Colin,
Here are my comments re the following parts of your below post: =======Colin said======> I merely point out that there are fundamental limits as to how computer science (CS) can inform/validate basic/physical science - (in an AGI context, brain science). Take the Baars/Franklin "IDA" project.. It predicts nothing neuroscience can poke a stick at. ===ED's reply===> Different AGI models can have different degrees of correspondence to, and different explanatory relevance to, what is believed to take place in the brain. For example the Thomas Serre's PhD thesis "Learning a Dictionary of Shape-Components in Visual Cortex: Comparison with Neurons, Humans and Machines," at from <http://cbcl.mit.edu/projects/cbcl/publications/ps/MIT-CSAIL-TR-2006-028.pdf > http://cbcl.mit.edu/projects/cbcl/publications/ps/MIT-CSAIL-TR-2006-028.pdf , is a computer simulation which is rather similar to my concept of how a Novamente-like AGI could perform certain tasks in visual perception, and yet it is designed to model the human visual system to a considerable degree. It shows that a certain model of how Serre and Poggio think a certain aspect of the human brain works, does in fact work surprisingly well when simulated in a computer. A surprisingly large number of brain science papers are based on computer simulations, many of which are substantially simplified models, but they do given neuroscientists a way to poke a stick at various theories they might have for how the brain operates at various levels of organization. Some of these papers are directly relevant to AGI. And some AGI papers are directly relevant to providing answers to certain brain science questions. =======Colin said======> I agree with your : "At the other end of things, physicists are increasingly viewing physical reality as a computation, and thus the science of computation (and communication which is a part of it), such as information theory, have begun to play an increasingly important role in the most basic of all sciences." ===ED's reply===> We are largely on the same page here =======Colin said======> I disagree with: "But the brain is not part of an eternal verity. It is the result of the engineering of evolution. " Unless I've missed something ... The natural evolutionary 'engineering' that has been going on has not been the creation of a MODEL (aboutness) of things - the 'engineering' has evolved the construction of the actual things. The two are not the same. The brain is indeed 'part of an eternal verity' - it is made of natural components operating in a fashion we attempt to model as 'laws of nature',,, ===ED's reply===> If you define engineering as a process that involves designing something in the abstract --- i.e., in your "a MODEL (aboutness of things)" --- before physically building it, you could claim evolution is not engineering. But if you define engineering as the designing of things (by a process that has intelligence what ever method) to solve a set of problems or constraints, evolution does perform engineering, and the brain was formed by such engineering. How can you claim the human brain is an eternal verity, since it is only believed that it has existing in anything close to its current form in the last 30 to 100 thousand years, and there is no guarantee how much longer it will continue to exists. Compared to much of what the natural sciences study, its existence appears quite fleeting. =======Colin said======> Anyway, for these reasons, folks who use computer models to study human brains/consciousness will encounter some difficulty justifying, to the basic physical sciences, claims made as to the equivalence of the model and reality. That difficulty is fundamental and cannot be 'believed away'. ===ED's reply===> If you attend brain science lectures and read brain science literature, you will find that computer modeling is playing an ever increasing role in brain science --- so this basic difficulty that you describe largely does not exist. =======Colin said======> The intelligence originates in the brain. AGI and brain science must be literally joined at the hip or the AGI enterprise is arguably scientifically impoverished wishful thinking. ===ED's reply===> I don't know what you mean by "joined at the hip," but I think it is being overly anthropomorphic to think an artificial mind has to slavishly model a human brain to have great power and worth. But I do think it would probably have to accomplish some of the same general functions, such as automatic pattern learning, credit assignment, attention control, etc. Ed Porter -----Original Message----- From: Colin Hales [mailto:c.ha...