An interview with Amazon's AI chief Peter DeSantis on plans to use in-house chips, Trainium and Inferentia, to develop AI models more cheaply, and more
Amazon's new artificial intelligence czar, Peter DeSantis, is a larger-than-life figure within the company where he has worked since its early days
Context & Ripple Effects
Amazon’s chip strategy has been part of AWS’s generative-AI positioning since AWS discussed the role of AI chips ahead of re:Invent. DeSantis’s plan makes the cost of developing models—not only supplying cloud capacity—the immediate rationale for Trainium and Inferentia.
The strategy also rests on specialized engineering capability: an Amazon executive involved in Trainium and Inferentia later moved to Arm to work on its AI-chip effort, underscoring the value of this specialized chip-development talent. Subsequent reporting that Amazon is in talks to sell Trainium for third-party data centers suggests the chips could ultimately extend beyond AWS’s internal stack.
First-order effects
- Amazon can steer more of its model-development workloads toward Trainium and Inferentia, making its own silicon a direct lever on AI development costs.
- The move gives DeSantis’s AI organization a tighter link between model choices and the infrastructure designed to run them, rather than treating accelerators solely as externally sourced capacity.
Second-order effects
- AWS must make its proprietary chips competitive enough in software support and workload performance for internal teams to use them broadly; otherwise the promised cost advantage will be limited.
- A more credible internal deployment base strengthens AWS’s case to customers considering its AI infrastructure, while raising the competitive pressure on other cloud providers to pair AI services with differentiated hardware.
Third-order effects
- If hyperscalers increasingly design chips around their own model and cloud workloads, AI economics may depend more on vertically integrated hardware, software, and cloud operations than on access to a single merchant accelerator supplier.
- The later prospect of selling Trainium into third-party data centers points to a possible expansion from cloud-specific silicon to a broader infrastructure offering, though that depends on adoption outside Amazon’s own environment.
The trend: This is part of AI industrialization, in which cloud platforms use custom silicon to turn model training and inference costs into a strategic advantage.