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		<title>Artificial Intelligence for Nuclear Deterrence Strategy</title>
		<link>https://globalsecurityreview.com/artificial-intelligence-for-nuclear-deterrence-strategy/</link>
					<comments>https://globalsecurityreview.com/artificial-intelligence-for-nuclear-deterrence-strategy/#respond</comments>
		
		<dc:creator><![CDATA[GSR Staff]]></dc:creator>
		<pubDate>Fri, 07 Jun 2024 14:07:30 +0000</pubDate>
				<category><![CDATA[AI & Deterrence]]></category>
		<category><![CDATA[AI]]></category>
		<category><![CDATA[artificial intelligence]]></category>
		<category><![CDATA[autonomous decisions. battlebots]]></category>
		<category><![CDATA[machine learning]]></category>
		<category><![CDATA[ML]]></category>
		<category><![CDATA[nuclear capabilities]]></category>
		<category><![CDATA[Nuclear Deterrence]]></category>
		<category><![CDATA[Nuclear Weapons]]></category>
		<category><![CDATA[quantum computing]]></category>
		<category><![CDATA[quantum theory]]></category>
		<category><![CDATA[robot missiles]]></category>
		<guid isPermaLink="false">https://globalsecurityreview.com/?p=28050</guid>

					<description><![CDATA[<p>The document &#8220;Artificial Intelligence for Nuclear Deterrence Strategy 2023&#8221; outlines the Advanced Simulation and Computing (ASC) program&#8217;s strategy to integrate artificial intelligence (AI) and machine learning (ML) into the U.S. nuclear deterrence mission. Here are the key points: Foreword and Executive Summary: The ASC program has utilized high-performance computing for nearly three decades to support [&#8230;]</p>
<p><a href="https://globalsecurityreview.com/artificial-intelligence-for-nuclear-deterrence-strategy/">Artificial Intelligence for Nuclear Deterrence Strategy</a> was originally published on <a href="https://globalsecurityreview.com">Global Security Review</a>.</p>
]]></description>
										<content:encoded><![CDATA[<p>The document &#8220;Artificial Intelligence for Nuclear Deterrence Strategy 2023&#8221; outlines the Advanced Simulation and Computing (ASC) program&#8217;s strategy to integrate artificial intelligence (AI) and machine learning (ML) into the U.S. nuclear deterrence mission. Here are the key points:</p>
<ol>
<li><strong>Foreword and Executive Summary</strong>:
<ul>
<li>The ASC program has utilized high-performance computing for nearly three decades to support U.S. nuclear deterrence following the 1992 ban on underground nuclear testing.</li>
<li>The integration of AI technologies aims to accelerate problem-solving for national security challenges.</li>
<li>The strategy emphasizes combining AI with existing modeling and simulation capabilities to enhance the U.S. Stockpile Stewardship Program.</li>
</ul>
</li>
<li><strong>AI4ND Strategy Objectives</strong>:
<ul>
<li>Apply AI methods to nuclear security missions, focusing on design, production, and analysis.</li>
<li>Develop ML tools to function with limited data and stringent accuracy requirements.</li>
<li>Create scalable and secure data infrastructures to support ML applications.</li>
<li>Foster a data-driven workforce by investing in training and developing expertise in AI and ML.</li>
</ul>
</li>
<li><strong>Motivations for AI in Nuclear Deterrence</strong>:
<ul>
<li>AI can reduce time for material discovery, model development, manufacturing, and maintenance.</li>
<li>AI/ML technologies promise to enhance the efficiency and responsiveness of the nuclear weapons lifecycle, including discovery, design optimization, manufacturing, certification, and maintenance.</li>
</ul>
</li>
<li><strong>Enabling Capabilities and Investment Areas</strong>:
<ul>
<li><strong>Physics-Informed Machine Learning (PIML)</strong>: Embedding physical constraints in ML models to ensure accuracy and speed in simulations.</li>
<li><strong>Limited and Sparse Data Sets</strong>: Developing methods to work with limited experimental data and augmenting it with simulations.</li>
<li><strong>Verification, Validation, Uncertainty Qualification, and AI Trustworthiness</strong>: Ensuring AI models are reliable and explainable, integrating existing verification practices.</li>
<li><strong>Data Infrastructure</strong>: Investing in performant data storage, federated data environments, and flexible data access interfaces.</li>
<li><strong>Machine Learning Architectures and Systems</strong>: Developing high-performance ML systems integrated with existing HPC platforms.</li>
</ul>
</li>
<li><strong>Workforce, Collaborations, and Partnerships</strong>:
<ul>
<li>Establishing partnerships with industry, academia, and other U.S. government agencies to leverage external advancements in AI/ML.</li>
<li>Developing international collaborations with similar programs in France, the UK, and Japan.</li>
<li>Building a capable workforce through training programs and collaboration with universities.</li>
</ul>
</li>
<li><strong>Conclusion</strong>:
<ul>
<li>The successful execution of this AI4ND strategy will enhance the ASC program&#8217;s ability to meet national security needs, increase efficiency, and attract specialized talent.</li>
<li>Collaboration with academia, industry, and other government agencies is crucial to achieving these goals.</li>
</ul>
</li>
</ol>
<p>The document emphasizes the transformative potential of AI in ensuring a secure and reliable nuclear deterrent through strategic investments in technology, data infrastructure, and workforce development. Get the <a href="https://psaap.llnl.gov/file-download/download/public/1146#:~:text=DETERRENCE%20MISSION,-AI%20and%20ML&amp;text=AI%2FML%20are%20technologies%20that,and%20surveillance%20of%20ND%20systems.">report</a>.</p>
<p>&nbsp;</p>
<p>&nbsp;</p>
<p><a href="https://globalsecurityreview.com/artificial-intelligence-for-nuclear-deterrence-strategy/">Artificial Intelligence for Nuclear Deterrence Strategy</a> was originally published on <a href="https://globalsecurityreview.com">Global Security Review</a>.</p>
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