[HN Gopher] The Society of Mind (1986) [pdf] ___________________________________________________________________ The Society of Mind (1986) [pdf] Author : eigenvalue Score : 111 points Date : 2022-12-22 23:01 UTC (23 hours ago) (HTM) web link (www.acad.bg) (TXT) w3m dump (www.acad.bg) | lisper wrote: | I was a grad student in AI at the time this book came out so I | can tell you a little bit about the historical context from my | personal perspective with benefit of hindsight. The field at the | time was dominated by two schools of thought, called the "neats" | and the "scruffies". At the risk of significant | oversimplification, the neats thought that the right way to do AI | was using formal logic while the scruffies took an empirical | approach: noodle around with code and see what works. Both | approaches led to interesting results. The neat legacy is modern- | day theorem provers while the scruffy legacy is chatbots, self- | driving cars, and neural nets. | | SoM didn't fit neatly (no pun intended) into either camp. It | wasn't empirical and it wasn't formal. It was just a collection | of random loosely-associated ideas and nothing ever came of it. | It was too informal to lead to interesting theoretical results, | and it was too vague to be implemented and so no one could test | it experimentally. And both of those things are still true today. | I think it's fair to say that if the author had been anyone but | Minsky no one would have paid any attention to it at all. | at_a_remove wrote: | This made its way into pop culture via the X-Files, in an | episode about A.I.: "Scruffy minds like me like puzzles. We | enjoy walking down unpredictable avenues of thought, turning | new corners but as a general rule, scruffy minds don't commit | murder." | eternalban wrote: | > It was just a collection of random loosely-associated ideas | and nothing ever came of it. | | I remember buying this in '89 and being completely underwhelmed | by it. There is nothing there imo. I stopped paying attention | to the name Minsky after this introduction to the 'great man'. | DonHopkins wrote: | https://web.media.mit.edu/~minsky/papers/SymbolicVs.Connecti... | Logical vs. Analogical or Symbolic | vs. Connectionist or Neat vs. | Scruffy Marvin Minsky | | INTRODUCTION BY PATRICK WINSTON | | Engineering and scientific education conditions us to expect | everything, including intelligence, to have a simple, compact | explanation. Accordingly, when people new to AI ask "What's AI | all about," they seem to expect an answer that defines AI in | terms of a few basic mathematical laws. | | Today, some researchers who seek a simple, compact explanation | hope that systems modeled on neural nets or some other | connectionist idea will quickly overtake more traditional | systems based on symbol manipulation. Others believe that | symbol manipulation, with a history that goes back millennia, | remains the only viable approach. | | Minsky subscribes to neither of these extremist views. Instead, | he argues that Artificial Intelligence must employ many | approaches. Artificial Intelligence is not like circuit theory | and electromagnetism. AI has nothing so wonderfully unifying | like Kirchhoff's laws are to circuit theory or Maxwell's | equations are to electromagnetism. Instead of looking for a | "Right Way," Minsky believes that the time has come to build | systems out of diverse components, some connectionist and some | symbolic, each with its own diverse justification. | | Minsky, whose seminal contributions in Artificial Intelligence | are established worldwide, is one of the 1990 recipients of the | prestigious Japan Prize---a prize recognizing original and | outstanding achievements in science and technology. | | https://en.wikipedia.org/wiki/Neats_and_scruffies | | Neat and scruffy are two contrasting approaches to artificial | intelligence (AI) research. The distinction was made in the 70s | and was a subject of discussion until the middle 80s. In the | 1990s and 21st century AI research adopted "neat" approaches | almost exclusively and these have proven to be the most | successful.[1][2] | | "Neats" use algorithms based on formal paradigms such as logic, | mathematical optimization or neural networks. Neat researchers | and analysts have expressed the hope that a single formal | paradigm can be extended and improved to achieve general | intelligence and superintelligence. | | "Scruffies" use any number of different algorithms and methods | to achieve intelligent behavior. Scruffy programs may require | large amounts of hand coding or knowledge engineering. | Scruffies have argued that the general intelligence can only be | implemented by solving a large number of essentially unrelated | problems, and that there is no magic bullet that will allow | programs to develop general intelligence autonomously. | | The neat approach is similar to physics, in that it uses simple | mathematical models as its foundation. The scruffy approach is | more like biology, where much of the work involves studying and | categorizing diverse phenomena.