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Sigh.
So it turns out we've mapped the neural connectome of Drosophila *and simulated it in silico*.
Pop-sci explainer here:
Key quote: "The step from a complete connectome to a working computational brain model is not trivial." And there's an even more important finding in this screenshot (alt text via OCR):
"The wiring is the computation".
/1
@cstross I think I'm going to have to read that a few times to understand if
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The experimenters then went on to hook up their Drosophila connectome to an anatomically detailed Drosophila body model within an open-source physics engine that "uses generalized coordinates and constraint-based contact dynamics to simulate rigid-body systems with high fidelity" including joint and antennae modeling and accurate modeling of surface adhesion—and compound eye simulation.
Lots of *really* interesting insights here.
/2
@cstross not lobsters then....
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Sigh.
So it turns out we've mapped the neural connectome of Drosophila *and simulated it in silico*.
Pop-sci explainer here:
Key quote: "The step from a complete connectome to a working computational brain model is not trivial." And there's an even more important finding in this screenshot (alt text via OCR):
"The wiring is the computation".
/1
@cstross Oh gods, Peter Watts was right.
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They managed to run a feedback loop between the full 127,400 neuron network in the biological connectome to the physical simulation, with feedback from proprioceptive signals received by the model "fly" in the simulation producing feedback spile trains in the simulation, and THEY GOT RESULTS (again, see alt text of screencap: it's too verbose for a toot):
/3
There is stuff missing, of course (alt text for screencap contains about 3 toots' worth of text explaining this): information about how the motor neurons connect to physical features of the body like the muscles, information on morphologically divergent neurons and fine detail on dendritic branching and synaptic inputs across dendritic compartments:
/4
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There is stuff missing, of course (alt text for screencap contains about 3 toots' worth of text explaining this): information about how the motor neurons connect to physical features of the body like the muscles, information on morphologically divergent neurons and fine detail on dendritic branching and synaptic inputs across dendritic compartments:
/4
... The next step on from Drosophila, the mouse brain, is 560 times larger—never mind a vastly more complex human brain. And to get the murine connectome we'll have to chop up *a lot* of brains: a human upload won't pass any kind of medical ethics review at this point!
But near-term, it's expected to yield "fundamentally new architectural principles for AI systems that are more sample-efficient, more robust, and more capable of behavioral generalization than current approaches"
/5
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... The next step on from Drosophila, the mouse brain, is 560 times larger—never mind a vastly more complex human brain. And to get the murine connectome we'll have to chop up *a lot* of brains: a human upload won't pass any kind of medical ethics review at this point!
But near-term, it's expected to yield "fundamentally new architectural principles for AI systems that are more sample-efficient, more robust, and more capable of behavioral generalization than current approaches"
/5
But I'm REALLY HAPPY right now because this kinda-sorta validates the key premise of the SF novel I just handed in last month (which involves serial reincarnation via destructive brain-slicing-and-imaging then imprinting onto an immature cortex, and then explores its disastrous societal failure modes).
... And it also hints that artificial consciousness might, eventually, be possible, if only via the hard path of doing it the same way we do it, only in simulation in silico.
/6 (ends)
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But I'm REALLY HAPPY right now because this kinda-sorta validates the key premise of the SF novel I just handed in last month (which involves serial reincarnation via destructive brain-slicing-and-imaging then imprinting onto an immature cortex, and then explores its disastrous societal failure modes).
... And it also hints that artificial consciousness might, eventually, be possible, if only via the hard path of doing it the same way we do it, only in simulation in silico.
/6 (ends)
@cstross very cool, thanks for sharing!
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Sigh.
So it turns out we've mapped the neural connectome of Drosophila *and simulated it in silico*.
Pop-sci explainer here:
Key quote: "The step from a complete connectome to a working computational brain model is not trivial." And there's an even more important finding in this screenshot (alt text via OCR):
"The wiring is the computation".
