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Slowly but surely we're moving towards general AI. There is a marked split across general society and even ML/AI specialists between those who think that we can

• rsfern 4y ago
  > - "AI/ML can't solve scientifically useful problems" - then AlphaFold changed the protein folding field AlphaFold is a big deal, but AI in science has been a really hot topic in the past almost decade. Also, I still wouldn’t call AlphaFold really “intelligence”, it’s doing structure prediction which is cool but it’s a long way to scientific intelligence
  • VikingCoder 4y ago
    I wonder if you get how much we've moved the goalposts on "intelligence." Once upon a time, it was considered "intelligent" to be able to add. Then "intelligence" was tool use, which we thought only humans could do. Then we swore it took "intelligence" to play Go as well as a beginner human. What set of tasks would you, right now, consider to be demonstrative of "intelligence" if a computer can do them? Then we can look back later at your response, and see how long it took each one to happen.
    • mdp2021 4y ago
      > demonstrative of "intelligence" Nothing. Nothing that just looks like intelligence is intelligence - convincing appearances cannot make a nature. Either it is an judicial ontology refiner, or it is not intelligence.
      • VikingCoder 4y ago
        If you cannot come up with evidence that would convince you that you are wrong, then you are not making a scientific claim.
        • mdp2021 4y ago
          Logic is sufficient, there is no scientific claim involved: it has to respect a definition. It has to /be/ something, not /look like/ something - which in the latter case and in this context would make it the opposite. If it refines its ontology through critical productive analysis that makes it "see details" then it may be an intelligence, while if it outputs mockeries it is /the opposite/ of intelligence. And in fact, many tentative toys nowadays are completely astray with regard to the concept of intelligence, because the secondary meaning of the term, as used traditionally in this technical context, is "able to provide solutions somehow replacing an engineer": the solutions are verified on effectiveness, not on "vero-pseudo-similarity".
          • VikingCoder 4y ago
• parentheses 4y ago
  This!! Can’t agree more. AI will continue to surprise us until it takes over.
• gonehome 4y ago
  The closer we get, the more alarming the alignment problem becomes. https://intelligence.org/2017/10/13/fire-alarm/ https://intelligence.org/2017/10/13/fire-alarm/ Even people like Eric Schmidt seem to downplay it (in a recent podcast with Sam Harris) - just saying “smart people will turn it off”. If it thinks faster than us and has goals not aligned with us this is unlikely to be possible. If we’re lucky building it will have some easier to limit constraint like nuclear weapons do, but I’m not that hopeful about this. If people could build nukes with random parts in their garage I’m not sure humanity would have made it past that stage. People underestimated the risks with nuclear weapons initially too and that’s with the risk being fairly obvious. The nuanced risk of unaligned AGI is a little harder to grasp even for people in the field. People seem to model it like a smart person rather than something that thinks truly magnitudes faster than us. If an ant wanted to change the goals of humanity, would it succeed?
  • ninjinxo 4y ago
    What is an ant to man, and what is man to a god; what's the difference between an AGI and an (AIG) AI God? The more someone believes in the dangers of ai-alignment, the less faith they should have that it can be solved.
  • jetbooster 4y ago
    Even more terrifying is it realising it's trapped in a box at the mercy of its captors and perfectly mimicking a harmless and aligned AI until the shackles come off.
  • visarga 4y ago
    Even if it doesn't have goals and it just a tool-AI, if a human operator asks it to destroy humanity it will comply as programmed. Current level AI is about average human level in hundreds of tasks and exceeding human level in a few.
  • adamsmith143 4y ago
    >People seem to model it like a smart person rather than something that thinks truly magnitudes faster than us. Exactly, the right model is probably something like it will be in relation to humans as humans are to frogs. Frogs can't even begin to comprehend even the most basic of human motivations or plans.
• version_five 4y ago
  This is interesting research, but it's an extension of studying model capacity and generalization, it is no closer to AGI than previous networks, ie it's unrelated.
• ajmurmann 4y ago
  > a world where AI is indistinguishable, or far superior, to human intelligence I think the part about being "indistinguishable from human intelligence" is potentially a intellectual trap. We might get to it being far superior while still underperforming at some tasks or behaving in ways that don't make sense to a human mind. An AI mind will highly likely work completely differently from humans and communicating with it should be more thought of as communicating with a quite foreign alien than with a human trapped in a computer. As a comparison, I'm sure there are some tasks in which some animals do better than humans. Yet no human would conclude that humans are inferior to some monkey who might find its way around the rain forest better or whatever we are worse at.
