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Is Biological Intelligence Different From Machine Intelligence?
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sojourner Offline
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Post: #25
RE: Is Biological Intelligence Different From Machine Intelligence?

@Ajita:

I am writing this after reading only the first paragraph of your latest reply. [I will read the remaining paragraphs as I get time.]

Also, for this post, I am taking off my behaviorist hat. I am someone who is just asking for the justification of the computer metaphor.

Quote: But why should we NOT see them as computers if that is the focus of our question?


I didn't understand the last part of the above sentence.

Why should we see plants/humans as computers any more than seeing them as steam locomotives or food processors?

Quote:"Because that is not useful to us" is not a wholly satisfactory answer

Isn't utility the only worthwhile value?

Quote:The practical applications of various discoveries made in science are not realized until decades or even centuries later, often because they are not immediately apparent.

If immediate practical applications do not follow, that alone should make someone stop and think. Also, one way practical applications do not follow is if the "science" in question is not very scientific at all, i.e., has fundamental problems. I can define IV1 as my body temperature + Sachin Tendulkar's body temperature squared + Oprah Winfrey's body temperature cubed and claim that this is a unified independent variable of which the Dow Jones average is a function. If nothing useful follows from it, this is only because the formulation is so ridiculous.

Quote: The question is often posed as an attempt to understand the system as in much of fundamental science, not necessarily to provide immediate practical applications.

An interpretation which leads to "control" (i.e., mastery over the subject matter) is superior to one which doesn't.

I am not sure what fundamental knowledge will arise using the computer metaphor for humans. It allows one to use words developed for something else but its use should be questioned.

It is not only the computer metaphor that I question. Every time I read that the earth is an organism, I cringe. This is a misuse of terms. Organism by definition means born from another organism, that it lives, reproductive capability, membership in a species, and so on.
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sojourner Offline
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Post: #26
RE: Is Biological Intelligence Different From Machine Intelligence?

Quote: (Skinner was) accused of (and even vilified for) suggesting that people may be programmed to serve organizational ends

Skinner may well have been accused of the above. [Some of his famous accusers were Spiro Agnew and Ayn Rand.]

But Skinner's point was that whether we admit it or not we are getting conditioned (i.e.., programmed), for instance, when we learn a first language from a primary caregiver (which most often is a mother).
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arvindiyer Offline
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Post: #27
RE: Is Biological Intelligence Different From Machine Intelligence?

(14-08-2011 04:47 AM)sojourner Wrote:  I am assuming that the readers are interested in giving everybody a fair shake, including Skinner.

I for one, like many other readers here I'm sure, remain eager to learn more about Skinner and about the case for behaviorism.

It will be easier for me to remain eager if efforts to introduce Behaviorism are not also accompanied by a gratuitous and anticipatory disparaging of a good two decades of recent advances, both fundamental and methodological, in the disciplines now under the umbrella 'cognitive sciences'.

It would also help if every critic of Skinner is not condescendingly misconstrued as automatically belonging to a gaggle of vitalists, dualists and Gaia-worshippers!

If we are to grant that the 'judgment of history' is pending and the 'jury is still out' on the debate between 'behaviorist' and 'cognitive scientist' camps, then while everyone can make a case for their 'favorite team', it will help if their support is accompanied with a disclaimer that their opinion is far from a scholarly consensus.
(This post was last modified: 14-08-2011 08:19 AM by arvindiyer.)
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Lije Offline
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Post: #28
RE: Is Biological Intelligence Different From Machine Intelligence?

(14-08-2011 04:28 AM)sojourner Wrote:  Also, one way practical applications do not follow is if the "science" in question is not very scientific at all, i.e., has fundamental problems. I can define IV1 as my body temperature + Sachin Tendulkar's body temperature squared + Oprah Winfrey's body temperature cubed and claim that this is a unified independent variable of which the Dow Jones average is a function. If nothing useful follows from it, this is only because the formulation is so ridiculous.

You keep saying it is not scientific, it is of zero use to humans etc.., but whenever specific examples are presented to show otherwise, you skirt around them and keep repeating the same point.
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Ajita Kamal Offline
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Post: #29
RE: Is Biological Intelligence Different From Machine Intelligence?

