just as there are an infinite number of primes. It's not like the 2,000,000,000,000,000th digit of pi is any more significant than say the 200th. At least with primes you reduce the time for factorization.
you need to know what to look for. In order to know what to look for you need to know what's meaningful and that requires some sort of useful model. Accumulating data in itself isn't that interesting.
No doubt they do. And they are probably among millions of others who go there to keep connected with friends that they wouldn't otherwise be able to. Vain people look in mirrors a lot. Does that mean only people who are vain own mirrors? What a ridiculous study.
In most academic domains including philosophy there is broad agreement on what positions are reasonable.
Well, how could there not be, considering already established "philosophers" effectively get to choose their successors? It doesn't mean they are right. It absolutely does not mean that they are focusing on the right issues.
To their credit, and unlike other professions, some of them recognize the problem (what Popper wrote on it in "The open society and its enemies" was IMH non-professional O very poignant. But it doesn't appear philosophy departments have done much to attempt to solve the problem.)
Of course it doesn't. I wasn't suggesting that it did. I was simply pointing out to the parent that arriving at an authoritative set of positions is not impossible. Whether they are correct or not is of course up for debate.
Yes, Popper (who was surprisingly resistant to criticism) made a lot of good suggestions about how to incorporate criticism into developing ides. His "Conjectures and Refutations" is useful here.
In most academic domains including philosophy there is broad agreement on what positions are reasonable.
Great minds think alike and fools never differ. (The last, and most important part, of that quote is often forgotten.) Peer review is important and is the best solution to many academic problems to date, but it is prone to false positives and false negatives. Ideally, you'd have three methodologies - two (peer review being one) run in parallel such that the second methodology is going to pick up probably good information that is rejected by peer review but is not going to pick up more than an absolute minimum of gunk. A third method is then needed to collate the two sets of potentially-good information. It only has to filter out the remaining gunk, it doesn't have to do anything more than that.
Sure, it's hard to tell whether the consensus exists because we are dealing with great minds or fools and some sorts of checks and balances can help sort that out but that doesn't preclude the idea that consensus may be built on such a system. In other words just because it's a consensus doesn't mean its wrong. I am all for questioning authority and not accepting superficial agreement as a sign of truth but on the other hand I think the most common bias these days is to go the other way (i.e. anyone that claims authority is ipso facto wrong, biased, acting only in their own interest, etc). This bias is just as bad. Some positions are better than others.
I've been struck by the negative opinions of the discipline of philosophy on Slashdot over the last few years. Lots of people saying "No empirical testing? Then it's crap!", without apparently realizing that vital questions they have to face in everyday life, such as ethics, are part of philosophy. It's not just all fanciful proofs of God or poststructural interpretations of classic literature.
Yes, many people seem to be really hung up on the fact that philosophy is not science. Unfortunately for them almost all of science is based on metaphysics and the scientific method (the very tool they are are using to heap scorn on philosophy) is the result of epistemology. Philosophy is thinking about thinking; it's a meta-subject. It will always have value as long as people are eager to have their ideas criticized. Unfortunately most of the people saying "No empirical testing? Then it's crap!" are the least scientific and the most dogmatic. As long as philosophy doesn't try to be or claim to be science there is no problem here. They serve complementary functions.
My experience in academia taught me that there was no such thing as the "authoritative" source. If one scholar thought one thing about a particular subject, there was always at least one other scholar who disagreed with him/her. Most of the encyclopedia articles written in more scholarly encyclopedias (like Britannica) are therefore usually written by a single scholar, not a crowd of them. Get a crowd of these yahoos together and odds are you won't even get them to agree on what time it is. I've sat in on meetings where grown Ph.D.'s argued like children over so-and-so getting to teach a 100-level class that someone else wanted to teach (because so-and-so is an idiot who disagreed with them in some journal article written 20 years ago). Any attempt to get agreement out of scholars usually just results in really bland "committee" history (the kind some prevalent in so many unreadable textbooks). Such controversy-free scholarly writing is bizarre at best, absolutely misleading at worst.
