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Ray Kurzweil does not understand the brain

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Re: Ray Kurzweil does not understand the brain

#91

Post by cageface »

orangecat wrote: post #83
cageface wrote: post #46

Earlier quoted context omitted.

You'd have to read the papers cited below to get the meat of the theory but the gist of it is that you can't model proteins by looking one level down, i.e. by studying only the properties of the atoms that make them up. Proteins have emergent behaviors not entirely predictable from the behaviors of their constituent atoms. Many still believe in the reductionist idea that a perfect understanding of physics would lead…

Proteins have emergent behaviors not entirely predictable from the behaviors of their constituent atoms. Define "emergent". I can believe that a protein's behavior is extremely sensitive to the initial configuration of its atoms and that as a practical matter we can't (currently?) get detailed enough measurements to predict exactly what's going to happen. But without exceptionally compelling evidence I'm not going to…

I suggest you read Prigogine's book if you're really interested but his work demonstrates that the problem isn't having detailed enough information about state, it's the irreversibility of time, which makes physics fundamentally non-deterministic.

Re: Ray Kurzweil does not understand the brain

#92

Post by SMrF »

api wrote: post #65

I'm a life-long programmer who presently works in software, but I studied biology in college... mostly because I wanted to learn about learning by studying how living systems do it. Biological systems are nothing like anything we would ever engineer, and to understand them we must remove our "anthropocentric engineer goggles" and look at them for what they are. Analogies between biological systems and computers, soft…

"I think it's now possible with a big rack of multi-core machines in an MPI cluster to approach the capabilities of a fruit fly's brain."

This seems so unlikely. Isn't it more likely that it takes a rack of multi-core machines to simulate a fruit fly's brain using our extremely primitive algorithms for approximating intelligence?

In other words, it's a software problem.

Re: Ray Kurzweil does not understand the brain

#93

Post by cageface »

rsaarelm wrote: post #29

Myers is attacking Kurzweil on the assumption that Kurzweil is actually proposing that the brain's structure should be reverse-engineesed from DNA, which would be intractably hard. Only Kurzweil isn't saying this anywhere. Instead, he seems to be using DNA as a measure for the amount of irreducible complexity that needs to go into a system that will end up with the complexity of a human brain. Basically, we have no i…

Myers is attacking Kurzweil on the assumption that Kurzweil is actually proposing that the brain's structure should be reverse-engineesed from DNA, which would be intractably hard. Only Kurzweil isn't saying this anywhere. Instead, he seems to be using DNA as a measure for the amount of irreducible complexity that needs to go into a system that will end up with the complexity of a human brain.

This is like saying that the underlying complexity of the Mandelbrot is the set of pairs of real numbers.

Re: Ray Kurzweil does not understand the brain

#94

Post by jerf »

dhs wrote: post #53
rsheridan6 wrote: post #16

I don't find these criticisms convincing. We haven't solved the protein folding problem? So solve it. Is there some reason to believe it won't ever be solved? If you had a sufficiently accurate simulation of a cell or organism (which we don't, but we might someday), you could do experiments on it much cheaper and faster than in a lab. I do agree that there's no freakin' way this will be done in ten years, or in the 6…

Protein folding is suspected to be an NP-complete problem http://www.liebertonline.com/doi/abs/10.1089/cmb.1998.5.27 >, so it seems to me that having reason to believe it will someday be solved equals having reason to believe that someday NP-complete problems can be computed in polynomial time. Alternatively, you might hope for a domain-specific approximative algorithm, but this seems tricky, too, since mis-folded pr…

Saying it's NP-complete doesn't prove we can't solve it well enough for simulation. As a physical problem become "pathologically NP", Nature becomes non-deterministic too; it seems unlikely that Nature will make extensive use of a protein that doesn't reliably fold in a certain way, or some small constrained set of ways.

See http://www.scottaaronson.com/papers/npcomplete.pdf

Re: Ray Kurzweil does not understand the brain

#95

Post by cdavid »

10ren wrote: post #50

I'm not so sure about the simulation, but Ray's right that the brain cannot be more complex than the data that specifies it, speaking information-theoretically. A biologist probably wouldn't get this, because he has too much knowledge of how difficult and complex the actual translation is. It's a mathematical idea, like non-constructive proofs, which freak out sensible folk - and rightfully so. ( EDIT no offence inte…

You are making the assumption that the information quantity is a good measure of the complexity, which is far from obvious. It is also wrong in general for the genetic code (for example, many organisms have a much bigger genetic code than human, even though they are arguably much simpler - e.g. rice has more encoding genes than human).

