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I feel like I'm the only one who isn't convinced getting a high score on the ARC eval test means we have AGI. It's mostly about pattern matching (and some of it
by qoez 1y ago
I feel like I'm the only one who isn't convinced getting a high score on the ARC eval test means we have AGI. It's mostly about pattern matching (and some of it ambiguous even for humans what the actual true response aught to be). It's like how in humans there's lots of different 'types' of intelligence, and just overfitting on IQ tests doesn't in my mind convince me a person is actually that smart.
- avmich 1y agoRoughly speaking, the job of a medical doctor is to diagnose the patient - and then, after the diagnosis is made, to apply the healing from the book, corresponding to the diagnosis. The diagnosis is pattern matching (again, roughly). It kinda suggests that a lot of "intelligent" problems are focused on pattern matching, and (relatively straightforward) application of "previous experience". So, pattern matching can bring us a great deal towards AGI.
- AnimalMuppet 1y agoPattern matching is instinct. (Or at least, instinct is a kind of pattern matching. And once you learn the patterns, pattern matching can become almost instinctual). And that's fine, for things that fit the pattern. But a human-level intelligence can also deal with problems for which there is no pattern. (I mean, not always successfully - finding a correct solution to a novel problem is difficult. But it is within the capability of at least some humans.)
- yorwba 1y agoI think the people behind the ARC Prize agree that getting a high score doesn't mean we have AGI. (They already updated the benchmark once to make it harder.) But an AGI should get a similarly high score as humans do. So current models that get very low scores are definitely not AGI, and likely quite far away from it.
- cubefox 1y ago> I think the people behind the ARC Prize agree that getting a high score doesn't mean we have AGI The benchmark was literally called ARC-AGI. Only after OpenAI cracked it, they started backtracking and saying that it doesn't test for true AGI. Which undermines the whole premise of a benchmark.
- whiplash451 1y agoYou're not the only one. ARC-AGI is a laudable effort, but its fundamental premise is indeed debatable: "We argue that human cognition follows strictly the same pattern as human physical capabilities: both emerged as evolutionary solutions to specific problems in specific evironments" (from page 22 of On the Measure of Intelligence) https://arxiv.org/pdf/1911.01547 https://arxiv.org/pdf/1911.01547
- Davidzheng 1y agoBut I believe that because of this "even edge" thing which people call of AI weakenesses being not necessarily same of humans, once we run out of these tests which AI is worse than humans it will actually in effect be very much superhuman. My main evidence for this is leela-zero the Go AI who struggled with ladders and some other aspects of Go play well into the superhuman regime (in go it's easier to see when it's superhuman bc you can have elos and play win-rates etc and there's less room for debates)
- energy123 1y agohttps://en.m.wikipedia.org/wiki/AI_effect https://en.m.wikipedia.org/wiki/AI_effect But on a serious note, I don't think Chollet would disagree. ARC is a necessary but not sufficient condition, and he says that, despite the unfortunate attention-grabbing name choice of the benchmark. I like Chollet's view that we will know that AGI is here when we can't come up with new benchmarks that separate humans from AI.
- loki_ikol 1y agoWell for most, the next steps are probably towards removing the highly deterministic and discrete characteristics of current approaches (we certainly don't think in lock steps). Those have no measures. Even the creative aspect is undermined by those characteristics.
- kubb 1y agoAGI isn't defined anywhere, so it can be anything you want.
- FrustratedMonky 1y agoYes. And a lot of humans also don't pass for having AGI.
- mindcrime 1y agoOh, it's defined in lots of places. The problem is.. it's defined in lots of places!
- oldge 1y agoToday’s llms are fancy autocomplete but lack test time self learning or persistent drive. By contrast, an AGI would require: – A goal-generation mechanism (G) that can propose objectives without external prompts – A utility function (U) and policy π(a│s) enabling action selection and hierarchy formation over extended horizons – Stateful memory (M) + feedback integration to evaluate outcomes, revise plans, and execute real-world interventions autonomously Without G, U, π, and M operating llms remain reactive statistical predictors, not human level intelligence.
- KoolKat23 1y agoI'd say we're not far off. Looking at the human side, it takes a while to actually learn something. If you've recently read something it remains in your "context window". You need to dream about it, to think about, to revisit and repeat until you actually learn it and "update your internal model". We need a mechanism for continuous weight updating. Goal-generation is pretty much covered by your body constantly drip-feeding your brain various hormones "ongoing input prompts".