Those kind of disagreements are usually only about fine details. In most academic domains including philosophy there is broad agreement on what positions are reasonable.
For all the ribbing it takes, my experience with Wikipedia is that it's generally pretty reliable. In the subjects of my narrow areas of expertise, I've found it to be pretty accurate--or at least as accurate as any other conventional source (i.e. Britannica). Of course, scholars don't like it because they don't get paid to write articles for it (the way they often do in encyclopedias) and writing for it gets them no tenure-track kudos in the publish-or-perish world. That means most scholars are never going to be happy with Wikipedia. And that has nothing to do with its purported lack of accuracy, but rather scholarly politics.
I love Wikipedia. It's a great place for people new to a topic to go to get some context and direction. The overall quality of the philosophy articles is poor though. Many times they are about the equivalent of an undergraduate essay. It's more than just politics, at least for philosophy. It really is a quality issue.
They forgot about debt. Assuming you had to take out loans for your degree, and loans for your car to get to work, and loans for your house $75k may not be enough, but, if you were debt-free, $75k would be plenty of money.
Right. And there used to be a market for the kind of journalism described by the parent post as well as the trash that currently passes as journalism but now it's all overwhelmingly trash.
As I asked the OP - which planet are you from? Because nothing has changed.
In the past newspapers could charge more and were less dependent on advertising.
Maybe on your planet. Not here on Earth.
Whatever. Go take a look. The ratio of journalism to trash was different and journalists for real newspapers had more respect. But, hey, why let facts get in the way of trendy and cool cynicism? It's not like that kind of cynicism leads to precisely where we are today (i.e. everybody is biased, everybody's opinion is equal, and my opinion is as good as everyone else's), right?
Journalism used to be about taking risks to bring critical public interest information to everyone, with a strong ethic and moral code.
On what planet? Here on earth journalism has always been about what will sell papers or garner eyeballs.
I mean seriously, the drek quoted above gets posted and moderated 'insightful' every time a story about the media posted - but it is not now and never has been true.
Right. And there used to be a market for the kind of journalism described by the parent post as well as the trash that currently passes as journalism but now it's all overwhelmingly trash. I blame consumers. We get the media we deserve. Well, to be fair, it's really that the market for news is very different now than it was in the past. In the past newspapers could charge more and were less dependent on advertising. Now consumers won't pay as much, even for first rate journalism, and therefore the difference must be made up in volume, and that means appealing to as many people as possible, and that means reporters can no longer risk offending anyone.
There is no reason to believe we are dealing with a Turing machine here...
And here is where you fail to understand the argument: there is ALL THE REASON to believe we are dealing with a Turing machine here, because a Turing machine is able to compute EVERYTHING that is computable, regardless of complexity...
Also, while I don't need this point for my argument you should know that your assertion that the Turing machine can compute anything computable is a conjecture called the Church-Turing thesis. It's not proven but of course it seems like a fairly solid thesis. However what is objectionable in your proposition is that you are reducing computability to Turing-computability. While the point is subtle think of it like this: anything Turing-computable is computable but anything computable is not necessarily Turing-computable.
Given your over-estimation of the domain of Turing-computability I'm pretty skeptical of your completely unsubstantiated thesis that the brain must be a Turing machine. It's simply dogma. Your prejudice is not uncommon and not surprising. In fact it's probably the most common prejudice amongst those educated enough to know what a Turing machine is but not quite educated enough to know its limits. So you are out of your depth but in good (or at least numerous) company.
A Turing machine is equivalent, from a theoretical point of view, to any computer.
The brain is physical thing, so it can be simulated, by a Turing machine or any powerful enough computer.
Your reductionism is not only logically flawed but empirically false. Your argument is the following: all physical things can be simulated by a Turing machine; the brain is a physical thing; therefore a Turing machine can simulate a brain. Do you see the problem here? Let me help. It's the major premise. Not all physical things can be simulated by a Turing machine. It's not even clear that all physical things can be simulated regardless of the method because of the inherent randomness of physical events. In case you don't see the connection, let me spell it out. Simulation requires abstraction and you can't abstract from random events because by definition there is no rule for the abstraction.
