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by zitterbewegung 2878 days ago
Your project sounds really interesting. Machine learning models that can be updated and treated more like packages will really give people an edge over people who can't perform that task.

I made a project called mms2concept. What it would do is given a picture taken by a phone (or anything that could send an MMS really) and it would attempt to identify the image based on the picture. I used Clarfai and Twilio to do this.

I think with very resource constrained edge devices either you would have a much more powerful "basestation" style deployments where you have an arduino or similar device collecting edge data and sending it back to that "basestation".
1 comments
radoye 2878 days ago
Can you share some writeup or repo for your project?

We internally have an auto-migration tool (currently very primitive) that can learn from cloud hosted model and cache it locally on the device (that's what this infra & packaging was built for ;)).

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zitterbewegung 2878 days ago
A writeup is at https://steemit.com/twilio/@zitterbewegung/mms2text-let-your....

I have a repository of the software at https://github.com/zitterbewegung/mms2text .

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radoye 2878 days ago
For some reason, your quick demo reminded me of this awesome MS project: https://www.microsoft.com/en-us/seeing-ai

Though we would be pushing it the boundary with 3+ DNNs on mobile, adding speech2text and text2speech to your app would make it an interesting addition to Seeing-AI, IMO.

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