(14-08-2011 04:28 AM)sojourner Wrote:  @Ajita:

I am writing this after reading only the first paragraph of your latest reply. [I will read the remaining paragraphs as I get time.]

I suggest you read the entire post (as well as take into account points made in previous posts) that you are responding to, because your replies are skirting important points that have already been made and repeating arguments that have already been addressed.

Quote:
Quote: But why should we NOT see them as computers if that is the focus of our question?


I didn't understand the last part of the above sentence.

Why should we see plants/humans as computers any more than seeing them as steam locomotives or food processors?

Please read the sentence you are quoting carefully and try to avoid any blind spots that may bias your understanding of it. Failure to do so results in confirmation bias.

The part of the statement that you are conveniently avoiding is "if that is the focus of our question".

We can choose to look at a system as a computational system. Similarly, we can choose to look at a system as a food processing system. In the case in question, we are looking at the system as a computational system. If you had read my entire comment before you had responded, you would be aware of what I said about how different questions address different levels of organization. Please go back and read it, including my demonstration of this fact using the example of photosynthesis in gladioli. I do not want to keep repeating myself.

Quote:Isn't utility the only worthwhile value?

No. Very little fundamental science is done with practical applications to humanity in mind. I would think this is a trivial point at such a level of discussion and am surprised that I'm having to explain it. To quote wikipedia of all sources for lack of time and patience, "Fundamental science, in contrast to applied science, is defined as a fundamental knowledge it develops. The progress of fundamental science is based on well controlled experiments and careful observation. Fundamental science is dependent upon deductions from demonstrated truths, or is studied without regard to practical applications."

Quote:Also, one way practical applications do not follow is if the "science" in question is not very scientific at all, i.e., has fundamental problems. I can define IV1 as my body temperature + Sachin Tendulkar's body temperature squared + Oprah Winfrey's body temperature cubed and claim that this is a unified independent variable of which the Dow Jones average is a function. If nothing useful follows from it, this is only because the formulation is so ridiculous.

This is a classic formal fallacy called Affirming the Consequent. The form of argument
If A, then B.
B, therefore A

is fallacious.
Of course if a fact-proposition is scientifically false/erroneous we can admit it probably does not contribute to the advancement of human well-being. But the fact that an idea does not (when prejudged) contribute to human well-being does not automatically imply that it is non-scientific.

Whether an idea is scientific or not is not determined by how useful it is in terms of immediate and obvious practical applications. This is such a fundamental concept that I am bewildered that we are even discussing it.

Quote:I am not sure what fundamental knowledge will arise using the computer metaphor for humans. It allows one to use words developed for something else but its use should be questioned.

I think your fundamental problem is in misunderstanding the analogy. The comparison is not simply between a computer and a brain as two physical objects. It is between the way the brain works and the way a complex computational system works. The relationship being compared is the process of computation. Again, all this should be apparent if you are willing to factor in what I have already said. Quoting myself:

Quote:"If we are talking only about machines created by us so far, then of course, YES, biological intelligence is vastly different from the most brilliant computers (or any other machines) we have."
"We are children in our understanding of computational complexity. I am not saying we will soon completely understand how the brain works by studying its computational mechanisms, but I think we can safely say that as our understanding of computational systems and the complex mathematics they are capable of increases, computers will become increasingly relevant in understanding how intelligent systems work."

The fundamental knowledge we are talking about is our growing knowledge about the brain's computational processes. Whether you like it or not, the brain is a computational system, among other things. In fact, I am prepared to say that the computational capabilities/mechanisms of the brain are nothing like those of the computers we have today (a point that I have been stressing throughout this thread, which you have consistently ignored) despite some evidence to the contrary.

Lastly, please stop referring to pseudoscientific ideas as analogous to the valid analogies we are discussing here. We can discuss the analogy of the brain as a computational system without resorting to such distractions.

"Fossil rabbits in the Precambrian"
~ J.B.S.Haldane, on being asked to falsify evolution.
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sojourner Offline
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Post: #30
RE: Is Biological Intelligence Different From Machine Intelligence?

