Industrial AI Conference | Stanford, CA

Language, Graphs, and AI in Industry

This talk addresses how to leverage both natural language and graph technologies together for AI applications in industry. We’ll look at how LLMs get used to build and augment graphs, and conversely how graph data gets used to ground LLMs for generative AI use cases in industry – where a kind of “virtuous cycle” is emerging for feedback loops based on graph data. Our team has been engaged, on the one hand, with enterprise use cases in manufacturing. On the other hand we’ve worked as intermediaries between research teams funded by enterprise and open-source projects needed by enterprise – particularly in the open-source ecosystem for AI models. Also, there are caveats; this work is not simple. Translating from the latest research into production-ready code is especially complex and expensive. Let’s examine caveats that other teams should understand, and look toward practical examples.

This talk addresses how to leverage both natural language and graph technologies together for AI applications in industry. We’ll look at how LLMs get used to build and augment graphs, and conversely how graph data gets used to ground LLMs for generative AI use cases in industry – where a kind of “virtuous cycle” is emerging for feedback loops based on graph data. Our team has been engaged, on the one hand, with enterprise use cases in manufacturing. On the other hand we’ve worked as intermediaries between research teams funded by enterprise and open-source projects needed by enterprise – particularly in the open-source ecosystem for AI models. Also, there are caveats; this work is not simple. Translating from the latest research into production-ready code is especially complex and expensive. Let’s examine caveats that other teams should understand, and look toward practical examples.