> Do I expect the middle layers of AGI to look like something an insurance company or zoning commission might write? Sure, why not? I expect a Chinese Room hard at work, in the middle layers of the AGI.
Isn't it almost certain that in the middle of our brains, a Chinese Room is hard at work? Who expects middle-tier executive neurons to be "sentient"? (Middle-level neurons are those who harass lower neurons and are performance-evaluated by higher-level neurons on a weekly basis.) On Wed, 20 Feb 2019 at 01:19, Nanograte Knowledge Technologies < [email protected]> wrote: > Linas > > Some clarity and thoughts... > > ------------------------------ > *From:* Linas Vepstas <[email protected]> > *Sent:* Tuesday, 19 February 2019 9:06 AM > *To:* AGI > *Subject:* Re: [agi] Some thoughts about Symbols and Symbol Nets > > Hi Robert, > > I'm waiting for unit tests to pass, and it's like watching paint dry. So > I write spurious emails as I wait. Spurious response follows. > > On Mon, Feb 18, 2019 at 11:45 PM Nanograte Knowledge Technologies < > [email protected]> wrote: > > Linas, Mike and Jim > > I find this to be a most-interesting conversation. Primarily, because it > suggests that the development of AGI may not only be challenged by the > development of competent theory, but also by programming capabilities to > put the theory into practice. > > > Yes. The people who know some of the theory usually don't know how to > program, and v.v. and getting both to meet up is hard. That, plus the fact > that there are 1001 theories, and there is very little (almost no) > consensus about the right approach. > > > > Evolving such an architecture then, should desired outcomes be for an AGI > entity to achieve self-theory and self-programming? > > > Uh, yes? This question seems to be phrased awkwardly. AGI isn't some > thing that is just like a self-driving car, but only a tiny bit smarter.... > > As a human, I have a self-theory. Parts of it are excellent: I really do > know where my hands are, and what they are doing. Parts of it are terrible: > I really don't know much about the vascularization of my lower legs, or how > a black-and-blue spot appeared there. But hey, self-driving cars have a > very good idea of what is on the road in front of them, and have no idea at > all about the chemistry of rubber. Self-driving cars have a self-model. > Which is maybe less than a self-theory? > > >> What I meant by self-theory was the ability to form a hypothesis and > evolve a theory and test for such a hypothesis, all the while spinning off > the learning as computational functions of programming. I think I have a > very-good idea of what from an agi-service would take. Agreed, it;s not a > smart machine. In my vision, it's a species. > > As a human, do I engage in self-programming? Sure. I make new-years > resolutions every day. I even keep some of them. Self-driving cars don't, > for obvious liability reasons. > > >> Self-programming would be an ability to code programs on demand, or via > threshold triggers, and so on. Perhaps, as an evolutionary step. > > Do I expect an AGI to be equally self-aware, and equally in self-control? > Yes. > > > In its most-simplistic from, a symbol is but a suitable abstraction of a > greater reality, similarly to how a symbol of a red-heart might be an > abstraction of a sentient being. Concept? Context? Meaning? Transaction. > > Who, or what decides what the symbolic world should look like and its > meaningfulness? > > > Is this a rhetorical question? > > >> Not really > > In the human sphere, the poets, painters, dancers and mathematicians > decide what the symbolic world should look like, and work very hard to > capture its meaning in poetry, paintings, movements and equations. I expect > AGI to struggle with the same issues. > > >> Too vague, too generalist. I think symbolism emerges from diversity, or > more accurately, programs of diversification. > > But if you mean "who decides whether symbol #4589342472934 should even > exist, or what it means?" ... heck I dunno. Some algorithm, the same > algorithm that decided that symbol #11316372398 is meaningful. > > >> The designer decides the system of symbolism. The agi entity has the > existential prerogative to symbolize. > > In between the symbols generated by algorithms and the symbols generated > by poets are the symbols generated by insurance companies, zoning > commissions, safety regulators and lawyers. These symbols have names like > "penal code #234241;para.4.b-addendum 62" and are almost as boring to read > as reading software. > > Do I expect the middle layers of AGI to look like something an insurance > company or zoning commission might write? Sure, why not? I expect a > Chinese Room hard at work, in the middle layers of the AGI. > > >> Linear and alinear systems contribute to holistic systems. I think it > was Checkland who made the point most clear. The discussion flux between > linear and alinear systems, and considers something in between. Why nto > simply extract the fractal value of an instance of linear and alinear > contexts and symbolize that in an agi, as a knowledge node, and so on. That > was my point on fractals, the search for a pattern of meta superpositions > (the paradoxes), which may well hold a key to finite-infinity within > systems. Gell-Mann provided theoretical essence in his discussions on > scalability (in the sense of boundary-independent form - my words) and his > notion of intermediate. > > Having said all this makes me realize that there is a lot more accepted > theory than we could imagine. What is required then are the