Quote:The fundamental knowledge we are talking about is our growing knowledge about the brain's computational processes. the brain is a computational system

1. The above is a bit like "If all we have is a hammer, the whole world will look like a nail". Since we are hellbent on using the computer analogy, the brain is going to look like a computational system.

2. With real computers, somebody writes a program and loads it for running. Nothing like that happens with humans. The human brain is hard wired to exhibit some behavior (reflexes and the like). It is also hardwired to continuously learn from experience via processes called The Law Of Effect and others. At a given moment, particular responses come out due to current and recent stimulation and deprivation/satiation. Some of the behavior is verbal and some of it verbal and private (i.e., thinking). Does the brain computational models take into account the above? Doing so is essential to understand how the brain produces behavior.

3. Also, facts established at the behavioral level set tasks to be explained at the neural level. This is like chemistry setting tasks for what happens at the next level down. [Eric Kandel, in his Nobel Prize winning effort, discovered what happens at the neural level for what is observed at the behavior level for Pavlovian conditioning.]

4. Skinner has listed his objections to cognitive psychology in his 1977 paper. I have provided a reference to it. [I haven't read this in several years nor do I have access to it at the moment.]
-------------------------------------------------
[1. I did take a quick look at the UCI plant work reference. They seem to be doing simulations. This does not make the plant a computing system.

2. "Earth as an organism": I saw this claim in one of the other threads in Nirmukta. That's why I mentioned it. If you agree that it is pseudoscience, we can move on.]
(This post was last modified: 14-08-2011 06:24 PM by sojourner.)
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Post: #31
RE: Is Biological Intelligence Different From Machine Intelligence?

Quote:I for one, like many other readers here I'm sure, remain eager to learn more about Skinner and about the case for behaviorism.

Readers can " learn more about Skinner and about the case for behaviorism" from the horse's mouth itself in the book About Behaviorism or the earlier one Science and Human Behavior.

There is also the monumental but difficult book Verbal Behavior which is a major milestone in human thought.

The material provided in Skinner's books are not the final word in our understanding of human behavior. Skinner fully expected his ideas to go out of date, replaced by better ones. However, these wouldn't be possible without his breakthrough ideas in the first place.
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arvindiyer Offline
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Post: #32
RE: Is Biological Intelligence Different From Machine Intelligence?

(14-08-2011 06:00 PM)sojourner Wrote:  Since we are hellbent on using the computer analogy, the brain is going to look like a computational system.

Using a 'computer analogy' is different from using a 'computing analogy' or a 'computational analogy'.
Churchland and Sejnowski illustrate this vividly in their book 'The Computational Brain' by the following example (paraphrased): If we pick up a pebble and roll it down the hillside, we can well say it is computing the potential energy minimum. In certain contexts, conceptual or pedagogic, it may make sense to talk of this as the energy-minimum-seeking behavior of the pebble or as a computational model of the dynamics of the pebble. Likewise, that certain neural processes lend themselves to a computational description is well-demonstrated and resort to such methods is very unfairly lambasted as a failure of the imagination of the scientists who use them.

(14-08-2011 06:00 PM)sojourner Wrote:  The human brain is hard wired to exhibit some behavior (reflexes and the like). It is also hardwired to continuously learn from experience via processes called The Law Of Effect and others.

One of the simplest and most standard models for explaining experience-dependent plasticity or 'rewiring' in the brain is Hebbian Learning which if often stated in the pop version "Neurons that fire together wire together." Hebbian Learning is in essence a 'computational description' of neural rewiring, in that it describes a network computation where wirings are reweighted in accordance to correlated firings. In terms of fundamental science, this theory has supplied a framework to understand Long Term Potentiation and memory-formation and in terms of applied science, this theory has lent itself to generalization and application to a number of useful bio-inspired algorithms.

(14-08-2011 06:00 PM)sojourner Wrote:  Some of the behavior is verbal and some of it verbal and private (i.e., thinking). Does the brain computational models take into account the above?

