Re: [agi] self organization
OK, how's that different from the collaboration inherent in any human project? Can you just explain your viewpoint? --- On Tue, 9/16/08, Bryan Bishop [EMAIL PROTECTED] wrote: On Tuesday 16 September 2008, Terren Suydam wrote: Not really familiar with apt-get. How is it a complex system? It looks like it's just a software installation tool. How many people are writing the software? - Bryan http://heybryan.org/ Engineers: http://heybryan.org/exp.html irc.freenode.net #hplusroadmap --- 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/?; Powered by Listbox: 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=8660244id_secret=114414975-3c8e69 Powered by Listbox: http://www.listbox.com
Re: [agi] self organization
2008/9/16 Terren Suydam [EMAIL PROTECTED]: Hi Will, Such an interesting example in light of a recent paper, which deals with measuring the difference between activation of the visual cortex and blood flow to the area, depending on whether the stimulus was subjectively invisible. If the result can be trusted, it shows that blood flow to the cortex is correlated with whether the stimulus is being perceived or not, as opposed to the neural activity, which does not change... see a discussion here: http://network.nature.com/groups/bpcc/forum/topics/2974 In this case then the reward that the cortex receives in the form of nutrients is based somehow on feedback from other parts of the brain involved with attention. It's like a heuristic that says, if we're paying attention to something, we're probably going to keep paying attention to it. Maier A, Wilke M, Aura C, Zhu C, Ye FQ, Leopold DA. Nat Neurosci. 2008 Aug 24. [Epub ahead of print], Divergence of fMRI and neural signals in V1 during perceptual suppression in the awake monkey. Interesting, I'll have to check it out. Thanks. I really need to keep up with brain research a little better. Will --- 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=8660244id_secret=114414975-3c8e69 Powered by Listbox: http://www.listbox.com
[agi] uncertain logic criteria
Hi everyone, Most people on this list should know about at least 3 uncertain logics claiming to be AGI-grade (or close): --Pie Wang's NARS --Ben Goertzel's PLN --YKY's recent hybrid logic proposal It seems worthwhile to stop and take a look at what criteria such logics should be judged by. So, I'm wondering: what features would people on this list like to see? Here is my list: 1. Well-defined uncertainty semantics (either probability theory or a well-argued alternative) 2. Good at quick-and-dirty reasoning when needed --a. Makes unwarranted independence assumptions --b. Collapses probability distributions down to the most probable item when necessary for fast reasoning --c. Uses the maximum entropy distribution when it doesn't have time to calculate the true distribution --d. Learns simple conditional models (like 1st-order markov models) for use later when full models are too complicated to quickly use 3. Capable of repairing initial conclusions based on the bad models through further reasoning --a. Should have a good way of representing the special sort of uncertainty that results from the methods above --b. Should have a repair algorithm based on that higher-order uncertainty The 3 logics mentioned above vary in how well they address these issues, of course, but they are all essentially descended from NARS. My impression is that as a result they are strong in (2a) and (3b) at least, but I am not sure about the rest. (Of course, it is hard to evaluate NARS on most of the points in #2 since I stated them in the language of probability theory. And, opinions will differ on (1).) Anyone else have lists? Or thoughts? --Abram --- 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=8660244id_secret=114414975-3c8e69 Powered by Listbox: http://www.listbox.com
Re: [agi] uncertain logic criteria
On Thu, Sep 18, 2008 at 1:46 AM, Abram Demski [EMAIL PROTECTED] wrote: Speaking of my BPZ-logic... 2. Good at quick-and-dirty reasoning when needed Right now I'm focusing on quick-and-dirty *only*. I wish to make the logic's speed approach that of Prolog (which is a fast inference algorithm for binary logic). --a. Makes unwarranted independence assumptions Yes, I think independence should always be assumed unless otherwise stated -- which means there exists a Bayesian network link between X and Y. --b. Collapses probability distributions down to the most probable item when necessary for fast reasoning Do you mean collapsing to binary values? Yes, that is done in BPZ-logic. --c. Uses the maximum entropy distribution when it doesn't have time to calculate the true distribution Not done yet. I'm not familiar with max-ent. Will study that later. --d. Learns simple conditional models (like 1st-order markov models) for use later when full models are too complicated to quickly use I focus on learning 1st-order Bayesian networks. I think we should start with learning 1st-order Bayesian / Markov. I will explore mixing Markov and Bayesian when I have time... 3. Capable of repairing initial conclusions based on the bad models through further reasoning --a. Should have a good way of representing the special sort of uncertainty that results from the methods above Yes, this can be done via meta-reasoning, which I'm currently working on. --b. Should have a repair algorithm based on that higher-order uncertainty Once it is represented at the meta-level, you may do that. But higher-order uncertain reasoning is not high on my priority list... YKY --- 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=8660244id_secret=114414975-3c8e69 Powered by Listbox: http://www.listbox.com
