edgetpu VS scrypted

I know the tensor power pixelbook was shutdown and I never heard the actual reason just a bunch of speculation about costs/profitability which is probably true.

It's a shame that there isn't more competition and development in the neural asic world to harness the power of llms/generative AI on a low power, cheap hardware platform like the pixelbook line. For someone that invented the TPU they have done a not so great job of ensuring it's commercialization and support. Both on the hardware and software side.

The coral edge tpu seemed to be the right high level idea but without proper execution.

https://github.com/google-coral/edgetpu/issues/668

> even in the 80s I wanted an FPGA accelerators in every machine

Mostly unrelated, but I recently discovered that you can buy TPUs, right now, as a consumer product, from https://coral.ai.

The stock firmware already allows you to run these things so hard they overheat, which is amazing.

But yes, I also want FPGA accelerators.

I'm looking at the coral.ai cards and they have a M.2 A+E card, same form factor as the wifi slot in the m900 tiny. Has anyone tried another card in that slot other than wifi?

Chips optimized to perform the type of calculations used for NN inference at high parallelism. A good example would be the google spinoff https://coral.ai/ (though their usecase is highly limited by sub-par software constraints)

By no means an expert, but I have seen prototypes using a raspberry pi and a dongle from Coral Ai. They have PCIE and USB based modules.

Last news on https://coral.ai/ was on May 5 2022

Activity on the github project seems to have stopped. https://github.com/google-coral

    https://coral.ai/

Your problem statement still needs more clarification. If the above applies, the best way is to evaluate your ML-based pattern matcher on high-level scenarios. One approach to speed up the evaluation is to lift and shift the execution of scenarios into cloud. Another approach is to use an AI accelerator, such as http://coral.ai or other.

You probably could but not with raspis. Maybe the TPUs they sell. https://coral.ai/

lazyweb: https://github.com/koush/scrypted (regrettably the licensing is "it depends" https://github.com/koush/scrypted/blob/v0.93.0/LICENSE.md#li... )

and don't overlook that user's other repos, as seems like there are quite a few fun things in there: https://github.com/koush?tab=repositories

I have taken a look at the page for debugging steps for Homekit recording and haven’t played with any setting mentioned there.

Unfortunately the options for HKSV doorbells is fairly limited. The Logitech circle view Doorbell looks like the best candidate but it has a spotty review history, with the biggest complaint being it breaking in direct sunlight.

I’m about to buy some cameras and I’m thinking of just buying Nest and using https://scrypted.app to bridge to HKSV.

In the demo video linked to from the Scrypted Github repo, the author has some kind of a delivery box (visible in the top camera), with a camera inside the box in night vision mode, able to report on whether there’s anything in the box. Does anyone know how this setup was achieved, or have done something similar to combine a camera with a closed delivery box?

You can migrate the scrypted setup with this: https://github.com/koush/scrypted/wiki/Scrypted-Backup-and-Restore

I see two options, both from brands that seem to be well-received on the brand report card.

You might want to try setting them up with Scrypted then use the plugin to get them into Homebridge.