VKR AI Research investigates the economics, evaluation, and infrastructure of useful AI systems.
The track studies the questions that determine where AI creates durable value: inference economics, evaluation quality, automation infrastructure, compute markets, and deployment risk.
Its standard is artifact-first. A good project should leave behind a technical memo, dataset, benchmark, market map, or reproducible tool that another serious reader can inspect.
Current working papers focus on useful-token economics and the verification bottlenecks that decide which AI work can be trusted and scaled.
Research Areas
Inference economics and pricing
Evaluation and benchmark design
Automation infrastructure
Compute markets
Deployment risk