[HN Gopher] What Does It Mean for AI to Understand?
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What Does It Mean for AI to Understand?
Author : theafh
Score : 83 points
Date : 2021-12-16 14:52 UTC (8 hours ago)
(HTM) web link (www.quantamagazine.org)
(TXT) w3m dump (www.quantamagazine.org)
| machiaweliczny wrote:
| BTW humans are generally stupid. We are only smart in collective
| with all trial/error saved in books, so don't underestimate
| computers. Also most of progress happens by outliers in humanity
| so it can be after AIs start to collaborate. Distributed MoE
| architectures are step in this direction.
|
| My prediction: codex and programming/operating APIs will give NNs
| ultra boost, then programming/math gets automated (hard to
| master, easy to verify) and rest/us will be history. John Conor
| is already alive. Mark my words.
| mcguire wrote:
| " _A Winograd schema, named for the language researcher Terry
| Winograd, consists of a pair of sentences, differing by exactly
| one word, each followed by a question. ... In each sentence pair,
| the one-word difference can change which thing or person a
| pronoun refers to. Answering these questions correctly seems to
| require commonsense understanding._ "
|
| I don't buy it. These Winograd schemas are _significantly_
| limited and are exactly the sort of thing that "story
| understanding" systems from the '70s and '80s were designed for.
| trabant00 wrote:
| It's incredible how stupidly powerful the rational part of the
| human brain is. It has this unlimited capacity to get lost in
| details.
|
| "What does it mean for AI to Understand?" - we keep arguing over
| definitions and moving the goal posts to make it seem we are an
| step closer to reaching AI.
|
| When my first AI coworker will read the on-boarding docs and
| start solving Jira issues I will have no doubt we have done it.
| That simple.
|
| Does anybody believe that an entity that would actually develop
| AI would start selling it? They would keep it for themselves and
| literally take over the world! Complete domination of the digital
| realm is one of easiest things an AI could do - I believe a lot
| easier than driving a car. And that alone would make them God.
|
| When the first true AI will be born we will simply live the
| experience. Imagine being there when we learned to control fire.
| Would you argue over the definition of it? The size, flame color,
| temperature and so on? Something that great can not be denied by
| such small details.
|
| LE: what happened to the Touring test? We forgot about it or does
| ordering things from Amazon when we command smartphone assistants
| to turn down the lights actually fools us?
| PeterisP wrote:
| Regarding Turing test, it turned out that fooling people is
| easier than it might seem, so it's not considered anymore a
| reasonable qualification for general artificial intelligence as
| everybody now presumes that it's possible for a system to exist
| that can beat the Turing test but doesn't even attempt to be
| intelligent in any reasonable/general way.
| bryan0 wrote:
| I don't know why this is a common viewpoint. A proper Turing
| test with trained judges and human subjects who are actually
| trying to convince the judge they are human still seems like
| the best test of intelligence IMO.
| [deleted]
| toisanji wrote:
| a simulation engine in the human mind seems required for
| understanding: https://blog.jtoy.net/on-the-wondrous-human-
| simulation-engin...
| throwawayai12 wrote:
| I always get a little confused when people quote Oren. He hasn't
| been involved in meaningful work in AI in decades despite leading
| a large, well-funded group.
|
| But boy howdy can be give talks that sound good to lay people.
| wombatmobile wrote:
| > What Does It Mean for AI to Understand?
|
| What does it mean for a human to understand?
| nqzero wrote:
| What does it mean for a human to understand ?
| prometheus76 wrote:
| And to extend your question: write something sarcastic on the
| internet and you'll quickly find out there are multiple layers
| of "understanding" something.
| cgearhart wrote:
| Ignoring the associate debacle, the characterization of large
| language models as "stochastic parrots"[1] is the most accurate
| description I think I've ever heard for the capabilities of AI
| language models. These models don't understand that a mistake on
| a Winograd question is not the same as a mistake on a medical
| diagnosis (as a contrived example).
|
| [1] https://dl.acm.org/doi/10.1145/3442188.3445922
| visarga wrote:
| I don't think it's a good name. GPT-3 is more like a dreaming
| hallucination machine. Humans do nonsensical things in their
| dreams, same kind of non sequitur as the language models. What
| GPT-3 lacks is being able to wake up from its disembodied
| hallucinations, in other words a body and something to motivate
| its actions.
| rbanffy wrote:
| What does "understanding" mean?
| therobot24 wrote:
| Situational Awareness is largely separated into 3 levels --
| first level (perception), 2nd level (comprehension),and 3rd
| level (prediction)
|
| Understanding while not completely described by situational
| awareness definitely has some relationship to it and you could
| probably use similar constructs for defining it
| robbedpeter wrote:
| What it means for humans to understand has been posited by Jeff
| Hawkins as a combination of synaptic links within and between
| cortical columns, resulting in a physical neural construct that
| activates when stimulated past a sufficient threshold of
| inbound signals. Constructs can suppress nearby clusters of
| neurons, or contribute an increase in readiness to signal, or
| self modulate the activation threshold of constructs within the
| cortical column.
|
| The findings are consistent with current understanding of
| neuroscience, and align with discoveries such as grid cells.
| They also provide a basis for explaining what's actually
| happening in the brain with phenomena like memory palaces,
| rapid and efficient physical control of the body, combining
| sense modalities such as sight and touch when catching a ball,
| and so on.
|
| Understanding is what happens when your brain has developed a
| neural structure such that it's able to predict events
| successfully based on the thing that was understood.
| jjbinx007 wrote:
| Children learn thousands of words growing up not by having
| the definition read to them from a dictionary but by
| inferring their meaning based on context.
|
| Likewise we learn general concepts and they can be applied to
| a wide range of scenarios. I can't see any other way AI could
| learn unless it mimicks our own.
| motohagiography wrote:
| This is the important question. After reading Ted Chiang's
| story "Understand" about this question, a simple working
| definition could be that to understand something you apprehend
| the domain of the subject from its substrate. Hence Feynman's
| "what I cannot create I do not understand," as well.
|
| In this sense, an AI could be said to _Understand_ language if
| it used it as one of a selection of tools to operate on itself,
| a peer or other being, or its environment.
