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ICECap looks to use exascale fusion simulations to pioneer digital design
Oct. 17, 2024 -
A groundbreaking multidisciplinary team of LLNL researchers is combining the power of exascale computing with AI, advanced workflows and graphics processor (GPU)-acceleration to advance scientific innovation and revolutionize digital design. The project, called ICECap (Inertial Confinement on El Capitan), is a transformative approach to inertial confinement fusion (ICF) design optimization...
DOE honors seven early-career Lab scientists
Sept. 19, 2024 -
Seven LLNL scientists are recipients of the DOE's Office of Science Early Career Research Program (ECRP) award. Among them is Shusen Liu, a computer scientist in the Machine Intelligence Group in the Center for Applied Scientific Computing. His work focuses on understanding and interpreting the inner mechanisms of neural networks and integrating human domain knowledge with machine...
Measuring failure risk and resiliency in AI/ML models
Aug. 27, 2024 -
The widespread use of artificial intelligence (AI) and machine learning (ML) reveals not only the technology’s potential but also its pitfalls, such as how likely these models are to be inaccurate. AI/ML models can fail in unexpected ways even when not under attack, and they can fail in scenarios differently from how humans perform. Knowing when and why failure occurs can prevent costly...
Measuring attack vulnerability in AI/ML models
Aug. 26, 2024 -
LLNL is advancing the safety of AI/ML models in materials design, bioresilience, cyber security, stockpile surveillance, and many other areas. A key line of inquiry is model robustness, or how well it defends against adversarial attacks. A paper accepted to the renowned 2024 International Conference on Machine Learning explores this issue in detail. In “Adversarial Robustness Limits via...
LLNL, DOD, NNSA dedicate Rapid Response Laboratory and supercomputing system to accelerate biodefense
Aug. 15, 2024 -
LLNL recently welcomed officials from the Department of Defense (DOD) and National Nuclear Security Administration (NNSA) to dedicate a new supercomputing system and Rapid Response Laboratory (RRL). DOD is working with NNSA to significantly increase the computing capability available to the national biodefense programs. The collaboration has enabled expanding systems of the same architecture...
International workshop focuses on AI for critical infrastructure
Aug. 12, 2024 -
On August 4, LLNL researchers Felipe Leno da Silva and Ruben Glatt hosted the AI for Critical Infrastructure workshop at the 33rd International Joint Conference on Artificial Intelligence (IJCAI) in Jeju, South Korea. Professors Wencong Su (University of Michigan – Dearborn) and Yi Wang (University of Hong Kong) joined them in organizing the workshop focused on exploring AI opportunities and...
Evaluating trust and safety of large language models
Aug. 8, 2024 -
Accepted to the 2024 International Conference on Machine Learning, two Livermore papers examined trustworthiness—how a model uses data and makes decisions—of large language models, or LLMs. In “TrustLLM: Trustworthiness in Large Language Models,” Bhavya Kailkhura and collaborators from universities and research organizations around the world developed a comprehensive trustworthiness...
Probing carbon capture, atom-by-atom
July 31, 2024 -
A team of scientists at LLNL has developed a machine-learning model to gain an atomic-level understanding of CO2 capture in amine-based sorbents. This innovative approach promises to enhance the efficiency of direct air capture (DAC) technologies, which are crucial for reducing the excessive amounts of CO2 already present in the atmosphere. The low cost of these sorbents has enabled several...
Department of Energy announces FASST initiative
July 16, 2024 -
On July 16, the Department of Energy formally announced the proposed Frontiers in Artificial Intelligence for Science, Security and Technology (FASST) initiative via the web page www.energy.gov/fasst (with accompanying video and fact sheet). As stated on the web page, the speed and scale of the AI landscape are significant motivators for investing in strategic AI capabilities: “Without FASST...
AI, fusion, and national security with Brian Spears (VIDEO)
July 13, 2024 -
This episode of the Eye on AI podcast delves into the cutting-edge world of AI and high-performance computing with Brian Spears, director of LLNL's AI Innovation Incubator. The episode is presented here as a video with the following description: "Brian shares his experience in driving AI into national security science and managing the nation’s nuclear stockpile. With a PhD in mechanical...
