Brains do not really grow new pathways, they are more or less set in stone after development finishes.
The goal of neuromorphic chips is also not to replace operating systems for the same reason that quantum computers won't replace conventional ones. They have strong sides and weak sides.
When you say that all the networks are is inspired by biology, it is true, but varies hugely between implementations.
Boahen is of the "true" neuromorphic school, people who use actual analog silicon neurons. These people are exclusively found in academia as all of industry only uses digital techonology. This includes the coveted IBM TrueNorth "neuromorphic" processor.
Thus the goal of these projects is not just to create supercomputing architectures, but to create systems that mimic the way the brain works and thereby learn how it manages to perform all these complex operations.
> Brains do not really grow new pathways, they are more or less set in stone after development finishes.
Neuroplasticity and Neurogenesis has been observed well into adulthood though [1].
> Thus the goal of these projects is not just to create supercomputing architectures, but to create systems that mimic the way the brain works and thereby learn how it manages to perform all these complex operations.
Sounds like a lot of expensive guesswork to me! Good luck to them I guess.
There have been successes of this line of research. For example, touchpads and Synaptics came from thinking about how to build analog capacitor networks [0]. There are spiking cameras that can produce significantly higher range and temporal resolution than conventional approaches [1]. Like neural networks, the field sort of quieted down in the 90s but perhaps now is a new time for the field.
If you view the purpose of academics to train the next generation rather than simply advancing the field, the quality of reasearchers and engineers that come out of Kwabenas lab is superb. They easily work at companies like Intel, SpaceX, NIH, etc.
Very true, but the neuroplasticity observed is markedly different from forming entirely new pathways. It is more like changing the weights of a network already in place.
The neurogenesis is also limited to the hippocampus and olfactory bulb. Your cortex does not have a steady supply of new cells.
Making these chips is really not all that expensive. Most groups produce only test chips in multi-project wafer runs, with a cost of 1-5k$ per chip. It is just like normal research, you have to make up experiments and then actually do them. So far there are a substantial number of successes in the domain of low-power neural networks.
The goal of neuromorphic chips is also not to replace operating systems for the same reason that quantum computers won't replace conventional ones. They have strong sides and weak sides.
When you say that all the networks are is inspired by biology, it is true, but varies hugely between implementations.
Boahen is of the "true" neuromorphic school, people who use actual analog silicon neurons. These people are exclusively found in academia as all of industry only uses digital techonology. This includes the coveted IBM TrueNorth "neuromorphic" processor.
Thus the goal of these projects is not just to create supercomputing architectures, but to create systems that mimic the way the brain works and thereby learn how it manages to perform all these complex operations.