---
title: "SZZT Electronics: The computing power operation service platform officially launched for external operation"
type: "News"
locale: "en"
url: "https://longbridge.com/en/news/242847849.md"
description: "According to the official WeChat account of SZZT, the company's self-developed computing power operation service platform has recently been officially launched for external operation. It is reported that traditional computing power resources suffer from issues such as geographical dispersion, architectural differences, and inefficient scheduling, resulting in a utilization rate of less than 40%. The SZZT computing power operation service platform builds an integrated computing power perception and scheduling private network, utilizing AI-driven intelligent scheduling algorithms, multi-level computing power network architecture, and computing power perception scheduling systems, to provide efficient computing power while saving energy and reducing carbon emissions, effectively promoting the \"flow\" of computing power"
datetime: "2025-06-03T01:46:01.000Z"
locales:
  - [zh-CN](https://longbridge.com/zh-CN/news/242847849.md)
  - [en](https://longbridge.com/en/news/242847849.md)
  - [zh-HK](https://longbridge.com/zh-HK/news/242847849.md)
---

> Supported Languages: [简体中文](https://longbridge.com/zh-CN/news/242847849.md) | [繁體中文](https://longbridge.com/zh-HK/news/242847849.md)


# SZZT Electronics: The computing power operation service platform officially launched for external operation

According to the official WeChat account of SZZT Electronics, the company's self-developed computing power operation service platform has recently been officially launched for external operation. It is reported that traditional computing power resources suffer from issues such as geographical dispersion, architectural differences, and inefficient scheduling, resulting in a utilization rate of less than 40%. The SZZT computing power operation service platform builds an integrated computing power perception and scheduling private network, utilizing AI-driven intelligent scheduling algorithms, multi-level computing power network architecture, and computing power perception scheduling systems, to provide efficient computing power while saving energy and reducing carbon emissions, effectively promoting the "flow" of computing power

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