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Accomplishments

Page • TitleDescription/More Information NNSA Panel Discussion on Ethics in AI Siva Rajamanickam from Sandia National Laboratories participated in a panel discussion at National Nuclear Security Administration (NNSA) Headquarters September 10th, 2025. The panel was moderated by Si Hammond and presided by acting deputy administrator of defense programs David Hoagland and Dr....

ASC Co-Pilots for Code

Page • This project provides funding to evaluate emerging practical large-language model solutions for the ASC and the ND program. Our initial set of tasks/projects includes an evaluation of language models for software engineering and code modernization (particularly for HPC and scientific programming), using language models for knowledge capture and retrieval.  Underpinning...

ASC Federated Models

Page • This project aims to develop large foundation models for generative AI capabilities tailored for ND applications across the three NNSA laboratories. By leveraging AI, the project seeks to significantly reduce the lengthy lifecycle times (over a decade) associated with ND modernization. The initiative will create a common framework for sharing...

Asmeret Naugle

Staff Page • R&D S&E, Computer Science. Biography Asmeret Naugle leads computational social science and human-AI teaming research at Sandia National Laboratories. She has interest and experience in: Human-AI teaming Trust and trustworthiness Dynamic simulation modeling, including system dynamics and agent based modeling Cognitive modeling Data science Asmeret is in the Applied Information...

BANYAN

Page • This project is exploring the development of new methods for building large multimodal generative artificial intelligence models and demonstrating neural methods on a mission-relevant exemplar. The models developed here will play a foundational role for Sandia developed multimodal models. BANYAN will demonstrate the approach by solving problems that were previously...

Cerebras

Page • Team members from Sandia's Advanced Memory Technology Program and BANYAN Institute collaborated with members of Cerebras onsite for a two-day training discussing HPC, ML, and AI. Sandia and Cerebras Team Demonstrate 1T Parameter Model Training in December: https://www.businesswire.com/news/home/20241210241089/en/Cerebras-Demonstrates-Trillion-Parameter-Model-Training-on-a-Single-CS-3-System

Collaborations

Page • This project provides funding to evaluate emerging practical large-language model solutions. Our initial set of tasks/projects includes an evaluation of language models for software engineering and code modernization (particularly for HPC and scientific programming), using language models for knowledge capture and retrieval. Underpinning all of this work are efforts to...

Home

Page • BANYAN-An Institute for Generative AI at Sandia BANYAN is a generative AI institute comprised of several projects funded by NNSA and Sandia LDRD. Uniting GenAI initiatives to leverage synergies across the lab by sharing datasets, models, software stacks, expertise, and industry collaborations. Research BANYAN Multimodal model training for ND, Stronglinks...

Invited Talks

Page • Publications Publications will be added when available. Invited Talks Talk Location Presenter Zero to 50 ExaFLOPS in Under a Year: Lessons from the TrenchesSNL: September 23rd, 2025Hagay Lupesko, Cerebras Systems Scaling AI for Scientific Discovery: Faster Kernels, Efficient Models, Better PhysicsSNL: April 17th, 2025Aparna ChandramowlishwaranUniversity of California, Irvine

NVIDIA

Page • NVIDIA FLARE™ (NVIDIA Federated Learning Application Runtime Environment) is a domain-agnostic, open-source, and extensible SDK for Federated Learning. It allows researchers and data scientists to adapt existing ML/DL workflow to a federated paradigm and enables platform developers to build a secure, privacy-preserving offering for a distributed multi-party collaboration.

PARADIGM

Page • This project will investigate how trust in generative models such as Large Language Models (LLMs) and Large Multimodal Models (LMMs) can be enhanced by integrating with a symbolic reasoning engine that embodies SME knowledge. We will explore neurosymbolic methods, neural augmentation (specialization of models) and uncertainty quantification methods to provide...

Research

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Santa Fe Institute

Page • At SFI we will evaluate fundamental visual reasoning abilities in multimodal LLMs, and develop novel neurosymbolic methods to advance such visual reasoning abilities.  Our development of new methods will draw on previous work on modeling active visual perception and analogical reasoning, and on insights from the cognitive science of human...

Team

Page • Meet Our Team