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      <title>Teaching AI to Find Needles in a Molecular Haystack</title>
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      <pubDate>Sun, 21 Jun 2026 00:00:00 +0800</pubDate>
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      <description>&lt;p&gt;Imagine being handed a box containing more objects than there are stars in the observable universe — and being told that somewhere inside it lies a material that could make batteries last ten times longer, or a molecule that kills antibiotic-resistant bacteria. You get to test a few hundred items before your budget runs out. Good luck.&lt;/p&gt;&#xA;&lt;p&gt;That, roughly speaking, is the problem facing chemists who search for new molecules. The space of synthesizable chemical compounds is estimated to exceed 10⁶⁰ candidates — a number so large it mocks the very idea of systematic search. For decades, discovering a useful new molecule has been a mixture of chemical intuition, educated guesswork, and sheer persistence. Now, a team from Los Alamos National Laboratory and Georgia Tech has built an AI system that learns how to search — and it&amp;rsquo;s dramatically better than anything we&amp;rsquo;ve had before.&lt;/p&gt;</description>
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