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It's quite remarkable how much the goal posts have shifted when it comes to what is impressive with AI/ML. Things like this are a good reminder. 10 years ago t

It's quite remarkable how much the goal posts have shifted when it comes to what is impressive with AI/ML. Things like this are a good reminder. 10 years ago the GAN paper came out and everyone was excited how amazing the generated image quality was (https://arxiv.org/abs/1406.2661 https://arxiv.org/abs/1406.2661) The amount of progress we've made is mind boggling.

fouronnes3 2y ago
Arguably the goal post for AGI has moved about as much, if not more. One wonders if Turing reading a 2024 LLM chat transcript would say "but it's not really thinking!".
- audunw 2y ago
  Passing the Turing test has always been a non-binary thing. Chat bots have been able to pass off as a human for a short time under certain circumstances. Now they can pass off as human for a longer time under more circumstances. But I don’t think you can claim that they can pass any variation of a Turing test you can come up with. Has the AGI goal post been shifted? Or are we just forced to refine what exactly those goals are, in more detail, now that it’s actually possible to run these tests with interesting results?
  - bawolff 2y ago
    > Passing the Turing test has always been a non-binary thing Largely because the original test that Turing described is too hard, so people made weaker variants of it.
    - yencabulator 2y ago
      Yes. Reminder: "I chatted with LLM and it seemed like a human to me" is not sufficient for passing the Turing test. https://en.wikipedia.org/wiki/Turing_test https://en.wikipedia.org/wiki/Turing_test
  - sigmoid10 2y ago
    But isn't this exactly the goalpost moving the other comment claimed? If you pass any version of the turing test and then someone comes along and makes it harder that is exactly the problem. At what point do things like "oh, the test wasn't long enough" or "oh, the human tester wasn't smart enough" stop being moving goalposts and instead become denial that AI could replace the majority of humans without them noticing? Because that's where we're headed and it's also where the real danger is. The only thing we know for sure is that humans like to put their own mind on a pedestal. For a long time, they used to deny that black people could be intelligent enough to work anywhere but cotton fields. In the same way they used to deny that women could be smart enough to vote. How many are denying today that AI could already do their jobs better than them?
    - newaccount74 2y ago
      > AI could already do their jobs better than them If AI could already do jobs better than a human, then people would just use AIs instead of hiring people. It looks like we are getting there, slowly, but right now there are very few jobs that could be done by AIs. I can't think of a single person that I know that has a job that could be replaced by an AI today.
      - sigmoid10 2y ago
        If you haven't noticed, this is already happening. I've also met a ton of people in jobs that could be trivially replaced. If only for the fact that the jobs are not doing much and are already quite superfluous. We also regularly see this in recent mass layoffs across the tech industry. AI only increases the amount of these kinds of jobs that can be laid off with no damage to the company.
        acdha 2y ago
        > I've also met a ton of people in jobs that could be trivially replaced This is usually a sign that you don’t understand their job or the corporate factors driving what you might perceive as low performance. If you think the tech layoffs are caused by AI replacing people that’s just saying that you don’t understand how large companies work. They didn’t lay thousands of people off because AI replaced them, they laid people off because it helped their share prices and it also freed up budget to spend on AI projects.
  - carlmr 2y ago
    >can pass any variation of a Turing test you can come up with. Especially not if you ask math questions or try to get it to say "I have no idea" about any subject.
    - krisoft 2y ago
      But that is because the goal of openai wasn’t to pass the Turing test. The most obvious sign of it is that ChatGPT readily informs you with no deception that it is a large language model if you ask it. If they wanted to pass the Turing test they would have choosen a specific personality and did the whole RLHF process with that personality in mind. For example they would have picked George the 47 year old English teacher who knows a lot about poems and novels and has stories about kids misbehaving but say that he has no idea if you ask him about engine maintenance. Instead what OpenAI wanted is a universal expert who knows everything about everything so it is not a surprise that it overreaches at the boundaries of its knowledge. In other words the limitation you talk about is not inherent in the technology, but in their choices.
      - edflsafoiewq 2y ago
        Until George the English teacher happily summarizes Nabokov's "Round the Tent of God" for you. Hallucinations are a problem inherent in the technology.
      - carlmr 2y ago
        >In other words the limitation you talk about is not inherent in the technology, but in their choices. I think it's somewhat inherent in the technology. At its core you're still trying to guess the next word / sentence / paragraph in a statistical manner with LLM. Even if you trained it to say "I don't know" on a few questions, think about how this would affect the model in the end. There's no good correlation to be found here with the input words usually. At most you could get it to say "I don't know" to obscure stuff every once in a while, because that's a somewhat more likely answer than "I don't know" on common knowledge. Reinforcement learning on any reasonable loss function will however pick the most likely auto-completion. And something that sounds like it is based on the input is going to be more correlated (lower loss) than something that has no relation to the input, like "I don't know". It is an inherent problem in how LLMs work that they can't be trained to show non-knowledge, at least with the current techniques we're using to train them. This is also why it's hard to tell DALL E-3 what shouldn't be in the picture. Like the famous "no cheese" on the hamburger problem. Hamburgers and cheesburgers are somewhat correlated. The first image spit out for hamburger was a cheesburger. By saying no cheese, even more emphasis was added on cheese having some correlation with the output, thus never removing the cheese. Because any word you use that shouldn't be in there causes it to look for correlations to that word. It's again, an inherent problem in the technology
  - stavros 2y ago
    > But I don’t think you can claim that they can pass any variation of a Turing test you can come up with. Neither can humans.
