https://video.ut0pia.org/videos/watch/be74d1be-9262-402f-ab16-0badbaf5414c Qwen 3 235B was asked for YouTube's year over year ad revenue growth from 2023 to 2024. It queried a table that didn't exist, tried again, got nothing back both times, and hallucinated an answer. The 4B model Snorkel finetuned with RL called get_table_name first, inspected the schema, ran a query, hit a column error, self-corrected, and got the right answer. The training run cost under $500. Kobe Crawford covers why tool discipline matters more than reasoning depth for this class of tasks, how single table training transferred cleanly to harder multi table problems (13.9% to 26.6% on the FinQA reasoning benchmark), and why breaking evals into rubrics helps identify which specific behavior to fix before writing any training data. Speaker info: https://www.linkedin.com/in/kobie-crawford, https://snorkel.ai/author/kobie-crawford/ Wed, 10 Jun 2026 21:03:37 GMT https://validator.w3.org/feed/docs/rss2.html PeerTube - https://video.ut0pia.org https://video.ut0pia.org/lazy-static/avatars/0287a09a-aae7-4840-9843-b416426e7046.webp https://video.ut0pia.org/videos/watch/be74d1be-9262-402f-ab16-0badbaf5414c All rights reserved, unless otherwise specified in the terms specified at https://video.ut0pia.org/about and potential licenses granted by each content's rightholder.