AI Engineer World's Fair 2024
Talks from AI Engineer World's Fair 2024, drafted from the AI Engineer channel's own playlists. Editorial metadata is best-effort parsed and under review.
Event 1
Track 9
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1 ↑4
Stop Making Models Bigger, Make Them Behave — Kobie Crawford, Snorkel
50.6K views 1.2K likes 72 comments
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2 ↑9
How to Construct Domain Specific LLM Evaluation Systems: Hamel Husain and Emil Sedgh
20.6K views 571 likes 8 comments
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3 ↑15
Lessons from the Trenches: Building LLM Evals That Work IRL: Aparna Dhinkaran
14.2K views 348 likes 9 comments
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4 ↑19
Why Eval++ Is the Next Great Compute Primitive — Sunil Pai & Matt Carey, Cloudflare
9.3K views 178 likes 14 comments
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5 ↑28
Self Driving Products: Product Signals to Pull Requests — Joshua Snyder, PostHog
5.9K views 135 likes 2 comments
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6 ↑34
Evals Are Broken, Use Them Anyway — Ara Khan, Cline
4.5K views 91 likes 3 comments
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7 ↑40
What It Actually Takes to Deploy GenAI Applications to Enterprises: Arjun Bansal and Trey Doig
3.6K views 53 likes 2 comments
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8 ↑40
How Zapier Builds AI Products and Features with the Help of Braintrust: Ankur Goyal & Olmo Maldonado
3.6K views 62 likes 4 comments
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9 ↑44
How agent o11y differs from traditional o11y — Phil Hetzel, Braintrust
3K views 46 likes 1 comments
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10 ↑49
Judging LLMs: Alex Volkov
2.4K views 60 likes 4 comments
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11 ↑58
The GenAI Maturity Curve or You Probably Don't Need Fine Tuning: Kyle Corbitt
1.7K views 37 likes 1 comments
