Merge pull request #22 from ibelem/fix-400x

Reducing Web AI Framework Overhead by 99%

Author: ibelem

content/en/blog/onnx2webnnreducing-web-ai-framework-overhead-by-400x.mdx

@@ -1,5 +1,5 @@
 ---
-title: ONNX2WebNN - Reducing Web AI Framework Overhead by 400x
+title: ONNX2WebNN - Reducing Web AI Framework Overhead by 99%
 description:
   'WebNN is a privacy-first browser API enabling hardware-accelerated, client-side AI inference. While frameworks 
   offer convenience, they inflate bundle sizes (2-20 MB) and slow startup. Alternatively, using WebNN directly in 
@@ -18,7 +18,7 @@ import InfoIcon from '../../../app/_components/icons/info.jsx'
 
 <TopContent lang={props.params.lang} {...metadata} />
 
-![ONNX2WebNN - Reducing Web AI Framework Overhead by 400x](/blog/onnx2webnn/article.png)
+![ONNX2WebNN - Reducing Web AI Framework Overhead by 99%](/blog/onnx2webnn/article.png)
 
 Machine learning in web browsers has come a long way from the early days of running everything on CPUs through JavaScript. The Web Neural Network (WebNN) API represents the latest evolution - a browser standard that taps directly into hardware acceleration, whether that's your CPU, GPU, or NPU.
 

content/zh/blog/onnx2webnnreducing-web-ai-framework-overhead-by-400x.mdx

@@ -1,5 +1,5 @@
 ---
-title: ONNX2WebNN - 将 Web AI 框架开销减少 400 倍
+title: ONNX2WebNN - 将 Web AI 框架开销降低至 1/400
 description:
   'WebNN 是一个隐私优先的浏览器 API，支持硬件加速的客户端 AI 推理。虽然框架提供了便利，但它们会增加包大小（2-20 MB）并减慢启动速度。
   相比之下，直接在原生 JavaScript 中使用 WebNN 的开销极小（数十到数百 KB）。ONNX2WebNN 和基于浏览器的代码生成器等工具可以自动将 ONNX 模型
@@ -17,7 +17,7 @@ import InfoIcon from '../../../app/_components/icons/info.jsx'
 
 <TopContent lang={props.params.lang} {...metadata} />
 
-![ONNX2WebNN - 将 Web AI 框架开销减少 400 倍](/blog/onnx2webnn/article.png)
+![ONNX2WebNN - 将 Web AI 框架开销降低至 1/400](/blog/onnx2webnn/article.png)
 
 浏览器中的机器学习从早期依赖 JavaScript 在 CPU 上运行的时代至今，已经取得了长足的进步。Web 神经网络（WebNN）API 代表了最新的演进 - 一个直接利用硬件加速的 Web 标准，无论是 CPU、GPU 还是 NPU。