SpiNNaker is an academic experiment to see if taking more cues from biology would make the models better — it turned out the answer was "nobody in industry cares" because scaling the much simpler models to bigger neural nets and feeding them more data was good enough all by itself so far.
> and they tend to be significantly more efficient
Surely you noticed that this claim is false, just from your own next line saying it needing 100 kW (not "kWh" but I assume that's auto-corrupt) for a mere billion?
Even accounting for how neuron != synapse — one weight is closer to a single synapse; a brown rat has 200e6 neurons and about 450e9 synapses — the stated 100 kW for SpiNNaker is enough to easily drive simpler perceptron-type models of that scale, much faster than "real time".
> and they tend to be significantly more efficient
Surely you noticed that this claim is false, just from your own next line saying it needing 100 kW (not "kWh" but I assume that's auto-corrupt) for a mere billion?
Even accounting for how neuron != synapse — one weight is closer to a single synapse; a brown rat has 200e6 neurons and about 450e9 synapses — the stated 100 kW for SpiNNaker is enough to easily drive simpler perceptron-type models of that scale, much faster than "real time".