Also, having a few set of simple rules is not enough to understand or reproduce a system in general.

Re: Ray Kurzweil does not understand the brain

#96

Post by Locke1689 »

rsheridan6 wrote: post #82
wcoenen wrote: post #52

Earlier quoted context omitted.

The physics can be modeled, but according to this article ( http://techglimpse.com/index.php/ibms-blue-gene-exploring-pr... ) a 1 petaflops machine is estimated to take 3 years to crunch through 100 microseconds of simulated time. And that's just for a single protein interacting with itself and a bit of water.

That might just mean they haven't found the right algorithm yet.

Most people suspect it to be NP-hard or NP-complete.

Re: Ray Kurzweil does not understand the brain

#98

Post by Keyframe »

10ren wrote: post #50

I'm not so sure about the simulation, but Ray's right that the brain cannot be more complex than the data that specifies it, speaking information-theoretically. A biologist probably wouldn't get this, because he has too much knowledge of how difficult and complex the actual translation is. It's a mathematical idea, like non-constructive proofs, which freak out sensible folk - and rightfully so. ( EDIT no offence inte…

> but Ray's right that the brain cannot be more complex than the data that specifies it

Indeed, however due to the Kolmogorov complexity http://en.wikipedia.org/wiki/Kolmogorov_complexity one can argue both for DNA being a resource and, with more common sense, that DNA and all appropriate resources during a lifetime up to a point where you take a measure of a whole brain all funnels into a resource from which you can describe a brain.

And this is only about Kolmogorov Complexity and under assumption that brain is a discrete set. I am not much well read on biology, but I think there were recent advancements where some organisms also showed quantum effects playing a biological role. Even with disregarding our current lack of knowledge we can still argue if brain is a discrete set or not, proving either would be a major contributing factor in our understanding of it I think.

Re: Ray Kurzweil does not understand the brain

#99

Post by rsheridan6 »

dhs wrote: post #53
rsheridan6 wrote: post #16

I don't find these criticisms convincing. We haven't solved the protein folding problem? So solve it. Is there some reason to believe it won't ever be solved? If you had a sufficiently accurate simulation of a cell or organism (which we don't, but we might someday), you could do experiments on it much cheaper and faster than in a lab. I do agree that there's no freakin' way this will be done in ten years, or in the 6…

Protein folding is suspected to be an NP-complete problem http://www.liebertonline.com/doi/abs/10.1089/cmb.1998.5.27 >, so it seems to me that having reason to believe it will someday be solved equals having reason to believe that someday NP-complete problems can be computed in polynomial time. Alternatively, you might hope for a domain-specific approximative algorithm, but this seems tricky, too, since mis-folded pr…

The article says that the HP model is NP-complete. But water folds protein very quickly. I may be misunderstanding things here, but if protein folding (as opposed to a particular model of protein folding) is NP-complete, shouldn't it be slow in real life too?

I recall reading an interview with someone who founded a company that builds computers for simulating biological systems in silico who thought that there were much better algorithms waiting to be discovered because nature can do it quickly. I can't find it now.

Re: Ray Kurzweil does not understand the brain

#100

Post by jerf »

There's a psychological principle that I've forgotten the name of that observes that by setting the stage correctly you can cause people to accept assumptions without even thinking about it by framing the debate correctly.

This conversation here on HN is a great example of that. Simply by the way the article is written, it is being taken nearly as fact by most participants that a human-scale AI simulation must work by physically simulating the brain. This may ultimately be true but there is no a priori reason to believe it. The brain may implement something that can be simulated "close enough" by a much simpler computation system.

Chaos is chaotic, obviously, but the human brain is a pretty fuzzy system too. It can't be too pathologically chaotic; people speak as if getting the 15th decimal place wrong will blow up the system but the brain simply can not be that sensitive or the removal of a single neuron would break our brains. Our brain state must be at least metastable to work at all. Removing a neuron or getting something wrong in the 15th decimal place may result in some small change of behavior three years later vs. not removing it or getting it right, but our brain states are already so fuzzy and noisy that's not going to be the stopper.

The stopper will be to see whether or not there is a higher-level simulation that can be run that is less complex that simulating the physics entirely. The secondary question is whether we can make something that we would call human-intelligent even if it turns out we can never "upload our brains" without critical data lossage occurring. That would be something as intelligent as us that is nevertheless fundamentally incompatible with human biology, with neither able to simulate or understand the other. I can make coherent arguments either way, as can many people, but by framing the question as physical simulation this has not been one of the more intelligent debates on the topic we've seen here. Physical simulation is one possible path, and not even the most likely or interesting, to AI and brain upload.

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