Augmented Intelligence for Science and Security: From Narrow AI to Sustainable and Trustworthy Foundation Models

During this seminar, Dr. Svitlana Volkova of Pacific Northwest National Laboratory will discuss a suite of augmented intelligence solutions powered by Artificial Intelligence (AI) models. She’ll show how these models can be used to detect, anticipate, and reason (with technical expertise and capability development) to analyze and extract knowledge from large amounts of unstructured scientific literature data.

This includes:

• showing the power of narrow AI solutions, which helps scientists gain actionable insights in real-time and make informed decisions.
• outlining the limitations of AI by presenting on foundation models, a new emerging technology.
• discussing the opportunities and risks of foundation models for science and security applications.
• presenting the requirements for sustainable, trusted, and responsible next-generation AI development.

AI and machine learning techniques, driven by tremendous growth in data availability, algorithmic advances, and compute power, are rapidly adapted technologies with positive impact across many science and security applications. Today, AI solutions are capable of successfully augmenting human intelligence by analyzing large amounts of complex data to find patterns and make predictions. This is often achieved via a partnership model between a human and machine, working together to enhance cognitive performance with regards to learning, decision making, and reasoning.

The Data Science Seminar Series presents talks from innovators in the cancer research and informatics communities both within and outside of NCI.