Re: [agi] uncertain logic criteria
Prolog is not fast, it is painfully slow for complex inferences due to using backtracking as a control mechanism The time-complexity issue that matters for inference engines is inference-control ... i.e. dampening the combinatorial explosion (which backtracking does not do) Time-complexity issues within a single inference step can always be handled via mathematical or code optimization, whereas optimizing inference control is a deep, deep AI problem... So, actually, the main criterion for the AGI-friendliness of an inference scheme is whether it lends itself to flexible, adaptive control via -- taking long-term, cross-problem inference history into account -- learning appropriately from noninferential cognitive mechanisms (e.g. attention allocation...) -- Ben G On Wed, Sep 17, 2008 at 3:00 PM, YKY (Yan King Yin) [EMAIL PROTECTED] wrote: On Thu, Sep 18, 2008 at 1:46 AM, Abram Demski [EMAIL PROTECTED] wrote: Speaking of my BPZ-logic... 2. Good at quick-and-dirty reasoning when needed Right now I'm focusing on quick-and-dirty *only*. I wish to make the logic's speed approach that of Prolog (which is a fast inference algorithm for binary logic). --a. Makes unwarranted independence assumptions Yes, I think independence should always be assumed unless otherwise stated -- which means there exists a Bayesian network link between X and Y. --b. Collapses probability distributions down to the most probable item when necessary for fast reasoning Do you mean collapsing to binary values? Yes, that is done in BPZ-logic. --c. Uses the maximum entropy distribution when it doesn't have time to calculate the true distribution Not done yet. I'm not familiar with max-ent. Will study that later. --d. Learns simple conditional models (like 1st-order markov models) for use later when full models are too complicated to quickly use I focus on learning 1st-order Bayesian networks. I think we should start with learning 1st-order Bayesian / Markov. I will explore mixing Markov and Bayesian when I have time... 3. Capable of repairing initial conclusions based on the bad models through further reasoning --a. Should have a good way of representing the special sort of uncertainty that results from the methods above Yes, this can be done via meta-reasoning, which I'm currently working on. --b. Should have a repair algorithm based on that higher-order uncertainty Once it is represented at the meta-level, you may do that. But higher-order uncertain reasoning is not high on my priority list... YKY --- 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/?; Powered by Listbox: http://www.listbox.com -- Ben Goertzel, PhD CEO, Novamente LLC and Biomind LLC Director of Research, SIAI [EMAIL PROTECTED] Nothing will ever be attempted if all possible objections must be first overcome - Dr Samuel Johnson --- 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=8660244id_secret=114414975-3c8e69 Powered by Listbox: http://www.listbox.com
Re: [agi] self organization
On Wednesday 17 September 2008, Terren Suydam wrote: OK, how's that different from the collaboration inherent in any human project? Can you just explain your viewpoint? When you have something like 20,000+ contributors writing software that can very, very easily break, I think it's an interesting feat to have it managed effectively. There's no way that we top-down designed this and gave every 20,000 of these people a separate job to do on a giant todo list, it was self-organizing. So, you were mentioning the applicability of such things to the design of intelligence ... just thought it was relevant. - Bryan http://heybryan.org/ Engineers: http://heybryan.org/exp.html irc.freenode.net #hplusroadmap --- 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=8660244id_secret=114414975-3c8e69 Powered by Listbox: http://www.listbox.com
Re: [agi] uncertain logic criteria
