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Best practices for structuring large datasets in Retrieval-Augmented Generation (RAG)
Retrieval-Augmented Generation, or RAG, is a game-changer for AI applications, allowing large language models to pull real-time, factual information from massive datasets...
A feedback loop alternative to RAG that aligns LLMs with knowledge graph models
Image by Gerd Altmann from Pixabay Discover AI–a YouTube channel run by an unidentified Austrian man who distills and highlights the findings of AI papers in an engagin...
Techniques for automated feature selection: Filter methods and implementation using Python libraries
Feature Selection is a crucial process in feature engineering as part of the Machine Learning life cycle. It focuses on identifying the most impactful features in the gi...
The Four Pillars of AI-driven Innovation
Innovation is more than just ideation. Ultimately, innovation is about value creation. AI has sparked a growing urgency in the concepts that drive innovation as org...
AI safety summit: Affect alignment and labor economics workshops
There are two pillars of human society—affect and intelligence. Just one is principal to being a part of any human group. Though both are required for [social and occup...
What to consider when selecting a learning model
Image by Malachi Witt from Pixabay I had the chance to listen to a talk that Ivan Lee, Founder and CEO of Datasaur, gave during October 2024’s AI Summit here at the Com...
How to accelerate prototyping in manufacturing product design
Discover strategies to accelerate prototyping in manufacturing product design. Learn about AI integration, optimized hardware, 3D printing, and AR/VR technologies for eff...
LLM Chunking, Indexing, Scoring and Agents, in a Nutshell
It is becoming a bit difficult to follow all the new AI, RAG and LLM terminology, with new concepts popping up almost every week. Which ones are important, and here to st...