Foundation models are revolutionizing the way we interact with AI—powering everything from search engines to scientific discovery. But as their reach expands, so do the risks. Can we truly trust these systems—before putting them to use? 🤔
From AlexNet to LLaVA 🧠, the pace of innovation is staggering. Yet one thing remains constant:
the urgent need for trustworthiness.
In the foundation model era, we ask:
🌍 What does trust mean at scale?
📜 Can classical insights still guide us?
This workshop brings together researchers, engineers, and thought leaders to confront these challenges head-on. We’ll explore how to create models that are not just powerful, but robust, fair, interpretable, and accountable.
