TFLite Micro Overview

Author: tanghao-xiaomi

…rence_framework/tflite_micro_overview.md en/edge_ai_dev/tflite_micro_overview.mden/ai_inference_framework/tflite_micro_overview.md renamed to en/edge_ai_dev/tflite_micro_overview.md en/ai_inference_framework/tflite_micro_overview.md renamed to en/edge_ai_dev/tflite_micro_overview.md

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 # TFLite Micro Overview
 
-[ English | [简体中文](../../zh-cn/ai_inference_framework/tflite_micro_overview.md) ]
+[ English | [简体中文](../../zh-cn/edge_ai_dev/tflite_micro_overview.md) ]
 
 TensorFlow Lite for Microcontrollers (hereinafter referred to as TFLite Micro) is a lightweight machine learning inference framework designed by Google specifically for resource-constrained embedded devices. As a streamlined version of TensorFlow Lite, this framework is deeply optimized for the characteristics of microcontrollers (MCUs), supporting the execution of complex neural network models on devices with only tens of KB of RAM and hundreds of KB of Flash.
 

zh-cn/edge_ai_dev/tflite_micro_overview.md

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 # TFLite Micro 框架概述
 
-[ [English](../../en/ai_inference_framework/tflite_micro_overview.md) | 简体中文 ]
+[ [English](../../en/edge_ai_dev/tflite_micro_overview.md) | 简体中文 ]
 
 TensorFlow Lite for Microcontrollers（以下简称 TFLite Micro）是 Google 专为资源受限的嵌入式设备设计的轻量级机器学习推理框架。作为 TensorFlow Lite 的精简版本，该框架针对微控制器（MCU）的特性进行了深度优化，支持在仅有数十 KB RAM 和数百 KB Flash 的设备上运行复杂的神经网络模型。