Making It Yours - Fine-Tuning, PEFT, and RAG

All Things LLM

Discover how generalist AIs become powerful specialists in this episode of "All Things LLM." Hosts Alex and AI expert Ben break down the next stage of the LLM lifecycle—customization—and unpack the practical techniques that transform foundation models into domain experts or business-ready assistants.

Learn about:

• Fine-Tuning: Why it’s essential for adapting pre-trained LLMs to specific fields, and how supervised training on labeled, high-quality data unlocks expert performance in areas like healthcare, law, or finance.
• Full Fine-Tuning vs. PEFT: The pros and cons of updating all model parameters versus using Parameter-Efficient Fine-Tuning (PEFT) methods like LoRA, which minimize costs, storage needs, and the risk of “catastrophic forgetting.”
• Cost, Complexity, and Practical Examples: Why full fine-tuning is resource-intensive, and how companies can now adapt models more efficiently—keeping generic skills while layering on domain expertise.
• Retrieval-Augmented Generation (RAG): How RAG lets you connect LLMs to external, up-to-date, or proprietary knowledge bases—enabling truly current, factual, and trustworthy answers without retraining the model.
• When and Why to Combine Approaches: Real-world strategies for using fine-tuning and RAG together, balancing deep customization, ongoing knowledge updates, and enterprise needs.

Perfect for listeners searching for:

• Fine-tuning vs. RAG
• Parameter Efficient Fine-Tuning (PEFT)
• What is LoRA?
• RAG in enterprise AI
• How to customize a large language model
• Catastrophic forgetting in AI
• LLM use cases for business

This episode distills essential techniques and practical guidance for business leaders, AI builders, and anyone interested in the future of customizable, intelligent assistants. Subscribe and tune in now—and join us next week as Alex and Ben reveal the art of prompt engineering: how expert prompts unlock even more power from today’s language models!

All Things LLM is a production of MTN Holdings, LLC. © 2025. All rights reserved.
For more insights, resources, and show updates, visit allthingsllm.com.
For business inquiries, partnerships, or feedback, contact: [email protected]

The views and opinions expressed in this episode are those of the hosts and guests, and do not necessarily reflect the official policy or position of MTN Holdings, LLC.

Unauthorized reproduction or distribution of this podcast, in whole or in part, without written permission is strictly prohibited.
Thank you for listening and supporting the advancement of transparent, accessible AI education.