What has to improve: accuracy, latency or the application itself?
Are you training a model, building an agent or putting software into a physical system? Compute is one part of the question. Research collaborators and a real application environment can matter just as much.
Capabilities to explore
- Model development, evaluation and inference
- AI agents and domain-specific software
- Compute architecture and workload optimisation
- Scientific and industrial application development
Compute services and a real application environment
Mentougou’s Jingxi Zhigu model-ecosystem service station is a published starting point for investigating domestic compute and model deployment support. For an AI team, the relevant comparison is the workload, software compatibility, engineering help and operating cost.
Beijing’s September innovation-voucher call also covers qualified compute services. Applicant eligibility, the service catalogue and remaining allocation determine whether support can be included in the budget. Tell Leo the workload or application problem; you can explore a project before deciding whether to establish locally.
What is blocking the next version?
Bring the workload, target behaviour and the constraint that matters: memory, inference cost, evaluation quality or integration with the real system.