New Hardware NN Approach Using Standard CMOS Transistors

https://scitechdaily.com/ai-breakthrough-scientists-transform-everyday-transistor-into-an-artificial-neuron/
The NUS research team has now demonstrated that a single,
standard silicon transistor, when arranged and operated in
a specific way, can replicate both neural firing and synaptic
weight changes — the fundamental mechanisms of biological
neurons and synapses. This was achieved through adjusting
the resistance of the bulk terminal to specific values,
which allow controlling two physical phenomena taking place
into the transistor: punch through impact ionization and
charge trapping. Moreover, the team built a two-transistor
cell capable of operating either in neuron or synaptic
regime, which the researchers have called “Neuro-Synaptic
Random Access Memory”, or NS-RAM.
“Other approaches require complex transistor arrays or novel
materials with uncertain manufacturability, but our method
makes use of commercial CMOS"
. . .
   They CLAIM low power consumption.
   Anyway, if adaptable to the larger scale, this can
   be a useful new way to do hardware NNs.
   Of course we WILL need Linux apps to help train
   these things .......