Browse 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

From MVP to Production // Day 2 Panel 2 // AI in Production Conference

RagSys: RAG is just RecSys in Disguise // Chang She // AI in Production Lightning Talk

Building a Python-Centric Feature Platform to Power Production AI Applications // Matt Bleifer

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

Data Engineering in the Federal Sector // Shane Morris // MLOps podcast #223

The State of Production Machine Learning in 2024 // Alejandro Saucedo // AI in Production

From Research to Production: Fine-Tuning & Aligning LLMs // Philipp Schmid // AI in Production

Vision Pipelines in Production: Serving & Optimisations // Biswaroop Bhattacharjee // AI in Prod

Navigating via Retrieval Evaluation to Demystify LLM Wonderland // Atita Arora // AI in Production

Charting LLMOps Odyssey // Yinxi Zhang @ Databricks // AI in Production Talk

Considerations of Data Quality // Anu Arora and Anass Bensrhir // MLOps podcast #216 clip

From Chatbot Creation to Ingestion Pipelines // Alex Volkov // MLOps Podcast #215 clip

What Business Stakeholders Want to See from the ML Teams // Peter Guagenti // MLOps Podcast #222

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

Building the Next Generation of Reliable AI // Shreya Rajpal // AI in Production Keynote

Anatomy of a Software 3.0 Company // Sarah Guo // AI in Production Keynote

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

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

Getting 50 people to comment on my shirt at Kubecon

The Art and Science of Training LLMs // Bandish Shah and Davis Blalock // MLOps Podcast #219

Kubecon Shirt Compliment Challenge

Hypothesis Testing and Stakeholder Collaboration // Alexandra Diem // MLOps Podcast #212 clip

Security and Privacy // Day 2 Panel 1 // AI in Production Conference

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

[Exclusive] Zilliz Roundtable // Why Purpose-built Vector Databases Matter for Your Use Case

Language Processing, Recommendations, System Integration // Aayush Mugdal // MLOps Podcast #211 clip

LLM Applications & Outcome Evaluation in the New Era // Aparna Dhinakaran // MLOps Podcast #210 clip

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

The Real E2E RAG Stack // Sam Bean // MLOps Podcast #217

Tecton's Approach to Scaling Data Aggregations // Mike Eastham // MLOps podcast #209 clip

Managing Data for Effective GenAI Application // Anu Arora and Anass Bensrhir // MLOps Podcast #216

Becoming an AI Evangelist // Alex Volkov // MLOps Podcast #215

A Survey of Production RAG Pain Points and Solutions // Jerry Liu // AI in Production Conference

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

Information Retrieval & Relevance // Daniel Svonava // MLOps Podcast #214

Evaluating and Integrating ML Models // Morgan McGuire and Anish Shah // MLOps Podcast #213

The AI Engineer Song

Data Governance and AI // Alexandra Diem // MLOps Podcast #212

DSPy: Understanding Stacking and Chaining Networks in Language Models // Omar Khattab

Prompt Templates the Song

Ads Ranking Evolution at Pinterest // Aayush Mudgal // MLOps Podcast #211

LLM Evaluation with Arize AI's Aparna Dhinakaran // MLOps Podcast #210

Mitigating LLM hallucinations paper breakdown

The Realistic Approach to MLOps // Jonathan Frankle // MLOps Podcast clip #205

Lightweight Feature Platform // Matt Bleifer & Mike Eastham // MLOps Podcast #209