Tensorflow

AI Inference for Real-time Data Streams with WasmEdge and YoMo

YoMo is a programming framework enabling developers to build a distributed cloud system (Geo-Distributed Cloud System). YoMo's communication layer is made on top of the QUIC protocol, which brings high-speed data transmission. In addition, it has a built-in Streaming Serverless “streaming function”, which significantly improves the development experience of distributed cloud systems. The distributed cloud system built by YoMo provides an ultra-high-speed communication mechanism between near-field computing power and terminals. It has a wide range of use cases in Metaverse, VR/AR, IoT, etc.…

Deploying Tensorflow models in production with less than 50 lines of code

Serverless Tensorflow functions in public clouds For software developers and students, artificial intelligence pays. In 2021, the average annual salary for Tensorflow (a popular AI framework) developers is $148,508. Skills in artificial intelligence are now mandatory in even entry level programming jobs. In fact, it is quite easily to follow an online tutorial and train your own Tensorflow model for tasks such as image recognition and natural language processing. You only need some basic Python knowledge to do the training and then run the model for a demo.…

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.…

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.…

🤖 Image recognition in Node.js

Deep learning is one of the most important advances in computer science in the last decade. Using trained deep neural networks, artificial intelligence (AI) inference algorithms can perform a variety of very useful tasks, such as image, speech, and facial recognition, natural language processing, image and video search, at unprecedented accuracy. While inference can be done on the edge device, such as mobile phones or IoT sensors, it is suggested that cloud-based inference is much faster and energy efficient in our always-connected world.…