How 'subjective states' essential to consciousness emerge from a physical system is question addressed philosophically as the Hard Problem of Consciousness and also via network models by the likes of Gerald Edelman. Here I use 'subjective' to include both 'private' and 'unobserved'. This lecture by Prof. Edelman will be particularly useful viewing as it clearly distinguishes the 'computer analogy' from the 'computational approach', illustrates how emergent properties of networks can potentially explain complex behaviors and does so in an entirely materialistic setting (which really goes without saying).

(14-08-2011 06:00 PM)sojourner Wrote:  Also, facts established at the behavioral level set tasks to be explained at the neural level.

Often there are discoveries that happen the other way round as well. The Nobel-prize-winning neuroscientist pair Hubel and Wiesel discovered oriented edge detectors in the early visual system in the late 1950s and this was a discovery at the single-neuron level. It wasn't until a few decades later that David Marr proposed a theory of how these detectors facilitate visual perception behavior with his idea of a 'primal sketch'.

Perhaps the quintessential success story of a computational approach is the use of nonlinear Ordinary Differential Equation models by Hodgkin and Huxley to to model the process of neural spiking and their bold prediction of the existence of voltage-gated ion channels in a neuron. They were proven right decades later after advances in fields like protein crystallography enabled sodium channels to be visualized.

(14-08-2011 06:00 PM)sojourner Wrote:  I did take a quick look at the UCI plant work reference. They seem to be doing simulations. This does not make the plant a computing system.

Neuroscientists build 'mechanistic models' which very closely model minute details of the physical apparatus of a process and also build 'minimal models' which are built at a higher level of abstraction just to model the transformation between an input and output variable. It is not that those who build 'minimal models' are unmindful of complexity, but just that they are approaching the problem at a different level of analysis. Hodgkin and Huxley's model was 'minimal' in that it was built pending full knowledge of membrane biochemistry but nevertheless occasioned fundamental discoveries.

It was in such a context that the argument for a computational approach to photosynthesis was made, and the emphases ought to serve as a clarification.
(14-08-2011 06:00 PM)Ajita Wrote:  In the 21st century, certain new questions are being asked that would not have been possible just a few decades ago- questions that require us to view the plant as a computational machine. In the context of photoshythesis, here is one such question that has been answered recently...
Other questions may require us to view a plant otherwise, and therefore nobody said that a 'plant is a computer'.

(14-08-2011 06:00 PM)sojourner Wrote:  Readers can " learn more about Skinner and about the case for behaviorism" from the horse's mouth itself in the book About Behaviorism or the earlier one Science and Human Behavior.

The Cognitive Sciences cart today is drawn by a number of 'horses' that have teamed up, and the contributions of interdisciplinary confluence has been illustrated repeatedly in this very thread. Forcing a narrative of a 'two-horse race' between the Behaviorists and Cognitive Scientists seems a very dated approach, and one that is pursued with very little payoff especially if the 'winning horse' has been picked already thanks to the predispositions of the commentator. If learning from the (other) horse's mouth is also a concern, 'The Computational Brain' by Churchland and Sejnowski is a highly recommended resource.
(This post was last modified: 14-08-2011 11:34 PM by arvindiyer.)
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Ajita Kamal Offline
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Post: #33
RE: Is Biological Intelligence Different From Machine Intelligence?

(14-08-2011 05:47 PM)sojourner Wrote:  1. The above is a bit like "If all we have is a hammer, the whole world will look like a nail". Since we are hellbent on using the computer analogy, the brain is going to look like a computational system.

This is rhetoric not logical refutation. We can use the same form of argument on your refusal to even consider organisms as computational systems. But even your basic premise is wrong, because we are not saying that the brain can be seen only as a computational system.

Multiple times both Arvind and I have made it clear that it is just one way of seeing the brain. I have even professed that it is a rather limited way of doing so at our current stage of technological advancement, given our poor computational abilities. To quote myself:
"This is not to say that good old behaviorism will be made redundant, any more than discovery of quantum computational effects in plant photosynthesis makes understanding the biochemistry of the process pointless. These are different levels of questions. The fundamental questions make it possible to ask the more complex ones. We are children in our understanding of computational complexity."

Again, please take a minute to see how your refusal to see that we are adopting a multifaceted scientific approach involving many layers of evidence and many approaches to the different levels of organizational complexity in these systems, is only possible because you are consistently ignoring those parts of our comments that are inconvenient. We are not denying that behavioral analysis has its role. But you are denying that the brain can be viewed as a computational system.