- onemoresoop 1y ago> I'd say we're not far off. How are we not far off? How can LLMs generate goals and based on what?
- NetRunnerSu 1y agoMinimize prediction errors.
- tsurba 1y agoBut are we close to doing that in real-time on any reasonably large model? I don’t think so.
- NetRunnerSu 1y agoThis is not about reasoning , this is about continuous learning and perpetual learning . https://github.com/dmf-archive/PILF https://github.com/dmf-archive/PILF https://dmf-archive.github.io/docs/posts/beyond-snn-plausible-sparsity/ https://dmf-archive.github.io/docs/posts/beyond-snn-plausibl...
- TheAceOfHearts 1y agoGetting a high score on ARC doesn't mean we have AGI and Chollet has always said as much AFAIK, it's meant to push the AI research space in a positive direction. Being able to solve ARC problems is probably a pre-requisite to AGI. It's a directional push into the fog of war, with the claim being that we should explore that area because we expect it's relevant to building AGI.
- autobodie 1y ago[flagged]
- deleted 1y ago[deleted]
- lostphilosopher 1y agoWe don't really have a true test that means "if we pass this test we have AGI" but we have a variety of tests (like ARC) that we believe any true AGI would be able to pass. It's a "necessary but not sufficient" situation. Also ties directly to the challenge in defining what AGI really means. You see a lot of discussions of "moving the goal posts" around AGI, but as I see it we've never had goal posts, we've just got a bunch of lines we'd expect to cross before reaching them.
- MPSimmons 1y agoI don't think we actually even have a good definition of "This is what AGI is, and here are the stationary goal posts that, when these thresholds are met, then we will have AGI". If you judged human intelligence by our AI standards, then would humans even pass as Natural General Intelligence? Human intelligence tests are constantly changing, being invalidated, and rerolled as well. I maintain that today's modern LLMs would pass sufficiently for AGI and is also very close to passing a Turing Test, if measured in 1950 when the test was proposed.
- fvdessen 1y ago
- ben_w 1y agoYou're not alone in this; I expect us to have not yet enumerated all the things that we ourselves mean by "intelligence". But conversely, not passing this test is a proof of not being as general as a human's intelligence.
- NetRunnerSu 1y agoUnfortunately, we did it. All that is left is to assemble the parts. https://news.ycombinator.com/item?id=44488126 https://news.ycombinator.com/item?id=44488126
- kypro 1y agoI find the "what is intelligence?" discussion a little pointless if I'm honest. It's similar to asking a question like does it mean to be a "good person" and would we know whether an AI or person is really "good"? While understanding why a person or AI is doing what it's doing can be important (perhaps specifically in safety contexts) at the end of the day all that's really going to matter to most people is the outcomes. So if an AI can use what appears to be intelligence to solve general problems and can act in ways that are broadly good for society, whether or not it meets some philosophical definition of "intelligent" or "good" doesn't matter much – at least in most contexts. That said, my own opinion on this is that the truth is likely in between. LLMs today seem extremely good at being glorified auto-completes, and I suspect most (95%+) of what they do is just recalling patterns in their weights. But unlike traditional auto-completes they do seem to have some ability to reason and solve truly novel problems. As it stands I'd argue that ability is fairly poor, but this might only represent 1-2% of what we use intelligence for. If I were to guess why this is I suspect it's not that LLM architecture today is completely wrong, but that the way LLMs are trained means that in general knowledge recall is rewarded more than reasoning. This is similar to the trade-off we humans have with education – do you prioritise the acquisition of knowledge or critical thinking? Maybe believe critical thinking is more important and should be prioritised more, but I suspect for the vast majority of tasks we're interested in solving knowledge storage and recall is actually more important.
