Browse Lessons

From an API to a Chat GPT Plugin // Mathieu Bastian // LLMs in Production Conference Part 2

All the Hard Stuff with LLMs in Product Development // Phillip Carter // MLOps Podcast #170

Everything We've Been Taught About ML is Wrong // Emmanuel Ameisen // LLMs in Prod Con Part 2

Ux of a LLM User // Panel 5 // LLMs in Production Conference Part 2

End-to-end Modern Machine Learning in Production // Omar Sanseviero // LLMs in Prod Con Part 2

Guardrails for LLMs: A Practical Approach // Shreya Rajpal // LLMs in Prod Conference Part 2

Language Models: Developing Apps - Challenges & Solutions // Barak Turovsky /MLOps Podcast #169 clip

RLHF Data Collection in Practice // Andrew Mauboussin // LLMs in Prod Conference Part 2

The Confidence Checklist for LLMs in Production // Rohit Agarwal // LLMs in Prod Conference Part 2

Incorporating LLMs in High-stake Use Cases // Yada Pruksachatkun // LLMs in Prod Conference Part 2

Bringing Structure to Unstructured Data with an AI-First System Design // Will Gaviria Rojas // LLMs

MLOps at the Age of Generative AI // Barak Turovsky // MLOps Podcast #169

From Experiment to Prompt Tracking in MLOps // Piotr Niedźwiedź // MLOps Podcast #168 clip

Designing Human in the Loop Experiences for LLMs // Alberto Rizzoli // LLMs in Prod Con Part 2

Unleashing Code Completion with LLMs // Monmayuri Ray // LLMs in Production Conference Part 2

Building Recommender Systems with Large Language Models // Sumit Kumar // LLMs in Production

Combining LLMs with Knowledge Bases to Prevent Hallucinations // Scott Mackie // LLMs in Prod Con 2

Experiment Tracking in the Age of LLMs // Piotr Niedźwiedź // MLOps Podcast #168

Controlled and Compliant AI Applications // Daniel Whitenack // LLMs in Production Conference Part 2

Making LLM Inference Affordable // Daniel Campos // LLMs in Production Conference Part 2

The Next Million AI Apps // Mark Huang // LLMs in Pod Con Part 2 Workshop Day 1

Benchmarking LLM performance with LangChain Auto-Evaluator // Lance Martin //LLMs in Prod Con Part 2

A Testing Library for AI Prompt Engineering // Maxime Beauchemin // MLOps Podcast #167 clip

Challenges in Providing LLMs as a Service // Hemant Jain // LLMs in Production Conference Part 2

Lessons Learned Productionising LLMs for Stripe Support // Sophie Daly // LLMs in Prod Con Part 2

LLM on K8s // Panel 2 // LLMs in Conference in Production Conference Part 2

Transforming AI Safety & Security // Manojkumar Parmar // LLMs in Production Conference Part 2

Navigating Through the Generative AI Landscape // Azin Asgarian // LLMs in Prod Conference Part 2.

Linguistically-informed LLMs Perform Better // Chris Brousseau // LLMs in Prod Conference

Building Products // Panel 3 // LLMs in Production Conference part 2

LLMs For the Rest of Us // Vikram Sreekanti & Joseph Gonzalez // LLMs in Prod Conference Part 2

Building Reliable AI Agents // Travis Fischer // LLMs in Production Conference Part 2

Foundation Models in the Modern Data Stack // Ines Chami // LLMs in Prod Conference Part 2

Wardley Mapping Prompt Engineering // Mark Craddock // LLMs in Production Conference Part 2

Create a Contextual Chatbot with LLM a Vector Database in 10 Minutes // Raahul Dutta // LLMs Part 2

Treating Prompt Engineering More Like Code // Maxime Beauchemin // MLOps Podcast #167

Building Data and ML Products // Roy Hasson & Santona Tuli // MLOps Podcast #166 short clip 1

Eliminating Garbage In/Garbage Out for Analytics and ML // Roy Hasson & Santona Tuli // Podcast #166

Tabular vs Complex Data // Sammy Sidhu // MLOps Podcast #165 short clip

It Worked When I Prompted It // Soham Chatterjee // LLMs in Production Conference Part 2

Evaluation // Panel 1 // Large Language Models in Production Conference Part 2

Evaluating LLM-based Applications // Josh Tobin // LLMs in Prod Conference Part 2

Solving LLM Data Problems // Yujian Tang // LLMs in Prod Conference Part 2

Python Power: How Daft Embeds Models and Revolutionizes Data Processing //Sammy Sidhu// Podcast #165

Stopping Hallucinations From Hurting Your LLMs // Atindriyo Sanyal // LLMs in Prod Conference Part 2

$360k Question - Understanding the LLM Economics // Nikunj Bajaj // LLMs in Production Conference

Building and Curating Datasets for RLHF and LLM Fine-tuning // Daniel Vila Suero // LLMs in Prod Con

Automating ML Infrastructure // Rob Hirschfeld // MLOps Podcast #164 short clip