An experiment about portable "intelligence"

The experiment

  • A Python script to scale all images to 200x200, standardizing the colorspace and format.
  • A convolutional neural network for extracting the features that define if an image is a render or a real house, I didn't want to do any type of feature engineering or image processing apart from scaling.
  • For this purpose I decided to use Keras on top of Tensorflow. Keras is a high-level deep learning library, well documented and written in ❤️ Python. It abstract many of the complexities if you would write code your directly in Tensorflow. Many thanks to François Chollet for his contribution :)
  • Do all the inference client side in the browser using Keras.js a Javascript implementation of Keras.
  • Train the model on my own GPU at home (Nvidia GTX 1080).
  • The site is built using Next.js framework.

The result

https://rendernet.abarmat.com

What do I like about all this?

  • Privacy: If you don't need to send your data to a server, your data is protected as all decision making is done right on your device.
  • Decentralization: All these models working as standalone agents mean that they will be resilient to server outages, network delays, and censorship.
  • Online learning: Learning is a slow process, but with future improvements in dedicated processors we could have millions of devices learning different strategies which will add diversity to avoid having a single machine-learning model failing massively on certain decisions. Much like we humans learn from our different experiences.

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Tech entrepreneur. Enjoy building things and making them real. Love technology & science, fascinated about the secrets of the human mind. https://abarmat.com

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Ariel Barmat

Ariel Barmat

Tech entrepreneur. Enjoy building things and making them real. Love technology & science, fascinated about the secrets of the human mind. https://abarmat.com

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