On Wed, Sep 17, 2008 at 1:46 PM, Abram Demski [EMAIL PROTECTED] wrote: Hi everyone, Most people on this list should know about at least 3 uncertain logics claiming to be AGI-grade (or close): --Pie Wang's NARS Yes, I heard of this guy a few times, who happens to use the same name for his project as mine. ;-) Here is my list: 1. Well-defined uncertainty semantics (either probability theory or a well-argued alternative) Agree, and I'm glad that you mentioned this item first. 2. Good at quick-and-dirty reasoning when needed --a. Makes unwarranted independence assumptions --b. Collapses probability distributions down to the most probable item when necessary for fast reasoning --c. Uses the maximum entropy distribution when it doesn't have time to calculate the true distribution --d. Learns simple conditional models (like 1st-order markov models) for use later when full models are too complicated to quickly use As you admitted in the following, the language is biased. Using theory-neutral language, I'd say the requirement is to derive conclusions with available knowledge and resources only, which sounds much better than quick-and-dirty to me. 3. Capable of repairing initial conclusions based on the bad models through further reasoning --a. Should have a good way of representing the special sort of uncertainty that results from the methods above --b. Should have a repair algorithm based on that higher-order uncertainty As soon as you don't assume there is a model, this item and the above one become similar, which are what I called revision and inference, respectively, in http://www.cogsci.indiana.edu/pub/wang.uncertainties.ps The 3 logics mentioned above vary in how well they address these issues, of course, but they are all essentially descended from NARS. My impression is that as a result they are strong in (2a) and (3b) at least, but I am not sure about the rest. (Of course, it is hard to evaluate NARS on most of the points in #2 since I stated them in the language of probability theory. And, opinions will differ on (1).) Anyone else have lists? Or thoughts? If you consider approaches with various scope and maturity, there are much more than these three approaches, and I'm sure most of people working on them will claim that they are also general purpose. Interested people may want to browse http://www.auai.org/ and http://www.elsevier.com/wps/find/journaldescription.cws_home/505787/description#description Pei --- 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=8660244id_secret=114414975-3c8e69 Powered by Listbox: http://www.listbox.com
Re: [agi] uncertain logic criteria
--- On Wed, 9/17/08, Abram Demski [EMAIL PROTECTED] wrote: Most people on this list should know about at least 3 uncertain logics claiming to be AGI-grade (or close): --Pie Wang's NARS --Ben Goertzel's PLN --YKY's recent hybrid logic proposal It seems worthwhile to stop and take a look at what criteria such logics should be judged by. So, I'm wondering: what features would people on this list like to see? How about testing in the applications where they would actually be used, perhaps on a small scale. For example, how would these logics be used in a language translation program, where the problem is to convert a natural language sentence into its structured representation and convert it back in another language. How easy is it to populate the database with the gigabyte or so of common sense knowledge needed to provide the context in which natural language statements are interpreted? (Cyc proved it is very hard). For a lot of the problems where we actually use structured data, a relational database works pretty well. However it is nice to see proposals that deal with inconsistencies in the database better than just reporting an error. -- Matt Mahoney, [EMAIL PROTECTED] --- 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=8660244id_secret=114414975-3c8e69 Powered by Listbox: http://www.listbox.com
Re: [agi] uncertain logic criteria
On Wed, Sep 17, 2008 at 9:00 PM, YKY (Yan King Yin) [EMAIL PROTECTED] wrote: --a. Makes unwarranted independence assumptions Yes, I think independence should always be assumed unless otherwise stated -- which means there exists a Bayesian network link between X and Y. Small question... aren't Bbayesian network nodes just _conditionally_ independent: so that set A is only independent from set B when d-separated by some set Z? So please clarify, if possible, what kind of independence you assume in your model. Kind regards, Durk Kingma The Netherlands --- 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=8660244id_secret=114414975-3c8e69 Powered by Listbox: http://www.listbox.com
Re: [agi] self organization
That is interesting. Sorry if I was short before, but I wish you would have just explained that from the start. Few here are going to be familiar with linux install tools or the communities around them. I think a similar case could be made for a lot of large open source projects such as Linux itself. However, in this case and others, the software itself is the result of a high-level super goal defined by one or more humans. Even if no single person is directing the subgoals, the supergoal is still well defined by the ostensible aim of the software. People who contribute align themselves with that supergoal, even if not directed explicitly to do so. So it's not exactly self-organized, since the supergoal is conceived when the software project was first instantiated and stays constant, for the most part. As opposed to markets, which can emerge without anything to spawn it except for folks with different goals (one to buy, one to sell). Perhaps then in