Author: Phillip Ramos - Page 19

Citation and Attribution in RAG Outputs: How to Build Trustworthy LLM Responses

by Phillip Ramos

Citations in RAG systems turn AI guesses into verifiable facts. Learn how to implement accurate, trustworthy citations using real-world frameworks, data prep tips, and the latest 2025 research to meet regulatory demands and build user trust.

Calibration and Outlier Handling in Quantized LLMs: How to Keep Accuracy When Compressing Models

by Phillip Ramos

Learn how calibration and outlier handling keep quantized LLMs accurate when compressed to 4-bit. Discover which techniques work best for speed, memory, and reliability in real-world deployments.

Fine-Tuned Models for Niche Stacks: When Specialization Beats General LLMs

by Phillip Ramos

Fine-tuned LLMs outperform general models in niche tasks like legal analysis, medical coding, and compliance. Learn how specialization beats scale, when to use QLoRA, and why hybrid RAG systems are the future.

Marketing Content at Scale with Generative AI: Product Descriptions, Emails, and Social Posts

by Phillip Ramos

Generative AI is transforming how businesses create product descriptions, emails, and social posts-cutting production time by up to 70% while scaling personalization. Learn how to use it effectively without losing brand voice or authenticity.