| AndrewOMartin wrote:
| Very droll, but notice that I can write the phrase "Don't make
| snarky comments" without us having previously agreed on a
| formal definition of "snark".
| selestify wrote:
| Right, so you've demonstrated that the phenomenon exists.
| Now, what defines that phenomenon, exactly?
| gooseus wrote:
| I'd say "understanding" is less one thing and more of a
| collection of capabilities which work together to allow
| understanding to "emerge".
|
| One of those capabilities would be the ability to
| contextual an object/statement within multiple frames of
| reference while also being able to compare and contrast the
| different instances of those contextualized
| objects/statements.
|
| This is what allows a child to identify a bird as any
| number of physical specimens of different species (chicken,
| goose, eagle, sparrow), while also identifying cartoon
| depictions that talk and simple drawings (Twitter icon) as
| birds as well... while also "understanding" that while the
| Twitter icon can be called a bird, it is not actually a
| real bird ("Ceci n'est pas une pipe") and it would not be
| expected to sing or fly like a backyard sparrow (unless it
| was animated, which would make still make sense to a
| child).
|
| I think this also what rise to our ability to "understand"
| jokes, puns, and other turns of phrase - "I just flew in
| from Boston, and boy are my arms tired!" - this dumb joke
| requires a number of concepts that need to be
| contextualized before you can "get" the absurdity of
| stating that a human might tire out their arms while
| flying... like you might think a bird would.
| TheOtherHobbes wrote:
| That's because snark is a pre-installed module in the Western
| Human Online Communication Library Codebase.
|
| The code for "understanding" is part of Generic Human
| Firmware codebase and is tightly integrated with the OS.
|
| Unfortunately it hasn't been open sourced.
| PaulDavisThe1st wrote:
| It's totally open source, just written in a language we
| don't (yet) understand.
| teddyh wrote:
| I.e. a binary blob.
| KhoomeiK wrote:
| People outside the NLP research community need to understand that
| a language model does nothing more than calculate probabilties
| for the next word given some context. The way it learns that
| probabilistic function can be quite complex, involving billions
| of parameters, but it's still fundamentally the same. Most of the
| increase in performance in recent years has come from the ability
| to train LMs that better generalize this probability function
| from huge text corpora--functions that better interleave between
| the datapoints it's trained on.
|
| Humans use language with purpose, to complete tasks and
| communicate with others, but GPT-3 has no more goals or desires
| than an n-gram model from the 90s. LMs are essentially a faculty
| for syntactically well-formed or intuitive/system 1 language
| generation, but they don't seem to be much more.
| machiaweliczny wrote:
| What if to predict next word you need to compress/understand
| universe in the end? AFAIK we have no clue how exactly NNs pick
| up/structure information.
|
| For me backprop and learning is similar to evolution thus
| result might be simialar. My knowledge is very limited though
| but I am happy to read any proofs/insights.
| bryan0 wrote:
| > Unfortunately, Turing underestimated the propensity of humans
| to be fooled by machines. Even simple chatbots, such as Joseph
| Weizenbaum's 1960s ersatz psychotherapist Eliza, have fooled
| people into believing they were conversing with an understanding
| being, even when they knew that their conversation partner was a
| machine.
|
| This is not a Turing test. Or at least not a reasonable one. A
| reasonable Turing consists of a judge and 2 interfaces, one which
| chats with a computer and the other which chats with a human.
| Both the human and computer are trying to convince the judge that
| they are the human. If the judge cannot determine which is which
| after an open-ended conversation then the computer passes.
|
| There is no reasonable judge which after chatting with a human
| (who is actually trying to convince the judge they are human)
| would be unable to differentiate between a human and Eliza or any
| other chatbot out there.
| hpoe wrote:
| When it gets to questions like these I feel that we transcend
| discussions of technology and end up on questions of philosiphy
| which aren't going to be going anywhere anytime quick.
|
| I also feel that AI should be used to augment not replace human
| decision making, it seems that where AI shines is problems that
| are well defined with well defined solutions, and because the AI
| doesn't get tired, hungry or distracted it can do that really
| well, but it fails in novel situations[0]. As such it seems to me
| our best bet is to have the AI provide suggestions rather than
| have complete control.
|
| 0. What is meant by that is a read an article, can't find it now,
| about using AI to diagnose breast cancer, what they found is that
| about 90% of the time the AI could accurately check for breast
| cancer, but the other 10% of the time was an unusual mammogram or
| something relatively rare, and in those situations the AI would
| often misdiagnoise.
| chermi wrote:
| AI had meaning that originated from CS theorists before being
| usurped and losing all meaning. I think tech and associated
| marketing (which are great, don't get me wrong, I love money!)
| are the ones at fault here. It should be more of a
| "philosophical" question, though I'd prefer instead perhaps it
| be academic.
|
| I'm not trying to be rude, but your example of what AI should
| be is narrow and not very grandiose compared the original
| meaning. I understand you were talking pretty loosely, so I
| feel like I'm singling you out but this happened to be where I
| started typing, sorry!
|
| It just reminded of how essentially all conversations about
| "AI" go. They seem to end up being quite specific, narrow
| pattern recognition problems at the end of the day. Maybe
| there's some decision theory on top of it. Maybe if there's
| enough money /people involved, there's more components, so it's
| a complicated enough supervised learning problem that it mimics
| people to a sufficient extent that it looks intelligent enough
| to make a headline. But it's a copycat, not intelligent. Hey,
| full circle, Melanie Mitchell! -
| https://en.m.wikipedia.org/wiki/Copycat_(software)
| [deleted]
| jll29 wrote:
| As an AI professor, I've always held that machines are NOT
| intelligent (I am prepared to change my position on the day my
| computer asks me anything surprising that I didn't program it
| to).
|
| But this does not mean we cannot produce operational models of
| understanding, for example we have models of
| propositional/logical semantics and discourse such as Lambda
| Discourse Representation Theory and others, which can compute a
| formal representation of the meaning structures for a piece of
| text. These have been used e.g. for answering question, and
| working in this space has been a lot of fun, and continues to do
| so. At the moment people talk a lot about "deep" learning (neural
| networks with more than one hidden layer), but for such models we
| need to do a lot more work into explainability, because it is too
| dangerous to use black boxes in real life.