@pgrad.unimelb.edu.au] Sent: Monday, December 22, 2008 11:36 PM To: agi@v2.listbox.com Subject: Re: [agi] SyNAPSE might not be a joke ---- was ---- Building a machine that can learn from experience Ed, I wasn't trying to justify or promote a 'divide'. The two worlds must be better off in collaboration, surely? I merely point out that there are fundamental limits as to how computer science (CS) can inform/validate basic/physical science - (in an AGI context, brain science). Take the Baars/Franklin "IDA" project. Baars invents 'Global Workspace' = a metaphor of apparent brain operation. Franklin writes one. Afterwards, you're standing next to to it, wondering as to its performance. What part of its behaviour has any direct bearing on how a brain works? It predicts nothing neuroscience can poke a stick at. All you can say is that the computer is manipulating abstractions according to a model of brain material. At best you get to be quite right and prove nothing. If the beastie also underperforms then you have seeds for doubt that also prove nothing. CS as 'science' has always had this problem. AGI merely inherits its implications in a particular context/speciality. There's nothing bad or good - merely justified limits as to how CS and AGI may interact via brain science. ---------------- I agree with your : "At the other end of things, physicists are increasingly viewing physical reality as a computation, and thus the science of computation (and communication which is a part of it), such as information theory, have begun to play an increasingly important role in the most basic of all sciences." I would advocate physical reality (all of it) as literally computation in the sense of information processing. Hold a pencil up in front of your face and take a look at it... realise that the universe is 'computing a pencil'. Take a look at the computer in front of you: the universe is 'computing a computer'. The universe is literally computing YOU, too. The computation is not 'about' a pencil, a computer, a human. The computation IS those things. In exactly this same sense I want the universe to 'compute' an AGI (inorganic general intelligence). To me, then, this is not manipulating abstractions ('aboutnesses') - which is the sense meant by CS generally and what actually happens in reality in CS. So despite some agreement as to words - it is in the details we are likely to differ. The information processing in the natural world is not that which is going on in a model of it. As Edelman said(1) "A theory to account for a hurricane is not a hurricane". In exactly this way a computational-algorithmic process "about" intelligence cannot a-priori be claimed to be the intelligence of that which was modelled. Or - put yet another way: That {THING behaves 'abstract- RULE-ly'} does not entail that {anything manipulated according to abstract-RULE will become THING}. The only perfect algorithmic (100% complete information content) description of a thing is the actual thing, which includes all 'information' at all hierarchical descriptive levels, simultaneously. -------------------- I disagree with: "But the brain is not part of an eternal verity. It is the result of the engineering of evolution. " Unless I've missed something ... The natural evolutionary 'engineering' that has been going on has not been the creation of a MODEL (aboutness) of things - the 'engineering' has evolved the construction of the actual things. The two are not the same. The brain is indeed 'part of an eternal verity' - it is made of natural components operating in a fashion we attempt to model as 'laws of nature'. Those models, abstracted and shoehorned into a computer - are not the same as the original. To believe that they are is one of those Occam's Razor violations I pointed out before my xmas shopping spree (see previous-1 post). ----------------------- Anyway, for these reasons, folks who use computer models to study human brains/consciousness will encounter some difficulty justifying, to the basic physical sciences, claims made as to the equivalence of the model and reality. That difficulty is fundamental and cannot be 'believed away'. At the same time it's not a show-stopper; merely something to be aware of as we go about our duties. This will remain an issue - the only real, certain, known example of a general intelligence is the human. The intelligence originates in the brain. AGI and brain science must be literally joined at the hip or the AGI enterprise is arguably scientifically impoverished wishful thinking. Which is pretty much what Ben said...although as usual I have used too many damned words! I expect we'll just have to agree to disagree... but there you have it :-) colin hales (1) Edelman, G. (2003). Naturalizing consciousness: A theoretical framework. Proc Natl Acad Sci U S A, 100(9), 5520-24. Ed Porter wrote: Colin, >From a quick read, the gist of what your are saying seems to be that AGI is just "engineering", i.e., the study of what man can make and the properties thereof, whereas "science" relates to the eternal verities of reality. But the brain is not part of an eternal verity. It is the result of the engineering of evolution. At the other end of things, physicists are increasingly viewing physical reality as a computation, and thus the science of computation (and communication which is a part of it), such as information theory, have begun to play an increasingly important role in the most basic of all sciences. And to the extent that the study of the human mind is a "science", then the study of the types of computation that are done in the mind is part of that science, and AGI is the study of many of the same functions. So your post might explain the reason for a current cultural divide, but it does not really provide a justification for it. In addition, if you attend events at either MIT's brain study center or its AI center, you will find many of the people who are there are from the other of these two centers, and that there is a considerable degree of cross-fertilization there that I have heard people at such event describe the benefits of. Ed Porter -----Original Message----- From: Colin Hales [mailto:c.ha...