Quote:2. With real computers, somebody writes a program and loads it for running. Nothing like that happens with humans.

Nobody has claimed that it does. Again, quoting myself for the second time from my first comment in this thread: "If we are talking only about machines created by us so far, then of course, YES, biological intelligence is vastly different from the most brilliant computers (or any other machines) we have."

Perhaps we should have a discussion first on what the word "computation" means. Whatever it means, it is not limited to "real computers", if by "real computers" you mean only those things that are called computers in the electronics store. This should be clear by now, especially since I have used multiple examples to make this point.

Quote:Does the brain computational models take into account the above?

What would preclude a computational model of the brain from taking them into account, other than a refusal to even consider the brain as a computational system? Time? Imagination? Processing power? If you read my very first post on this thread, you may see that the points you raise are irrelevant to my actual claims. Again, quoting myself from the very first comment: "Time and imagination limit non-biological machines from attaining qualities akin to those we possess."

I would like to know from you if you disagree with my assertion that given unlimited time and computational resources, using evolutionary algorithms, and probabilistic reasoning, it is theoretically possible to create machines that function like brains. If you disagree, then what will these machines be missing?

Quote:[1. I did take a quick look at the UCI plant work reference. They seem to be doing simulations. This does not make the plant a computing system.

Of course the fact that they are doing simulations does not make the plant a computational system. But a plant can function as a computational system of sorts (not like a computer in a store, just to make sure you don't misunderstand me) regardless of whether they are doing simulations on it or not. As I have been saying all along, we are just beginning to understand computational complexity. Also, note that you have conveniently disregarded the scientific study I pointed to that demonstrated an advanced computational process in a plant system, and are selectively quoting the example in which they are doing a simulation to make the point that it "does not make the plant a computing (sic) system". Doesn't that strike you are rather disingenuous? Such selective filtering of evidence is what I referred to earlier as confirmation bias.

Quote:2. "Earth as an organism": I saw this claim in one of the other threads in Nirmukta. That's why I mentioned it. If you agree that it is pseudoscience, we can move on.]

I do not make hasty generalizations without taking into consideration the context. Doing so is crude and misses the point. My use of the word "pseudoscience" was general, to prevent digression, by pointing out that of course there are pseudoscientific analogies out there, but it is disingenuous to use them to dismiss all analogies as pseudoscientific.

But let's get into it now.

You initially said "Every time I read that the earth is an organism..". That is, you actually were comparing our conversation to those who say that the earth is an organism. I am well aware of the number of pseudoscientific claims made along those lines (such as the gaia hypothesis that Arvind pointed out, on which I have also had long arguments with pantheists and such).But I also know there are valid points of commonality when the metaphor is not abused but rather used as it should.

So, instead of getting sidelined into another digression, having to either agree with or disagree with something that is presented incompletely without context, I simply said :"please stop referring to pseudoscientific ideas as analogous to the valid analogies we are discussing here. We can discuss the analogy of the brain as a computational system without resorting to such distractions."

Unfortunately, it looks like you are intent on continuing to pursue the distraction. Fine, I'll go for the ride. Please point me to the thread in question, clearly state in detail what relationship between the compared objects the analogy in context is concerned about, and then ask me the question of whether THAT analogy is pseudoscience. Until then, I will assume that you are talking about a pseudoscientific analogy, and point out that it is logically inconsistent to use it to dismiss all analogies as pseudoscientific.

"Fossil rabbits in the Precambrian"
~ J.B.S.Haldane, on being asked to falsify evolution.
(This post was last modified: 15-08-2011 02:11 AM by Ajita Kamal.)
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LMC Offline
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Post: #34
RE: Is Biological Intelligence Different From Machine Intelligence?

