Emissions
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.
- Xeonva: WebGPU
- Xenova: Xenova on X
Syntax: X Instagram Tiktok LinkedIn Threads
Wes: X Instagram Tiktok LinkedIn Threads
