Artificial Intelligence
and Machine Learning
Artificial intelligence (AI) and machine learning (ML) are helping INL scientists pursue advances in engineering and energy research. Computers that copy human thinking and use complex formulas to study data can help researchers solve technical problems. This new approach aids in everything from materials design for advanced reactors to making nuclear power plant control rooms more usable and efficient. AI and ML will help us glean new research insights and enhance INL’s core research capabilities.
INL is actively engaged in the Genesis Mission, a national initiative to build the world’s most powerful scientific platform to accelerate discovery science, strengthen national security, and drive energy innovation.
What is artificial intelligence and machine learning?
AI involves computer-based approaches to activities that normally require intelligence (translating data and information into knowledge) to perform effectively. ML is a form of artificial intelligence in which computer algorithms learn from data to form predictive models.
Supporting INL’s research missions
INL’s vision is to change the world’s energy future and secure our nation’s critical infrastructure. To support INL’s research missions, we have five goals in the AI/ML space.
- Methods: Use AI/ML to bridge existing research gaps.
- Data: Use INL’s unique data sources and expertise to leverage AI/ML for new insights.
- Tools: Innovate an agile AI/ML computing infrastructure.
- People: Develop and mature researchers’ AI/ML capabilities.
- Security: Ensure trustworthy AI/ML that is explainable to end users and decision makers.
Powering INL’s Mission
Artificial intelligence and machine learning support a variety of research in our mission focus areas.
Nuclear Energy
The rapid adoption of AI will accelerate nuclear energy deployment in the U.S., and INL is helping lead this transition by:
- Applying AI/ML to speed reactor design and licensing.
- Using data analytics to reduce project risks and delays.
- Enabling autonomous SMR and microreactor operations with advanced sensors and AI.
- Testing and qualifying advanced fuels and materials through specialized facilities and partnerships.
Integrated Energy
INL applies AI and ML across its Integrated Energy research areas by:
- Using AI, ML, and digital twins in geoscience to accelerate mineral discovery, optimize production, and strengthen critical material supply chains.
- Managing complex energy systems with AI-driven analytics to enhance reliability, resilience, cybersecurity, and grid performance.
- Improving biomass supply chains through predictive modeling, simulations, and advanced sensing technologies.
- Delivering AI-powered economic and market insights to guide energy investments, assess impacts, and optimize performance in modern energy markets.
National Security
AI and ML strengthen national security through innovative technologies that:
- Detect anomalous network activity and autonomously counter cyber threats, including protection of critical infrastructure.
- Identify malicious traffic in 4G/5G networks and map industrial control systems.
- Classify radio frequency signals and adapt waveforms in congested or contested spectrum environments.
- Use simulations and digital twins to predict system behavior, enhance cyber resilience, and improve reactor performance.
- Embed cybersecurity and AI risk management into SMRs and microreactors from the outset.
INL AI/ML Symposiums
INL hosts symposiums aimed at introducing AI/ML concepts, fostering collaborations, and showcasing practical applications of AI/ML technologies. These events also outline planned activities and engagements to advance AI/ML capabilities in various sectors.
Symposium 13.0 – March 28, 2024
The 13.0 Symposium focused on vision and visualization with AI/ML.
Symposium 12.0 – November 2, 2023
The 12.0 Symposium focused on Diversity, Equity and Inclusion in AI/ML.
Symposium 11.0 – April 27, 2023
The 11.0 Symposium focused on AI/ML in instrumentation, control, and automation.
Symposium 10.0 – January 19, 2023
The 10.0 Symposium focused on AI/ML technology and some novel applications.
Symposium 9.0 – September 8, 2022
The 9.0 Symposium focused on natural language processing methods and applications.
Symposium 8.0 – May 26, 2022
The 8.0 symposium focused on computation infrastructure in artificial intelligence and machine learning.
Symposium 7.0 – February 10, 2022
The 7.0 Symposium focused on addressing data issues and using data for different science and engineering applications.
Symposium 6.0 – October 14, 2021
The 6.0 Symposium focused on resilience, both in resilience applications of AI/ML or in resilience in AI/ML approaches.
Symposium 5.0 – June 8, 2021
The 8.0 symposium focused on computation infrastructure in artificial intelligence and machine learning.
Symposium. 4.0 – February 9, 2021
The 4.0 Symposium focused on trustworthy AI/ML.
Symposium. 4.0 – February 9, 2021
The 4.0 Symposium focused on trustworthy AI/ML.
Symposium 2.0 – July 9, 2020
The 2.0 Symposium discussed how ML and AI are currently being applied in the industry, including opportunities for engagement and collaboration.
Symposium 1.0 – April 17, 2020
INL held the first symposium on AI/ML approaches and activities related to science and engineering in April. The “1.0 Symposium” focused on internal-to-INL activities and capabilities. A total of eleven speakers discussed a variety of current topics and future applications. Over 200 INL staff participated in the symposium.
In the media
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