Browse Lessons

Age of Industrialized AI // Dan Jeffries // LLMs in Production Conference

DevTools for Language Models: Unlocking the Future of AI-Driven Applications // Diego Oppenheimer

The Future of Scalability in Machine Learning: Predictions and Challenges

The Birth and Growth of Spark: An Open Source Success Story // Matei Zaharia // MLOps Podcast #155

Deep Learning in Google Maps

Scaling Algorithms with Machine Learning: A Google Engineer's Journey

Vector Databases and Large Language Models // Samuel Partee // LLMs in Production Conference

Challenges and Opportunities in Building Data Science Solutions with LLMs // QuantumBlack Roundtable

Want High Performing LLMs? Hint: It is All About Your Data // Vikram Chatterji // LLMs in Prod Con

Solving the Last Mile Problem of Foundation Models with Data-Centric AI //Alex Ratner // LLM in Prod

Declarative MLOps - Streamlining Model Serving on Kubernetes // Rahul Parundekar// MLOps Meetup #123

ML Scalability Challenges // Waleed Kadous // MLOps Podcast # 154

ML Evolution & Recurring Themes // Waleed Kadous // MLOps Podcast # 155 short clip

Formula for Successful Jupyter Notebook Deployment // Keith Trnka // MLOps Podcast #148 short clip

Tecton 0.6: Notebook-driven Development // Jason Dunne // MLOps Meetup #122

Code Modularization Techniques // Rodolfo Núñez // MLOps Podcast #153 short clip

Multilingual Programming and a Project Structure to Enable It // Rodolfo Núñez // MLOps Podcast #153

The Future of Data Science Teams: A World Without Data Teams?

Balancing Technical Debt and Future Thinking in Product Development

The Challenge of Dynamic AI Models in the Real World

Enabling Rapid Updates of Models: Parallels with Software and Security

Improving User Experience with YouChat Conversational Interface

How A Manager Became a Believer in DevOps for Machine Learning // Keith Trnka // MLOps Podcast #152

Addressing Latency Challenges in Large Language Models

Airflow Sucks for MLOps // Stephen Bailey // MLOps Podcast #141

The Trade-off between Lookup Efficiency and Accuracy in LLMs

Prioritizing Needs in ML Platform Design // Jean-Michel Daignan // MLOps Podcast #151 short clip

Evaluating Language Model Outputs: Beyond Grammar and Coherence

ML in Production: A DS from Ubisoft Perspective // Jean-Michel Daignan // MLOps Podcast #151

The Evolution of Foundation Models and the Complexity of Automation

Balancing the Benefits and Risks of Language Models

The Importance of Communication Skills in Customer-Facing Machine Learning Engineering

Ensuring Model Effectiveness in MLOps: A Customized Approach

Is Machine Learning the Right Approach for Your Business Problem?

Large Language Models in Production Round-table Conversation

The Trustworthy Chatbot Search Engine // Saahil Jain // MLOps Podcast #151 clip

Optimizing ML Capabilities for Business Success // Jason McCampbell // MLOps Podcast #149 clip

The 7 Lines of Code You Need to Run Faster Real-time Inference // Adrian Boguszewski // Meetup #121

Ethical Machine Learning: Collecting the Least Amount of Data Necessary

Defining Intelligence in Artificial Intelligence // Karl Fezer // MLOps Podcast # 148 clip

From Prototype to Production: A Successful Process for Deploying Machine Learning Models

Blind Spots in Business Knowledge: Recognizing and Overcoming Them

Let's Talk About Raw Documents // Crag Wolfe // MLOps Meetup #120

The Challenges of Productionizing Machine Learning in the Era of Big Models

The Importance of Domain Experts in Creating Stress Tests

AI and the Future of Database Optimization // Alex Debrie // MLOps Podcast #146 short clip

The Value of Communication in the Age of Machine Learning

Differences in Challenges Faced by Staff Engineers in Startups and Large Organizations