<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Edge Computing on SoloSoft</title><link>https://www.solosoft.dev/tags/edge-computing/</link><description>Recent content in Edge Computing on SoloSoft</description><generator>Hugo</generator><language>en-us</language><atom:link href="https://www.solosoft.dev/tags/edge-computing/index.xml" rel="self" type="application/rss+xml"/><item><title>How Iran is Ending the Dream of Remote-Controlled Warfare and Reshaping the Glob</title><link>https://www.solosoft.dev/trends/2026-04-08-commentary-iran-is-ending-the-dream-of-remote-cont/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://www.solosoft.dev/trends/2026-04-08-commentary-iran-is-ending-the-dream-of-remote-cont/</guid><description>&lt;h2 id="the-drone-myth-shattered-when-ai-meets-electronic-fog"&gt;The Drone Myth Shattered: When AI Meets Electronic Fog?&lt;/h2&gt;
&lt;p&gt;&lt;strong&gt;The answer is clear:&lt;/strong&gt; When highly autonomous drone systems enter environments with powerful electronic jamming and cyberattacks, their combat effectiveness plummets, potentially failing completely. This exposes the fatal weakness of many current AI systems: their over-reliance on stable rear-area connectivity and clear data environments.&lt;/p&gt;
&lt;p&gt;Over the past decade, the global military-industrial complex and tech giants painted a future battlefield picture filled with remotely controlled vehicles operated by rear commanders via high-speed data links, with cloud-based AI performing global situational analysis and real-time dispatch. The core assumption of this model was possessing unshakable communication and network superiority. However, Iran and its proxy forces have systematically employed multi-layered electronic warfare tactics in actual combat—from GPS spoofing and communication band jamming to network intrusion—successfully blinding the &amp;ldquo;eyes&amp;rdquo; and &amp;ldquo;ears&amp;rdquo; of their adversaries&amp;rsquo; high-tech equipment.&lt;/p&gt;</description></item><item><title>Solidigm Targets AI Memory Bottleneck with Advanced Storage Technology and Ecosy</title><link>https://www.solosoft.dev/trends/2026-04-10-solidigm-targets-the-ai-bottleneck-with-advanced-s/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://www.solosoft.dev/trends/2026-04-10-solidigm-targets-the-ai-bottleneck-with-advanced-s/</guid><description>&lt;h2 id="in-the-ai-frenzy-why-has-memory-become-the-most-silent-killer"&gt;In the AI Frenzy, Why Has Memory Become the Most Silent Killer?&lt;/h2&gt;
&lt;p&gt;&lt;strong&gt;The answer is straightforward: because computing power is advancing too fast for memory to keep up.&lt;/strong&gt; While the industry focuses intently on GPU floating-point operations per second, a more fundamental limitation is emerging: the speed of data feeding. AI model parameters often reach hundreds of billions or trillions, and the massive data required for training and inference must flow efficiently through the memory hierarchy. The traditional architecture centered on DRAM, supplemented by slow hard drives, is struggling under AI workloads. This is not a problem that can be solved by upgrading a single component; it requires a complete redesign of the entire &amp;ldquo;data pipeline&amp;rdquo; from processor cache to archival storage. Solidigm&amp;rsquo;s strategy precisely targets this system-level pain point.&lt;/p&gt;</description></item></channel></rss>