[a] | | https://www.amazon.com/Made-Up-Minds-Constructivist-Artifici... | | Made-Up Minds: A Constructivist Approach to Artificial | Intelligence (Artificial Intelligence Series) Paperback - | January 1, 2003 | | Made-Up Minds addresses fundamental questions of learning and | concept invention by means of an innovative computer program | that is based on the cognitive-developmental theory of | psychologist Jean Piaget. Drescher uses Piaget's theory as a | source of inspiration for the design of an artificial cognitive | system called the schema mechanism, and then uses the system to | elaborate and test Piaget's theory. The approach is original | enough that readers need not have extensive knowledge of | artificial intelligence, and a chapter summarizing Piaget | assists readers who lack a background in developmental | psychology. The schema mechanism learns from its experiences, | expressing discoveries in its existing representational | vocabulary, and extending that vocabulary with new concepts. A | novel empirical learning technique, marginal attribution, can | find results of an action that are obscure because each occurs | rarely in general, although reliably under certain conditions. | Drescher shows that several early milestones in the Piagetian | infant's invention of the concept of persistent object can be | replicated by the schema mechanism. | | https://dl.acm.org/doi/10.1145/130700.1063243 | | Book review: Made-Up Minds: A Constructivist Approach to | Artificial Intelligence By Gary Drescher (MIT Press, 1991) | varjag wrote: | Well it did spur the research into multi-agent systems (popular | study area in 1990s) and interaction protocols. So there was a | degree of influence. | | But taken on its own it is indeed more a book of musings. I put | GEB, ANKOS and the like into the same genre. | lisper wrote: | I'm with you on ANKOS, but GEB is an accessible and fun (if a | bit wordy) introduction to formal systems and Godel's | theorem, so I wouldn't put it in the same category. GEB also | was not marketed as anything revolutionary (except in its | pedagogy). ANKOS and SoM were. | neilv wrote: | Another thing to be aware of with SoM is that Minsky was | reading in many fields, and trying to sketch out theories | informed by that. | | One time, before the DL explosion, during a lull in AI, I sent | a colleague a Minsky pop-sci quote from the earlier AI years, | before our time, asserting that, soon, a self-teaching machine | will be able to increase in power exponentially. I was making a | joke about how that was more than a little over-optimistic. My | colleague responded something like, "What you fail to see is | that modern-day Marvin _is_ that machine. " | | By the time I was bumping into AI at Brown and MIT, the | students (including Minsky's protege, Push Singh, who started | tackling commonsense reasoning) described SoM various ways, | including: | | * Minsky sketching out spaces for investigation, where each | page was at least one PhD thesis someone could tackle. I see | some comments here about the book seeming light and hand-wavy, | but I suppose it's possible there's more thinking behind what | is there than is obvious, and that it wasn't intended to be the | definitive answer, but progress on a framework, and very | accessible. | | * Suggestion (maybe half-serious) that the different theories | of human mind or AI/robotics reflect how the particular | brilliant person behind the theory thinks. I recall the person | said it as "I can totally believe that Marvin is a society of | mind, ___ thinks by ___ ..." | | I don't know anyone who held it out as a bible, but at the time | it seemed probably everyone in AI would do well to be aware of | the history of thinking, and the current thinking of people who | founded the field and who have spent many decades at the center | of the action of a lot of people's work. | echelon wrote: | This corroborates my experience. | | Reading _Society of Mind_ in undergrad is one of the things | that led me to doubt AI progress and to stray away from the | field [1]. It was handwavy, conceptual, and far removed from | the research and progess at the time. If you held it up to | Norvig 's undergraduate level _Artificial Intelligence: A | Modern Approach_ , you could sense Minsky's book was as | wishfully hypothetical as Kaku's pop-sci books on string | theory. | | [1] Recent progress has led me right back. There's no more | exciting place to be right now than AI. | briga wrote: | Even if it didn't lead to empirical results I think most of | the value of the book today is in the questions Minsky asked. | How is intelligence organized in a distributed system like a | neural net? ChatGPT may be able