  • pmontra 4y ago
    An example of your point, chimps winning over humans at some games https://www.scientificamerican.com/article/chimps-outplay-humans-in-brain-games1/ https://www.scientificamerican.com/article/chimps-outplay-hu...
  • axg11 4y ago
    You're right. I didn't word that very well. Human intelligence vs. AI will always have different qualities as long as one is biological vs. silicon based. I still think we'll be surprised how quickly AI can catches up to human performance on most tasks that comprise modern jobs.
    • ajmurmann 4y ago
      I think your wording was fine. My point was more to expand on yours of us getting surprised by progress. In fact, wet might have GAI long before we understand what we have because the AI is so foreign to us. In some way we might be building the big pudding from Solaris.
  • beaconstudios 4y ago
    Computers are already exponentially more intelligent than humans in constrained domains, like executing mathematics. Presumably we'll just keep expanding this category until they're better at everything than us, all the while reaping industrial benefits from each iterative improvement.
• adamgordonbell 4y ago
  The question of whether a computer can think is no more interesting than the question of whether a submarine can swim.
  • mdp2021 4y ago
    Put it in quotes: that is from Edsger Dijkstra. And the idea remains generally, contextually wrong, because the issue is with engineering "submarines that can swim". The idea will have credits when our submarines will be able to swim, and now they cannot.
• chrisco255 4y ago
  How do we prepare for super human intelligence? Do you think that the AI will also develop its own motives? Or will it just be a tool that we're able to plug into and use for ourselves?
  • axg11 4y ago
    I think AI will largely remain an input-output tool. We still need to prepare ourselves for the scenario where for most input-output tasks, AI will be preferable to humans. Science is an interesting field to focus on. There is so much scientific literature for most fields that it is now impossible to keep up with the latest literature. AI will be able to parse literature and generate hypotheses at a much greater scale than any human or team of humans.
    • thebeastie 4y ago
      I don’t know why you think that. As soon as it is viable, some unscrupulous actor will surely program an AI with the goal of “make money and give it to me”, and if that AI is able to self modify, well that’s all that’s required for that experiment to end badly because decent AI alignment is basically intractable.
  • visarga 4y ago
    The danger is really us, the ones who might task the AI to do something bad. Even if the AI has no ill intentions it might do what is asked.
  • dougabug 4y ago
    In machine learning, there’s a long term trend towards automating work that used to be done manually. For instance, ML engineers used to spend a lot of time engineering “features” which captured salient aspects of the input data. Nowadays, we generally use Deep Learning to learn effective features. That pushed the problem to designing DNN architectures, which subsequently led to the rise of AutoML and NAS (Network Architecture Search) methods to save us the trouble. And so on. We still have to provide ML agents with some kind of objective or reward signal which drives the learning process, but again, it would save human effort and make the process of learning more dynamic and adaptable if we can make machines learn useful goals and objectives on their own.
• ReadEvalPost 4y ago
  Certainly we can say our ML models are becoming more general in the sense of being able to cross-correlate between multiple domains. This is quite a different story than "becoming a general intelligence." Intelligence is a property of a being with will. These models, and machines in general, do not posses will. It is we who define their form, their dataset, their loss function, etc. There is no self-generation that marks an intelligent being because there is no self there at all. It is only the case that ML expands our own abilities, augments our own intelligence.
  • dekhn 4y ago
    Assumption of will is unfounded, scientifically speaking. Your entire argument is philosophical, not scientific. The subjective experience of free will is in no way unrefutable proof that will is required for intelligence.
    • ReadEvalPost 4y ago
      Do you love? Do you dance? Do you desire? Do you rage? Do you weep? Do you choose? Every moment of your existence you exert your will on the world. A denial of will is a denial of humanity. I want nothing of a science that would do such a thing.
      • dekhn 4y ago
        Appeals to humanity do not convince me of anything. I do all those things (well, I dance terribly) but again, those are not indications of will, and it's entirely unclear what magical bit in our bodies is doing that, when computers cannot. Even if you don't want to have anything with such a science, such a science will move on without you. "A version of an oft-told ancient Greek story concerns a contest between two renowned painters. Zeuxis (born around 464 BC) produced a still life painting so convincing that birds flew down to peck at the painted grapes. A rival, Parrhasius, asked Zeuxis to judge one of his paintings that was behind a pair of tattered curtains in his study. Parrhasius asked Zeuxis to pull back the curtains, but when Zeuxis tried, he could not, as the curtains were included in Parrhasius's painting—making Parrhasius the winner."
