Want High Performing LLMs? It's All About Your Data - Importance of Quality Data in AI Development
Explore data-centric AI development for high-performing LLMs. Learn pre-training techniques, avoid common pitfalls, and understand the critical role of quality data in model performance.
The Birth and Growth of Spark: An Open Source Success Story
Explore a insightful conversation with Matei Zaharia, creator of Apache Spark, on open-source success, MLflow development, and the future of AI applications combining LLMs with other systems.
Age of Industrialized AI - Challenges and Solutions for LLMs in Production
Explore the challenges and solutions for integrating LLMs into software, addressing hallucinations, security risks, and future developments in AI infrastructure.
Machine Learning Education at Uber - Developing an Internal ML Platform
Explore Uber's innovative ML education program, designed to empower employees with machine learning skills and enhance platform development through user feedback and engineering principles.
MLOps Build or Buy - Startup vs. Enterprise Perspectives
Explore MLOps strategies for startups and enterprises, focusing on build vs. buy decisions, data privacy, and recommender systems. Gain insights from Slack's ML engineers on platform development and integration challenges.
Why is MLOps Hard in an Enterprise? - Challenges and Solutions
Explore MLOps challenges in enterprise settings, focusing on data ecosystem complexity, cross-team collaboration, and standardization issues. Learn strategies for model reusability and effective implementation.
Fine-Tuning LLMs: Best Practices and When to Go Small - Lecture 124
Explore best practices for fine-tuning LLMs, including strategies for improving performance, overcoming challenges, and determining when to use smaller models for specific tasks.
Clean Code for Data Scientists - MLOps Coffee Sessions
Explore clean coding practices for data scientists, Shopify's real-time serving platform Merlin, and insights on LLMs in production with Matt Sharp, Data Developer at Shopify.
The Long Tail of ML Deployment - Challenges and Solutions
Explore ML deployment challenges and solutions with Baseten co-founder Tuhin Srivastava. Gain insights on engineering perspectives, LLM limitations, and the future of ML-powered products in this informative podcast episode.
Dataframes Are All You Need: MLOps on Easy Mode
Explore the power of dataframes in MLOps with Jay Chia. Learn how this flexible abstraction simplifies complex data processing, analytics, and machine learning pipelines using Daft as an example.
From Arduinos to LLMs: Exploring the Spectrum of ML - MLOps Podcast Episode 162
Explore MLOps spectrum from LLMs to TinyML. Gain insights on model deployment challenges, IoT integration, and strategies for constrained environments. Learn about the intersection of machine learning and electronics.
Democratizing AI - Vector Databases and LLM Applications
Explore vector databases, LLM app building, and AI democratization with Yujian Tang. Learn about Milvus, production use cases, data challenges, and the future of AI technologies.
The Emerging Toolkit for Reliable, High-quality LLM Applications
Explore emerging techniques in LLMOps for building, tuning, and maintaining high-quality LLM applications. Learn about testing tools, programming frameworks, and methods to control LLM outputs for desired goals.
Building LLM Applications for Production
Explore key challenges in deploying LLMs to production, covering essential considerations for real-world application development and implementation.
Scalable Evaluation and Serving of Open Source LLMs
Explore challenges and solutions for serving open-source LLMs in production, focusing on scalable evaluation and deployment strategies.
Using Vector Databases: Practical Advice for Production - LLMs in Prod Conference
Explore vector databases for LLMs in production. Learn design patterns, context retrieval, feature injection, and common pitfalls. Gain practical insights for efficient deployment and management.
Embeddings and Retrieval for LLMs: Techniques and Challenges
Explore embedding-based retrieval for AI apps, including key limitations and mitigation techniques. Learn about Chroma, an open-source embedding database for LLM applications.
Understanding the LLM Economics: The $360k Question - Lecture
Explore LLM economics, comparing costs of RAG vs fine-tuning and open-source vs commercial models. Gain insights on optimizing expenses for production-ready LLM applications.
Evaluating LLM-based Applications - Part 2
Learn hands-on techniques for evaluating language models, including data sourcing, automated metrics, and human evaluation. Gain practical tools for assessing LLM-based applications effectively.
Eliminating Garbage In/Garbage Out for Analytics and ML
Discover strategies to eliminate bad data at the source, improve data quality ownership, and enhance observability in Analytics/ML stacks. Learn from experts in data engineering and product management.
Building Products with LLMs in Production - Panel Discussion
Explore key challenges and pitfalls in building LLM-based products, including costs, latency, and effective implementation strategies. Gain insights from industry experts on navigating the complexities of AI development.