to do amazing things, but the | mechanisms it uses are still very opaque. So even if the | theory may not be "useful", it is still worth pursuing IMO | | It's also pretty well written and written by someone who | clearly spent a lot of mental energy on the problem | detourdog wrote: | Inspired me as an undergrad Industrial Design student in | 1989ish that and The Media Lab: Inventing the Future at M.I.T | by Stewart Brand were the two most influential technology books | for me at that time. | | Coincidentally enough it turns out my cousin was in the thick | of it while the pre-media lab was still part of the | architecture school. She would tell me stories of what she was | up to in college... when I read that back I had to loop back | and ask her about it. | codetrotter wrote: | > Marvin Minsky's "Society of Mind" is a theoretical framework | for understanding the nature of intelligence and how it arises | from the interaction of simpler processes. The concept suggests | that the mind is not a single entity, but rather a society of | many different agents or processes that work together to produce | intelligent behavior. | | > The concept of a "Society of Mind" is still relevant today and | has influenced a number of fields, including artificial | intelligence, cognitive psychology, and philosophy. It has also | influenced the development of artificial intelligence systems | that are designed to mimic the way the human mind works, using | techniques such as artificial neural networks and machine | learning. | | > Overall, the concept of a "Society of Mind" continues to be an | important and influential idea in the study of intelligence and | the nature of the mind. | | Or so at least, says ChatGPT when I asked it about this just now. | Simplicitas wrote: | How long before "ChatGPT" is just "Chat", as in "I just asked | Chat and it said ..."? | jaredsohn wrote: | Won't they just give it a name? i.e Siri, Alexa, Jeeves | | Just noticed that GPT sounds a little like Jeeves. | lhuser123 wrote: | I hope never. But we really like to make things harder by | giving the same name to many things. | naillo wrote: | Minsky's "Society of Mind" is still relevant today, IMO. It's a | provocative idea that explains the complexity of the human mind | as a society of simpler processes working together. In AI, it's | inspired researchers to try and build systems with lots of | interconnected, simple processes that work together like the | human mind. And in cognitive psychology, it's a key concept | that's helped researchers understand the mind as a complex | network of simpler processes. | timkam wrote: | There is still plenty of research going on on agents, symbolic | AI, and other approaches that sometimes and somewhat reflect (or | have informed) ideas from Society of Mind. Some of the ideas are | relevant from an application perspective (for sure, we have | complex socio-technical systems where different 'agents' | interact), others make it into learning, for example into RL, | which was hyped some years go. Other ideas feel old-fashioned and | stuck in the past; this is, in my opinion, not necessarily | because the ideas are generally bad, but often because some of | the sub-communities move very slowly and struggle to embrace a | pragmatic approach to modern applied research. | | Generally, I think it's good to maintain 'old' knowledge, and the | only way to do so in a sustainable manner is to maintain a | diversity of research directions, where plenty of researchers are | committed to keep the lights on by slowly advancing directions | that are not on top of the hype cycle at the moment. | sdwr wrote: | This post is fucking catnip for me. I still believe society of | mind is due for a huge resurgence, due to exactly what you're | saying. Bottom-up composable skills will be a huge step forward, | and free up GPT etc to be creative while getting the low-level | stuff 100% correct (instead of screwing up arithmetic half the | time) | | The inverse side of the coin is emotions, meaningful | relationships, and wisdom, which I think work in similar way but | more diffuse. There can be a horny submodule that analyzes | incoming content for sexual context, one for anger, fear, | gratitude, etc. The same way an image processor convolves over | pixels looking for edges and features, an emotional processor | will operate over data looking for changes in relationships. | | Feelings act like filters on incoming data, and are composed out | of base physiological reactions. Like anger involves adrenaline, | which increases pain tolerance and dampens conscious thought in | favor of subconscious and instant reactions. | FredPret wrote: | This makes so much intuitive sense to me. I love society of | mind, I wonder if it bears a relationship to how the human mind | works | tern wrote: | Absolutely, see Internal Family Systems. With a little | practice, you