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Energy Secretary, CEO for OpenAI and ORNL researcher are standing over a table talking to event participants

ORNL took part in the “1,000 Scientists AI Jam Session,” a first-of-its-kind virtual event that brought together leading scientists from nine national laboratories to test generative artificial intelligence models for their functionality in scientific research.

Secretary Wright leans over red computer door, signing with silver sharpie as ORNL Director Stephen Streiffer looks on

During his first visit to Oak Ridge National Laboratory, Energy Secretary Chris Wright compared the urgency of the Lab’s World War II beginnings to today’s global race to lead in artificial intelligence, calling for a “Manhattan Project 2.”

Six images fanned out across the right side of the page with the first page showcasing the report cover. To the right hand side is a green oak leaf.

A workshop led by scientists at ORNL sketched a road map toward a longtime goal: development of autonomous, or self-driving, next-generation research laboratories. 

Large group of over 30 students gather in conference room for a presentation, seated with their laptops

Not only did ORNL take home top honors at the 2024 International Conference for High Performance Computing, Networking, Storage, and Analysis (SC24), but the lab’s computing staff also shared career advice and expertise with students eager to enter the world of supercomputing.

Stock image of a person in a doctor's coat pointing to white graphics if a person, world and dots, symbolizing the artificial intelligence technology used for cancer pathology
In a major milestone for cancer research, the Department of Energy’s Oak Ridge National Laboratory helped reduce the time between cancer diagnosis and pathology report processing from 22 months to just 14 months, utilizing advanced artificial
ORNL R&D data scientist Max Pasini is posing for a portrait with a blue background, black button up long sleeve shirt

Massimiliano (Max) Lupo Pasini, an R&D data scientist from ORNL, was awarded the National Energy Research Scientific Computing Center’s High Performance Computing Achievement Award for High Impact Scientific Achievement for his work in “Groundbreaking contributions to scientific machine learning, particularly through the development of HydraGNN.”

A male researcher is standing next to a poster board displayed on an easel to the right. The researcher is dressed in professional attire, and the poster board is positioned beside him, showing research or visual information.

Ryan Culler is the program manager at Oak Ridge National Laboratory, where he oversees the production of actinium-225, a promising treatment for cancer. Driven by a personal connection to cancer through his late brother, Culler is dedicated to advancing medical isotopes to help improve cancer care. 

ORNL researcher Phong Le poses for a photo outside on a walkway bridge over the pond. The photo is framed with brown and green plants

Phong Le is a computational hydrologist at ORNL who is putting his skills in hydrology, numerical modeling, machine learning and high-performance computing to work quantifying water-related risks for humans and the environment. 

Picture shows magnetic domains in uranium with a blue and orange organic shapes, similar to lava flowing through water, but in graphic form

The US focuses on nuclear nonproliferation, and ORNL plays a key role in this mission. The lab conducts advanced research in uranium science, materials analysis and nuclear forensics to detect illicit nuclear activities. Using cutting-edge tools and operational systems, ORNL supports global efforts to reduce nuclear threats by uncovering the history of nuclear materials and providing solutions for uranium removal. 

FREDA logo with a blue background and neon blue lines coming from the bottom left, plus a circle in the middle filled with half science atom symbol and half gear

FREDA is a new tool being developed at ORNL that will accelerate the design and testing of next-generation fusion devices. It is the first tool of its kind to combine plasma and engineering modeling capabilities and utilize high performance computing resources.