ChatGPT

Towards a Universal Knowledge Graph Chatbot: ChatGPT versus Traditional Question Answering for Knowledge Graphs

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B9 L2 H2 H2

Conversational AI and Question-Answering systems (QASs) for knowledge graphs (KGs) are both emerging research areas: they empower users with natural language interfaces for extracting information efficiently and effectively. While Conversational AI simulates human-like conversations, its effectiveness is limited by the available training data. However, QASs retrieve the most up-to-date information from KGs by translating natural language queries into formal queries that the database engine can process. In this talk, we examine the characteristics of existing approaches for combining Conversational AI and QASs to create novel KG chatbots. We also introduce KGQAn, a universal QA system that can be applied to any KG without the need for customization.

Workshop Unlocking the Power of “ChatGPT” at KAUST

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B20 Auditorium

Abstract Explore GPT Technology and LLM in KAUST! Brief Biography Preview the pilot for a new KAUST ChatGPT Portal, an exciting tool designed to streamline your work using Generative AI technology with the chance to be among the selected group of participants, we are excited to announce that you will be granted early access to test the KAUST ChatGPT Portal and provide feedback. This is a fantastic opportunity to be one of the pioneers in adopting this new technology within KAUST.
KAUST-CEMSE-CS-Vision-CAIR-Mohamed-Elhoseiny

Mohamed Elhoseiny

Associate Professor, Computer Science
Professor Elhoseiny’s research focuses on developing affective artificial intelligence that understands and generates novel visual content. He has contributed to and led numerous seminal works of affective AI art creation.