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MLOps.community · Technology

AAIF Live

The Agentic AI Foundation is where the agentic stack is being built. Come join the ride.

Episodes

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

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