There is no reason to believe we are dealing with a Turing machine here...
And here is where you fail to understand the argument: there is ALL THE REASON to believe we are dealing with a Turing machine here, because a Turing machine is able to compute EVERYTHING that is computable, regardless of complexity, and evidently the process of building a (human) brain is computable since in fact it has been "computed" a few billion times. (On the other hand, figuring out if some arithmetic statements are true or not is not a computable problem, see e.g., Godel's theorem). So whatever is interpreting genome-language instructions to build a brain is doubtlessly a Turing machine.
And however, our task is *much simpler* than that, since although the genome-language Turing machine has indeed to "know" things as complex as protein folding to be able to do its job, we can *completely* abstract that and similar problems: our models of the brain can be happily built with concepts such as "information", "processing", "perception data", "behavior", etc., which are much higher level (and therefore much more concise) than raw molecular biology.
So the argument is this: the construction of a brain is computable (has been computed), and we have a model of computation that starts with the genome (i.e., a very definite amount of information) and ends with a functioning brain (which is what we want), so we know the task is *possible* and the complexity manageable *in principle*. BUT... we won't go at it the same way the genome does, at least not for information-processing purposes which is one of our immediate interests, we'll take a few shortcuts to make the complexity even more manageable than "in principle". Sure, the project might succeed or not, but that's an *empirical* question to be decided by facts (and hopefully, constructively, i.e., trying to build one and either succeeding or failing in a way that we can analyze and use to attain a higher level of understanding). However objections that try to prove that the project is intrinsically (i.e., theoretically) non-viable need to be carefully examined, and if they are based in the non-Turing-machin-ness of the phenomena under observation then they need to be clearly rejected and showed wrong.
You are begging the question. You are essentially saying that genome is computable because it is computable. Here's your task: show me how the cellular processes involved in cell replication and specialization operate like a Turing machine. Obviously this does not mean that these process could not be simulated using a Turing machine, but, the argument is that these processes operate like a Turing a machine and thus we have a good idea of what "50 million bytes" means by an analogy to computer programming.
In any case even if the genome is computed, which may or may not be the case, the fact that there are "50 million bytes" by itself tells us nothing about how much information we need to understand how to design the brain. It tells us the *lower* bound of what the body needs to "know" to build the body, not the *upper* bound of what we need to know to build a brain. The problem here is the distinction between syntax and semantics. The body only needs the syntactical information to work but we need the semantic "information" to understand *how* it works. Also consider that the development of the body and brain are a process in which the syntax may have different meaning at different points in the process of development (and there is evidence that this is the case) which would further increase complexity. His thesis is predicated on an incredibly naive and simplistic understanding of biology which for me makes all of his pronouncements suspect because he is not taking into account such complexity. He's a charlatan, plain and simple.
In other words because Kurzweil's theories are, in your opinion, nonsense they shouldn't be tested?
It's not my "opinion". It's based on theory, the very information theory that he criticizes Myers for not understanding. Obviously he doesn't understand it either.
If you mean the bit about the brain being a Turing machine, then I would say its fine to try testing that theory (many people have been for many years), but the assumption that consciousness is substrate-independent is completely unjustified.
In other words because Kurzweil's theories are, in your opinion, nonsense they shouldn't be tested?
It's not my "opinion". It's based on theory, the very information theory that he criticizes Myers for not understanding. Obviously he doesn't understand it either.
is right. Myers criticism may be off the mark but Kurzweil's speculation about brain design, like some much of his other speculation, is bullshit. His basic argument in the blog post is that the amount of information in the human genome constrains the amount of information (and the complexity) required to design the brain. This thesis is wrong on a bunch of levels but let's take the most obvious. The amount of information in the genome is the amount of information that the "body" (to simplify) requires to replicate or create parts of itself. The amount of information required is relative to the machinery which is going to interpret it. There is no reason to believe we are dealing with a Turing machine here where the amount of bits required for a program to perform a function is going to be more or less consistent across languages and platforms (assuming similar complexity of the code). The machine interpreting the bits matters. So while the body may only need "50 million bytes" to create itself we may need many, many more millions of bits to specify how to build it. Just consider the complexity of protein folding.
