@MaximeRivest: If you pay for an LLM to do inference (which you pretty much always do), you should save any successful run; it is, by …

X AI KOLs Timeline News

Summary

Maxime Rivest argues that any successful paid LLM inference run should be saved, since it constitutes a valuable example dataset, a view echoed by Gal Elmalah who frames data as a future asset.

If you pay for an LLM to do inference (which you pretty much always do), you should save any successful run; it is, by definition, a valuable example dataset for you.
Original Article
View Cached Full Text

Cached at: 10/20/26, 07:36 AM

If you pay for an LLM to do inference (which you pretty much always do), you should save any successful run; it is, by definition, a valuable example dataset for you.

Gal Elmalah (@GalElmalah): This is pretty cool! Need to start thinking about my data as future asset

Similar Articles

Your LLM inference benchmark is lying to you

Reddit r/artificial

The article explains why synthetic benchmarks for LLM inference can be misleading, as production traffic is bursty and variable, and recommends testing with real workloads to choose the right inference framework.