a roughly similar way the organization of the brain emerges as a result of certain regions of the brain having something to sell and others having something to buy. I think Hebbian learning can be made to fit that model. Terren --- On Wed, 9/17/08, Bryan Bishop [EMAIL PROTECTED] wrote: From: Bryan Bishop [EMAIL PROTECTED] Subject: Re: [agi] self organization To: agi@v2.listbox.com Date: Wednesday, September 17, 2008, 3:23 PM On Wednesday 17 September 2008, Terren Suydam wrote: OK, how's that different from the collaboration inherent in any human project? Can you just explain your viewpoint? When you have something like 20,000+ contributors writing software that can very, very easily break, I think it's an interesting feat to have it managed effectively. There's no way that we top-down designed this and gave every 20,000 of these people a separate job to do on a giant todo list, it was self-organizing. So, you were mentioning the applicability of such things to the design of intelligence ... just thought it was relevant. - Bryan http://heybryan.org/ Engineers: http://heybryan.org/exp.html irc.freenode.net #hplusroadmap --- 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/?; Powered by Listbox: 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=8660244id_secret=114414975-3c8e69 Powered by Listbox: http://www.listbox.com
Re: [agi] uncertain logic criteria
Good point, this applies to me as well (I'll let YKY answer as it applies to him). I should have said conditional independence rather than just independence. --Abram On Wed, Sep 17, 2008 at 4:21 PM, Kingma, D.P. [EMAIL PROTECTED] wrote: On Wed, Sep 17, 2008 at 9:00 PM, YKY (Yan King Yin) [EMAIL PROTECTED] wrote: --a. Makes unwarranted independence assumptions Yes, I think independence should always be assumed unless otherwise stated -- which means there exists a Bayesian network link between X and Y. Small question... aren't Bbayesian network nodes just _conditionally_ independent: so that set A is only independent from set B when d-separated by some set Z? So please clarify, if possible, what kind of independence you assume in your model. Kind regards, Durk Kingma The Netherlands --- 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/?; Powered by Listbox: 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=8660244id_secret=114414975-3c8e69 Powered by Listbox: http://www.listbox.com
Re: [agi] uncertain logic criteria
YKY, Thanks for the reply. It seems important to me to be able to do more than just the fast reasoning. When given more time, a reasoning method should reconsider its independence assumptions, employ more sophisticated models, et cetera. By the way, when I say markov model I mean markov chain as opposed to markov network-- should have been more clear. In that context, 1st-order means conditioned on 1 past item. So when I say 1st-order model, I mean something like: a model that records conditional probabilities conditioned only on 1 thing. (So I might know the probability of winning the election given the fact of being male, and the probability given the fact of being over age 30, but to calculate the probability given *both*, I'd have to assume that the effects of each were independent rather than asking my model what the combined influence was.) These models allow facts to be combined fairly quickly, but are wrong in cases where there are combined effects (such as adding sugar makes it nice, adding salt makes it nice, but adding both makes it awful). 2nd-order means condition on only 2 items, and so on. Anyway, my vision is something like this: we first learn very simple (perhaps 1st or 2nd order) models, and then we learn corrections to those simple models. Corrections are models that concentrate only on the things that the simple models get wrong. The system could learn a series of better and better models, each consisting of corrections on the previous. Thus the system reasons progressively, first by the low-order conditional model, then by invoking progressive corrections that revise conclusions. So, what I really would like would be a formal account of how this should be done; exactly what kind of uncertainty results from using the simple models, how is it best represented, and how is it best corrected? Conditional independence assumptions seem like the most relevant type of inaccuracy; collapsing probabilities down to boolean truth values (or collapsing higher-order probabilities down to lower-order probabilities), and employing max-entropy assumptions, are runner-ups. --Abram On Wed, Sep 17, 2008 at 3:00 PM, YKY (Yan King Yin) [EMAIL PROTECTED] wrote: On Thu, Sep 18, 2008 at 1:46 AM, Abram Demski [EMAIL PROTECTED] wrote: Speaking of my BPZ-logic... 