<?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 The Coders Blog</title><link>https://thecodersblog.com/tag/edge-computing/</link><description>Recent content in Edge Computing on The Coders Blog</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Sun, 10 May 2026 11:02:35 +0000</lastBuildDate><atom:link href="https://thecodersblog.com/tag/edge-computing/index.xml" rel="self" type="application/rss+xml"/><item><title>On-Device AI: Building Real-World Applications with LiteRT and NPU</title><link>https://thecodersblog.com/on-device-ai-with-litert-and-npu-2026/</link><pubDate>Sun, 10 May 2026 11:02:35 +0000</pubDate><guid>https://thecodersblog.com/on-device-ai-with-litert-and-npu-2026/</guid><description>&lt;p&gt;The promise of Artificial Intelligence is no longer confined to massive data centers or the nebulous cloud. It&amp;rsquo;s rapidly becoming a tangible, responsive presence directly on our mobile devices, unlocking new frontiers in user experience, privacy, and real-time intelligence. At the heart of this on-device AI revolution lies the ever-increasing power of Neural Processing Units (NPUs), dedicated hardware accelerators designed to crunch through AI workloads with unprecedented efficiency. Enter LiteRT, a framework that, according to its recent announcement, aims to harness this power for production-ready on-device AI across mobile, desktop, and IoT. But does it live up to the hype, especially when the technical blueprints are still largely under wraps?&lt;/p&gt;</description></item></channel></rss>