So is the method that the worm uses for learning known? If we know approximately the current weights, and we knew the way those update, what else is needed?
If this doesn’t count as uploading a worm, however, what would? Consider an experiment where someone trains one group of worms to respond to stimulus one way and another group to respond the other way. Both groups are then scanned and simulated on the computer. If the simulated worms responded to simulated stimulus the same way their pysical versions had, that would be good progress. Additionally you would want to demonstrate that similar learning was possible in the simulated environment.
That is a way to prove that the worm was uploaded. But how would you actually do that? What other info is needed to get to that, and how can we get that? Why can’t we test when the neurons fire in order to get the weights out of that? (I get it’s more complicated than that or it would have been done, but don’t get why.)
Also, typo: pysical to physical. Edit: looks fixed, good.
Basically this is electrophysiology research on C elegans. Most of the research being done, AFAIK, is hypothesis testing and doesn’t systematically measure all of the connection strengths at once. Plus then you have the correlation vs causation problem even if you did measure them all at, which is why davidad wanted to do optogenetics, but again AFAIK that didn’t actually get done.
Bottom line: this research is technically difficult and like most research topics is not well funded.
More details: he was planning to engineer a nematode to make neurons give off light when activating and to be light-sensitive so you can activate individual neurons with light. This lets you see which neurons fire in response to others. He wrote:
In short form, my justification for working on such a project where many have failed before me is:
The “connectome” of C. elegans is not actually very helpful information for emulating it. Contrary to popular belief, connectomes are not the biological equivalent of circuit schematics. Connectomes are the biological equivalent of what you’d get if you removed all the component symbols from a circuit schematic and left only the wires. Good luck trying to reproduce the original functionality from that data.
What you actually need is to functionally characterize the system’s dynamics by performing thousands of perturbations to individual neurons and recording the results on the network, in a fast feedback loop with a very very good statistical modeling framework which decides what perturbation to try next.
With optogenetic techniques, we are just at the point where it’s not an outrageous proposal to reach for the capability to read and write to anywhere in a living C. elegans nervous system, using a high-throughput automated system. It has some pretty handy properties, like being transparent, essentially clonal, and easily transformed. It also has less handy properties, like being a cylindrical lens, being three-dimensional at all, and having minimal symmetry in its nervous system. However, I am optimistic that all these problems can be overcome by suitably clever optical and computational tricks.
I’m a disciple of Kurzweil, and as such I’m prone to putting ridiculously near-future dates on major breakthroughs. In particular, I expect to be finished with C. elegans in 2-3 years. I would be Extremely Surprised, for whatever that’s worth, if this is still an open problem in 2020.
I believe he’s no longer working on this, however, and the NemaLoad project is stalled. The last update is a year ago and there haven’t been any updates to the project’s github page since April 2014. It does look like davidad contributed to a 2013 paper surveying methods of neural recording, but this seems to mostly be a discussion of theoretical capability based mostly on others’ work than anything learned from NemaLoad experiments.
So is the method that the worm uses for learning known? If we know approximately the current weights, and we knew the way those update, what else is needed?
That is a way to prove that the worm was uploaded. But how would you actually do that? What other info is needed to get to that, and how can we get that? Why can’t we test when the neurons fire in order to get the weights out of that? (I get it’s more complicated than that or it would have been done, but don’t get why.)
Also, typo: pysical to physical. Edit: looks fixed, good.
Basically this is electrophysiology research on C elegans. Most of the research being done, AFAIK, is hypothesis testing and doesn’t systematically measure all of the connection strengths at once. Plus then you have the correlation vs causation problem even if you did measure them all at, which is why davidad wanted to do optogenetics, but again AFAIK that didn’t actually get done.
Bottom line: this research is technically difficult and like most research topics is not well funded.
More details: he was planning to engineer a nematode to make neurons give off light when activating and to be light-sensitive so you can activate individual neurons with light. This lets you see which neurons fire in response to others. He wrote:
I believe he’s no longer working on this, however, and the NemaLoad project is stalled. The last update is a year ago and there haven’t been any updates to the project’s github page since April 2014. It does look like davidad contributed to a 2013 paper surveying methods of neural recording, but this seems to mostly be a discussion of theoretical capability based mostly on others’ work than anything learned from NemaLoad experiments.
He wrote, “If I’d had $1 million seed, I wouldn’t have had to cancel the project when I did...” on this Quora answer.
#Civilizationalinadequacy