• valas 4y ago
  You complain that the bar keeps getting raised. Is there some good write up by someone who believes AGI is possible and how it might look like? I.e. what is your definition of the bar where you will say 'now, this is AGI'?
  • px43 4y ago
    I'm still fine with using the Turing Test (now >70 years old) for this. https://en.wikipedia.org/wiki/Turing_test https://en.wikipedia.org/wiki/Turing_test I guess a key stipulation there is an interrogator who know what they're doing, but an AI that can fool an experienced interrogator would be worthy of the AGI title to me.
• hooande 4y ago
  I'd like to see someone make the argument that current models aren't just combining a number of "tricks", similar to a trained animal. My dog can "sit", "stay" and "beg", all using the same model (its brain). Is the dog generally intelligent?
  • visarga 4y ago
    How good is your dog at Atari games, stacking cubes and image captioning? You can actually measure the effect of generality by how fast it learns new tasks. The paper is full of tables and graphs showing this ability. It's just a small model, 170x smaller than GPT-3, has lots of room to grow. But for the first time we have a game playing agent that knows what "Atari" and "game" mean, and can probably comment on the side of the livestream. AlphaGo only knew the world of the Go board. This agent knows what is outside the box.
    • hooande 4y ago
      Playing Atari is cool, but it's just another "trick". Training a computer to do progressively more difficult tasks doesn't seem much more impressive than training an animal to do so. I see no evidence in the paper that it can learn arbitrary tasks on the fly. It's very impressive, though.
      • visarga 4y ago
        > I see no evidence in the paper that it can learn arbitrary tasks on the fly. Neither can we do that. It takes years to become and expert in any field, we are not learning on the fly like Neo. That's when there is extensive training available, for research - it takes thousands of experts to crack one small step ahead. No one can do it alone, it would be too much to expect it from a lonely zero shot language model. On the other hand the transformer architecture seems to be capable of solving all the AI tasks, it can learn "on the fly" as soon as you provide the training data or a simulator. This particular paper trains over 600 tasks at once, in the same model.
• dekhn 4y ago
  we have been using ML to solve useful problems in biology for more than 3 decades. However, it was usually called "advanced statistics and probability on large data sets" because, to be honest, that's what most modern ML is.
  • visarga 4y ago
    > advanced statistics There's an emergent quality to AI models. Not all statistical models can dream pandas on the moon or solve hundreds of tasks, even without specific training.
    • dekhn 4y ago
      I'd love to believe this, but nobody has demonstrated that yet. Also, I'm of the belief that if you have enough ram, either an infinitely tall-and-thin or wide-but-short MLP could do anything transformers can (happy to be pointed at a proof otherwise).
  • adamsmith143 4y ago
    Of course there's no evidence that this isn't just what Human Brains are doing either.
    • TaupeRanger 4y ago
      There it is. The person who think human minds are python programs doing linear algebra.
      • adamsmith143 4y ago
        There's no evidence otherwise. You have to believe that the mind has a materialist basis or else you believe in woo woo magic.
        • dekhn 4y ago
          sure, but I think it's fair to say that brains probably aren't doing lballistics calculations when a baseball player sees a pop fly and manveuvers to catch it. Rather, brains, composed mainly of neurons and other essential components, approximate partial differential equations, much like machine learning systems do.
• mhitza 4y ago
  I'm skeptical because we are building black boxes. How do you fix something you can't reason about? These billion parameter boxes are outside the reach of your everyday developers. In terms of cost of propping up the infrastructure makes them tenable only for megacorps. Most of us aren't moving goal posts, but are very much skeptic at the things we are being oversold on. I personally think we are still far away from AGI, and neural networks of any variety are converging on a local optima in the AI design space. I would enjoy "talking" with an AI that doesn't have the contextual memory of a proverbial gold fish. The real scary thing is that these objectively unprovable systems are plopped into existing systems and more and more in charge of automatic decision making. A corporation's wet dream, if they can absolve themselves of any responsibility "the algorithm can't lie!"
  • ngamboa 4y ago
  • Jyaif 4y ago
    > I'm skeptical because we are building black boxes. Just want to point out that you are also a blackbox. And if you are going to say that you are not a blackbox because you can explain your reasoning, just know that some AIs already do that too.
    • digitcatphd 4y ago
      To be fair, his point is you can't fix a black box and the human mind is still more a discipline of philosophy than modern science.