can empirically determine that this is how your | mind and emotions work. | | https://ifs-institute.com/ | bryan0 wrote: | Im not an expert in this field, but I think things have actually | gone in the other direction. Look at IBM's Watson (which won on | jeopardy), and it was a system which consisted of diverse agents | which would all evaluate the question in their own way and report | back a result and a confidence score. | | Now look at GPT, it is transformers all the way down and it is | doing much more diverse things than Watson could ever do. | | So I think the key is not in the diversity of agents, but in the | diversity of data representations. GPT is limited by the text | representing language, but what if you could train on data even | more fundamental and expressive | tern wrote: | In a clinical setting, the idea is alive and well in the form of | Internal Family Systems and other "parts work." | | I wouldn't be surprised if microservices come from the same root | of inspiration as well, via object oriented programming (message | passing), etc. | | The very idea of intelligence arising from communicating parts I | think originated from that time-period and has influenced many | fields, though there could be earlier references. | FredPret wrote: | The society of agents idea helped me understand politics more. | | Of course he applies the idea to a single mind where each agent | is a neuron / set of neurons, and in politics each agent is a | mind. | NelsonMinar wrote: | I haven't heard anyone talk about this book in a long time. I | read it while a grad student at the MIT Media Lab in the 90s | (albeit not his course). I struggled to understand its relevance | even then. I think for many people that book was an introduction | to ideas about multi-agent and distributed systems. I'd already | had that and didn't feel the book added much to the discussion | other than introducing the idea. | | Academia has fashions. I feel like agent based systems will have | their day again, perhaps with each agent backed by a deep | learning system. It'll be easier to reason about than "convolve | all these deep learning systems in a giant impenentrable | network". That may be good or it may be bad. | | Minsky is of course infamous for having killed neural networks | for a whole generation of researchers. He lived long enough to | see their resurgence, I wonder if he commented on that? | mtraven wrote: | Logical Versus Analogical or Symbolic Versus Connectionist or | Neat Versus Scruffy: | https://ojs.aaai.org//index.php/aimagazine/article/view/894 | (from 1991, and a response to the revival of connectionism that | happened in the late 80s). | | I often wonder what Minsky would think about the current | generation of AI. My guess is that he'd be critical, because | while their accomplishments are pretty impressive on the | surface, they do very little to explain the mechanics of how | humans perform complex problem solving, or really any kind of | psychological model at all, and that is what he was really | interested in. This has been a methodological problem with | neural net approaches for many generations now. | | Minsky was as much a psychologist as a mathematician/engineer - | Society of Mind owed a lot to Freud. That style of thinking | seems to have dropped by the wayside, maybe for good reasons, | but it's also kind of a shame. I'm not sure what insights you | get into the human mind from building LLMs, powerful though | they may be. | | For more of Minsky's thoughts on human intelligence, here's a | recent book that collected some of his writings on education: | https://direct.mit.edu/books/book/4519/Inventive-MindsMarvin... | (disclaimer: I wrote the introduction). | jerb wrote: | > I often wonder what Minsky would think about the current | generation of AI. | | I suspect he'd react similiarly to Chomsky who in, a recent | interview (MLST), was highly critical of LLMs as "not even a | theory" (of what, i'm not sure... language aquisition? | language production? maybe both) | | Minksy was more broadly critical of NNs because it wasn't | clear how difficult the problems they solved actually were. | Until we had a better measure of that, saying "I got a NN to | do X" is kind of meaningless. He elaborates in this excellent | interview from 1990, beginning at 45:00: | https://youtu.be/DrmnH0xkzQ8?t=2700 | ghaff wrote: | >My guess is that he'd be critical, because while their | accomplishments are pretty impressive on the surface, they do | very little to explain the mechanics of how humans perform | complex problem solving, or really any kind of psychological | model at all, and that is what he was really interested in. | | The success of machine learning/neural nets--in no small part | because of the amount of computation resources we can throw | at them--has really led to hogging the attention compared to | fields like