The surprising places you’ll find machine learning (VIDEO)
June 20, 2024 -
LLNL data scientists are applying ML to real-world applications on multiple scales. A new DSI-funded video highlights research at the nanoscale (developing better water treatment methods by predicting the behavior of water molecules under the extremely confined conditions of nanotubes); mesoscale (determining the likelihood and location of a dangerous wildfire-causing phenomenon called arcing...
LLNL and BridgeBio announce trials for supercomputing-discovered cancer drug
June 6, 2024 -
In a substantial milestone for supercomputing-aided drug design, LLNL and BridgeBio Oncology Therapeutics (BridgeBio) today announced clinical trials have begun for a first-in-class medication that targets specific genetic mutations implicated in many types of cancer. The development of the new drug—BBO-8520—is the result of collaboration among LLNL, BridgeBio and the National Cancer...
The Laboratory’s habit of innovation
June 4, 2024 -
LLNL’s HPC and data science capabilities play a significant role in international science research and innovation, and Lab researchers have won 10 R&D 100 Awards in the Software–Services category in the past decade. The latest issue of Science & Technology Review features several award-winning projects, including ZFP and CANDLE: (1) ZFP introduces a new method of compressing large data sets...
Statistical framework synchronizes medical study data
June 3, 2024 -
The risks and benefits of heart surgery, chemotherapy, vaccination, and other medical treatments can change based on the time of day they are administered. These variations arise in part due to changes in gene expression levels throughout the 24-hour day-night cycle, with around 50% of genes displaying oscillatory behavior.
To evaluate new therapies, investigators study how a gene’s...
Machine learning optimizes high-power laser experiments
May 17, 2024 -
Commercial fusion energy plants and advanced compact radiation sources may rely on high-intensity, high-repetition rate lasers, capable of firing multiple times per second, but humans could be a limiting factor in reacting to changes at these shot rates. Applying advanced computing to this problem, a team of international scientists from LLNL, Fraunhofer Institute for Laser Technology (ILT)...
GUIDE team develops approach to redesign antibodies against viral pandemics
May 8, 2024 -
In a groundbreaking development for addressing future viral pandemics, a multi-institutional team involving LLNL researchers has successfully combined an AI-backed platform with supercomputing to redesign and restore the effectiveness of antibodies whose ability to fight viruses has been compromised by viral evolution. The team’s research is published in the journal Nature and showcases a...
Igniting scientific discovery with AI and supercomputing (VIDEO)
April 15, 2024 -
LLNL’s fusion ignition breakthrough, more than 60 years in the making, was enabled by a combination of traditional fusion target design methods, high-performance computing (HPC), and AI techniques. The success of ignition marks a significant milestone in fusion energy research, and was facilitated in part by the precision simulations and rapid experimental data analysis only possible through...
Predicting climate change impacts on infrastructure (VIDEO)
Feb. 26, 2024 -
At LLNL, electrical grid experts and climate scientists work together to bridge the gap between infrastructure and climate modeling. By taking weather variables such as wildfire, flooding, wind, and sunlight that directly impact the electrical grid into consideration, researchers can improve electrical grid model projections for a more stable future. In a new video, LLNL computer scientist...
Machine learning tool fills in the blanks for satellite light curves
Feb. 13, 2024 -
When viewed from Earth, objects in space are seen at a specific brightness, called apparent magnitude. Over time, ground-based telescopes can track a specific object’s change in brightness. This time-dependent magnitude variation is known as an object’s light curve, and can allow astronomers to infer the object’s size, shape, material, location, and more. Monitoring the light curve of...
Conference paper illuminates neural image compression
Dec. 8, 2023 -
An enduring question in machine learning (ML) concerns performance: How do we know if a model produces reliable results? The best models have explainable logic and can withstand data perturbations, but performance analysis tools and datasets that will help researchers meaningfully evaluate these models are scarce. A team from LLNL’s Center for Applied Scientific Computing (CASC) is teasing...