What's your current estimate (or probability distribution) for how much computational power would be needed to run the C. elegans simulation? Once your project succeeds, can we derive an upper bound for a human upload just by multiplying by the ratio of neurons and/or synapses, or would that not be valid because human neurons are much more complicated, or for some other reason?
Also, how are you planning to turn the data you gather using optogenetics into computational models of neurons? (Or do you already have the models and just need to plug in parameters based on the data?)
What's your current estimate (or probability distribution) for how much computational power would be needed to run the C. elegans simulation?
I think the simulation environment should run in real-time on a laptop. If we're lucky, it might run in real-time on an iPhone. If we're unlucky, it might run in real-time on a cluster of a few servers. In any case, I expect the graphics and physics to require much (>5x) more computational power than the C. elegans mind itself (though of course the content of the mind-code will be much more interesting and diffi...
This post is shameless self-promotion, but I'm told that's probably okay in the Discussion section. For context, as some of you are aware, I'm aiming to model C. elegans based on systematic high-throughput experiments - that is, to upload a worm. I'm still working on course requirements and lab training at Harvard's Biophysics Ph.D. program, but this remains the plan for my thesis.
Last semester I gave this lecture to Marvin Minsky's AI class, because Marvin professes disdain for everything neuroscience, and I wanted to give his students—and him—a fair perspective of how basic neuroscience might be changing for the better, and seems a particularly exciting field to be in right about now. The lecture is about 22 minutes long, followed by over an hour of questions and answers, which cover a lot of the memespace that surrounds this concept. Afterward, several students reported to me that their understanding of neuroscience was transformed.
I only just now got to encoding and uploading this recording; I believe that many of the topics covered could be of interest to the LW community (especially those with a background in AI and an interest in brains), perhaps worthy of discussion, and I hope you agree.