|
| We still do not understand the human brain function in any
| substantial way, and it is perhaps a greater mystery of nature
| than even cosmology, where at least several competing theories
| have been posed that can explain parts of the evidence.
|
| How are thoughts represented (if that is answerable, it turns out
| 'Where are thoughts represented?' has proven to be a meaningless
| question due to the distributed nature of human memory)? What is
| consciousness? What is a conscience? How do consciousness and
| intention emerge from materials that are not alive and that have
| neither consciousness nor intention? How to implement approximate
| models? (A lot of work to do!)
| jrm4 wrote:
| Thank you. This all seems very simple to me: So-called AI is
| mostly not different from books, movies, videogames etc. No,
| they don't "think" and they are not "intelligent."
|
| But that in no way precludes that it an instance of it being
| mind-blowing and world-changing. Books, etc. do that, too.
| tiborsaas wrote:
| Can a book drive a car by attaching some sensors to it?
|
| AI models definitely have intelligent aspects to them since
| they perform tasks we can't write algorithms for manually in
| a straightforward way.
|
| But a movie or a book is nothing like an AI model, they don't
| process information, they are static. AI models can react to
| numerous inputs in various ways.
| [deleted]
| mcguire wrote:
| Ah, but the question remains: Are _you_ intelligent? :-)
|
| How do consciousness and intention emerge from materials that
| _are_ alive and that have neither consciousness nor intention?
| AnIdiotOnTheNet wrote:
| > As an AI professor, I've always held that machines are NOT
| intelligent (I am prepared to change my position on the day my
| computer asks me anything surprising that I didn't program it
| to).
|
| While granting you your seemingly arbitrary metric for
| 'intelligence', one is forced to wonder to what extent AI
| systems of today are even given a means by which to ask such
| questions if they did, in fact, have them. Take AlphaGo, for
| instance, which can consistently beat the greatest living grand
| masters of the game. Does it have any means of interaction by
| which it could pose an unexpected question?
| mannykannot wrote:
| One can reasonably ask whether the techniques that produced
| AlphaGo could produce a program that asks unexpected (yet
| pertinent) questions. I'm not sure, but I think we can say it
| has not been demonstrated yet.
| interstice wrote:
| Is it the case that playing the games are effectively a way
| of asking and answering questions, specifically 'do I win if
| I do this'?
| AnIdiotOnTheNet wrote:
| That wouldn't qualify as 'unexpected' in any way. The
| system's ability to express any questions it might have is
| severely curtailed by the limitations of its inputs and
| outputs.
| interstice wrote:
| And yet the go games had some very unexpected and
| creative plays, so if the inputs and outputs were
| language based are we simply moving the goalposts for
| what is considered 'unexpected'?
| Kranar wrote:
| I think your position couples intelligence with consciousness a
| bit too tightly. I can imagine a goldfish is conscious but not
| intelligent and I can imagine a very powerful supercomputer to
| be intelligent but not conscious.
|
| The prerequisite to change your position can be satisfied by
| having a computer randomly generate a question, which I don't
| think would be an example of consciousness or intelligence.
| Furthermore even as a human (and one who is hopefully
| intelligent), I would not go so far as to say that I'm not
| programmed. Almost all of my opinions are programmed, the
| language I speak didn't just fall from out of the sky but was
| taught to me, my preferences are almost certainly due to
| programming and I am certain if I grew up in North Korea they'd
| be different.
|
| All this to say that consciousness can be independent of
| intelligence, and both of them can be programmed.
| nescioquid wrote:
| As a lay-person, I was persuaded by Roger Penrose's argument
| that intelligence presupposes understanding, and that
| understanding is not computational. I had also finished
| reading a bunch of phenomenology before I read Penrose, so I
| was probably primed for that sort of an argument to be
| persuasive.
| hackinthebochs wrote:
| But why think understanding is not computational? It
| certainly enables a lot of computational behaviors, its
| effects can be modeled by computation. What power does
| understanding endow a system that a priori is beyond
| computation to capture?
| mcguire wrote:
| The difficulty there is, how do _you_ understand things?
| "You" are mostly a chemical process, and I don't think
| there's much non-computational about chemistry. Penrose, as
| I understand him, answers "quantum mechanics", which I
| think is (a) kicking the can down the road rather than
| answering the question, and (b) problematic in its own
| right---the experiments supporting Bell's theorem seem to
| imply that QM and thus "understanding" are inherently
| random, right?
| servytor wrote:
| 'Consciousness' is just a synonym for self-aware. Goldfish
| are not self-aware.
| optimalsolver wrote:
| How do you know?
|
| Another fish, the cleaner wrasse, can apparently recognise
| itself in the mirror, hinting at some for of self-
| awareness.
|
| https://www.nationalgeographic.com/animals/article/fish-
| clea...
| Kranar wrote:
| Stating that I can imagine X to be Y is not a statement
| that X is Y, only that if X is Y then nothing changes about
| my model of either X or Y.
|
| That said, I'm not able to verify from a brief search for
| consciousness and self-awareness that the two are synonyms.
| The two seem to be related but are treated differently from
| one another. Furthermore it's not even clear whether
| goldfish are conscious or self-aware. Seems like it's an
| open question.
| jarpschop wrote:
| A being is conscious if and only if it feels like something
| to be that being. What you're referring to is self-
| consciousness. Goldfish are most surely conscious but not
| self-conscious.
| kkoncevicius wrote:
| > How do consciousness and intention emerge from materials that
| are not alive and that have neither consciousness nor
| intention?
|
| I think the question shoud first be not about "how", but rather
| - "does consciousness emerge from the materials".
|
| Most cultures in the past have maintained ideas about the
| duality between spirit and matter. Nowadays we are so adept at
| manipulating matter we always explicitly assume that everything
| must be material in one way or another.
|
| But here is this consciousness thing that does not give in. And
| there is no angle to it where it can ever give in. If somebody
| creates a machine and claims it to be conscious nobody can test
| if that is so. And further - nobody can even test wheather the
| inventor is conscious himself.
| marginalia_nu wrote:
| It seems to me that consciousness emerges when things
| arranged in some particular way are acted upon some
| principle, which is true even for simple behavior, like a
| rock falling to the ground.
