21:14
Your LLM Judge Is a Confident Liar: Building Better Verifiers — Browserbase
Miguel González Fernández · Corby Rosset
Evals · Agent engineering · Computer use
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AI Engineer topic
Fine-tuning — Page 3
Talks 97–106 of 106 AI Engineer conference talks about Fine-tuning.
AI Engineer World's Fair 202629:28
Parsing the Epstein Files for JMail — Palak Agarwal & Omar Alhait, Reducto
Palak Agarwal · Omar Alhait
Document understanding & OCR · Privacy & data governance · Data quality & curation
AI Engineer World's Fair 202626:41
Robot Demos Are Easy. Reliability Is Hard — Jason Ma, Dyna Robotics
Jason Ma
Robotics · Fine-tuning · Observability & reliability
AI Engineer NYC 2026 Online Talks15:21
Reliable, Smart Workflows for Finance, Wealth and Insurance — Karthic Rao, Perpetual
Karthic Rao
AI in finance · Agent orchestration · Safety & governance
13:46
GLM-5.2: Open Weights, Near-Frontier Intelligence — Zixuan Li, Z.ai
Zixuan Li
Coding agents · Agent engineering · Reasoning & test-time compute
AI Engineer World's Fair 202617:15
Small Models, Big Results: Training a Finance Agent for Under $500 — Charles Dickens, Snorkel AI
Charles Dickens
AI in finance · Fine-tuning · Synthetic data
AI Engineer World's Fair 202655:30
Teaching Agents to Search with NVIDIA Data Designer — Dhruv Nathawani, NVIDIA
Dhruv Nathawani
Synthetic data · Search & retrieval · MCP
AI Engineer World's Fair 202617:01
From 15% to 90% GPU Utilization: Fix the Data Pipeline, Not the Model
Tarun Sunkaraneni
Infrastructure & deployment · Inference · Fine-tuning
AI Engineer World's Fair 202647:25
Turning My Obsidian Vault Into a Local AI Engineer — Filip Makraduli, Superlinked
Filip Makraduli
Document understanding & OCR · MCP · Infrastructure & deployment
AI Engineer Code 202519:39
Z.ai GLM-4.6: What We Learned From 100 Million Open Source Downloads — Yuxuan Zhang, Z.ai
Yuxuan Zhang
Coding agents · Evals · Infrastructure & deployment