Published Sep 6, 2023

Fine-tuning vs RAG

Dive into the dynamic world of AI with insights from the MLOps Community on evolving AI applications, explore challenges in AI model evaluation, unravel the complexities of fine-tuning versus Retrieval Augmented Generation, and navigate the strategic landscape of enterprise AI adoption amid data privacy concerns.

Episode Highlights

Topics covered

Episode Highlights

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Dexa/Demetrios Brinkmann

Fine-tuning vs RAG

Topics covered

Popular Clips

Retrieval Augmented Generation

Scaling AI Solutions

Fine Tuning Challenges

Report Generation Insights

Fine Tuning Insights

Enterprise AI Skepticism

Debugging LLM Performance

Community and Collaboration

LLM Hackathon Insights

Conference Insights

Model Strategy Insights

Evaluating AI Models

Learning MLOps Strategies

LLM Frustrations

Episode Highlights

MLOps Community Trends

AI Model Evaluation

Fine-Tuning vs RAG

Enterprise AI Insights

Related Episodes

Navigating Machine Learning Careers: Insights from Meta to Consulting // Ilya Reznik // #286

MLOps for GenAI Applications // Harcharan Kabbay // #256

Retrieval Augmented Generation

Extending AI: From Industry to Innovation // Sophia Rowland & David Weik // #246

Meta GenAI Infra Blog Review // Special MLOps Podcast

AI's Next Frontier // Aditya Naganath // #277

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

Scaling AI in production // Srivatsan Srinivasan // MLOps Coffee Sessions #40

From Arduinos to LLMs: Exploring the Spectrum of ML // Soham Chatterjee // MLOps Podcast #162

RAG Has Been Oversimplified // Yujian Tang // #206

[Bonus Episode] Practical AI x MLOps // Demetrios Brinkmann, Mihail Eric, Daniel Whitenack and Chris Benson

All About Evaluating LLM Applications // Shahul Es // #179

Design and Development Principles for LLMOps // Andy McMahon // #254

MLOps vs ML Orchestration // Ketan Umare // #183

Engineering MLOps // Emmanuel Raj // MLOps Meetup #69

Fine-tuning vs RAG

Topics covered

Popular Clips

Episode Highlights

MLOps Community Trends

AI Model EvaluationThe discussion shifts to the challenges of benchmarking AI models and debugging performance issues in LLM deployments. Demetrios Brinkmann and Daniel Whitenack explore the limitations of current evaluation methods and the complexities of diagnosing system-wide issues.

AI Model Evaluation

Fine-Tuning vs RAGDemetrios Brinkmann addresses common misconceptions about fine-tuning in AI, emphasizing the complexity and resource demands involved. He contrasts this with Retrieval Augmented Generation (RAG), highlighting its efficiency and practicality for AI applications.

Fine-Tuning vs RAG

Enterprise AI InsightsThe conversation shifts to the skepticism enterprises have towards AI adoption, focusing on data privacy and trust issues. The discussion also covers OpenAI's enterprise strategy and its varied reception among different company sizes.

Enterprise AI Insights

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