The New AI Arms Race Is Systems Efficiency
By Abishek Balendran, Partner, SilverX Fund
AI progress is no longer primarily a model capability race. It has become a full-stack systems efficiency race — where competitive advantage is determined by how efficiently the entire inference stack (model, hardware, software, network, power) can be coordinated and deployed at scale.
Key Arguments
- Foundation model capabilities are converging across leading labs; the moat is shifting to deployment efficiency
- Inference cost optimization — through quantization, distillation, and specialized silicon — is becoming the primary competitive lever
- Systems-level AI companies (infra, tooling, optimization) will capture outsized value as the model layer commoditizes
- India's systems engineering talent — deep in networking, embedded systems, and semiconductor design — is uniquely positioned for this transition
Published by SilverX Fund Research. View all research