- ben_w 1y ago
- OtomotO 1y agoYou're not alone in this, no. My definition of AGI is the one I was brought up with, not an ever moving goal post (to the "easier" side). And no, I also don't buy that we are just stochastic parrots. But whatever. I've seen many hypes and if I don't die and the world doesn't go to shit, I'll see a few more in the next couple of decades
- deleted 1y ago[deleted]
- NetRunnerSu 1y agoTo pass Arc, you need a living model with sentient abilities, not the dead frog now. https://news.ycombinator.com/item?id=44488126 https://news.ycombinator.com/item?id=44488126
- nxobject 1y agoI understand Chollet is transparent that the "branding" of the ARC-AGI-n suites is meant to be suggestive of its purpose, than substantial. However, it does rub me the wrong way - as someone who's cynical of how branding can enable breathless AI hype by bad journalism. A hypothetical comparison would be labelling SHRDLU's (1968) performance on Block World planning tasks as "ARC-AGI-(-1)".[0] A less loaded name like (bad strawman option) "ARC-VeryToughSymbolicReasoning" should capture how the ARC-AGI-n suite is genuinely and intrinsically very hard for current AIs, and what progress satisfactory performance on the benchmark suite would represent. Which Chollet has done, and has grounded him throughout! [1] [0] https://en.wikipedia.org/wiki/SHRDLU https://en.wikipedia.org/wiki/SHRDLU [1] https://arxiv.org/abs/1911.01547 https://arxiv.org/abs/1911.01547
- heymijo 1y agoI get what you're saying about perception being reality and that ARC-AGI suggests beating it means AGI has been achieved. In practice when I have seen ARC brought up, it has more nuance than any of the other benchmarks. Unlike, Humanity's Last Exam, which is the most egregious example I have seen in naming and when it is referenced in terms of an LLMs capability.
- maaaaattttt 1y agoI've said this somewhere else, but we have the perfect test for AGI in the form of any open world game. Give the instructions to the AGI that it should finish the game and how to control it. Give the frames as input and wait. When I think of the latest Zelda games and especially how the Shrine chanllenges are desgined they especially feel like the perfect environement for an AGI test.
- Lerc 1y agoAnd if someone makes a machine that does all that and another person says "That's not really AGI because xyz" What then? The difficulty in coming up with a test for AGI is coming up with something that people will accept a passing grade as AGI. In many respects I feel like all of the claims that models don't really understand or have internal representation or whatever tend to lean on nebulous or circular definitions of the properties in question. Trying to pin the arguments down usually end up with dualism and/or religion. Doing what Chollet has done is infinitely better, if a person can easily do something and a model cannot then there is clearly something significant missing It doesn't matter what the property is or what it is called. Such tests might even help us see what those properties are. Anyone who wants to claim the fundamental inability of these models should be able to provide a task that it is clearly possible to tell when it has been succeeded, and to show that humans can do it (if that's the bar we are claiming can't be met). If they are right, then no future model should be able to solve that class of problems.
- maaaaattttt 1y agoGiven your premise (which I agree with) I think the issue in general comes from the lack of a good, broadly accepted definition of what AGI is. My initial comment originates from the fact that in my internal definition, an AGI would have a de facto understanding of the physics of "our world". Or better, could infer them by trial and error. But, indeed, it doesn't have to be the case. (The other advantage of the Zelda games is that they introduce new abilities that don't exist in our world, and for which most children -I've seen- understand the mechanisms and how they could be applied to solve a problem quite naturaly even they've never had that ability before).
- davidclark 1y agoIn the video, François Chollet, creator of the ARC benchmarks, says that beating ARC does not equate to AGI. He specifically says they will be able to be beaten without AGI.
- cubefox 1y agoHe only says this because otherwise he would have to say that - OpenAI's o3 counts as "AGI" when it did unexpectedly beat the ARC-AGI benchmark or - Explicitly admit that he was wrong when assuming that ARC-AGI would test for AGI
- sweezyjeezy 1y agoFWIW the original ARC was published in 2019, just after GPT-2 but a while before GPT-3. I work in the field, I think that discussing AGI seriously is actually kind of a recent thing (I'm not sure I ever heard the term 'AGI' until a few years ago). I'm not saying I know he didn't feel that, but he doesn't talk in such terms in the original paper.
- cubefox 1y ago> We argue that ARC can be used to measure a human-like form of general fluid intelligence and that it enables fair general intelligence comparisons between AI systems and humans. https://arxiv.org/abs/1911.01547 https://arxiv.org/abs/1911.01547
- davidclark 1y ago> It is important to note that ARC is a work in progress, not a definitive solution; it does not fit all of the requirements listed in II.3.2, and it features a number of key weaknesses… Page 53 > The study of general artificial intelligence is a field still in its infancy, and we do not wish to convey the impression that we have provided a definitive solution to the problem of characterizing and measuring the intelligence held by an AI system. Page 56
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- aaron695 1y ago[dead]
- cainxinth 1y ago> It's mostly about pattern matching... For all we know, human intelligence is just an emergent property of really good pattern matching.