More dubious statements follow:
"The goal of reverse-engineering the brain is the same as for any other biological or nonbiological system – to understand its principles of operation. We can then implement these methods using other substrates other than a biochemical system that sends messages at speeds that are a million times slower than contemporary electronics. The goal of engineering is to leverage and focus the powers of principles of operation that are understood, just as we have leveraged the power of Bernoulli’s principle to create the entire world of aviation."
This completely begs the question of whether it can be replicated in another substrate. He just assumes that it can be done and by doing so he already assumes a model of the brain that could be (and is most likely) wrong. The brain is clearly not a Turing machine. That's not say it is not another kind of "computer" (for some expanded definition of computer) or follow mechanistic principles however. Assuming the brain is like a Turing machine (which Kurzweil implicitly does) is one of the biggest obstacles to developing real AI.
Speculation of Kurzweil kind does not belong in the "Science" category, maybe "Idle".
It make sense that newts would have cancer suppressors turned off because they can reproduce and die of other causes before any cancer would kill them and regeneration is likely very handy. Humans on the other hand need to live a fair amount of time to ensure reproductive success and regeneration is likely of less value due to the social supports in human society.
Heisenberg's uncertainty principle is still a fundamental cornerstone in quantum physics. Incompatible observables remain incompatible. What the article says isn't that the principle is wrong, but that there is a work-around for a technical problem which the principle was causing. Much the same way the invention of airplanes did not imply gravity is wrong.
That's all I can say without seeing some math.
And more likely than not the Heisenberg uncertainty principle will prove to be a limit (in the mathematical sense) to the precision of the measurements just as classical mechanics can function as a limit to quantum mechanics. So, as more possible states are entangled the precision will improve but not to such a degree that it will violate the principle.
Slashdot Mirror
It's actually 13 orders of magnitude less significant than the 200th.
Yeah, I knew some smart ass would say that. I almost didn't use the word "significant" but the meaning of the word is ambiguous. So we are both right.
just as there are an infinite number of primes. It's not like the 2,000,000,000,000,000th digit of pi is any more significant than say the 200th. At least with primes you reduce the time for factorization.
C'mon samzenpus, you can do better than this...
Agreed. A simple google search would show the reviewer is a shill.
you need to know what to look for. In order to know what to look for you need to know what's meaningful and that requires some sort of useful model. Accumulating data in itself isn't that interesting.
No doubt they do. And they are probably among millions of others who go there to keep connected with friends that they wouldn't otherwise be able to. Vain people look in mirrors a lot. Does that mean only people who are vain own mirrors? What a ridiculous study.
Well, how could there not be, considering already established "philosophers" effectively get to choose their successors? It doesn't mean they are right. It absolutely does not mean that they are focusing on the right issues.
To their credit, and unlike other professions, some of them recognize the problem (what Popper wrote on it in "The open society and its enemies" was IMH non-professional O very poignant. But it doesn't appear philosophy departments have done much to attempt to solve the problem.)
Of course it doesn't. I wasn't suggesting that it did. I was simply pointing out to the parent that arriving at an authoritative set of positions is not impossible. Whether they are correct or not is of course up for debate.
Yes, Popper (who was surprisingly resistant to criticism) made a lot of good suggestions about how to incorporate criticism into developing ides. His "Conjectures and Refutations" is useful here.
Great minds think alike and fools never differ. (The last, and most important part, of that quote is often forgotten.) Peer review is important and is the best solution to many academic problems to date, but it is prone to false positives and false negatives. Ideally, you'd have three methodologies - two (peer review being one) run in parallel such that the second methodology is going to pick up probably good information that is rejected by peer review but is not going to pick up more than an absolute minimum of gunk. A third method is then needed to collate the two sets of potentially-good information. It only has to filter out the remaining gunk, it doesn't have to do anything more than that.