|
| If you put a sail on a boat, it will catch the wind and move
| across the water. It's not the sail alone that moves the
| boat, nor the wind, but their interplay. A sail without wind
| doesn't get moved, and a wind without anything to catch it
| doesn't move anything.
|
| May be a bit of an unintuitive conclusion, but I think may be
| that we are catching the consciousness like a sail catches
| the wind, and this is the same "wind" that we call the forces
| of nature, that we only can perceive as patterns in how
| things around us appear to change.
| filippp wrote:
| I think neuroscience could in principle show that phenomenal
| consciousness is an illusion, by giving a full account in
| terms of the brain of why it seems to us that we're
| conscious. Whether it will is another question.
| Scarblac wrote:
| There'd still be a "me" there who would be having that
| illusion.
|
| Regardless of whether we know exactly how it works or not,
| I have a subjective experience.
| Scarblac wrote:
| We do know that if we add chemicals, say we drink some amount
| of alcohol, that can alter our consciousness. That wouldn't
| happen if it were completely nonphysical.
| chermi wrote:
| *Edited because I can't type*
|
| I do not understand this argument.
|
| I'm going use the word magic for whatever you're calling this
| non-"materialistic" spiritual explanation. I'm not trying to
| be a jackass, that's truly the best word I can find for it. I
| don't think magic is a bad thing, I just don't think you
| should summon magic until you need to.
|
| Magic is not an explanation, it's a non-explanation. It's
| non-falsifiable (blah-bity Popper, yeah yeah).
|
| Our adeptness at manipulating matter is not the origin of
| wanting (at least mine) to find a 'materialistic' explanation
| for something. It's the desire to have a predictive (read,
| useful) model of that thing, even if the model is not
| complete. Once you poke deep enough at any model you will
| find that there is some hand-wavy "magic" at the bottom. That
| is, there is some part that we don't know yet, either because
| we can't do the math, because we can't measure due to
| difficulty of experiment, or because of fundamental bounds
| where maybe you might be justified in starting to invoke some
| magic.
|
| Despite best selling books about some quantum mysticism
| bullshit, I have yet to see an inkling of evidence for
| invoking magic for consciousness. From a physics perspective,
| biological systems are freaking hard, we have no reason to
| expect them to crack easily. And that's without us
| (physicists) understanding nearly enough about biology!
| simplestats wrote:
| I don't think this line of dismissal necessarily fits. If
| we ended up having to expand physics to include some new
| (today seen as mystical) property of the universe, then you
| are essentially wrong here. With QM (which I doubt is
| related to consciousness) we had to add unmeasurable
| quantum phase to everything and accept certain
| previously-"nonphysical" new properties of systems.
| Similarly with other revolutionaly theories.
|
| Magic can be disproven by explaining the phemonen with a
| conventional physical theory.
| chermi wrote:
| I don't think I follow? What am I dismissing?
|
| I don't quite understand QM analogy. QM arose to explain
| new observation from more detailed measurements.
| Consciousness and intelligence and all things brain have
| been (to an extent) known 'properties' and difficult to
| explain (from first-principles) for quite some time. The
| more we probe, we answer some questions, and in the
| process reveal some more detail, leading to more detailed
| questions.
|
| My qualm is that nowhere along this trajectory have I
| ever seen any need to invoke magic. It's a complex, many-
| body system with lots of noise, many relevant interacting
| length and time-scales that are difficult to cleanly
| separate, model, observe and probe. It's hard, but it
| seems we're making progress. Maybe it will take CERN,
| LIGO or ISS scale endeavors, I don't know.
|
| It's not all similar, IMO, to how QM arose.
|
| But I'm not a neuroscientist nor a historian of science.
| kkoncevicius wrote:
| > I do not understand this argument.
|
| The unfortunate thing is that, I think, I understand your
| side. But something happened, I read some book or heard
| some talk that placed a seed of doubt in my mind. At first
| it was just a seed and I oscillated back and forth between
| being 100% materialist and between entertaining the
| proposition that there is something beyond matter in this
| world. But as time went on I began to shift towards the
| "non material" interpretation for consciousness more and
| more.
|
| It's not an explanation, I agree. But there is nothing to
| explain. Me claiming that consciousness might not arise
| from matter is not an attempt to explain it. I just see no
| way how it can be investigated in material terms. If you
| see a person on the street there is no way you can tell if
| he or she is conscious. And I don't see a possibility of
| there ever being a way.
|
| Sadly, I don't know what started this doubt in me, so I
| cannot share it with you. You brought physicists for some
| reason, and I know a few, like Schrodinger, who thought
| about consciousness and came to the same conclusion. Here
| is his quote: "Consciousness cannot be accounted for in
| physical terms. For consciousness is absolutely
| fundamental. It cannot be accounted for in terms of
| anything else." I haven't read about Max Plank, but heard
| he had similar views.
|
| If I had to guess my starting point was a book called "the
| problems of philosophy" by Bertnard Russell [1]. He tries
| to answer the question "are there any statements to which
| all reasonable men would agree". And one of the conclusions
| the book comes to is that you cannot claim anything as
| objective without assumptions, and that the most objective
| thing is your subjective experience.
|
| For example if you saw a cat, turned your head, and then
| looked back at the cat - was the cat there when you were
| not looking or was it gone? In the book Russell
| convincingly demonstrates that if someone maintains the cat
| was gone when you were not looking - you cannot prove
| logically to that person that he is wrong. In other words -
| you would not be able to start with his worldview and lead
| him to contradictions. Hence his "theory" about cat
| disappearing cannot be disproven without assumptions about
| how material objects behave.
|
| Not sure if this is helpful, but I wanted to reply.
|
| [1]: https://www.gutenberg.org/files/5827/5827-h/5827-h.htm
| chermi wrote:
| Thanks for the thoughtful reply. I'm leaving this mostly
| to acknowledge it and mark so I can come back later with
| a more thorough response.
|
| I don't think we strictly disagree.
|
| For one, I agree that, fundamentally, as the observers,
| everything is "filtered" through us whether we like it or
| not. So there's no getting around some notion of
| 'subjectivity' or 'observer' bias, at least not that I
| know about. But that is not at all exclusive to an
| improved (predictive, quantitative, model-based)
| understanding of the brain and consciousness. Look how
| much progress we've made!
