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Now, as our production systems become more distributed geographically, we can push some ML capabilities to the edge.
- 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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TensorFlow.js : Bringing ML into the Browser?
Brian Sletten is a renowned consultant, speaker and software engineer with a focus on forward-leaning technologies. He provides advice and practical solutions for organizations interested in adopting disruptive technologies and concepts to their development and management.