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At Snips we are running all our Voice AI models on embedded devices (like a Raspberry Pi 3) and we can also work on MCUs, and we believe that embedded ML will b

• adamdrake 8y ago
  Fully agreed. I think the privacy angle is particularly compelling, and doing on-device analytics using models that have low memory requirements and acceptable (although not academically impressive) accuracy will be the norm. I wrote about the privacy perspective a bit: https://adamdrake.com/scalable-machine-learning-with-fully-anonymized-data.html https://adamdrake.com/scalable-machine-learning-with-fully-a... and I recently gave a lecture more focused on the performance aspect: https://adamdrake.com/big-data-small-machine.html https://adamdrake.com/big-data-small-machine.html The case for doing centralized data collection and model training seems to be increasingly related to corporate greed and moat-building rather than actually providing a good experience for users.
  • endymi0n 8y ago
    Technically, on-device processing is clearly the way forward (it's interesting how Apple is currently pioneering the field in a way). The pessimist in me already sees how three letter agencies worldwide will welcome this change in order to push down their selectors to the device as well. Recording only the one percent of potentially relevant conversations will make backdoors exponentially easier to hide in the background traffic as well as being much lighter to process.