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:
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Why inference is becoming the dominant cost and performance bottleneck in AI
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How Cerebras’ wafer-scale architecture overcomes GPU memory and communication limits
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What it takes to compete with incumbents like NVIDIA and AMD as a new chip company
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The tradeoffs between training and inference at scale
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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.
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