Interesting - spiking neurons or sigmoidal neurons as referenced in Milestone 2 reference paper. http://papers.nips.cc/paper/1307-noisy-spiking-neurons-with-temporal-coding-have-more-computational-power-than-sigmoidal-neurons.pdf
I have always taken the use of the word neurons when making comparisons as being on an equivalent computational power basis so it is comparing apples with apples.
What seems to be missing from your technology due diligence is the Spikenet acquisition and the work of Simon Thorpe as well as the subsequent acquisition of exclusive rights to the jAST rules.
My take has been that as SNAP64 was ready to be put on Silicon in 2015 the integration of Spikenet old and new technology has been integrated to a very high degree it has taken almost 3 years and much shareholder pain. Brain Studio and accelerator was all Spikenet and Simon Thorpe had already demonstrated the FPGA.
The new Portfolio Patent which is expected to result in 18 new patents has not been published so we don't know the extent that SNAP64 has been modified to create a new Akida Spiking Neuron and its equivalence in computational per Sigmoidal Neuron
For AI at the edge and considering the neural net is configurable to the size needed for the function 1.2 million Sigmoidal neuron network equivalent delivers more than enough AI at the edge and probably enough to also have network cybersecurity on the chip which I see as essential.
Anyway keep up the due diligence
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