/1
@cstross apparently Aristotle was right about substance and essence
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But I'm REALLY HAPPY right now because this kinda-sorta validates the key premise of the SF novel I just handed in last month (which involves serial reincarnation via destructive brain-slicing-and-imaging then imprinting onto an immature cortex, and then explores its disastrous societal failure modes).
... And it also hints that artificial consciousness might, eventually, be possible, if only via the hard path of doing it the same way we do it, only in simulation in silico.
/6 (ends)
@cstross Agreed that artificial consciousness might be possible from the bottom up, starting with agency and a complete model.
I don't believe for a picosecond that current LLMs (or other AI) are conscious.
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@cstross not lobsters then....
@robcornelius The Lobster stomatogastric ganglion sim happened in the 1990s. That's where I got the idea for "Lobsters" (written 1997/98) from.
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@cstross very cool, thanks for sharing!
@mwl Also very cool, the Indian sci/tech news website that ran that feature! (From the writing style I initially thought it might be AI slop, but no: Indian English is just a bit different.)
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There is stuff missing, of course (alt text for screencap contains about 3 toots' worth of text explaining this): information about how the motor neurons connect to physical features of the body like the muscles, information on morphologically divergent neurons and fine detail on dendritic branching and synaptic inputs across dendritic compartments:
/4
@cstross
Also shows that much "AI" terminology is marketing, not science. Computer "AI" doesn't have Neural Networks (it's a distributed dataflow database) nor "learning".I've suspected this result for decades.
"Uploading" human consciousness is still SF based on Transhumanism, which is a religion, not science.
I doubt it will yield anything for computer AI. Except current LLM based AI is a dead end.
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@cstross Agreed that artificial consciousness might be possible from the bottom up, starting with agency and a complete model.
I don't believe for a picosecond that current LLMs (or other AI) are conscious.
I absolutely agree.
At best, what current LLMs are is evidence that linguistic processing follows statistically modelable rules.
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But I'm REALLY HAPPY right now because this kinda-sorta validates the key premise of the SF novel I just handed in last month (which involves serial reincarnation via destructive brain-slicing-and-imaging then imprinting onto an immature cortex, and then explores its disastrous societal failure modes).
... And it also hints that artificial consciousness might, eventually, be possible, if only via the hard path of doing it the same way we do it, only in simulation in silico.
/6 (ends)
@cstross Does that make your work Science Fact-ion instead of Science Fiction?
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Sigh.
So it turns out we've mapped the neural connectome of Drosophila *and simulated it in silico*.
Pop-sci explainer here:
Key quote: "The step from a complete connectome to a working computational brain model is not trivial." And there's an even more important finding in this screenshot (alt text via OCR):
"The wiring is the computation".
/1
@cstross "the wiring is the computer" is not too surprising. Years ago playing w/ algorithms for FPGA, needed to invent a bit-string perfect hash table. One way of doing a perfect hash function/table involves a matrix and offset, H = Mx + v, but our math needed to be boolean (AND, XOR), a "1" coefficient was a wire, and if we wanted a one-cycle hash index, then we needed no more 1's in a row than maximum inputs to an FPGA XOR. So, a sparse boolean matrix. The wiring was the computation..
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But I'm REALLY HAPPY right now because this kinda-sorta validates the key premise of the SF novel I just handed in last month (which involves serial reincarnation via destructive brain-slicing-and-imaging then imprinting onto an immature cortex, and then explores its disastrous societal failure modes).
... And it also hints that artificial consciousness might, eventually, be possible, if only via the hard path of doing it the same way we do it, only in simulation in silico.
/6 (ends)
@cstross
Also since cryogenic freezing a brain destroys the structure of an already dead brain (basically deteriotated), the folk paying for that are being scammed.I agree it's nice info for SF world building.
Presumably they'd have to replace the blood of a living mouse with a special fluid to preserve the structure?
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I absolutely agree.
At best, what current LLMs are is evidence that linguistic processing follows statistically modelable rules.
@cstross @future_upbeat
Mostly but not entirely. -
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