I can't find much information about Novumind (NovuTensor is their product) nor Cambricon. NovuTensor seems to be only doing inference , and only a specific type of inference (judging from their hardware, probably only images), which is a lot simpler to speed up than the training that TPUs do.

I'd take the statement "Unknown Chinese company beating Google with fewer resources and less time" with a huge grain of salt.

FWIW, there are other small companies that have made amazing chips, like Adapteva and REX Computing.

Uhhh.

NovuMind only does 3x3 convolutions. Literally a hard burnt ASIC. Also, the TPU's efficiency is close. (Btw both their "FLOPs/watt " numbers are useless, they don't account for utilization)

And Cambricon... well, I'll just leave it at that...

I don't think that relevant. For running NNs, this is pretty much all what you need from an asic hardware - raw floating point matrix multiplications per second. And measuring how much power it takes for it to do so is a good measure of power efficiency.

Pretty sure the novumind chip has hard coded the Winograd 3x3 convolution algorithm.

You seem to be pretty knowledgeable in the subject. Are you someone working in the field? IC designer?

psst, click their username: "Founder of a deep learning chip startup called Vathys.ai (YC Winter 2018)."

:)

(Edited to answer the below question: Dave Andersen - http://www.cs.cmu.edu/~dga/

I'm back at CMU full time, but was having too much fun at Google to quit entirely.)

Yup, guilty as charged :)

EDIT: Question answered :)

Yep, Vathys; W18