cognitive science, neurophysiology, and so forth. | Work is certainly going on in other areas but I'm still | struck that some of the questions that were being asked when | I took brain science as an undergrad many decades ago (e.g. | how do we recognize a face as a face?) are still being asked | today. | | Given that ML is the thing that's getting the flashy results, | it's not surprising it's the thing in a limelight--even if | there's a suspicion that it maybe (probably?) only gets you | so far without better understanding how learning happens in | people (and other animals) and other aspects of thinking and | intelligence. | EliasY wrote: | I believe "the society of mind" contains a bunch of really good | but unorganized ideas for building intelligent models, but was | written in such a way that it remained virtually impossible to | implement them into a working program. Minsky's last book called | "The Emotion Machine" tries to reorganize these ideas into one | giant architecture composed of at least five interconnected | macrolevels of cognitive processes built from specialized agents. | Having said that, "The Society of Mind" is one of the most | difficult books I've read. | empiko wrote: | You can argue that there might be some similarities or analogies | to be made. But that's it. The book is actually very irrelevant | and it had literally no impact on how these new systems were | created and conceptualized. | btown wrote: | In a way, any GAN | (https://en.wikipedia.org/wiki/Generative_adversarial_network) | has aspects of a Society of Mind: two different networks | communicating with each other, with the discriminator attempting | to find flaws with the generator's ongoing output. | | And | https://scholar.google.com/scholar?hl=en&as_sdt=0%2C31&as_vi... | shows many attempts to generalize this to multiple adversarial | agents specializing in different types of critique. | | One of the challenges, I think, is that while some of these | agents could interact with the world, it's just far more rapid | for training if they just use their own (imperfect) models of the | relevant subset of the world to give answers instantaneously. | Bridging this to increasingly dynamic physical environments and | arbitrary tasks is a fascinating topic for research. | scottlocklin wrote: | [dead] | Barrin92 wrote: | I don't think the work has become irrelevant at all. ML models | are fine but they're really just big function approximators. In | the context of Minsky's book they're the sort of processes or | agents which when put together and interacting could maybe | constitute a generally intelligent system. Which is how they | actually tend to be used in the real world already, as parts of | more complex systems that interact or communicate. | bhouston wrote: | I think it is an interesting idea and it is sort of akin to | Freud's ego, superego, subconscious, etc. It is a | conceptualization, an abstraction, probably a little arbitrary, | that does not map well to physical constructs. | | To view it from the perspective of deep learning neural networks, | one would view the society of mind as a proposed super structure | on top of the various deep learning neutral networks. There is | this already, like the reinforcement learning structure for Chat | GPT, or the multi-focus attentional systems used for code | generation. | | As we built out a full AGI that can interact with the whole, it | is likely we will have specialized systems which mimic a society | of mind, but given that Minsky's ideas are pretty rough and sort | of vague, I am not sure his writings provide the best guidance, | but probably can inspire a bit of work. | edgyquant wrote: | Think of humans as artificial neurons. Language is how we back | propagate etc | 1letterunixname wrote: | The technological singularity is close for purely automate-able | processes. | | General AI, either in the form mimicking humans or a "being" | similar is a ways off, amorphous, and far off for what people | might see portrayed in fiction. | | One also has to ponder the functional definitions of self- | awareness, intelligence(s), and consciousness as not magical but | as emergent properties of the "individual" inferred by others | through behaviors, especially communication. It is | anthropocentric and arrogant to assume other agents are lesser or | incapable simply by lacking a common language or mutual | behavioral understanding. Learning and optimization for improving | one's power and resources (fitness function, gradient vectors, | bank account balance;), etc.), especially through play and speed | of adaptation through feedback would be strong signals of this. | dang wrote: | Related: | | _The Society of Mind (2011)_ - | https://news.ycombinator.com/item?id=30586391 - March 2022 (37 | comments) | | _The Society of Mind_ - | https://news.ycombinator.com/item?id=12050936 - July 2016 (2 | comments) | | _Marvin Minsky 's Society of Mind Lectures_ - | https://news.ycombinator.com/item?id=10971310 - Jan 2016 (6 | comments) | | _The Society of Mind (1988)_ - | https://news.ycombinator.com/item?id=8877144 - Jan 2015 (6 | comments) | | _The Society of Mind Video Lectures_ - | https://news.ycombinator.com/item?id=8668750 - Nov 2014 (10 | comments) | | _Marvin Minsky 's "The Society of Mind" now CC licensed_ - | https://news.ycombinator.com/item?id=6846505 - Dec 2013 (2 | comments) | | _MIT OCW:The Society of Mind (Graduate Course by Minsky)_ - | https://news.ycombinator.com/item?id=856714 - Oct 2009 (2 | comments) | abudabi123 wrote: | You can follow a lecture series at MIT presented by Marvin Minsky | on Ai. I think it was recorded before Nvidia fitted GPUs in a | shoe box and changed the game and the price. | cs702 wrote: | Funnily enough, I'm currently trying to make my way through a | preprint showing that models of dense associate memory with | bipartite structure, _including Transformers_ (!!!), are a | special case of a more general routing algorithm that implements | a "block of agents" in a differentiable model of Minsky's | Society of Mind: https://arxiv.org/abs/2211.11754. Maybe | "symbolic" and "connectionist" AI are two sides of the same coin? | | EDIT: I feel compelled to mention that the efficient | implementation of that more general routing algorithm can handle | input sequences with more than 1M token embeddings in a single | GPU, which quite frankly seems like it should be impossible but | somehow it works: | https://github.com/glassroom/heinsen_routing#routing-very-lo.... | p1esk wrote: | How does his routing algorithm compare to attention? I saw this | question in the repo faq, but no satisfactory answer is given. | cs702 wrote: | I _think_ the next-to-last faq ( "Is it true that | EfficientVectorRouting implements a model of associative | memory?") answers that. Did you see it? | p1esk wrote: | Oh I see, thanks! Interesting. It sounds like this is some | kind of _dynamic_ attention, as opposed to static attention | in transformers, where queries and key don't change during | the calculation of their similarity. His routing algorithm | computes the similarity iteratively. | | Is this your assessment as well? | cs702 wrote: | I'm still trying to make my way through the preprint :-) | | EDIT: According to https://ml-jku.github.io/hopfield- | layers/#update , attention is the update rule for an | (iterative) "dense associate memory," even though in | practice it seems that one update works really, _really_ | well for attention if you train it with SGD. | [deleted] | dpflan wrote: | Thank you. If you gain any insights while reading, please | share! | eigenvalue wrote: | Wow, this sounds exactly like what I was talking about. Thanks | for the reference. | eigenvalue wrote: | Minsky wrote this book in 1986, towards the end of his very long | career thinking about how to build intelligent machines. For a | basic overview, see: | | https://en.wikipedia.org/wiki/Society_of_Mind | | You can find a complete pdf of the book here: | | http://www.acad.bg/ebook/ml/Society%20of%20Mind.pdf | | My question to the HN community is, has all this work become | irrelevant given recent progress in machine learning, | particularly with Transformer based models such as GPT-3 or | "mixed modality" models such as Gato? | | It seems to me that some of these ideas could make a comeback in | the context of a group of interacting models/agents that can pass | each other messages. You could have a kind of "top level" master | model that responds to a request from a human (e.g., "I just | spilled soda on my desk, please help me") and then figures out a | reasonable course of action. Then the master model issues | requests to various "specialist models" that are trained on | particular kinds of tasks, such as an image based model for | exploring an area to look for a sponge, or a feedback control | model that is trained to grasp the sponge, etc. Or in a more | relevant scenario to how this tech is being widely used today, a | GitHub Copilot type agent might have an embedded REPL and then | could recruit an "expert debugging" agent which is particularly | good at figuring out what caused an error and how to modify the | code to avoid the error and fix the bug. | | I suppose the alternative is that we skip this altogether and | just train a single enormous Transformer model that does all of | this stuff internally, so that it's all hidden from the user, and | everything is learned at the same time during end-to-end | training. | endlessvoid94 wrote: | I just might have to dust off the copy on my shelf and give it a | re-read. | [deleted] | mindcrime wrote: | I've read this book a couple of times, with my most recent re- | read being within the last year or two. So I guess that means | that I, for one at least, find something of value