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Why Hardware-Software Co-Design Is AI's Real 100x: Dylan Patel of SemiAnalysis, Sonic AI
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Why Hardware-Software Co-Design Is AI's Real 100x: Dylan Patel of SemiAnalysis
Sequoia Capital
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Jun 30, 2026
•
1:09:43
Interview
Why Hardware-Software Co-Design Is AI's Real 100x: Dylan Patel of SemiAnalysis
Shaun Maguire
(Sequoia)
•
Sonya Huang
(Host)
•
Dylan Patel
(Founder, SemiAnalysis)
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Executive Summary
The AI inference market is projected to become larger than the oil market, eventually accounting for multiple percentage points of global GDP, signaling a monumental economic shift.
AI's demand for energy is growing exponentially, with major labs expected to require over 100 gigawatts by 2030 and total inference demand reaching terawatts by 2040, creating immense challenges and opportunities in energy infrastructure.
The competitive landscape is defined by a hardware-software co-design arms race, with models from OpenAI and Anthropic/Google being optimized for different chip architectures (NVIDIA GPUs vs.
Google TPUs), challenging the idea of a single dominant platform.
A new ecosystem of specialized "neocloud" providers (e.g., CoreWeave, Crusoe) is emerging, challenging the dominance of traditional hyperscalers by offering more performant and specialized AI infrastructure, a trend actively encouraged by NVIDIA to create a more multipolar market.
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AI's Insatiable Demand for Compute and Power
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