Sure, it's hard to tell whether the consensus exists because we are dealing with great minds or fools and some sorts of checks and balances can help sort that out but that doesn't preclude the idea that consensus may be built on such a system. In other words just because it's a consensus doesn't mean its wrong. I am all for questioning authority and not accepting superficial agreement as a sign of truth but on the other hand I think the most common bias these days is to go the other way (i.e. anyone that claims authority is ipso facto wrong, biased, acting only in their own interest, etc). This bias is just as bad. Some positions are better than others.
I've been struck by the negative opinions of the discipline of philosophy on Slashdot over the last few years. Lots of people saying "No empirical testing? Then it's crap!", without apparently realizing that vital questions they have to face in everyday life, such as ethics, are part of philosophy. It's not just all fanciful proofs of God or poststructural interpretations of classic literature.
Yes, many people seem to be really hung up on the fact that philosophy is not science. Unfortunately for them almost all of science is based on metaphysics and the scientific method (the very tool they are are using to heap scorn on philosophy) is the result of epistemology. Philosophy is thinking about thinking; it's a meta-subject. It will always have value as long as people are eager to have their ideas criticized. Unfortunately most of the people saying "No empirical testing? Then it's crap!" are the least scientific and the most dogmatic. As long as philosophy doesn't try to be or claim to be science there is no problem here. They serve complementary functions.
My experience in academia taught me that there was no such thing as the "authoritative" source. If one scholar thought one thing about a particular subject, there was always at least one other scholar who disagreed with him/her. Most of the encyclopedia articles written in more scholarly encyclopedias (like Britannica) are therefore usually written by a single scholar, not a crowd of them. Get a crowd of these yahoos together and odds are you won't even get them to agree on what time it is. I've sat in on meetings where grown Ph.D.'s argued like children over so-and-so getting to teach a 100-level class that someone else wanted to teach (because so-and-so is an idiot who disagreed with them in some journal article written 20 years ago). Any attempt to get agreement out of scholars usually just results in really bland "committee" history (the kind some prevalent in so many unreadable textbooks). Such controversy-free scholarly writing is bizarre at best, absolutely misleading at worst.
Those kind of disagreements are usually only about fine details. In most academic domains including philosophy there is broad agreement on what positions are reasonable.
For all the ribbing it takes, my experience with Wikipedia is that it's generally pretty reliable. In the subjects of my narrow areas of expertise, I've found it to be pretty accurate--or at least as accurate as any other conventional source (i.e. Britannica). Of course, scholars don't like it because they don't get paid to write articles for it (the way they often do in encyclopedias) and writing for it gets them no tenure-track kudos in the publish-or-perish world. That means most scholars are never going to be happy with Wikipedia. And that has nothing to do with its purported lack of accuracy, but rather scholarly politics.
I love Wikipedia. It's a great place for people new to a topic to go to get some context and direction. The overall quality of the philosophy articles is poor though. Many times they are about the equivalent of an undergraduate essay. It's more than just politics, at least for philosophy. It really is a quality issue.
I've been going to plato.stanford.edu for years.
They forgot about debt. Assuming you had to take out loans for your degree, and loans for your car to get to work, and loans for your house $75k may not be enough, but, if you were debt-free, $75k would be plenty of money.
working on it (according to rumors that have been circulating for a while anyhow). They are going to create an HTML5 web-based iTunes.
As I asked the OP - which planet are you from? Because nothing has changed.
Maybe on your planet. Not here on Earth.
Whatever. Go take a look. The ratio of journalism to trash was different and journalists for real newspapers had more respect. But, hey, why let facts get in the way of trendy and cool cynicism? It's not like that kind of cynicism leads to precisely where we are today (i.e. everybody is biased, everybody's opinion is equal, and my opinion is as good as everyone else's), right?
On what planet? Here on earth journalism has always been about what will sell papers or garner eyeballs.
I mean seriously, the drek quoted above gets posted and moderated 'insightful' every time a story about the media posted - but it is not now and never has been true.
