Artificial Intelligence and Machine Learning
INL applies modern computing capabilities to research and development, with critical implications for nuclear energy, integrated energy and national security.
Artificial intelligence is accelerating human advancements because generative AI works differently than the computing we’ve relied on for decades. Rather than simply storing and retrieving information, AI models learn, reason and generate. INL is well positioned to support AI efforts in scientific discovery, national security, advanced manufacturing, energy dominance and other mission-critical areas.
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. Machine learning 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 News | Artificial Intelligence
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