Knowledge graphs are network graphs that link related concepts and properties together to create a form of inferencing engine, with knowledge engineering being the programming aspect of graph usage. Explore how knowledge graphs are created and queried, how they are used as part of a broader form of enterprise metadata management, and how they tie into ML and the IoT.
Image by David from Pixabay Mobile phones make it possible to secure and manage personal data on-device, which opens up a novel opportunity for both… Read More »Samsung and Apple’s knowledge-centric approaches to secure, personalized AI on phones
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… Read More »A feedback loop alternative to RAG that aligns LLMs with knowledge graph models
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… Read More »LLM Chunking, Indexing, Scoring and Agents, in a Nutshell
Image by René Bittner from Pixabay I had the opportunity courtesy of managing director Sheena Tu of Techequity-ai to attend a good portion of their… Read More »Pill bots, agents and solving gen AI’s data challenges: Takeaways from the AI Summit
This book features new advances in game-changing AI and LLM technologies built by GenAItechLab.com. Written in simple English, it is best suited for engineers, developers,… Read More »New Book: Building Disruptive AI & LLM Technology from Scratch
Image by Gerd Altmann from Pixabay A few enterprise takeaways from the AI hardware and edge AI summit 2024 Enterprises haven’t seemed as enthusiastic about… Read More »A few enterprise takeaways from the AI hardware and edge AI summit 2024
In this article, I describe some of the most common types of databases that apps such as RAG or LLM rely upon. I also provide… Read More »Large AI Apps: Optimizing the Databases Behind the Scenes
An interview with Amit Sheth, founding director, Artificial Intelligence Institute, University of South Carolina Amit Sheth has survived and thrived through multiple AI winters because… Read More »Scaling knowledge graphs and neurosymbolic AI
Katalin Bártfai-Walcott (KBW) of Ambient Enterprises posted some helpful observations and thoughts via LinkedIn in September on how LinkedIn and other comparable platforms are treating… Read More »A user-centric approach to responsible AI
This is the third and final article in this series, featuring some of the most powerful features to improve RAG/LLM performance. In particular: speed, latency,… Read More »30 Features that Dramatically Improve LLM Performance – Part 3