Right. And there used to be a market for the kind of journalism described by the parent post as well as the trash that currently passes as journalism but now it's all overwhelmingly trash. I blame consumers. We get the media we deserve. Well, to be fair, it's really that the market for news is very different now than it was in the past. In the past newspapers could charge more and were less dependent on advertising. Now consumers won't pay as much, even for first rate journalism, and therefore the difference must be made up in volume, and that means appealing to as many people as possible, and that means reporters can no longer risk offending anyone.
never works. It only emboldens that aggressor.
There is no reason to believe we are dealing with a Turing machine here ...
And here is where you fail to understand the argument: there is ALL THE REASON to believe we are dealing with a Turing machine here, because a Turing machine is able to compute EVERYTHING that is computable, regardless of complexity...
Also, while I don't need this point for my argument you should know that your assertion that the Turing machine can compute anything computable is a conjecture called the Church-Turing thesis. It's not proven but of course it seems like a fairly solid thesis. However what is objectionable in your proposition is that you are reducing computability to Turing-computability. While the point is subtle think of it like this: anything Turing-computable is computable but anything computable is not necessarily Turing-computable.
Given your over-estimation of the domain of Turing-computability I'm pretty skeptical of your completely unsubstantiated thesis that the brain must be a Turing machine. It's simply dogma. Your prejudice is not uncommon and not surprising. In fact it's probably the most common prejudice amongst those educated enough to know what a Turing machine is but not quite educated enough to know its limits. So you are out of your depth but in good (or at least numerous) company.
A Turing machine is equivalent, from a theoretical point of view, to any computer.
The brain is physical thing, so it can be simulated, by a Turing machine or any powerful enough computer.
Your reductionism is not only logically flawed but empirically false. Your argument is the following: all physical things can be simulated by a Turing machine; the brain is a physical thing; therefore a Turing machine can simulate a brain. Do you see the problem here? Let me help. It's the major premise. Not all physical things can be simulated by a Turing machine. It's not even clear that all physical things can be simulated regardless of the method because of the inherent randomness of physical events. In case you don't see the connection, let me spell it out. Simulation requires abstraction and you can't abstract from random events because by definition there is no rule for the abstraction.
There is no reason to believe we are dealing with a Turing machine here ...
And here is where you fail to understand the argument: there is ALL THE REASON to believe we are dealing with a Turing machine here, because a Turing machine is able to compute EVERYTHING that is computable, regardless of complexity, and evidently the process of building a (human) brain is computable since in fact it has been "computed" a few billion times. (On the other hand, figuring out if some arithmetic statements are true or not is not a computable problem, see e.g., Godel's theorem). So whatever is interpreting genome-language instructions to build a brain is doubtlessly a Turing machine.
And however, our task is *much simpler* than that, since although the genome-language Turing machine has indeed to "know" things as complex as protein folding to be able to do its job, we can *completely* abstract that and similar problems: our models of the brain can be happily built with concepts such as "information", "processing", "perception data", "behavior", etc., which are much higher level (and therefore much more concise) than raw molecular biology.
So the argument is this: the construction of a brain is computable (has been computed), and we have a model of computation that starts with the genome (i.e., a very definite amount of information) and ends with a functioning brain (which is what we want), so we know the task is *possible* and the complexity manageable *in principle*. BUT ... we won't go at it the same way the genome does, at least not for information-processing purposes which is one of our immediate interests, we'll take a few shortcuts to make the complexity even more manageable than "in principle". Sure, the project might succeed or not, but that's an *empirical* question to be decided by facts (and hopefully, constructively, i.e., trying to build one and either succeeding or failing in a way that we can analyze and use to attain a higher level of understanding). However objections that try to prove that the project is intrinsically (i.e., theoretically) non-viable need to be carefully examined, and if they are based in the non-Turing-machin-ness of the phenomena under observation then they need to be clearly rejected and showed wrong.
You are begging the question. You are essentially saying that genome is computable because it is computable. Here's your task: show me how the cellular processes involved in cell replication and specialization operate like a Turing machine. Obviously this does not mean that these process could not be simulated using a Turing machine, but, the argument is that these processes operate like a Turing a machine and thus we have a good idea of what "50 million bytes" means by an analogy to computer programming.
