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METR’s new cost metric tests when AI agents stop being a bargain
Key Takeaways
- METR has introduced the “expenditure horizon” to compare the cost of AI agents and human labor on the same task.
- The framework combines labor, inference, and experimental compute into a single economic measure.
- In a NanoGPT speedrun case study, early results suggested human contributors can still be more cost-effective on harder improvements.
- The metric is designed to test practical value, not just whether an AI system can complete a benchmark.
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DT Editorial Team··via the-decoder.com