appropriate > frameworks to put those theories to work in context of an agi service. > > > The global state of social evolution may cause terrible confusion in any > learning entity. The learning objectives should be specific, not > generalized. Isn't learning incorrectly worse than not learning at all? > > > That is certainly a hotly debated question in Brexit and Trump > discussions. More accurately, the problem is one of not having an accurate > understanding of the world, and being unable to get one. > > >> the clamor for truth vs big data? > > its not so much a case of "learning badly", but one of hallucinating: > hallucinating that things will be better, or worse, if England leaves the > EU, etc. The combined sensory-system+political-brains seem to be incapable > of figuring this out. > > >> general relativity - self interest drives what we see, and learn. > > I expect AGI to hallucinate, too. Just not like us. Actually, I expect > AGI to be schizophrenic, psychopathic, and a zilllion other rather negative > things that are existentially dangerous to humans. That's the tricky part, > the part that is unpleasant to face. > > >> I think agi, as a concept, already is. > > > I think, there should be a general agi-architecture, replete with the > capacity to develop and function within a generic world view. Furthermore, > I think the real value would be derived from specialized AGI. Maybe beyond > that, an AGI architecture would - in future - morph via its own social > networking and inherent capabilities to become more than the sum of its > parts. > > > Well, you used lower-case-agi and Upper-Case-AGI there. There's no such > thing as an Upper-Case-AGI architecture -- claiming to have one is like > claiming to have the blueprints for a rocket-ship to another galaxy. > > >> An interesting observation. I have no idea why the case-sensitivity. > Perhaps it does not really matter at all. How did you come so far on your > journey to another galaxy without a blueprint? Surely, it must all be just > luck? No, it's the result of years of driving passion and vision. The > blueprint must exist in your collective minds. > > However, lower-case-agi-- well, that is more like mountain climbing: you > try to go one way, until you find that you can't so you try another way, > until you can. You explore, looking for routes to get from here to there. > So, if Upper-Case-AGI is a mountain peak, then we are at the foothills of > the Himilayas, fumbling and tripping and getting exhausted. Explorer X > says that the deep-learning route is promising; explorer Y disagrees. > Everybody's got a base-camp, and some are busier and livelier than others. > > > To do so, would take a lot more than intersections. I agree with the > statements made about binary/vector theory, but it seems obvious to me that > this would not be sufficient for this task. You implied fractals. > > > Heh. Careful with the analogies, there. Fractals are manifestations of > shift-spaces. Which are infinite-dimensional vector spaces. The last three > decades have exposed a deep and abstract mathematical theory for > "fractals". That theory is ... interesting, but has rather very little to > do with AGI. Like pretty much nothing at all > > >> every fractal has a distinct boundary. it might be a symbolic black > hole to some, but I would argue how it's not an "infinite-dimensional > vector space". A pure object is a fractal too, as is a context. Not in a > physical sense, but in an informational sense, where Physics behave in the > role of the carrier and information in the role of the content being > carried. I contend how fractals has very much everything to do with AGI. > > We, as researchers, may not all be using the same terminology, but the > concepts you are discussing in your latest response to Rob are not foreign > to my mind. Perhaps, there are different routes via which to discover AGI, > and as evidenced within Ben Goertzel's treatise on world religions, there > exist different paths for different people towards achieving AGI > enlightenment. > > What if we had at our disposal a common language to start putting these > paths together within a single AGI frame? Imagine, consensus. > > PS: I'd think the answer to your compound relational question is: 27. Even > so, if a rule was being enforced where a singular, existential method of > association between X and Y entities were being deployed. Hierarchy itself > is linear. It can flow over an alinear system. > > > -- linas. > > > To my mind, that would be the only way to proceed. As such, I think the > primary issue remains a design issue. > > Robert Benjamin > > ------------------------------ > *From:* Linas Vepstas <[email protected]> > *Sent:* Monday, 18 February 2019 10:36 PM > *To:* AGI > *Subject:* Re: [agi] Some thoughts about Symbols and Symbol Nets > > > > On Mon, Feb 18, 2019 at 1:17 PM Mike Archbold <[email protected]> wrote: > > I'm not sure I completely follow your point, but I sort of get it. > > I tend to think of symbols as one type of the "AI stuff" a computer > uses to think with -- the other main type of "AI stuff" being neural > networks. These have analogies to the "mind stuff" we use to think > with. > > > Symbol systems and neural-net systems can be seen to be variants of the > same thing; two sides of the same coin. I posted an earlier thread on this. > There's a 50-page long PDF with math, here: > https://github.com/opencog/opencog/raw/master/opencog/nlp/learn/learn-lang-diary/skippy.pdf > > roughly: both form networks. They differ primarily in how they represent > the networks, and how they