<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Production on StorageNews</title><link>https://storagenews.top/tags/production/</link><description>Recent content in Production on StorageNews</description><generator>Hugo</generator><language>en</language><lastBuildDate>Thu, 19 Feb 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://storagenews.top/tags/production/index.xml" rel="self" type="application/rss+xml"/><item><title>Storage architecture fixes AI bottlenecks now</title><link>https://storagenews.top/posts/storage-architecture-fixes-ai-bottlenecks-now/</link><pubDate>Thu, 19 Feb 2026 00:00:00 +0000</pubDate><guid>https://storagenews.top/posts/storage-architecture-fixes-ai-bottlenecks-now/</guid><description>&lt;meta charset="utf-8">
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&lt;p class="std-text">With &lt;strong>80 percent&lt;/strong> of early AI budgets burned on compute, storage was an afterthought until data readiness emerged as the true production bottleneck. The era of treating enterprise data infrastructure as a passive utility is over; today, &lt;strong>strategic storage constraints&lt;/strong> dictate the velocity and viability of generative AI deployments more than raw GPU power ever could.&lt;/p></description></item></channel></rss>