A small AI model takes on Postgres query planning
Your database has a plan. Rohan Bansal trained a small AI model to find a better one—then tested whether its choices could make Postgres queries run faster.
The actual story.
Bansal describes an experiment using supervised fine-tuning and reinforcement learning to improve the query plans selected by a four-billion-parameter model. He reports a 44.7% latency reduction across 113 join-heavy benchmark queries. The work explores whether execution-time feedback can teach a small model to choose better plans. These are results from his experimental setup, not a guarantee of faster performance on every database or workload.
A small specialized model can be useful when its decisions can be tested against a concrete outcome.
Receipts, not rumors.
Read the original reporting: rohanbansal.com ↗
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