Analogies have helped progress in all domains , they aren't only
Quote:stuff of American TV preachers
, they are ofcourse abused often, depending on the accuracy required, and the level of the audience metaphors may be appropriately chosen

Can anybody clear this for me if it is possible to have parallel computing on computers?, i mean really parallel not pseudo-parallel as with many-core computers where os switches from one to other fast enough to give illusion of simultaneous processing, brain performs 'parallel computing', different parts of brain work simultaneously

Quote:I would like to know from you if you disagree with my assertion that given unlimited time and computational resources, using evolutionary algorithms, and probabilistic reasoning, it is theoretically possible to create machines that function like brains. If you disagree, then what will these machines be missing?
There are various fields where computers outperform human brain, the main problem in understanding a machine to be human- like is that it is hard to imagine anything man-made to be sentient, movies often portray robots to be emotion-less and a sentient robot is rather an unexpected accident,

for the purpose of discussion i'd like to quote from daniel denett's consciousness explained and seek your views on it, i'll just post the relevant parts and the entire section(not the entire book) i'll upload here
Quote:if the self is "just" the Center of Narrative Gravity, and if all the
phenomena of human consciousness are explicable as "just" the activities
of a virtual machine realized in the astronomically adjustable connections
of a human brain, then, in principle, a suitably "programmed"
robot, with a silicon-based computer brain, would be conscious, would
have a self. More aptly, there would be a conscious self whose body
was the robot and whose brain was the computer. This implication of
my theory strikes some people as obvious and unobjectionable. "Of
course we're machines! We're just very, very complicated, evolved machines
made of organic molecules instead of metal and silicon, and we
are conscious, so there can be conscious machines — us." For these
readers, this implication was a foregone conclusion. What has proved
to be interesting to them, I hope, are the variety of unobvious implications
encountered along the way, in particular those that show how
much of the commonsense Cartesian picture must be replaced as we
learn more about the actual machinery of the brain.
Other people, however, find the implication that there could be,
in principle, a conscious robot so incredible that it amounts in their
eyes to the reductio ad absurdum of my theory. A friend of mine once
responded to my theory with the following heartfelt admission: "But,
Dan, I just can't imagine a conscious robot!" Some readers may be
inclined to endorse his claim. They should resist the inclination, for
he misspoke. His error was simple, but it draws attention to a fundamental
confusion blocking progress on understanding consciousness.
"You know that's false," I replied. "You've often imagined conscious
robots. It's not that you can't imagine a conscious robot; it's that you
can't imagine how a robot could be conscious."
(This post was last modified: 16-08-2011 04:20 AM by LMC.)
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LMC Offline
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Post: #35
RE: Is Biological Intelligence Different From Machine Intelligence?

Quote:But imagine a computer that records all conversations it hears between humans. Over time, this computer will build up a considerable database that it can use to make conversation. If it is asked a question, it looks up the question in its database and reproduces the answer given by a real human.

In this way a computer with a big enough look up table can always have a conversation that is essentially indistinguishable from one that humans would have

"So if there is a fundamental obstacle to computers passing the Turing Test, then it is not to be found in computability theory," says Aaronson.

Instead, a more fruitful way forward is to think about the computational complexity of the problem. He points out that while the database (or look up table) approach "works," it requires computational resources that grow exponentially with the length of the conversation.

that is just one of the way to cheat a turing test, there is always a memory required-response time-accuracy tradeoff

cheating on turing test does not require very high accuracy , infact most algos do not look for exact word-to word responses but rather tokens or keywords, most algos do not require "computational resources that grow exponentially with the length of the conversation"

at cost of accuracy algos can have resources increasing at nlogn rather than exponentially,or even with a maximum finite limit

infact this algorithm isn't very accurate either, for example response to the question say "are you watching the the india-pak worldcup final tommorrow?" may be saved as "yeah sure man i've been waiting for it for years " .
(This post was last modified: 16-08-2011 04:55 AM by LMC.)
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Post: #36
RE: Is Biological Intelligence Different From Machine Intelligence?

@Ajita;

There are probably dozens of questions in this thread that I haven't gotten a chance to answer. I am not ducking them. I was and am planning to answer them. Nor am I interested in distractions. The earth as an organism was an aside -- I was reacting to seeing it again on Nirmukta.

I will pick a couple of open questions and answer them. If you want me to take up one of the unanswered ones, point it out and I will consider taking it up right away.

