🇫🇷Hellixia & Generative AI: Creating Semantic and Causal Bayesian Networks for Decision Support
Dr. Lionel Jouffe, Bayesia S.A.S.
Recorded at the 2024 BayesiaLab Spring Conference in Cincinnati on April 11, 2024.
Abstract
This presentation explores the revolutionary potential of Hellixia, BayesiaLab's specialized assistant, for knowledge discovery and decision support using large-scale language models (LLMs) such as GPT-4.
Hellixia presents itself as a significant innovation, exploiting the wealth of knowledge embedded in LLMs to identify and suggest the most relevant dimensions of a field of study (a process akin to crowdsourcing).
Hellixia uses user-selected keywords (such as causes, levers, effects, concepts, forces, and ideas) to generate mathematical representations capturing the semantics (embeddings), enabling automatic learning of semantic Bayesian networks with BayesiaLab.
Hellixia doesn't limit itself to semantics; it can go further by testing causal hypotheses and automatically generating causal networks, thus providing invaluable help in analyzing and understanding complex relationships within the domains under study.
This ability to automatically translate latent knowledge into semantic and causal networks opens up new avenues for knowledge extraction and decision support, marking a significant advance in knowledge extraction and decision support, marking a significant advance in exploiting the capabilities of LLMs for a wide range of fields, including marketing, industry, medicine, economics, politics, literature, and even philosophy.
Presentation Video
About the Presenter
Dr. Lionel Jouffe is co-founder and CEO of France-based Bayesia S.A.S. Lionel holds a Ph.D. in Computer Science from the University of Rennes and has worked in Artificial Intelligence since the early 1990s. While working as a Professor/Researcher at ESIEA, Lionel started exploring the potential of Bayesian networks.
After co-founding Bayesia in 2001, he and his team have been working full-time on the development of BayesiaLab. Since then, BayesiaLab has emerged as the leading software package for knowledge discovery, data mining, and knowledge modeling using Bayesian networks. It enjoys broad acceptance in academic communities, business, and industry.
Recent Hellixia Webinars
🆕pageWebinar: Discovering Complex Causal Structures with HellixiapageWebinar: Harnessing Hellixia: Innovations in Bayesian Belief Network ConstructionPrevious Conference Presentations
🇫🇷pageIntroducing BayesiaLab's New Native ChatGPT Integration for Domain Knowledge Augmentation🇫🇷pageInnovations in Knowledge Elicitation🇫🇷pageBayesiaLab 10 Update🇫🇷pageIntroducing BayesiaLab 10🇫🇷pageIntroducing BayesiaLab 9🇫🇷pageIntroducing BayesiaLab 8Last updated
