Beginner Lessons

AI Safety and Reliability // Petar Tsankov // MLOps podcast #218 clip

Fine Tuning Llamas // Kai Davenport // AI in Production Lightning Talk

Productionizing Health Insurance Appeal Generation // Holden Karau // AI in Production Talk

Graduating from Proprietary to Open Source Models in Production // Philip Kiely // AI in Production

Designing ML Infra for ML & LLM Use Cases // Amritha Arun Babu & Abhik Choudhury // Podcast #221

Expressing Data Desires through Vectors // Daniel Svonava // MLOps podcast #214 clip

4 Years of the MLOps Community // Demetrios Brinkmann // MLOps Podcast #220

Model Merging and Mixtures of Experts // Maxime Labonne // AI in Production Conference

A Decade of AI Safety and Trust // Petar Tsankov // MLOps Podcast #218

LLM Use Cases in Production // AI in Production Conference // Panel 1

Challenging Big Data Assumptions // Hannes Mühleisen & Jordan Tigani // MLOps Podcast #202 clip

PDF Parsing and Value Chain Analysis // Paco Nathan // MLOps Podcast #201 clip

Practical Approach to ML and AI System Design // Nathan Ryan Frank // MLOps Podcast #199 clip

Small Data, Big Impact: The Story Behind DuckDB // Hannes Mühleisen & Jordan Tigani // Podcast #202

Language, Graphs, and AI in Industry // Paco Nathan // MLOps Podcast #201

Evaluating Tech Tools for Product Development // Nick Hasty // MLOps Podcast #198 clip

Evolution of ML Engineering and Automation // Niels Bantilan // MLOps Podcast clip #197

Challenges Operationalizing ML (And Some Solutions) // Nathan Ryan Frank // MLOps Podcast #199

Inferring Creativity // Nick Hasty // MLOps Podcast #198

The Role of Infrastructure in ML Leveraging Open Source // Niels Bantilan // MLOps Podcast #197

[Exclusive] Weights & Biases Round-table // Model Management in a Regulated Environment