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740: Local AI Models in JavaScript - Machine Learning Deep Dive With Xenova

Mar 8, 2024 · 1 hr 19 min
0:00-1:19:36

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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.
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