[mafribe]

Neuromorphic has been an ongoing failure (for general purpose processors or even AI accelerators), ever since Carver Mead introduced (and quickly abandoned them) them nearly half a century ago. Bill Dally (NVidia CTO) concurs: "I keep getting those calls from those people who claim they are doing neuromorphic computing and they claim there is something magical about it because it's the way that the brain works ... but it's truly more like building an airplane by putting feathers on it and flapping with the wings!" From: Hardware for Deep Learning, HotChips 2023 keynote.

We have NO idea how the brain produces intelligence, and as long as that doesn't change, "neuromorphic" is merely a marketing term, like Neurotypical, Neurodivergent, Neurodiverse, Neuroethics, Neuroeconomics, Neuromarketing, Neurolaw, Neurosecurity, Neurotheology, Neuro-Linguistic Programming: the "neuro-" prefix is suggesting a deep scientific insight to fool the audience. There is no hope of us cracking the question of how the human brain produces high-level intelligence in the next decade or so.

Neuromorphic does work for some special purpose applications.

[chasd00]

I like the feather analogy. Early on all humans knew about flight was from biology (watching birds fly) but trying to make a flying machine modeled after a bird would never work. We can fly today but plane designs are nothing like biological flying machines. In the same way, all we know about intelligence comes from biology and trying to invent an AGI modeled on biological intelligence may be just as impossible as a plane designed around how birds fly.

/way out of my area of expertise here

[quotemstr]

And it's only now, having built our own different kind of flying machine, that we understand the principles of avian flight well enough to build our own ornithopters. (We don't use ornithopters because they're not practical, but we've known how to build them since the 1960s.) We would have never gotten here had we just continued to try to blindly copy birds.