Scott and Wes are joined by special guest Xenova to explore local AI models in JavaScript. From Hugging Face to Transformers.js and practical applications like real-time speech recognition and object detection, this episode dives deep into the world of machine learning. Show Notes 00:00 Welcome to Syntax! 00:41 Brought to you by Sentry.io 01:05 Who is Xenova? 02:08 What is Hugging Face? 03:29 What is Transformers.js? 06:16 How was the library developed? SponsorBlock 09:04 How is it able to run? 10:09 Do they have to run in Python and how does Onnx work? Onnx.ai Hugging Face Optimum 14:19 What are some things you can do with this tech? 16:15 Vision tools. 17:38 This is actually running locally. 18:35 Doodle Dash 21:09 They currently run on CPU, what is required to make it run on GPU? 24:44 Can you run in JavaScript? 28:32 How it works with image vectors. 34:23 Why would people want to run it in another language? 35:55 Resizing images in the browser instead of on the server. 38:55 Applications distributed on the web vs running locally. 43:54 Electron has Node and Chrome, where would you run Transformers.js? 44:32 The API of Transformers.js 46:30 Object Detection. Semantic Image Search Client Real-Time Object Detection Background Removal Tool 48:33 What is the easiest way to get started? 51:26 Real-time speech recognition on the horizon? 52:08 Will we ever be able to run Stable Diffusion via JavaScript? 56:10 The Web LLM. 57:22 Practical applications for YouTube. 59:39 What we want to build for Syntax.fm. 01:06:43 Mean pooling, why it’s necessary. 01:09:30 Stopping YouTube spam comments. 01:10:34 K-Means Clustering. Text Clustering 01:13:49 Quantization. 01:17:35 Sick Picks + Shameless Plugs. Sick Picks Xeonva: WebGPU Shameless Plugs Xenova: Xenova on X Hit us up on Socials! Syntax: X Instagram Tiktok LinkedIn Threads Wes: X Instagram Tiktok LinkedIn Threads Scott:X Instagram Tiktok LinkedIn Threads Randy: X Instagram YouTube Threads