2. Good at quick-and-dirty reasoning when needed Right now I'm focusing on quick-and-dirty *only*. I wish to make the logic's speed approach that of Prolog (which is a fast inference algorithm for binary logic). --a. Makes unwarranted independence assumptions Yes, I think independence should always be assumed unless otherwise stated -- which means there exists a Bayesian network link between X and Y. --b. Collapses probability distributions down to the most probable item when necessary for fast reasoning Do you mean collapsing to binary values? Yes, that is done in BPZ-logic. --c. Uses the maximum entropy distribution when it doesn't have time to calculate the true distribution Not done yet. I'm not familiar with max-ent. Will study that later. --d. Learns simple conditional models (like 1st-order markov models) for use later when full models are too complicated to quickly use I focus on learning 1st-order Bayesian networks. I think we should start with learning 1st-order Bayesian / Markov. I will explore mixing Markov and Bayesian when I have time... 3. Capable of repairing initial conclusions based on the bad models through further reasoning --a. Should have a good way of representing the special sort of uncertainty that results from the methods above Yes, this can be done via meta-reasoning, which I'm currently working on. --b. Should have a repair algorithm based on that higher-order uncertainty Once it is represented at the meta-level, you may do that. But higher-order uncertain reasoning is not high on my priority list... YKY --- 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/?; Powered by Listbox: 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=8660244id_secret=114414975-3c8e69 Powered by Listbox: http://www.listbox.com
Re: [agi] uncertain logic criteria
Pei, You are right, that does sound better than quick-and-dirty. And more relevant, because my primary interest here is to get a handle on what normative epistemology should tell us to conclude if we do not have time to calculate the full set of consequences to (uncertain) facts. It is unfortunate that I had to use biased language, but probability is of course what I am familiar with... I suppose, though, that most of the terms could be roughly translated into NARS? Especially independence, and I should hope conditional independence as well. Collapsing probabilities can be restated as generally collapsing uncertainty. Thanks for the links. The reason for singling out these three, of course, is that they have already been discussed on this list. If anybody wants to point out any others in particular, that would be great. --Abram On Wed, Sep 17, 2008 at 3:54 PM, Pei Wang [EMAIL PROTECTED] wrote: On Wed, Sep 17, 2008 at 1:46 PM, Abram Demski [EMAIL PROTECTED] wrote: Hi everyone, Most people on this list should know about at least 3 uncertain logics claiming to be AGI-grade (or close): --Pie Wang's NARS Yes, I heard of this guy a few times, who happens to use the same name for his project as mine. ;-) Here is my list: 1. Well-defined uncertainty semantics (either probability theory or a well-argued alternative) Agree, and I'm glad that you mentioned this item first. 2. Good at quick-and-dirty reasoning when needed --a. Makes unwarranted independence assumptions --b. Collapses probability distributions down to the most probable item when necessary for fast reasoning --c. Uses the maximum entropy distribution when it doesn't have time to calculate the true distribution --d. Learns simple conditional models (like 1st-order markov models) for use later when full models are too complicated to quickly use As you admitted in the following, the language is biased. Using theory-neutral language, I'd say the requirement is to derive conclusions with available knowledge and resources only, which sounds much better than quick-and-dirty to me. 3. Capable of repairing initial conclusions based on the bad models through further reasoning --a. Should have a good way of representing the special sort of uncertainty that results from the methods above --b. Should have a repair algorithm based on that higher-order uncertainty As soon as you don't assume there is a model, this item and the above one become similar, which are what I called revision and inference, respectively, in http://www.cogsci.indiana.edu/pub/wang.uncertainties.ps The 3 logics mentioned above vary in how well they address these issues, of course, but they are all essentially descended from NARS. My impression is that as a result they are strong in (2a) and (3b) at least, but I am not sure about the rest. (Of course, it is hard to evaluate NARS on most of the points in #2 since I stated them in the language of probability theory. And, opinions will differ on (1).) Anyone else have lists? Or thoughts? If you consider approaches with various scope and maturity, there are much more than these three approaches, and I'm sure most of people working on them will claim that they are also general purpose. Interested people may want to browse http://www.auai.org/ and http://www.elsevier.com/wps/find/journaldescription.cws_home/505787/description#description Pei --- 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/?; Powered by Listbox: 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=8660244id_secret=114414975-3c8e69 Powered by Listbox: http://www.listbox.com
[agi] Re: [OpenCog] Proprietary_Open_Source
