What Happens When the Cost of Intelligence Drops 100x
The article explores the economic shift in AI development, moving from a focus on model capability to the importance of cost-efficiency for high-volume tasks. It argues that reducing the cost of intelligence by 100x will unlock new use cases that were previously budget-prohibitive.
Why it matters
Lowering the cost of AI inference is critical for scaling automation in research, data analysis, and enterprise workflows.
All posts What Happens When the Cost of Intelligence Drops 100x August 19, 2026 · 14 min read · By Benjamin Dichter
Progress in large language models is usually reported as what the best model can now do that no model could do before. That is the direction that produces headlines, and it has indeed been truly incredible. Each step up at the top of the range lets a model handle a kind of task that was previously out of reach, whether that is fixing a bug that spans a whole codebase or, lately, making progress on outstanding mathematical problems that had not been solved by anyone.
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