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
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