LULuxonis-Brandon·Jul 8, 2020
Thanks for the kind words. Brandon the founder here. :-)
So although I could see how that quote could appear like that, the quote is not kissing the ring. We scoured the whole semiconductor start up scene to find a chip that could be used for this.
There are only 2 chips (as I'm aware, as of this writing) that can be used in such a way:
1. Intel Movidius Myriad X
2. Inuitive NU4000AI.
And the Inuitive, until super recently (i.e. 1.5 years after we have already built hardware off the Myriad X) was not ready to be used (had tape-out issues at the fab).
So this made the Myriad X the only chip that (1) had the capabilities needed and (2) was actually available and in production.
In terms of our open-source nature, the latter is what we've implemented - where we have closed source binaries running on the Myriad X - which then have a slew of
Read the rest
open-source counterparts on the host. Sorry if this came off disingenuous. Do you have advice on how to phrase it in a better way?
https://github.com/luxonis/depthai-hardware - DepthAI hardware designs themselves.
https://github.com/luxonis/depthai - Python Interface and Examples
https://github.com/luxonis/depthai-api - C++ Core and C++ API
https://github.com/luxonis/depthai-ml-training - Online AI/ML training leveraging Google Colab (so it’s free)
https://github.com/luxonis/depthai-experiments - Experiments showing how to use DepthAI.
The above includes open source hardware, core capabilities in C++ which can be cross-compiled for various hosts, and open-source training notebooks and use-case examples.
So the goal of open-sourcing all that we can (including hardware) is to enable folks who have their own applications to leverage this, modify it, use it, etc. w/out having to even talk to us. We cannot open-source the code that runs on the Myriad X however, as then we wouldn't have a way to monetize, and would have to give up on the mission. (That, and we're also not allowed to.)
Thoughts?
Thanks,
Brandon