Slides: Stop Making Models Bigger, Make Them Behave — Kobie Crawford, Snorkel
Source Video
Stop Making Models Bigger, Make Them Behave — Kobie Crawford, Snorkel
Relationship To World's Fair 2026
These slides are extracted from a public AI Engineer YouTube video connected to World's Fair 2026. Speaker-matched clips are supporting context unless later confirmed as exact session recordings; official livestream recordings are day-level/event-level source material.
Related Scheduled Sessions
- No individual scheduled session mapping has been assigned yet; treat this as an event livestream deck.
Extracted Slides

- Recreated text/layout view: open HTML recreation
- AI slide classifier:
title_cardconfidence0.98 - Text source: agent_vision.
Slide text:
Stop Making Models Bigger.
Make Them Behave
Making a 4B Model Outperform 235B on Tool Use for Financial Analysis
Kobie Crawford, Developer Advocate

- Recreated text/layout view: open HTML recreation
- AI slide classifier:
content_slideconfidence0.99 - Text source: agent_vision.
Slide text:
What we’ll cover
1 Research Objective
2 The Approach
3 The Result

- Recreated text/layout view: open HTML recreation
- AI slide classifier:
content_slideconfidence0.91 - Text source: agent_vision.
Slide text:
Qwen3 235B
FinQA Tool Use

- Recreated text/layout view: open HTML recreation
- AI slide classifier:
content_slideconfidence0.98 - Text source: advanced OCR
rapidocr-live/border-trim/opencv-adaptive. - OCR decision: ready — dense chart slide with small labels, percentages, and QR code
Slide text:
GLLM Snorke
AIE 4B + RL 59.7%
.
235B 51.4%
ACCURACY SCORE Pass@1 line (59.7%)
Engineering the future ofAl
Hidden Non-Slide Evidence
- `slide-001.jpg` —
speaker_stageconfidence0.97; stage photo with speaker and audience; projected slide is not a clean presentation frame - `slide-006.jpg` —
sponsor_logoconfidence0.96; closing logo/branding card, not a content slide
Classification audit: raw/sources/slide-ai-classification/slides/TNwJ1LMiENk/audit.json
Slide-Derived Subjects To Review
Subject extraction uses video title, related session titles/descriptions, transcript context, and OCR text when available. OCR is best-effort and should be reviewed against the embedded slide images.