Aw shucks… I’m flattered. ðŸ™‚

And, just in case you Googled my name, I am indeed the Bill Kaminsky who used to write:

http://williamkaminsky.wordpress.com/

Maybe I should start blogging again. Hmmm… but can I honestly expect to avoid the peril so poignantly depicted in this xkcd: http://xkcd.com/386/ ?! I think not. ðŸ™‚

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And now to everyone on this blog still thinking about computational complexity obstacles to cryonics (which I doubt is all that many people given all the focus now on Deolaikar’s P vs. NP proof)…

I should amend the comments I made (#33 and 35) with the following one.

—————

While *randomly-generated* neural networks are generically “complex” in the sense I mentioned (comment #33) of having a number of metastable states growing *exponentially* in the number of neurons, it’s quite possible *our brains* might be much “simpler” neural networks encoding only a *polynomial* number of metastable states. (NB: Given that we have something like 10^11 neurons, this would still should be a humongous number!)

Indeed, in the most popular models of neural networks that statistical physicists play with, one aims to *avoid* complexity in the sense I mentioned and instead figure out a way to plant just a *linear* number of desired metastable states and ensure there aren’t any other metastable states to get in the way of the dynamics reaching the desired metastable states.

To the best my knowledge, no one’s ever written down a model that allows one to plant a superlinear number of desired metastable states without having unwanted metastable states get in the way.

Now, correct me if I’m wrong, but there’s no scientifically consensus yet how the human brain’s neurons wire together specifically to encode memories and behaviors, is there?

As such, I don’t think we’re able to distinguish presently between the following 2 possibilities:

1) Your brain requires its neurons to be wired together in some specific way so that *a priori* there’s a known set of metastable states. This is something that well might restrict the number of metastable states to be linear (or at most polynomial) in the number of neurons. Personality-preserving, post-mortem reconstruction of the neural network your dead, frozen brain encoded when it was warm and alive could thus in principle be a computationally tractable task.

VS

2) Your brain can manage just fine with its neurons being wired together quasi-randomly. Yeah, there’s an absurdly large set of metastable states: one exponentially large in the number of neurons. Yet somehow, your brain manages to isolate some teeny-tiny fraction of these metastable states to use to encode your memories and behaviors. But the teeny-tinyness of this fraction that gets used makes personality-preserving, post-mortem reconstruction of/from frozen brains then seem computationally intractable even with computers trillions and trillions of times faster than those today.

]]>I think the synthetic bio approach might be the way to go. Instead of freezing, try digitizing and saving and then regrowing according to the saved info.

I wonder if there is a way to crawl the network that is the brain using some sort of a bug (motile bacteria?) and record its connectivity. Might we might also need to know the potency of various neural types in producing certain transmitters? For example, this might encode the strength of emotions we feel in response to events—something not encoded in the topology.

Is there anybody working on this problem of a fast and accurate way of mapping the topology of the brain?

]]>I did wonder what the \alt was, so it was a relief when you included that datum in your footnotes. I like it when authors pay attention to my needs. ðŸ™‚

]]>My first link (to the Fahy paper) appears to be broken: this one will hopefully work better.

]]>1)It’s not written in latex.

2)I think proving P \neq PSPACE or NL \neq NP would already get you a Godel prize and a Turing award. As someone said in some similar context, proving results like those two would already be “blue sky”, while proving P vs NP is “Andromeda galaxy” in comparison. Walk before you run, and all that.

]]>Will you be at Tel Aviv Uni? Will you do a lecture there? ]]>