Sovereign AI
summary
Argues that countries can build practical, cost‑effective sovereign AI by combining reference architectures, software and accelerated hardware rather than mystique or massive bespoke R&D. Claims 193 nations surveyed, 70 countries with full strategy, and shows units of compute shifting from thousands of CPU servers to two GPU servers for the same workload. Describes deployed blueprints: Sweden’s AI factory and Swedish LLM, Japan/Taiwan in‑country inference stacks, and India using retrieval‑augmented generation for courts handling 50,000 higher‑court daily cases with NVIDIA inference microservices.
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chapters (10)
- 0:00Introduction
- 3:38AI landscape and strategies
- 6:25Building AI Nations stack
- 9:55AI factories' role
- 12:24Energy efficiency in AI
- 17:03Case studies: Japan, Taiwan, Sweden
- 19:55France’s AI startups
- 21:42India’s judicial RAG
- 24:34Best practices for governments
- 25:46Q&A
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