How to Build RAG / LLM Apps with Knowledge Graphs
Hands-on workshop for developers and AI professionals, featuring state-of-the-art technology, case studies, code-share, and live demos. Recording and GitHub material will be available to registrants who cannot attend the free 60-min session.
Overview
As the digital landscape evolves, the ability to leverage Knowledge Graphs for advanced data insights has become crucial for businesses aiming to stay ahead. This webinar will delve into how Knowledge Graph RAG, particularly with SingleStore, is revolutionizing data analytics, making it possible to retrieve and generate information in real-time with unprecedented accuracy. With AI-driven data processing at the forefront, businesses can significantly improve decision-making, enhance customer experiences, and drive innovation. Expect to witness a live demo and code-share during the webinar, showcasing the practical applications of these technologies.
You’ll learn:
o The fundamentals of Knowledge Graph RAG and its applications in data analytics.
o How SingleStore can be leveraged to improve data retrieval and generation accuracy.
o Strategies for implementing Knowledge Graph RAG to enhance business insights.
o Insights into the impact of advanced data analytics on business performance.
o A live demonstration of creating a Knowledge Graph RAG system using SingleStore.
Axiom Mathematics - Research Scientist - Creator of The Aeon Ship
9 个月Knowledge graphs aren't the only strategy that should be used from graph theory for advanced data insights. There is a plethora of graph techniques that can be useful in providing additional insight. Even more abstract than a Knowledge Graph, is a Concept Graph that represents suggested relationships between concepts which can give deeper insights into data. Also, more advanced techniques like graph databases or object-oriented databases can provide even more insights into the relationship between data structures. Utilizing trees like the Minimum spanning tree and their subsequent algorithms can provide additional tools for data management. These techniques typically used in telecommunications can be effective strategies in AI development and more. More concepts like Frucht's theorem, Bayesian network, Markov random field, and Cayley graph can all provide additional tools that will give you a more comprehensive analysis of data, especially if these techniques are used by AI systems. There's a whole list of graph theory concepts that can be utilized in RAG and LLM apps, the more of these concepts that you can include in your AI systems, the more versatile and powerful they will be at data retrieval, analysis, and manipulation.
Realtor Associate @ Next Trend Realty LLC | HAR REALTOR, IRS Tax Preparer
9 个月Thanks for Sharing.
Chairman, President & CEO at Synergism, Inc. and Owner, Synergism, Inc.
9 个月Isn’t this too involved for many of us, since knowledge might be unfathonable at best and immensely interpretable by spacetime evolution at worst?
Noah Evers