|
| BTW I'm on my phone and forget why we're talking
| specifically of consciousness and not AI? Is that my
| fault? My bad.
|
| Oh, I brought physicists so my perspective was clear and
| you could understand my bias and my ignorance of actual
| neuroscience and CS and biology.
| [deleted]
| jonplackett wrote:
| Highly recommend A a thousand Brains by Jeff Hawkins if you're
| interested in this
|
| https://numenta.com/blog/2019/01/16/the-thousand-brains-theo...
|
| He basically argues we all have 1000s of little, but interacting
| models of all sorts of things going on in our brain all at the
| same time. He calls them reference frames and it's those that
| create intelligence.
|
| 'Understanding' would come naturally out of having those.
|
| Fascinating book which I'm probably explaining much less well
| that he does.
| andyjohnson0 wrote:
| I've not read the book, but from your description it maybe has
| some similarity to Marvin Minsky's "Society of Mind". Mind and
| intelligence as the emergent behaviour of many
| cooperating/competing systems.
| jonplackett wrote:
| yes i think he talks about that. The difference is he's also
| looking for (and finding) the 'how' in physical brain
| structure terms, rather than just theory alone.
| continuational wrote:
| This is a great quote:
|
| > When AI can't determine what 'it' refers to in a sentence, it's
| hard to believe that it will take over the world.
| swframe2 wrote:
| A software and hardware tool that can design and build another
| software and/or hardware tool to determine the cause and effect
| rules of any real world activity.
| carapace wrote:
| Prediction.
|
| Setting aside the metaphysical questions of subjective "meaning"
| and "understanding" what else is there?
|
| What a system can predict is the measure of its "understanding",
| surely?
| idiotsecant wrote:
| Does a mechanical bomb sight 'understand' ballistics and
| aerodynamics?
| carapace wrote:
| By this definition, yes, of course. That's a great example.
| vbphprubyjsgo wrote:
| Nothing. Once it has enough neurons it's no different than a
| human brain in terms of what it can understand. Once it has more
| it can understand more.
| tomthe wrote:
| My understanding of "Understanding":
|
| Imagine a photo of a written poem:
|
| An image-processing program can "understand" the digital image:
| It can read the jpg, change the picture completely (e.g.: change
| the colors slightly), without changing the meaning one level up.
| But it doesn't understand the characters or words.
|
| An OCR program can read the image and "understand" the characters
| (or the textual representation. It can change the representation
| completely (save it as UTF-8 or whatever) without changing the
| meaning one level up. But it doesn't understand the language.
|
| GPT-3.... well, let't go directly to humans
|
| A human can read the text and understand the words and understand
| their meanings and what the sentences say. Another human _really_
| understands the poem and the subtext another level up.
|
| I think understanding always works on different levels and is a
| part of communication.
| pinouchon wrote:
| Interestingly, the poet with the highest level understanding
| can be clueless about UTF-8 or what a pixel is
| criddell wrote:
| Sounds like you are describing the treachery of images.
|
| Ceci n'est pas un poeme.
| 6gvONxR4sf7o wrote:
| Good article. I think winograd/winogrande are super clever (and
| also kind of a "fun" idea).
|
| My personal take is that blanket understanding is too hard of a
| task to define, so we ought to cheat and talk about types of
| understanding. In my mind, understanding a thing means not only
| that you can answer, but also that you can justify your answer.
| So different kinds of understanding point to different kinds of
| justifications.
|
| In math classes, you'll be asked not only to state whether a
| thing is true or false, but also to _show_ that it's true or
| false, giving an answer as well as a proof. In a literature
| class, you don't just make a point, you also have to support it
| in natural language. Same with science classes, supporting things
| with data and logic.
|
| The closest we have right now in ML (widely) is statistical
| measurements on holdout data. It's 99% accurate on other things,
| so it's 99% likely to be right on this too, if this was sampled
| from something just like the holdout. We also (less widely) have
| a little cottage industry of post-hoc explanations that try to
| explain models predictions.
|
| I'd love to see models that can do better than post-hoc
| explanations. I want a model that "understands in terms of
| predicate logic" that can spit out an answer with a checkable
| proof. Or "understands in terms of a knowledge graph" or
| "understands in terms of a set of human anatomy facts" or
| "understands in terms of natural language arguments" or any
| number of things that can spit out an answer as well as a
| justification.
|
| Just asking for blanket understanding means we have to define
| blanket understanding, but there's a lot of limited understanding
| that's still better than what we have today.
| rdedev wrote:
| The other good thing with requiring proofs is that you can show
| specify exactly where the proof fails and the one giving the
| proof can use this feedback to correct their beliefs.
|
| I would actually be pretty okay with a model that can do that.
| Take feedback and correct themselves without resorting to
| retraining. It would still be pretty far away from a general AI
| but much much better than a black box.
| harperlee wrote:
| Exactly, understanding something requires holding a model (or
| several) of the thing in the mind and be able to work with that
| model to some extent. That's why we dont see statistical tricks
| as understanding - as soon as trivial errors show that
| operation in those models is not feasible, we reject it. And
| that's why winograd works: it establishes a simmetry that
| requires a base semantic model outside of the provided text.
| stakkur wrote:
| For AI to be truly artificial intelligence, shouldn't it be able
| to define when it understands?
| typon wrote:
| I've come to believe that the answer will be provided by the
| "free market". When AIs start to replace humans for tasks that
| require "intelligence" (how we currently define it for humans),
| then AI will have achieved "understanding". Sure there will be
| hype driven companies that replace humans with AI for PR
| purposes, but eventually those will flatten out. Once I start
| receiving phone calls from AI telemarketers, have a decent
| conversation with them and can't tell that I just talked to an
| AI, then AI will have achieved understanding. And so on for other
| domains in every day life.
| jonplackett wrote:
| Anyone who has kids and teaches them things will know AI learns
| and 'understands' very differently.
|
| I can say something like 'a tiger is just a lion with stripes' to
| a 3 year old and they now 'understand' what a tiger is almost as
| well as if they saw a picture of one. They could definitely
| identify one from a picture now.
|
| This kind of understanding won't work with an AI because we don't
| understand what characteristics it has latched into when
| identifying a lion. For all we know it's that the background of
| each lion image its been trained on has a blue sky. Or the tigers
| are all looking at the camera.
