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Why Hyperscale AI Models Are Too Expensive for Most Use Cases
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Summary
John Bradshaw argues the economics of hyperscale AI models don't stack up for most enterprise use cases, and makes the case for domain-specific and small language models running closer to users — trading raw parameter count for cost efficiency, latency, and fit-for-purpose outcomes.
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