Dylan Patel, founder of SemiAnalysis, stated that AI inference will become one of the world’s largest markets, surpassing oil and accounting for several percentage points of global GDP. Patel expects that by 2030, the combined power demand of OpenAI and Anthropic will exceed 100 gigawatts. He believes the primary constraints lie in terrestrial energy costs and power infrastructure capacity, making the migration of compute to space inevitable. Patel noted that improvements in AI efficiency primarily stem from model-layer and cross-layer optimization, with DeepSeek’s expert models specifically optimized for NVIDIA’s Hopper architecture. He added that Jensen Huang’s support for emerging cloud providers aims to prevent hyperscale cloud vendors from monopolizing compute resources. InferenceX shows that inference costs are declining by approximately 60 times annually, while intelligence per watt is improving by about 40 times.
Dylan Patel Predicts AI Inference Market to Surpass Oil, with Long-Term Compute Shortage Expected
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Dylan Patel, founder of SemiAnalysis, predicts the AI inference market will surpass oil in economic impact, reaching several percentage points of global GDP by 2030. He estimates that OpenAI and Anthropic’s combined compute demand will reach 100 gigawatts, limited by energy costs and power capacity. Patel views space-based compute as inevitable. DeepSeek’s model is optimized for NVIDIA’s Hopper, and Huang is supporting new cloud providers to prevent monopolies. InferenceX data shows inference costs declining 60-fold annually, while intelligence per watt improves 40-fold. Traders monitoring altcoins to watch may find AI-driven trends influencing the Fear & Greed Index.
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