TensorFlow.js : Bringing ML into the Browser?

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Now, as our production systems become more distributed geographically, we can push some ML capabilities to the edge.

Imagine:

• Reusing existing models in distributed and decentralized architectures
• Image and object detection from local video streams
• Event classification from IoT-based sensors
• Interact with WebAssembly-optimized code on all browsers and platforms
• Natural Language Processing of user text and audio

If models aren’t too big and can be cached, the Web architecture will happily support these new use cases.

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