Lh64nneadcpikhkfj4oj
SkillsCast

TensorFlow.js : Bringing ML into the Browser?

5th July 2018 in London at CodeNode

There are 22 other SkillsCasts available from Infiniteconf 2018 - The conference on Big Data and AI

Please log in to watch this conference skillscast.

711792374 640

The numerics of machine learning seem like the least likely thing you would expect to run in a browser. The recently-released TensorFlow.js will provide exactly that, however. This Javascript implementation of the TensorFlow APIs is backed by GPU-accelerated WebGL and the optimizations available to modern Javascript engines.

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.

YOU MAY ALSO LIKE:

Thanks to our sponsors

TensorFlow.js : Bringing ML into the Browser?

Brian Sletten

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.

SkillsCast

Please log in to watch this conference skillscast.

711792374 640

The numerics of machine learning seem like the least likely thing you would expect to run in a browser. The recently-released TensorFlow.js will provide exactly that, however. This Javascript implementation of the TensorFlow APIs is backed by GPU-accelerated WebGL and the optimizations available to modern Javascript engines.

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.

YOU MAY ALSO LIKE:

Thanks to our sponsors

About the Speaker

TensorFlow.js : Bringing ML into the Browser?

Brian Sletten

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.

Photos