In any case even if the genome is computed, which may or may not be the case, the fact that there are "50 million bytes" by itself tells us nothing about how much information we need to understand how to design the brain. It tells us the *lower* bound of what the body needs to "know" to build the body, not the *upper* bound of what we need to know to build a brain. The problem here is the distinction between syntax and semantics. The body only needs the syntactical information to work but we need the semantic "information" to understand *how* it works. Also consider that the development of the body and brain are a process in which the syntax may have different meaning at different points in the process of development (and there is evidence that this is the case) which would further increase complexity. His thesis is predicated on an incredibly naive and simplistic understanding of biology which for me makes all of his pronouncements suspect because he is not taking into account such complexity. He's a charlatan, plain and simple.
In other words because Kurzweil's theories are, in your opinion, nonsense they shouldn't be tested?
It's not my "opinion". It's based on theory, the very information theory that he criticizes Myers for not understanding. Obviously he doesn't understand it either.
If you mean the bit about the brain being a Turing machine, then I would say its fine to try testing that theory (many people have been for many years), but the assumption that consciousness is substrate-independent is completely unjustified.
In other words because Kurzweil's theories are, in your opinion, nonsense they shouldn't be tested?
It's not my "opinion". It's based on theory, the very information theory that he criticizes Myers for not understanding. Obviously he doesn't understand it either.
is right. Myers criticism may be off the mark but Kurzweil's speculation about brain design, like some much of his other speculation, is bullshit. His basic argument in the blog post is that the amount of information in the human genome constrains the amount of information (and the complexity) required to design the brain. This thesis is wrong on a bunch of levels but let's take the most obvious. The amount of information in the genome is the amount of information that the "body" (to simplify) requires to replicate or create parts of itself. The amount of information required is relative to the machinery which is going to interpret it. There is no reason to believe we are dealing with a Turing machine here where the amount of bits required for a program to perform a function is going to be more or less consistent across languages and platforms (assuming similar complexity of the code). The machine interpreting the bits matters. So while the body may only need "50 million bytes" to create itself we may need many, many more millions of bits to specify how to build it. Just consider the complexity of protein folding.
More dubious statements follow:
"The goal of reverse-engineering the brain is the same as for any other biological or nonbiological system – to understand its principles of operation. We can then implement these methods using other substrates other than a biochemical system that sends messages at speeds that are a million times slower than contemporary electronics. The goal of engineering is to leverage and focus the powers of principles of operation that are understood, just as we have leveraged the power of Bernoulli’s principle to create the entire world of aviation."
This completely begs the question of whether it can be replicated in another substrate. He just assumes that it can be done and by doing so he already assumes a model of the brain that could be (and is most likely) wrong. The brain is clearly not a Turing machine. That's not say it is not another kind of "computer" (for some expanded definition of computer) or follow mechanistic principles however. Assuming the brain is like a Turing machine (which Kurzweil implicitly does) is one of the biggest obstacles to developing real AI.
Speculation of Kurzweil kind does not belong in the "Science" category, maybe "Idle".
It make sense that newts would have cancer suppressors turned off because they can reproduce and die of other causes before any cancer would kill them and regeneration is likely very handy. Humans on the other hand need to live a fair amount of time to ensure reproductive success and regeneration is likely of less value due to the social supports in human society.
Heisenberg's uncertainty principle is still a fundamental cornerstone in quantum physics. Incompatible observables remain incompatible. What the article says isn't that the principle is wrong, but that there is a work-around for a technical problem which the principle was causing. Much the same way the invention of airplanes did not imply gravity is wrong.
That's all I can say without seeing some math.
And more likely than not the Heisenberg uncertainty principle will prove to be a limit (in the mathematical sense) to the precision of the measurements just as classical mechanics can function as a limit to quantum mechanics. So, as more possible states are entangled the precision will improve but not to such a degree that it will violate the principle.
Bullets are more reliable, effective, and cheaper.
It looks like the distribution follows a power law. I'm not sure if that's an artifact of the numbers chosen but it would be cool if it were true.