becoming the dominant cost and performance bottleneck in AI
• How Cerebras’ wafer-scale architecture overcomes GPU memory and communication limits
• What it takes to compete with incumbents like NVIDIA and AMD as a new chip company
• The tradeoffs between training and inference at scale
• Cerebras’ product strategy across systems, cloud offerings, and enterprise deployments

This episode is a deep dive into AI infrastructure, semiconductor architecture, and system-level design, and is especially relevant for builders, engineers, and leaders thinking about the future of AI compute.

 Listen to the full episode of Startup Project on YouTube or your favorite podcast platform.