in SofM even | now. | | So the question then might be "what do you find valuable in it?" | | That would take a lot of words to answer fully, but let me start | by saying that I agree with a lot of the other comments in on | this post. The theory, inasmuch as you can call it that, isn't | super concrete, isn't necessarily something you can implement | directly as such, does mostly lack any kind of experimental | evidence, and is kind of hand wavy. Sooooo... what value does it | have? | | Well for me it's mostly something I look at as inspirational from | a very high-level, abstract point of view. It strikes me as more | of a framework that could support very many theories, rather than | a specific realizable theory. But I believe that there's | something fundamentally correct (or at least _useful_ ) about the | idea of a collections of semi-autonomous agents collaborating in | a style akin to SofM. And on top of that, I think there are at | least a handful of specific notions contained in the book that | might be realizable and might prove useful. If you want a | specific example, I'd say that I think something like K-lines may | prove useful. | | Of course I have no experimental evidence, or much of anything | else beyond intuition, to support my beliefs in this. And I'm | just one random guy who's pretty much a nobody in the AI field. I | just sit quietly at my computer and work, not really trying to | attract a lot of attention. And in the process of doing so, I do | occasionally consult _Society of Mind_. YMMV. | | And just to be clear in case anybody wants to misinterpret what | I'm saying. It's not my "bible", and I'm not a Minsky acolyte, | and I don't consider SofM to be the "be all end all" any more | than I consider _A New Kind of Science_ , _Godel Escher, Bach_ , | _Hands on Machine Learning with Scikit-Learn, Keras & | Tensorflow_, _Computational Approaches to Analogical Reasoning: | Current Trends_ , or _Parallel Distributed Processing, Vol. 1: | Foundations_ to be the "be all, end all". I'm all about applying | Bruce Lee's mantra: | | _" Use only that which works, and take it from any place you can | find it."_ | squokko wrote: | Society of Mind is just a bunch of unfalsifiable speculations... | more New Age mysticism than science or engineering. Not sure how | it would have any impact | dev_0 wrote: | [dead] | LesZedCB wrote: | it reminds me a little bit of the thousand brains theory from | Numenta. we'll see what they turn out in the future. i think | philosophically they're a closer match to minsky. | dr_dshiv wrote: | One of the first AI proposals was from Oliver Selfridge. He | called it Pandemonium because it was a set of demons (into | processes) and the loudest demon was successful. | | In response, Paul Smolensky made the "Harmonium"--which was the | first restricted Boltzmann machine. There whichever process | produces the most harmony among the elements was successful. It's | still a really great paper. | | Harmony maximization was the same as free energy minimization. | When Smolensky and Hinton collaborated (they were both Postdocs | under David Rummelhart and Don Norman at UCSD), they called it | "goodness of fit." Still used today! | eigenvalue wrote: | Interesting! I started reading through this pdf after reading | your comment here and it has a lot of cool ideas: | | https://stanford.edu/~jlmcc/papers/PDP/Volume%201/Chap6_PDP8... | neilv wrote: | Also look at his later book, "The Emotion Machine". | | When I took Minsky's "Society of Mind" class, he was working on | the later book, and many lectures were him talking about what he | had been working on earlier that day. | XMPPwocky wrote: | https://socraticmodels.github.io/ seems somewhat related, using a | LLM as the top-level model. | schizo89 wrote: | Minsky is hand waiver to say the least. | lolc wrote: | I've been wondering about this too. The book gave me a way to | think about consciousness, but I do wonder whether we'll ever see | machines that use concepts at the described level. Because humans | don't seem to be built that way, and the models we've built so | far don't either. | mooneater wrote: | Sounds similar to what Google's SayCan is doing. https://say- | can.github.io/ | | They taught it separate skills. When a situation arises, the | skills (which you could almost consider sub-agents) compete to | decide who is most likely to be relevant here. Then that skill | takes over for a bit. | | They also have a version called "Inner Monologue" in which the | different parts "talk to each other" in the sense of | collaboratively creating a single inner monologue, allowing for | reactiveness/closed loop behaviour. | | I interviewed 2 authors of SayCan/Inner Monologue here: | https://podcasts.apple.com/us/podcast/karol-hausman-and-fei-... ___________________________________________________________________ (page generated 2022-12-23 23:00 UTC)