Machine Learning on Server Side with Julia and WASM

Julia is a high-performance programming language that has gained traction in the machine-learning community due to its simplicity and speed. The talk looks at how Julia can potentially be used to build machine learning models on the server using WebAssembly (WASM) and the WebAssembly System Interface in this talk (WASI) but also look at some of the major hurdles along the way. The talk will go over the benefits of using WASM and WASI for building such as improved performance and security.

As the demand for machine learning applications grows, so does the need for efficient and performant solutions. Julia is a high-performance programming language that has gained traction in the machine learning community due to its simplicity and speed. We will look at how Julia could ideally be used to build machine learning models on the server using WebAssembly (WASM) and the WebAssembly System Interface in this talk (WASI). But we will focus on what is limiting Julia from being able to do so on the backend. We will go over the benefits of using WASM and WASI for deployment, such as improved performance and security. Attendees will have a better understanding of the subject by the end of this talk.

Table of Content:

1. Introduction to server side machine learning
2. How can Julia be used for machine learning
3. What is WebAssembly (WASM) and the WebAssembly System Interface (WASI)
4. how Julia can be potentially used to build machine learning models on the server using WebAssembly (WASM) and the WebAssembly System Interface but covering some of the limitations in being able to do so.