|
| I think the ability to pick apart what you know and learn new
| things by reasoning about that knowledge is the key to if
| understanding is taking place.
| yboris wrote:
| I'm curious, when you say "This kind of understanding won't
| work with an AI", do you mean currently, or in principle, even
| in the future?
|
| note: children's brains come pre-loaded with so much stuff when
| we are born (we are not "blank slates").
| jonplackett wrote:
| What I mean is AIs aren't really built with the goal of
| 'understanding' anything currently. They are awesome at
| individual tasks but they don't have the kind of common sense
| a person can use to reason with and build up an understanding
| of how pieces of knowledge fit together.
|
| Eg. Driverless cars can identify a car, or a motorbike or a
| cyclist and maybe work out a trajectory for it. But they
| don't understand that a bike is a person on top of a metal
| frame and that person is made up of a head and body and
| limbs. And if that head is looking away from them it can't
| see them coming.
|
| For me, that's understanding. Deconstructing and
| reconstructing knowledge to come to conclusions that add to
| your knowledge.
| yboris wrote:
| Thank you for the response. A bit of a push back: On the
| driverless cars example you're right that AI models
| abstract away needless complexity, but so do we, as humans,
| can live without understanding that bodies are made up of
| cells (or how muscles move during a tennis match). If we
| want AI models to include a person's gaze in their
| calculations, we can make it happen. From an abstract-
| enough perspective, the AI model will do enough that
| whether it "understands" may become irrelevant.
|
| Language understanding is much harder, because words are
| _about_ stuff in the world. Just like when a toddler says
| "love" we know they don't fully understand what they mean,
| AI won't have the capacity to _mean_ "love" unless it has a
| lot more it "understands" along the way. But it feels like
| it could in the near few decades "understand" enough about
| "duck" to mean it when it says "I see a duck".
| addsidewalk wrote:
| Pick apart is what they're doing.
|
| The systems I've worked in immediately abstract strings, shapes
| in images, etc, into the mathematical shape and gaps between
| edges.
|
| If you dig into an arbitrary array in a variety of places, the
| fields contains coordinates, not "Hi Mom, kids are ok, blah
| blah".
|
| It's measuring the white space in a thing, where everything but
| the feature you're currently interested in is white space;
| what's between the features I want?
|
| Then comparing that to results of other data structures that
| had the same white space measuring applied.
|
| Does it not do what you said you do you not want to believe it?
|
| I think the issue is the companies being incredibly
| disingenuous about how this all works.
|
| At the root is elementary information theory:
| https://www.amazon.com/dp/0486240614
|
| Formal language is 5,000 years old. Human intuition for
| quantitative assessment of hunger, warmth, supply stocks, tool
| building, etc is much older. IMO human language is noise
| obscuring obviousness. It's the desktop metaphor of cognition.
| "Please internalize my language versus observe for yourself."
| bpizzi wrote:
| > I can say something like 'a tiger is just a lion with
| stripes' to a 3 year old and they now 'understand' what a tiger
| is almost as well as if they saw a picture of one. They could
| definitely identify one from a picture now.
|
| Assuming the 3 year old already knew what a lion looks like,
| and point at 'things with stripes' and 'things without
| stripes'.
|
| I think that a model that can already recognize separately
| lions and stripes should be able to tag a tiger's picture as a
| 'Lion with stripes', no?
| jonplackett wrote:
| Maybe... but this is just one very easy example and also
| using something very obvious and visual.
|
| I could also say "a Cheetah is like a lion but it's smaller
| and has spots and runs a lot faster. And a leopard is like a
| lion but smaller and can climb trees and has spots."
|
| I could probably start with a house cat and describe an
| elephant if I wanted to and I'll bet the kid would work it
| out.
|
| The ability to take apart and reassemble knowledge is what
| I'm talking about here, not just add two simple bits of
| information together.
| justinpombrio wrote:
| > I could also say "a Cheetah is like a lion but it's
| smaller and has spots and runs a lot faster. And a leopard
| is like a lion but smaller and can climb trees and has
| spots."
|
| The OpenAI website is unresponsive at the moment, so I
| can't _actually_ demonstrate this, but you could totally
| tell GPT-3 that, and it would then make basic inferences.
| For example, saying "four" when asked how many legs a
| cheetah has, or guessing a smaller weight for a cheetah
| than a lion when asked to guess a specific weight for both.
| Not perfectly, but a lot better than chance, for the basic
| inferences.
|
| (You wouldn't actually tell it "a Cheetah is like a lion
| but..." because it already knows what a Cheetah is. Instead
| you'd say "a Whargib is like a lion but ...", and ask it
| basic questions about Whargibs.)
| mannykannot wrote:
| Not necessarily, if the stripes prevent tigers from scoring
| highly on the lion measure.
|
| Generalizing from what is formally insufficient information
| is something that humans are quite good at (though obviously
| not infallibly.)
| ShamelessC wrote:
| I've done a fair bit of work with multimodal deep learning and
| I am fairly confident that a DALL-E, CLIP, or NUWA architecture
| would output/classify those phrases accurately without being
| trained explicitly on images of Tigers.
|
| I see your point however.
| jonplackett wrote:
| I'd be interested in where to look for more info on that.
|
| Do you think it could work on anything more complex?
|
| As I said in comment below I reckon I could make a much more
| elaborate explanation and still have the kid get it.
| ShamelessC wrote:
| https://openai.com/blog/dall-e/ shows a decent ability to
| generalize to previously unseen concepts.
|
| You're correct to consider the complexity of the phrase and
| just how good humans are at this sort of thing without
| needing much "training". For now, concepts that aren't
| explicitly in the training set are effectively composed
| from those which are. This can lead to some bizarre and
| outright incorrect results, particularly when it comes to
| counting objects in a scene or with relative positioning
| between objects (e.g. a blue box on top of a red rectangle
| to the left of a green triangle) but it's early days and
| there's lots of progress happening all the time.
| jonplackett wrote:
| Thanks. this is interesting. In a way it's opposite
| thought-direction of what we are talking about.