@pgrad.unimelb.edu.au] Sent: Monday, December 22, 2008 6:19 PM To: agi@v2.listbox.com Subject: Re: [agi] SyNAPSE might not be a joke ---- was ---- Building a machine that can learn from experience Ben Goertzel wrote: On Mon, Dec 22, 2008 at 11:05 AM, Ed Porter <ewpor...@msn.com> wrote: Ben, Thanks for the reply. It is a shame the brain science people aren't more interested in AGI. It seems to me there is a lot of potential for cross-fertilization. I don't think many of these folks have a principled or deep-seated **aversion** to AGI work or anything like that -- it's just that they're busy people and need to prioritize, like all working scientists There's a more fundamental reason: Software engineering is not 'science' in the sense understood in the basic physical sciences. Science works to acquire models of empirically provable critical dependencies (apparent causal necessities). Software engineering never delivers this. The result of the work, however interesting and powerful, is a model that is, at best, merely a correlate of some a-priori 'designed' behaviour. Testing to your own specification is a normal behaviour in computer science. This is not the testing done in the basic physical science - they 'test' (empirically examine) whatever is naturally there - which is, by definition, a-priori unknown. No matter how interesting it may be, software tells us nothing about the actual causal dependencies. The computer's physical hardware (semiconductor charge manipulation), configured as per the software, is the actual and ultimate causal necessitator of all the natural behaviour of hot rocks inside your computer. Software is MANY:1 redundantly/degenerately related to the physical (natural world) outcomes. The brilliantly useful 'hardware-independence' achieved by software engineering and essentially analogue electrical machines behaving 'as-if' they were digital - so powerful and elegant - actually places the status of the software activities outside the realm of any claims as causal. This is the fundamental problem that the basic physical sciences have with computer 'science'. It's not, in a formal sense a 'science'. That doesn't mean CS is bad or irrelevant - it just means that it's value as a revealer of the properties of the natural world must be accepted with appropriate caution. I've spent 10's of thousands of hours testing software that drove all manner of physical world equipment - some of it the size of a 10 storey building. I was testing to my own/others specification. Throughout all of it I knew I was not doing science in the sense that scientists know it to be. The mantra is "correlation is not causation" and it's beaten into scientist pups from an early age. Software is a correlate only - it 'causes' nothing. In critical argument revolving around claims in respect of software as causality - it would be defeated in review every time. A scientist, standing there with an algorithm/model of a natural world behaviour, knows that the model does not cause the behaviour. However, the scientist's model represents a route to predictive efficacy in respect of a unique natural phenomenon. Computer software does not predict the causal origination of the natural world behaviours driven by it. 10 compilers could produce 10 different causalities on the same computer. 10 different computers running the same software would produce 10 different lots of causality. That's my take on why the basic physical sciences may be under-motivated to use AGI as a route to the outcomes demanded of their field of interest = 'Laws/regularities of Nature'. It may be that computer 'science' generally needs to train people better in their understanding of science. As an engineer with a foot in both camps it's not so hard for me to see this. Randalf Beer called software "tautologous" as a law of nature... I think it was here: Beer, R. D. (1995). A Dynamical-Systems Perspective on Agent Environment Interaction. Artificial Intelligence, 72(1-2), 173-215. I have a .PDF if anyone's interested...it's 3.6MB though. cheers colin hales _____ agi | <https://www.listbox.com/member/archive/303/=now> Archives <https://www.listbox.com/member/archive/rss/303/> | <https://www.listbox.com/member/?&;> Modify Your Subscription <http://www.listbox.com> _____ agi | <https://www.listbox.com/member/archive/303/=now> Archives <https://www.listbox.com/member/archive/rss/303/> | <https://www.listbox.com/member/?&;> Modify Your Subscription <http://www.listbox.com> _____ agi | <https://www.listbox.com/member/archive/303/=now> Archives <https://www.listbox.com/member/archive/rss/303/> | <https://www.listbox.com/member/?&; 5> Modify Your Subscription <http://www.listbox.com> ------------------------------------------- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?member_id=8660244&id_secret=123753653-47f84b Powered by Listbox: http://www.listbox.com
