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

'Lonely men are not our problem' RE: Hannah Cox | Maintaining Frame 122