radoye

3 ms·

1. 1.▲
   by radoye 8y 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 t
2. 2.▲
   by radoye 8y 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
3. 3.▲
   by radoye 8y ago

   That depends on your choice of training framework and runtime engine (TF Lite/TF Mobile/Numericcal/Caffe2/etc.). We wrapped multiple runtime engines to provide as much flexibility as possible, quickly. For example, some
4. 4.▲
   by radoye 8y ago

   Exactly, there is a lot of potential on the Edge, but dealing with fragmentation is really painful.
5. 5.▲
   by radoye 8y ago

   I'm quite interested in hearing how things turn out. Let us know if you write/release something.
6. 6.▲
   by radoye 8y ago

   Yeah, as the cloud/edge interface settles we plan to build SDKs for pulling models from iOS, GNU/Linux through Swift, Python and C#. Let me check your repo.
7. 7.▲
   Launch HN: Numericcal (YC.S18) – Lifecycle Management for ML Models on the Edge

   49 points by radoye 8y ago|13 comments