Scaling Data Science does not mean Scaling Machines
Summary: Argues that optimizing for machine-level scale and cloud compute cost misses key dimensions of scaling data science—usability and data scientist productivity. Shows this narrow focus yields unfamiliar tools and calls for user-centered metrics beyond raw compute/scale. (summarized by gpt-5-mini on Feb 09 2026)
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