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Image Classification as A Service in Node.js
In the previous article, we discussed how WebAssembly could tie together native TensorFlow, Node.js JavaScript, and Rust functions to create high performance and safe web services for AI. In this article, we will discuss how to apply this approach to ImageNet's MobileNet image classification model, and more importantly, how to create web applications for your own retrained MobileNet models. NOTE This article demonstrates how to call operating system native programs from the SSVM.…
RustJavaScripttensorflowWebAssemblyNode.jsAI as a serviceFaaSAIImage Classification
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High performance and safe AI as a Service in Node.js
Today’s dominant programming language for AI is Python. Yet, the programming language for the web is JavaScript. To provide AI capabilities as a service on the web, we need to wrap AI algorithms in JavaScript, particularly Node.js. However, neither Python nor JavaScript by itself is suitable for computationally intensive AI applications. They are high-level, ie, slow, languages with heavy-weight runtimes. Their ease-of-use comes at the cost of low performance. Python got around this by wrapping AI computation in native C/C++ modules.…
RustJavaScripttensorflowWebAssemblyNode.jsAI as a serviceFaaSAIFace detection