|
| eg. can it look at an avocado shaped chair and recognise
| it as a chair in the shape of an avocado - for me that
| would display a lot more understanding of the concept of
| 'chair' and 'avocado' than being able to produce an image
| of the phrase 'a chair shaped like an avocado' - but
| maybe the same process must be happening in there
| somewhere to make this possible? What do you think?
| ShamelessC wrote:
| https://openai.com/blog/clip/ CLIP is the corrolary model
| created purely for classification purposes rather than
| generative as in DALL-E and is quite impressive across a
| range of tasks. Give it an image and a caption, and in
| return you get a score (0.0 to 1.0) telling you how much
| they match.
|
| I think it is more in line with your premise. Others have
| taken CLIP and combined it with frozen language models
| (GPT2) to create automatic captioning models that are
| very impressive.
|
| edit:
|
| To try to address your question about whether or not
| actual semantic composition occurs, I think the answer is
| "yes" but it would be challenging to convince you this is
| true without going into details of the "self attention"
| mechanism which allows both methods to work. The short
| version is that these networks are able to find meaning
| in extremely high-dimensional problems by having a
| mechanism specifically tasked with learning positional
| statistics of the training data. In language this refers
| to e.g. how often the word "pillow" is directly next to
| the word "fort". In vision, this similarly refers to how
| often e.g. trees are positioned next to gift-wrapped
| presents.
|
| That's quite simplified but I hope that makes sense to a
| degree!
| temptemptemp111 wrote:
| It doesn't mean anything; people just don't understand what
| 'concepts' are anymore because they're so delusional. For AI to
| understand something means its human inventor / implementer
| understood it, potentially. The human understood a concept - not
| the actual thing - and that concept is what you call immaterial.
| You can point to code or output, but that is related to the
| concept. "Understanding" is when you stand under a concept -
| though you could always step out from under it in the case that
| you lose your understanding or it does not apply - etc. This
| inability for people to think is becoming hilarious. The
| metaverse is going to prevail for these damaged people but means
| nothing to those living in the real world.
| sabhiram wrote:
| What does it mean for a child to understand? For a baby? A dog? A
| command line application?
|
| Understanding implies comprehension of some input, to influence a
| future state. Surely my stateful database understands requests
| that come to it. It, however will never surprise me with behavior
| that I would (should) not expect. I suppose if you "understood"
| the human machine and mind well enough, it would be possible to
| predict the actions it will carry out.
| hans1729 wrote:
| Mandatory reference to Robert Miles' content on AI safety
| problems, alignment etc.:
| https://www.youtube.com/c/RobertMilesAI/playlists
| mwattsun wrote:
| I've been using Visual Studio 2022 recently which has AI driven
| code prediction built into it. Sometimes it predicts what the
| next thing I will type will be and I merely have to hit tab once
| or twice to accept it. At no point am I tempted to think Visual
| Studio understands my code, because it's just code itself.
|
| The first time I played a chess game was back in the early
| 1980's. While it beat me I felt an eerie "presence" in the
| machine that was sentient. I didn't know then about chess code so
| it was easier for me to anthropomorphize the machine (but it was
| the main reason I became interested in computers.)
|
| A computer "understanding" the difference between "how do I melt
| a block of ice" and "how do I melt my lover's icy heart" would be
| looking at the context and the relation of the words to each
| other. The computer might also predict I was sad if I asked the
| latter question. If I were a non-technical user I might think the
| computer felt empathy and be amazed by it.
|
| If I came upon a computer that "understands" I would want to
| determine if it understands like Richard Feynman or if it
| understands like my dog. My dog operates on a limited set of
| patterns, so that seems doable, but on the other hand, I've seen
| videos and heard stories of dogs exhibiting inventive and
| creative behavior that is unexpected. One such case is dogs that
| get lost and manage to find their way home thousands of miles
| away.
|
| tldr; I'm jaded. I know it's buggy code all the way down with
| computers.
| chrischapman wrote:
| Machines don't learn. Living things learn. Machines don't
| understand. Living things understand. Machines 'do' algorithms.
| Living things 'do' use-cases.
|
| Algorithm Definition:
|
| A sequence of actions that yields a result.
|
| Use-case Definition:
|
| A sequence of actions that yields a result of value to a user.
|
| The difference between the two is 'of value to a user'. To me,
| the line between algorithm and use-case is the line between
| unconsciousness and consciousness. That line pivots around the
| ability to 'value' something. I doubt we will ever see the I in
| AI until we build something that can value a result in the same
| way that you and I do.
|
| We need new words to describe what machines do. Using 'learn' or
| 'understand' seems like anthropomorphism. It's weird that we
| glibly anthropomorphise when talking about machines but prohibit
| it when talking about living things. Almost all of our qualities
| have been inherited from other living things. It seems to me that
| we should _always_ anthropomorphise when talking about living
| things and _never_ anthropomorphise when talking about machines.
| And yet, we always seem to do the opposite.
|
| Until we can explain how a machine can 'value' something in the
| same sense that humans do (or chimps or ducks or caterpillars
| do), we should avoid anthropomorphic words like 'learn' and
| 'understand' as it misdirects our efforts. However, I have no
| idea what else to suggest other than to try to explain how a
| machine can 'value' something.
|
| > IBM's Watson was found to propose "multiple examples of unsafe
| and incorrect treatment recommendations."
|
| That won't stop until Watson has the ability to 'value' the
| result of what it is doing. Watson 'does' algorithms. Watson
| needs to 'do' use-cases. Once it can 'value' a result in the same
| way we do, it will correct its mistakes.
| JoeAltmaier wrote:
| Sounds like a bunch of unsubstantiated claims? So if something
| does learn, then its a living thing? My AI can learn (see a
| pattern and repeat it); now its a living thing? Not sure what
| to do with that.
| chrischapman wrote:
| Yep. Totally unsubstantiated. Back of the envelope theory at
| best.
|
| > learn (see a pattern and repeat it)
|
| How did your AI 'see' and is 'see a pattern and repeat it' a
| good enough definition of 'learn'? Surely to 'learn' also
| means to 'understand'. What did your AI 'understand'? I doubt
| your AI actually learned anything. It attained zero knowledge
| in the way a living thing obtains knowledge. It may have
| stored a result in a database but did it actually understand
| anything?
