Where are We in the Journey to a Knowledgeable Assistant?
Discover the future of AI with Meta Chief Scientist Xin “Luna” Dong. As AI assistants transition from chatbots to wearables, the demand for reliability is paramount. Learn how the Dual-Neural Knowledge framework targets hallucinations, ensuring your digital assistant provides the precise, real-time accuracy required to navigate our complex information age.
Experience the Event
Discover the future of AI with Meta Chief Scientist Xin “Luna” Dong. As AI assistants transition from chatbots to wearables, the demand for reliability is paramount. Learn how the Dual-Neural Knowledge framework targets hallucinations, ensuring your digital assistant provides the precise, real-time accuracy required to navigate our complex information age.
The world is in a transformative era, with AI revolutionizing industries, reshaping innovation, and unlocking opportunities once thought impossible. Its vast potential inspires optimism for a future where technology drives progress across industries, governments, NGOs, and society as a whole. However, with this promise comes significant responsibility. Concerns over bias, inequitable access, safety vulnerabilities, and ethical uncertainties highlight the urgent need for a guiding framework. RISE (Responsible, Inclusive, Safe and Ethical) AI fulfills this role, ensuring that AI technologies are developed and applied responsibly, inclusively, and ethically.
The RISE AI Conference provides a unique platform to explore how artificial intelligence can be harnessed to tackle complex societal and contemporary challenges while upholding the principles of RISE. The inaugural RISE AI Conference took place from October 6-8, 2025 at the University of Notre Dame, and was hosted by the Lucy Family Institute for Data and Society.
For more information, please visit the RISE AI Conference website.
MoreMeet the Speaker: Xin "Luna" Dong
Xin “Luna” Dong is a chief scientist at Meta Wearables AI, leading the ML efforts in building an intelligent personal assistant for wearable devices. Before that, she has spent more than a decade building knowledge graphs, such as the Amazon Product Graph and the Google Knowledge Graph. She has co-authored books Machine Knowledge: Creation and Curation of Comprehensive Knowledge Bases and Big Data Integration. She was named an ACM Fellow and an IEEE Fellow for “significant contributions to knowledge graph construction and data integration”, awarded the VLDB Women in Database Research Award and VLDB Early Career Research Contribution Award. She serves in the PVLDB advisory committee, was a member of the VLDB endowment, a PC co-chair for KDD’2022 ADS track, WSDM’2022, VLDB’2021, and Sigmod’2018.