Competitive landscape, page-2957

I have said this before but the conversation here keeps either
1) ignoring BRN best fit is way ahead of any competition
2) Is nowhere near the answer to everything in Ai or computing in general

What does BRN/Akida do better.........

1) spiking neural networks. Anything associated with a change in the data in a short period of time.
2) Very low energy cost for tracking and responding to small data changes
3) The ability to learn as in: take account of the new data as a new reference point, at the edge.

What Akida does not do better.........

a) sensors - visual or radar data gathering
b) comparison to a massive settled db of rules (CNN), as in go/Chess/Language(text) translation
c) compute in memory (which is not in production anywhere anyway)
d) analog - low precision calculation
e) memory in general
f) heavy-duty cloud computing

The net is that Akida appears critical for Electric Vehicle mileage increases between recharge because of its low energy needs and time-sensitive SNN.
There are around 70m vehicles produced a year.
That is the key market and the Mercedes concept car demonstrated the mileage gain that is achievable without detailing how much was due to Akida.
It isn't the only possible app...refrigerators....air conditioning....DYOR
So keep focus and await evidence of IP being used in automotive or anywhere else, and ignore the areas put about by downrampers about where BRN/Akida is not a player or intends to be one.
DYOR.
IMO.