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ORNL’s Suhas Sreehari explains the algebraic and topological foundations of representation systems, used in generative AI technology such as large language models. Credit: Lena Shoemaker/ORNL, U.S. Dept. of Energy

In the age of easy access to generative AI software, user can take steps to stay safe. Suhas Sreehari, an applied mathematician, identifies misconceptions of generative AI that could lead to unintentionally bad outcomes for a user. 
 

Steven Hamilton, an R&D scientist in the HPC Methods for Nuclear Applications group at ORNL, leads the ExaSMR project. ExaSMR was developed to run on the Oak Ridge Leadership Computing Facility’s exascale-class supercomputer, Frontier. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy

The Exascale Small Modular Reactor effort, or ExaSMR, is a software stack developed over seven years under the Department of Energy’s Exascale Computing Project to produce the highest-resolution simulations of nuclear reactor systems to date. Now, ExaSMR has been nominated for a 2023 Gordon Bell Prize by the Association for Computing Machinery and is one of six finalists for the annual award, which honors outstanding achievements in high-performance computing from a variety of scientific domains.  

The image shows a visualization of a radiation transport simulation for a spaceflight radioisotope power system and complex interactions of radiation fields with operational environments. Credit: Michael B. R. Smith and M. Scott Greenwood/ORNL, U.S. Dept. of Energy

Researchers at 91°µÍø are developing a first-of-a-kind toolkit drawing on video game development software to visualize radiation data.

VERA’s tools allow a virtual “window†inside the reactor core, down to a molecular level.

A software package, 10 years in the making, that can predict the behavior of nuclear reactors’ cores with stunning accuracy has been licensed commercially for the first time.