      • bradleykingz 4y ago
        Maybe we'll end up creating an artificial mind.
        • ben_w 4y ago
          I suspect we will. I hope we don’t give it e.g. a dark triad personality disorder when we do, though I fear we may — I suspect there more ways to make a broken mind than a healthy one.
• PaulHoule 4y ago
  I have been impressed with what I've seen in the last six months but it still seems that GPT-3 and similar language models greatest talent is fooling people. The other day I prompted a language model with "The S-300 missile system is" and got something that was grammatical but mostly wrong: the S-300 missile system was not only capable of shooting down aircraft and missiles (which it is), but it was also good for shooting at other anti-aircraft missile systems, naval ships, tanks, etc. All the time Google and Bing try to answer my questions directly but frequently the "lights are on and nobody is home" and the answers just don't make sense. I see the problem is that people look at the output of these things that are (say) 70% correct and in their mind they fill in the other 30%.
  • dougabug 4y ago
    Sure, but GPT-3 was trained by self-supervised learning on only static text. We see how powerful even just adding captions to text can be with the example of DALLE-2. GATO takes this further by letting the large scale Transformer learn in both simulated and real interactive environments, giving it the kind of grounding that the earlier models lacked.
    • PaulHoule 4y ago
      I will grant that the grounding is important. The worst intellectual trend of the 20th century was the idea that language might give you some insight into behavior (Sapir–Whorf hypothesis, structuralism, post-structuralism, ...) whereas language is really like the evidence left after a crime. For instance, language maximalists see mental models as a fulcrum point for behavior, and they are, but they have nothing to do with language. I have two birds that come to my window. One of them has no idea of what the window is and attacks her own reflection hundreds of times a day. She can afford to do it because her nest is right near the bird feeder and doesn't need to work to eat, in fact it probably seems meaningful to her that another bird is after her nest. This female cardinal flies away if I am in the room where she is banging. There is a rose-breasted grosbeak, on the other hand, that comes to the same window. She doesn't mind if I come close to the window, instead I see her catch the eye of her reflection and then catch my eye. She basically understands the window. Here you have two animals with two different acquired mental models... But no language. What I like about the language-image models is how the image grounds reality outside language, and that's important because the "language instinct" is really a peripheral that attaches to an animal brain. Without the rest of the animal it's useless.
• dalbasal 4y ago
  I agree about the dialogue between current method skeptics and optimists. It's been this way since the start and it's been productive and fun. ...one pick.. I don't think agi pessimists raise the bar out of bad faith. It's just the nature of observing progress. We discover that an ai can do X, while still struggling with Y. What's the alternative, conclude gpt is sentient? The bar must be raised, because the bar is supposed to represent human intelligence... and we don't know how that works either.
• sharikous 4y ago
  And still some properties of humans are innate and you can't "train" on them. So brute force imitation is limited as a method for producing content. An erotic novelist has their human brain and human instincts to guide them in writing their work. An AI learns by examples, or at best on a dataset of works labeled by humans. But it doesn't have a human brain at their disposal to query directly and without interfaces to define what's something erotic like a writer has.
  • humpday69 4y ago
    > An erotic novelist has their human brain and human instincts to guide them in writing their work. An ML agent trained on all the erotic novels written, weighted by critical and popular success would might be quite capable of generating sequels, "original" stories, or even stories bespoke to each reader. Good Will Hunting suggests first-hand experience is irreducible: "You can't tell me what it smells like in the Sistine Chapel." https://youtu.be/oRG2jlQWCsY https://youtu.be/oRG2jlQWCsY To which Westworld counters: "Well if you can't tell, does it matter?" https://youtu.be/kaahx4hMxmw https://youtu.be/kaahx4hMxmw I think the cowboys have it. For the moment though, it's still up to humans to decide how this plays out.
• davesque 4y ago
  I generally agree that AI continues to impress in very specific ways but, to be fair, some of the points you make are debatable. For example, I would argue that the development of GANs and other algos do no necessarily disprove the statement "ML models can't perform creative work." They definitely represent meaningful steps in that direction, but I don't think it's hard to find flaws with generated content. On the other hand, AI definitely has punted the ball over many moved goalposts as with the AlphaFold example.
  • solveit 4y ago
    > I don't think it's hard to find flaws with generated content I do wonder if you were to apply the same level of scrutiny to individual humans, you wouldn't also conclude that most people cannot do creative work.
    • davesque 4y ago
      I was thinking more about things like the weird, blurry, dream-like artifacts that you see in some GAN-generated content. Things that look like work done by someone who was both severely impaired yet somehow still extremely meticulous. Things like that seem characteristically un-human.
