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.

• 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.

• Xeonva: WebGPU

• Xenova: Xenova on X

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