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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