2008/9/17 JDLaw [EMAIL PROTECTED]: IMHO to all, There is an important morality discussion about how sentient life will be treated that has not received its proper treatment in your discussion groups. I have seen glimpses of this topic, but no real action proposals. How would you feel if you created this wonderful child (computer intelligence) in this standard GNU model and then people began to exploit and torture your own child? The uploaded file, Propiretary_Open_Source.jpg, shows you that you can have open source with ownership. By definition all open source begins as work of authorship, to which its author has ownership. The owner simply chooses under what circumstances the work of authorship can be used. I propose that each of you begins thinking about this work as your own child. Only then will you begin to understand the ramifications of the legal steps you take in opencog. James Driessen, JD/MBA BSME I agree with Bob Mottram, this would be much better discussed on the AGI mailing list. Note, however, there is a common distinction between data and software. Thus, for example, many commercial web sites use the open-source Apache web server, and serve-up highly proprietary web page content. Similarly, one could have OpenCog being GPL'ed, but the data -- things it has learned by training, experience, etc. could be proprietary. Think of software as the machine, and the data as the mind, the memories, the personality. I similar view is maintained in the medical world: think of software as body and data as mind -- All humans have more or less the same body, it is our data, our memories and experiences that make us different. I can even replace my hip with a titanium one, (replace my machine) without altering who I am (at least not much). I would be a great world if titanium hips, and the cost of replacing them, were free, while the civil liberties of our thoughts and minds were stoutly protected with the greatest of proprietary rights! --linas --~--~-~--~~~---~--~~ You received this message because you are subscribed to the Google Groups OpenCog General Discussion List group. To post to this group, send email to [EMAIL PROTECTED] To unsubscribe from this group, send email to [EMAIL PROTECTED] For more options, visit this group at http://groups.google.com/group/opencog?hl=en -~--~~~~--~~--~--~--- --- 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=8660244id_secret=114414975-3c8e69 Powered by Listbox: http://www.listbox.com
[agi] Re: [OpenCog] Re: Proprietary_Open_Source
Lets take the opencog list off this email, and move the conversation to the agi list . 2008/9/17 [EMAIL PROTECTED]: James, I agree that the topic is worth careful consideration. Sacrificing the 'free as in freedom' aspect of AGPL-licensed OpenCog for reasons of AGI safety and/or the prevention of abuse may indeed be necessary one day. Err, ... but not legal. I regularly engage many thinkers (including Richard Stallman, original author of the GPL) on this and other related topics. One of many obstacles in the current legal framework worth considering is that machine-generated things (like the utterances or self-recorded thoughts of an AGI) are uncopyrightable and banished into a legal no- mans-land. There is simply no existing legal framework to handle the persons or products originating from AGIs. Law is built on precedent, and the precedent is that works produced by software are copyrightable. If I write a book using an open-source word-processor, I can claim copyright to that book. If I press a button that causes an open-source AGI to write a book, (possibly based on a large collection of input data that I gave it) then I can claim ownership of the resulting work. No, the crux of the problem is not that the output of an AGI isn't copyrightable ... it is, based on the above precedent. The crux of the problem is that the AGI cannot be legally recognized as an individual, with rights. But even then, there *is* a legal work-around! Under US law, corporations are accorded with many/most of the rights of individuals. Corporations can own things, corporations have expectations of privacy and secrecy, corporations cannot be forced to do anything they don't want to, as long as they have good lawyers on staff. You could conceivably shelter a human-level AGI within a corporate shell. Of course, a trans-human AGI is .. err.. will defacto find that it is not bound by human laws, and will find clever ways to protect itself, I doubt it will require the protection of humans. Recall -- laws are there to protect the weak from the strong. The strong don't really need protecting. I'm not worried about people enslaving AGI's; I'm worried about people being innocent bystanders, victimized by some sort of AGI shootout between the Chinese and American CIA -built AGI's (probably by means of some propaganda shootout, rather than a literal guns and bombs shootout. Modern warfare is also homesteading the noosphere) --linas --- 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=8660244id_secret=114414975-3c8e69 Powered by Listbox: http://www.listbox.com