assign weights to network connections (and how > they update weights on network connections). > > > On their own, symbols don't mean anything, of course, and inherently > don't contain "understanding" in any definition of understanding. > > Is there a broad theory of symbols? We kind of proceed with loose > definitions. I remember reading the Newell and Simon works, and they > say AI strictly in terms of symbols and LISP (as I recall anyway). > > > Yes. The "broad theory of symbols" is called "model theory" by > mathematicians. It's highly technical and arcane. It's most prominent > distinguishing feature as that everything is binary: it is or it ain't. > Something is true, or false. A formula takes values, or there is no such > formula. A relation binds two things together, or there is no relation. > There's no blurry middle-ground. > > So, conventionally, networks of symbols, and the relations between them, > and the formulas transforming them -- these form a network, a graph, and > everything on that network/graph is a zero or a one -- an edge exists > between two nodes, or it doesn't. > > The obvious generalization is to make these fractional, to assign weights. > Neural nets do this. But neural nets do something else, that they probably > should not: they jam everything into vectors (or tensors) This is kind-of > OK, because the algebra of a graph is a lot like the algebra of a vector > space, and the confusion between the two is an excusable mistake: it takes > some sophistication to realize that they are only similar, but not the same. > > I claim: fix both these things, and you've got a winner. Use symbolic > systems, but use fractional values, not 0/1 relations. Find a good way of > updating the weights. So, deep-learning is a very effective weight-update > algorithm. But there are other ways of updating weights too (that are > probably just as good or better. Next, clarify the > vector-space-vs-graph-algebra issue, and then you can clearly articulate > how to update weights on symbolic systems, as well. > > (Quickly explained: probabilities are not rotationally-symmetric under the > rotation group SO(N) whereas most neural-net vectors are: this is the spot > where deep-learning "gets it wrong": it incorrectly mixes gibbs training > functions with rotational symmetry.) > > So Jim is right: discarding symbolic systems in favor of neural nets is a > mistake; the path forward is at the intersection of the two: a net of > symbols, a net with weights, a net with gradient-descent properties, a net > with probabilities and probability update formulas. > > -- Linas > > > On 2/18/19, Jim Bromer <[email protected]> wrote: > > Since I realized that the discrete vs weighted arguments are passe I > > decided that thinking about symbol nets might be a better direction for > me, > > > > 1. A symbol may be an abstracted 'image' of a (relatively) lower level > > object or system. > > An image may consist of a feature of the referent, it may be an icon of > > the referent or it may be a compressed form of the referent. > > 2. A symbol may be more like a 'label' for some object or system. > > 3. A generalization may be represented as an image of what is being > > generalized but it also may be more of a label. > > 4. An 'image', as I am using the term, may be derived from a part or > > feature of an object or from a part of a system but it may be used to > refer > > to the object or system. > > 5. An image or label may be used to represent a greater system. A system > > may take on different appearances from different vantage points, and > > analogously, some features of interest may be relevant in one context but > > not from another context. A symbol may be correlated with some other > > 'object' and may stand as a referent to it in some contexts. > > > > So, while some symbols may be applied to or projected onto a 'lower' > corpus > > of data, others would need to use an image to project onto the data > field. > > I use the term, 'lower' somewhat ambiguously, because I think it is > useful > > to symbolize a system of symbols so a 'higher' abstraction of a system > > might also be used at the same level. And it seems that a label would > have > > to be associated with some images if it was to be projected against the > > data. > > > > One other thing. This idea of projecting a symbol image onto some data, > in > > order to compare the image with some features of the data, seems like it > > has fallen out of favor with the advancements of dlnns and other kinds of > > neural nets. Projection seems like such a fundamental process that I > cannot > > see why it should be discarded just because it would be relatively slow > > when used with symbol nets. And, there are exceptions, GPUs, for example, > > love projecting one image onto another. > > Jim Bromer > > > -- > cassette tapes - analog TV - film cameras - you > > -- > cassette tapes - analog TV - film cameras - you > *Artificial General Intelligence List <https://agi.topicbox.com/latest>* > / AGI / see discussions <https://agi.topicbox.com/groups/agi> + > participants <https://agi.topicbox.com/groups/agi/members> + delivery > options <https://agi.topicbox.com/groups/agi/subscription> Permalink > <https://agi.topicbox.com/groups/agi/Tcc0e554e7141c02f-M6f5b4a8d2ee3f5bdf718c233> -- Stefan Reich BotCompany.de // Java-based operating systems ------------------------------------------ Artificial General Intelligence List: AGI Permalink: https://agi.topicbox.com/groups/agi/Tcc0e554e7141c02f-M745d9f703d0045eaf2b8333c Delivery options: https://agi.topicbox.com/groups/agi/subscription