> note that you have conveniently disregarded the scientific study I pointed to that demonstrated an advanced computational process in a plant system

Not at all. I had clearly mentioned while responding to that one post that I had seriously considered only the first paragraph. I had not gotten around to the others.
-----------------------------------------------------------------------
> "If we are talking only about machines created by us so far, then of course, YES, biological intelligence is vastly different from the most brilliant computers (or any other machines) we have."

I of course have no problems with the above.
----------------------------------------------------------------------
> I would like to know from you if you disagree with my assertion that given unlimited time and computational resources, using evolutionary algorithms, and probabilistic reasoning, it is theoretically possible to create machines that function like brains. If you disagree, then what will these machines be missing?

1. I would like to replace "brain" with "humans". More than brain is involved in human functioning. Let me know whether you disagree.

2. If is hard to say anything about things involving "unlimited time and computational resources". There will always be limits. Let's say you mean very large amount.

3. You also say "theoretically'. Again the proof is in the pudding.

4. I will still bite. Here is my guess: "Evolutionary algorithms and probabilistic reasoning" alone will not enough. If we want to create human like machines, I think that we need to build into them what is known about humans, namely the following:

a. Humans build a repertoire of behavior as they are exposed to contingencies

b. Humans respond to discriminative stimuli

5. I didn't take up your above question (which follows my ">") up until now for a simple reason: my major point in this thread is something else. (See 6 below.)

6. One of the reasons given for using the computer metaphor (with obviously today's computers) is that it will throw light on the behavior of flesh and blood humans. My view is that this completely misguided. I am with Searle100% on this.

7. When a person calculates the 15% tip on a restaurant bill, he is engaged in behavior that may be called computing. Likewise when he works on calculations. Other than this obvious sense, he is not involved in computing at all.

8. Neurons fire to produce different behavior in different circumstances. Nothing is gained by calling this computing.

9. Also, a lot of people who claim to engage in cognitive neuroscience, do not observe brain functions directly at all which would involve using special instruments. They make statements from observing behavior. The nervous system they describe is a conceptual nervous system as opposed to the real "flesh and blood" nervous system.

10. Let's say that two different people make two different statements about a natural process. One demonstrates mastery over the subject matter and the other doesn't. For instance, in an ABABAB design, where A is baseline and B is treatment (where a single variable changed), if a given effect occurs in B, things go back to the baseline in A, the same effect occurs in B, we can claim that the change in the variable in B is responsible for the effect. This is what I meant by "utility" in an earlier discussion (rather loosely speaking). I didn't mean that we need to take it to the level of a practical application every time. If we can demonstrate that a variable has an effect, that can lead to practical applications, of course. It is the mastery over the subject matter that is important in the lab.

11. You guys are freethinkers and should at least be willing to consider what I have to say.

12. "Thinking" is a word which means multiple things. To a behaviorist, some most important parts of what is called thinking are private verbal operant behavior, under the control of variables that affect other operant behavior (like a pigeon's key press). You should at least give this view a chance. I am not the best person to describe it. It is well described in several books that I have referred to already and will do so again.

13. Of course, reading all these books will take time. They are all counter intuitive. What you could easily do is to look at the reviews in Amazon of some of the Skinnerian books and books by people like Jon Bailey. You will see that people are bowled over by these books. Of course, this alone doesn't mean anything. I am sure somebody will bring up the "cool aid/ Jonestown" incident. That doesn't prove anything either. People are able to do extraordinary things by applying the kind of principles that I am talking about. M.J. Vaughn has applied Skinnerian principles to improve the quality of life of quadriplegics using capuchin monkeys. People who always have required custodial care have been taught to achieve a measure of independence in self-care. The applications in education alone are very impressive.

14. I do not come from a risk-taking background at all. I was so moved to take up this field. What stopped me was my lack of confidence in my skills and the job market.

15. And this is not a hasty flaky interest. My interest is a 40 year one.

16. A way to give my view fair treatment is to read the "Why I Am Not A Cognitive Psychologist" article by Skinner.
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Let me repeat this: If you feel that I have not addressed any of your points, raise it and I will give it top consideration.
(This post was last modified: 16-08-2011 05:54 AM by sojourner.)
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