Reliability of large-scale AI systems due to the high failure rate of individual chips.
The risk of silent data corruption, where a chip produces incorrect results without failing completely.
The slowing performance improvement of general-purpose CPUs (approx. 5% per year), which necessitates costly specialization.
Opportunities Identified
Leveraging massive computational gains to accelerate scientific breakthroughs and enterprise workflows, potentially compressing 10 years of research into one.
Enabling the next wave of AI applications, the "agentic era," with specialized, low-latency inference hardware.
A predicted resurgence of general-purpose CPUs to orchestrate and manage complex AI agent workflows.
Continued gains from vertical integration and custom silicon, as demonstrated by customer Citadel achieving 2-4x efficiency improvements and 30% cost reduction.