- cttet 1y agoThe point is not that having a high score -> AGI, their ideas are more of having a low score -> we don't have AGI yet.
- CamperBob2 1y agoIf you can write code to solve ARC by "overfitting," then give it a shot! There's prize money to be won, as long as your model does a good job on the hidden test set. Zuckerberg is said to be throwing around 8-figure signing bonuses for talent like that. But then, I guess it wouldn't be "overfitting" after all, would it?
- gonzobonzo 1y agoI agree with you but I'll go a step further - these benchmarks are a good example of how far we are from AGI. A good base test would be to give a manager a mixed team of remote workers, half being human and half being AI, and seeing if the manager or any of the coworkers would be able to tell the difference. We wouldn't be able to say that AI that passed that test would necessarily be AGI, since we would have to test it in other situations. But we could say that AI that couldn't pass that test wouldn't qualify, since it wouldn't be able to successfully accomplish some tasks that humans are able to. But of course, current AI is nowhere near that level yet. We're left with benchmarks, because we all know how far away we are from actual AGI.
- criddell 1y agoThe AGI test I think makes sense is to put it in a robot body and let it navigate the world. Can I take the robot to my back yard and have it weed my vegetable garden? Can I show it how to fold my laundry? Can I take it to the grocery store and tell it "go pick up 4 yellow bananas and two avocados that will be ready to eat in the next day or two, and then meet me in dairy"? Can I ask it to dice an onion for me during meal prep? These are all things my kids would do when they were pretty young.
- gonzobonzo 1y agoI agree, I think of that as the next level beyond the digital assistant test - a physical assistant test. Once there are sufficiently capable robots, hook one up to the AI. Tell it to mow your lawn, drive your car to the mechanic and have the mechanic to get checked, box up an item, take it to the post office, and have it shiped, pick up your dry cleaning, buy ingredients from a grocery store, cook dinner, etc. Basic tasks an low-skilled worker would do as someone's assistant.
- bumby 1y agoI think the next harder level in AGI testing would be “convince my kids to weed the garden and fold the laundry” :-)
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- SubiculumCode 1y ago[1]https://app.rescript.info/public/share/W_T7E1OC2Wj49ccqlIOOztg2MJWaaVbovTeyxcFEQdU https://app.rescript.info/public/share/W_T7E1OC2Wj49ccqlIOOz... Perhaps it's because the representations are fractured. The link above is to the transcript of an episode of Machine Learning Street Talk with Kenneth O. Stanleyabout The Fractured Entangled Representation Hypothesis[1]
- crazylogger 1y agoI think next year's AI benchmarks are going to be like this project: https://www.anthropic.com/research/project-vend-1 https://www.anthropic.com/research/project-vend-1 Give the AI tools and let it do real stuff in the world: "FounderBench": Ask the AI to build a successful business, whatever that business may be - the AI decides. Maybe try to get funded by YC - hiring a human presenter for Demo Day is allowed. They will be graded on profit / loss, and valuation. Testing plain LLM on whiteboard-style question is meaningless now. Going forward, it will all be multi-agent systems with computer use, long-term memory & goals, and delegation.
- Miraltar 1y agoThis sounds like a terrible idea to me, you're training intelligent computer to aim for power. It's fine as long as they're bad but if they get good then we have a problem
- mindcrime 1y ago> I feel like I'm the only one who isn't convinced getting a high score on the ARC eval test means we have AGI. Wait, what? Approximately nobody is claiming that "getting a high score on the ARC eval test means we have AGI". It's a useful eval for measuring progress along the way, but I don't think anybody considers it the final word.
- andoando 1y agoWho says intelligence is anything more than "pattern matching"? Everything is patterns
- sva_ 1y agoIt is a necessary condition, but not a sufficient one.
- tippytippytango 1y agoHe’s playing the game. You have to say AGI is your goal to get attention. It’s just like the YouTube thumbnail game. You can hate it, but you still have to play if you want people to pay attention.
- cess11 1y agoMuch like other forms of psychometry, especially related to so called intelligence, it's mainly about stratification and discrimination for ideological purposes.
- yunwal 1y agoThe author of the test agrees with you.
- dfilppi 1y ago[dead]
- jxjnskkzxxhx 1y ago> I feel like I'm the only one who isn't convinced getting a high score on the ARC eval test means we have AGI Francois explicitly says that's not how ARC is supposed to be interpreted.