A decentralized AI inference network built on: (1) edge computing nodes (e.g., 'Run this model on your GPU for $0.01/1K tokens'), (2) a marketplace for uncensored models (e.g., 'Host Llama 3 in India without Meta’s filters'), (3) sodium-ion battery-powered micro data centers (GM tech) for off-grid nodes, and (4) tokenized incentives (e.g., 'Earn tokens for sharing GPU compute'). Target Web3 projects first (e.g., 'Generate 10,000 NFT avatars locally'), then enterprises (e.g., 'Run your chatbot in India without latency').

Web3 projects, AI startups, and enterprises in emerging markets (India, Southeast Asia, Africa) AI inference is centralized (AWS, Google Cloud, Meta), making it: (1) expensive ($0.50–$2 per 1K tokens), (2) latency-heavy (200–500ms for Indian users), and (3) censored (e.g., Meta’s India data center may block 'sensitive' prompts). Meanwhile, GM’s sodium-ion batteries hint at decentralized energy solutions for edge AI. Web3 projects need: (1) cheaper inference, (2) uncensored models, and (3) local data sovereignty (e.g., 'Don’t send my prompts to US servers'). Startups in India pay 3–5x more for AI inference vs. US-based competitors. Web3 projects burn $10K–$100K/month on centralized API calls.