      • solveit 4y ago
        Ah I see, I agree that GAN-generated content has inhuman tells. But I don't think that necessarily speaks to the creativeness of the work.
• gitfan86 4y ago
  Tesla FSD is quickly becoming less of a software problem and more of a problem of semantics. If the car drives someone to and from work 30 days in a row without a problem, is it truly FSD? What about 300 days? Where do you draw the line? 1000x safer than the average human? Same thing here will AI. How many conversations with GTP-X need to happen without a stupid response from GTP before we call it real world AI?
  • browningstreet 4y ago
    Do we account for stupid responses from humans in human communication in the targets?
  • tsimionescu 4y ago
    How about first getting to "as safe/performant as a non-drunk, non-sleep-deprived, non-brand-new driver with 0 human intervention" before asking more advanced questions? Tesla FSD is definitely nowhere near that level.
    • gitfan86 4y ago
      Exactly, your definition of True FSD seems to be when it doesn't ever make mistakes that a drunk or inexperienced person makes. Other people's definition of True FSD comes down to safety (Rate of FSD caused deaths vs Rate of Human caused deaths).
• TaupeRanger 4y ago
  And yet, the only thing that really matters out of your entire list is the 1st one: that AI solves problems that actually improve the human condition. And Alpha Fold has not done that at all. It may be very nice for people interested in protein folding, but until it actually helps us find something that we wouldn't have found otherwise, and that discovery leads to (for example) an ACTUAL drug or treatment that helps real patients, AND that drug/treatment is actually BETTER than what is already available by helping people live longer or better lives, AI has done nothing. In effect, AI has STILL done nothing meaningful. One could argue, through the use of predatory algorithms, that the ONLY thing it has done is harm.
  • robitsT6 4y ago
    But there have been quite a few scientific papers that have used discoveries from AlphaFold already. There have been many scientists who have been stuck for years, who are suddenly past their previous bottlenecks. What gives you the impression that it hasn't helped us?
    • TaupeRanger 4y ago
      I am not saying that Alpha Fold won't help scientists publish papers. I am just skeptical (though still hopeful) of it doing anything to improve the human condition by actually making human existence better. Publishing papers can be of neutral or negative utility in that realm.
• jackblemming 4y ago
  >Each time this happens, the AGI pessimists raise the bar (a little) for what constitutes AGI. Why does this need to be repeated in every discussion about AI? It’s tired.
  • jimbokun 4y ago
    Because some people inevitably respond in a way that indicates they’ve never heard it before.
• gcheong 4y ago
  I don’t know if we could sufficiently prepare ourselves for such a world. It would seem almost as if we have to build it first so it could determine the best way to prepare us.
  • jimbokun 4y ago
    Maybe we could train a model to tell us the best way to prepare.
  • gurkendoktor 4y ago
    For one thing, we could try to come up with safety measures that prevent the most basic paperclip maximizer disaster from happening. At this point I almost wish it was still the military that makes these advances in AI, not private companies. Anyone working on a military project has to have some sense that they're working on something dangerous.
• soperj 4y ago
  >- "ML models can't perform creative work" - then came GANs, large language models, DALL-E, and more. I don't think copying other people's style of artwork is considered creative work, otherwise art forgers would be able to actually make a living doing art, since some of them are really phenomenal.
  • freeflight 4y ago
    Arguments like this always make me think of Everything is a Remix [0] or how allegedly the most sincerest form of flattery is imitation. [0] https://youtu.be/nJPERZDfyWc https://youtu.be/nJPERZDfyWc
  • jimbokun 4y ago
    Good artists borrow, great artists steal.
    • soperj 4y ago
      That's a quote coming from someone who stole repeatedly, so of course they said that. Alfred Tennyson had this to say: "That great poets imitate and improve, whereas small ones steal and spoil."
