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	<title>scattering media &#8211; BIOENGINEER.ORG</title>
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		<title>Light-Powered Learning: Chip Trains Itself With Physical Gradient Descent</title>
		<link>https://bioengineer.org/light-powered-learning-chip-trains-itself-with-physical-gradient-descent/</link>
		
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		<pubDate>Mon, 05 Oct 2026 16:01:42 +0000</pubDate>
				<category><![CDATA[Technology]]></category>
		<category><![CDATA[energy-efficient computing]]></category>
		<category><![CDATA[gradient descent]]></category>
		<category><![CDATA[holography]]></category>
		<category><![CDATA[in situ training]]></category>
		<category><![CDATA[inverse design]]></category>
		<category><![CDATA[meta-learning]]></category>
		<category><![CDATA[Nature Computational Science]]></category>
		<category><![CDATA[neuromorphic computing]]></category>
		<category><![CDATA[optical neural networks]]></category>
		<category><![CDATA[photonic integrated circuits]]></category>
		<category><![CDATA[photonics]]></category>
		<category><![CDATA[scattering media]]></category>
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					<description><![CDATA[Researchers have demonstrated a photonic chip that trains itself on the hardware using on-chip holography to compute physical gradients, achieving 0.26 percent error and dramatic gains in model compression and training speed.]]></description>
		
		
		
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