Building Trust In AI: Semantic Interoperability and Knowledge Graphs at the Rescue of LLMs
A Talk by Jérémy Ravenel (Founder & CEO, naas.ai)
About this Talk
Currently, AI suffers from some key issues. Today’s AI is prone to errors, and is plagued by bias and discrimination as well as privacy issues. Thus, among increasing calls for stringent AI governance and compliance, the loss of consumer trust leads to reduced adoption and financial setbacks.
Large Language Models (LLMs) should not be trusted, they need to be integrated into a broader workflow to maximize their utility and ensure reliability. Semantic interoperability is how this can be achieved.
Imagine semantic interoperability as the subtle dance of grounded AI communication, essential for ensuring clarity and precision. It's foundational for building a trusted AI ecosystem.
Knowledge Graphs can be the backbone of trust for AI. Implementing Knowledge Graphs and developing opinionated data models during the pre-processing stage force AI systems builders to create a more structured user experience and journey.
Building ABI, an AI system for businesses, we realized the importance of KG and opinionated data models is not even enough; you need to think in terms of flywheel: interconnected and interoperable elements, a logical flow in the head of the user.
In this talk, we share what we learned on the future of Semantic AI. Connecting Personal AI, Business AI, and Institutional AI to enhance personal, business, and societal trusted outcomes.
About The Speakers
We’re a cloud tech company that provides organisations around the world with computing infrastructure and software to help them innovate, unlock efficiencies and become more effective. We also created the world’s first – and only – autonomous database to help organise and secure our customers’ data.