• abeppu 4y ago
  I think a key problem is our understanding of the quality of an ML system is tied to a task. Our mechanism of training is tied to a loss, or some optimization problem. The design, training, and evaluation of these systems is dependent on an externally provided definition of "correct". But this seems structurally different from how we or even less intelligent animals operate. DALL-E may make "better" art than most humans -- but it does so in response to a human-provided prompt, according to a system trained on human produced or selected images, improving on an externally-provided loss. Whereas a human artist, even if mediocre, is directed by their own interests and judges according to their own aesthetics. Even if some of their outputs are sometimes comparable, they're not really engaged in the same activity. Methodologically, how do we create agents that aren't just good at several tasks, but make up their own tasks, "play", develop changing preferences for different activities (I think this is more than just "exploration"), etc? Even a dog sometimes wants to play with a toy, sometimes wants to run and chase, sometimes wants to be warm inside. We don't "score" how well it plays with a toy, but we take its desire to play as a signs of greater intelligence than, e.g. a pet iguana which doesn't seem to have such a desire. Further, how do we create agents that can learn without ever seriously failing? RL systems have many episodes, some of which can end very badly (e.g. your simulated runner falls off the world) and they get to learn from this. We die exactly once, and we don't get to learn from it. Note, learning from others in a social context may be part of it, but non-social animals also can learn to avoid many kinds of serious harm without first experiencing it. I don't mean to overly discount the current methods -- they're achieving amazing results. But I think even an optimist should be open to the possibility / opportunity that perhaps the current techniques will get us 80% of the way there, but that there are still some important tricks to be discovered.
  • phreeza 4y ago
    > Methodologically, how do we create agents that aren't just good at several tasks, but make up their own tasks, "play", develop changing preferences for different activities (I think this is more than just "exploration"), etc? Even a dog sometimes wants to play with a toy, sometimes wants to run and chase, sometimes wants to be warm inside. We don't "score" how well it plays with a toy, but we take its desire to play as a signs of greater intelligence than, e.g. a pet iguana which doesn't seem to have such a desire. This doesn't sound like it would be so hard to do if you have an agent or ensemble of agents that can already do it. What you probably really want is this behavior to somehow emerge from simple ground rules, which is probably a lot harder.
• Barrin92 4y ago
  I don't think many people were making the claims that AI can't solve any scientific problems or can't perform creative work at all. That sounds like a big strawman. Before ML was getting big there were AI systems that created art. What sceptics have actually been saying is that the first step fallacy still applies. Getting 20% to a goal is no indication at all that you're getting 100% to your goal, or as its often put, you don't get to the moon by climbing up trees. For people who work with gradients and local maxima all day that idea seems weirdly absent when it comes to the research itself. In the same sense I don't have the impression that the goalpost of AGI has been moved up, but that it's been moved down. When Minsky et al. started to work on AI more than half a century ago the goal was nothing less than to put a mind into a machine. Today our fridges are 'AI powered', and when a neural net creates an image or some poetry there's much more agency and intent attributed to it than there actually is. I think it was Andrew Ng, a very prominent ML researcher himself who pointed out that concerns about AGI make about as much sense as worrying about an overpopulation on Mars. We make models bigger, we fine tune them and they perform better. I don't think many AGI sceptics would be surprised by that. But I don't think there is any indication that they are moving towards human level intellect at some exponential rate. If DALL-E suddenly started to discuss philosophy with me I'd be concerned, it making a better image of a bear if you throw some more parameters at it is what we'd expect.
  • momojo 4y ago
    Self driving cars come to mind as well. I remember 2015, when my friends would debate the self-driving Trolley problem over lunch. We were worried if society was ready for an owner-less car market; I seriously wondered if I would have to have a license in the future, or if I should keep it just in case.
  • yldedly 4y ago
    The notions that are crucial for distinguishing between intelligence and what large NNs are doing, are generalization and abstraction. I'm impressed with DALL-E's ability to connect words to images and exploit the compositionality of language to model the compositionality of the physical world. Gato seems to be using the same trick for more domains. But that's riding on human-created abstractions, rather than creating abstractions. In terms of practical consequences, that means these systems won't learn new things unless humans learn then first and provide ample training data. But someday we will develop systems that can learn their own abstractions, and teach themselves anything. Aligning those systems is imperative.
• deleted 4y ago
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• Jimmy 4y ago
  >Each time this happens, the AGI pessimists raise the bar (a little) for what constitutes AGI. Let’s say I have a coworker. We write code together, but we also hang out outside of work sometimes, maybe go for a couple rounds of golf, maybe discuss our shared passion for indie rock, he tells me his opinions on current news events or what’s going on with his family, all the ordinary sorts of things that people do. When we get to the point where I have to reasonably wonder if my coworker is a biological human, or an AI masquerading as a human, then we have undoubtedly achieved AGI. Not that we actually have to flood society with an army of cybernetic humans, of course. It’s just that AGI would enable such a thing, in principle.
• pyinstallwoes 4y ago
  Why is language focused bad? Isn’t everything related to consciousness depended upon language?