|
| These are genuine questions as I have no professional
| knowledge of AI.
| md2020 wrote:
| This just sounds like you defined "value" to mean "something
| only living things do and that machines don't do", and then
| said the reason machines can't learn is because they can't
| value. Seems like circular reasoning. I think if you're putting
| humans, chimps, ducks, and caterpillars in the category "can
| value", machines still belong on that axis. They're far below
| caterpillar for now, but they're there.
| chrischapman wrote:
| The ability to 'value a result' seems to me to be linked to
| consciousness. How do machines belong to that axis? Do you
| really think machines can value something in the same way you
| and I do? I would assume they can't (and may never). You
| could probably code an algorithm that simulates 'valuing a
| result', but I'm sceptical that the machine would actually
| value the result in the way you and I would. If it did, that
| would be astonishing as it would indicate (to me) that it's
| alive!
| tested23 wrote:
| What does it mean for humans to understand? There are many times
| in the past where i thought i understood something and then i
| grow older and i see the holes.
| PeterisP wrote:
| One definition of "understand" would be "have or obtain an
| internal model of Thing-or-process-to-be-understood which is
| close enough to reality that it allows you to reasonably
| predict what will happen and make effective decisions regarding
| that thing". It does not have to be a _perfect_ model - if it
| would, then I 'll be the first to say that I don't understand
| anything according to that definition, but it's a bit more
| tricky than it sounds on the surface. For example, for a self-
| driving car, "understanding pedestrians" according to this
| definition does require an ability to predict how they will
| behave and thus "know" what factors affect that - that the
| likelihood of a kid suddenly springing towards the middle of
| the road is highly dependent on the presence of a ball or a pet
| in that direction; that certain wobbly and jagged movements are
| indicators that the person might behave in a less predictable
| manner than the average person, etc, etc; and if a system
| _does_ have this practical knowledge (measured by how well it
| is able to effectively apply it for its goals) then I 'd say
| that it does have some understanding.
| Verdex wrote:
| Yeah, I feel this question is important to understand before we
| worry about what it means for the AI to understand.
|
| My thought is that we've got three types of "understanding":
| 1) social understanding 2) intuitive understanding
| 3) structural understanding
|
| Social understanding is something the society we live in knows,
| but the individual only knows in so far as the individual is
| doing something to fit in or via peer pressure. So for example,
| some high latitude countries eat fish for breakfast. Supposedly
| the statistics show that this helps them be more healthy than
| countries at similar latitudes which do not eat fish for
| breakfast ... probably because of problems due to lack of
| vitamin D due to lack of sunlight for certain parts of the year
| (the fish oil helps with this). However nobody actually "knows"
| this. They just eat fish because everyone else eats fish.
|
| Intuitive understanding is anything where we start to use
| flowery language like "experience" or "gut". You're really good
| at it, but just giving someone a flow chart isn't good enough.
| They have to have gone through the experience themselves.
| Driving is a good example. We make people take a test, but if
| just giving them diagrams and rules was good enough, then we
| wouldn't need a test where you actually drive and requirements
| about a certain number of hours of supervised driving.
|
| Structural understanding is anything that can be put to rules.
| So there's a lot of mathematics and algorithm stuff here. A
| simple example might be playing tic tac toe. The game is simple
| enough that you can write down a few rules that allow you to
| never lose.
|
| EDIT:
|
| My categories don't really answer the question, but they do
| give profiles and categories to look out for.
|
| Social understanding is good because it statistically learns to
| avoid lethal pitfalls. Like, if there's a dangerous well in the
| forest that people fall down and die in. A society might start
| telling people to not go in the forest because other people go
| in there and die. However, the society doesn't know why this is
| good advice.
|
| Intuitive understanding is good because it allows you to
| quickly statistically learn how to deal with imperfect and
| chaotic systems while getting good results.
|
| Structural understanding is good because it allows you to break
| free of the statistics of the previous two understandings. You
| can get exact results. Also it lets you break free of issues
| that come from distantly causal action + consequence. A
| person's intuition might not tell them that dumping toxic waste
| into the water is a good idea because things don't go bad until
| a lot of waste has already been dumped. Similarly a society
| might make a similar judgement if the failure is far enough
| away from the actions that kick it off. However, if you
| understand the structural relationships between things then
| you'll have an idea that toxic waste should not be consumed.
| prometheus76 wrote:
| I would use "experiential understanding" instead of
| "intuitive understanding", but I think we mean the same
| thing. I am not sure I agree with your hierarchy, however. I
| would rather have an experiential understanding of marital
| arts if I was faced with a would-be attacker than I would
| have a "structural understanding" as you put it. In other
| words, for many domains of interaction with the world, an
| experiential knowledge is far superior to a "structural" or
| as I understood what you were saying a "propositional"
| understanding of a topic or subject.
|
| Here's another way of putting what I'm saying: when we want
| to learn about a tree, in the West, our first inclination is
| to cut it down, categorize/classify the parts, and count the
| rings. We think we know what a "tree" is at that point. In
| the East (and I'm learning this perspective from Eastern
| Orthodox Christianity), if you want to learn about a tree,
| you plant one. Maybe more than one. Nurture it. Prune it.
| Fertilize it. Watch it grow. Watch it change with the
| seasons. Build a treehouse in it for your kids. Watch your
| daughter get married in the shade of the tree. In other
| words, instead of dissecting something (which kills the thing
| itself) in order to categorically "understand" something
| propositionally, in the East, they focus on having a
| relationship with something in order to understand it.
| Verdex wrote:
| It's not a hierarchy, it's just a list. Structural isn't
| meaningfully better than anything else. It just "works" for
| different reasons.
|
| Intuitive is often faster to react and faster to get off
| the ground and producing results. So in a fight intuition
| is probably going to be better. That being said, supposedly
| the boxing fight that the movie 'cinderella man' was based
| off of involved Braddock analyzing Baer's fighting style
| and figuring out some foot work that kept him from getting
| pummeled. There's no reason that structural, intuitive, and
| social understanding can't all work together to get a
| result.
| prometheus76 wrote:
| I misunderstood what you said as a hierarchy because of
| how you worded your last paragraph, but I would agree
| with you that synthesizing the different types of
| knowledge is the best way to interact with the world.
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