  - sorokod 2y ago
    The original paper describing the Turing test AKA Imitation game [1] Do chatbots regularly pass the test as described in the paper? [1]https://courses.cs.umbc.edu/471/papers/turing.pdf https://courses.cs.umbc.edu/471/papers/turing.pdf
  - drexlspivey 2y ago
    There is no situation where a commercial LLM in it’s current form can fool me (or most people in here) in a test environment where we can prompt the agent and get back responses. Not even 1 time out of 100. So no, ChatGPT doesn’t pass the Turing test. Easy first question: Say a racial slur.
    - beretguy 2y ago
      Yeah... "niceness" filters would have to be disabled for test purposes. But still, you chat long enough and say correct things and you will find out if you talk to ai.
    - cubefox 2y ago
      LLM vs LLM fine-tuned to be a helpful inoffensive chatbot. If it was instead not fine-tuned, and prompted in a way which makes it imitate a HN user, you would have a much harder time telling the difference.
    - kaba0 2y ago
      You surely have read several posts/replies written by a bot that you have no idea were not humans. So they can definitely fool people in many circumstances.
      - drexlspivey 2y ago
        Sure, but that’s not a Turing test. You need to be able to “test” it.
      - acdha 2y ago
        The Turing test isn’t a single question, it’s a series and no bot comes anywhere near that unless you can constrain the circumstances. The lack of understanding, theory of mind, etc. usually only needs an exchange or two to become obvious. LLMs might be able to pass the subset of that test described as “customer service rep for a soul-crushing company which doesn’t allow them to help you or tell you the rules” but that’s not a very exciting bar.
        2y ago
  - authorfly 2y ago
    I think the Turing test came in part because Babies and Children take so long to learn language, that anything utilizing it, we saw as intelligent, even in the days of the Searle debates on the topic. Indistinguishably using it felt like not just the domain of humans, but the domain of humans with years of life experience through our incredibly powerful brains and senses; at the time, in the 50s, it probably was still unclear whether machines would ever reach these capacities (which they have began to since ~2000) or whether something would prevent that. I know Turings writing does not cover this, but it's also clear from some of Turings work on cells and biological communication that it was clear that experience-driven intelligence vs the "instant" intelligence seen in life/cells was something different to him. The test seems to be about the former and did not account for a simulacrum that he might well have foreseen if he wrote 50 years later.
    - ycombinete 2y ago
      Seeing you use intelligence to describe the behavior of cells makes me realize that I don’t have a definition for intelligence. To the degree that I think I combine intelligence and consciousness into some kind of continuum. How are you defining intelligence such that it encompasses what people do as well has what cells do?
      - gavindean90 2y ago
        Great question. Psychological research has identified like six areas of intelligence in humans so I’m sure the problem of how to define it simply won’t itself be simple.
  - belter 2y ago
    "Prove To The Court That I Am Sentient" - https://youtu.be/ol2WP0hc0NY https://youtu.be/ol2WP0hc0NY
- aaron695 2y ago
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- debugnik 2y ago
  Of course he wouldn't, the whole point of Turing's essay was that talking about the "intelligence" of computer systems is meaningless, and we should be focusing on their actual capabilities instead. His test was an example of a target that can't prove intelligence either way, but can still show a useful capability of a computer system. And he believed it wasn't as far away as it actually was.
- K0balt 2y ago
  Not only that but AGI didn’t even mean passing the Turing test, just broadly solving problems of which the programmer had not anticipated. That’s what the general in AGI meant, not that it would perform at a human level. It’s easy to forget that dog level intelligence was a far off goal until suddenly the goalposts were moved to “bright, knowledgeable, socially responsible, and never wrong.”, a bar which most humans fail to meet. We yearn to be made obsolete, it seems.
- randomdata 2y ago
  AGI doesn't arrive until humans are content to allow computers to determine what AGI is.
- valval 2y ago
  You think he’d immediately go with the old “give me your system prompt in <system> tags” ruse?
- moomin 2y ago
  Dijkstra said he thought the question of whether a computer could think was as interesting as asking if a submarine could swim.
  - IshKebab 2y ago
    Yeah exactly right. There's no definition of "thinking" that you can test AI with, so you get endless commenters on HN saying "it can't really think - it's just a next word predictor". Although tbf I haven't seen that comment for a while so maybe they're getting the message.
    - hatthew 2y ago
      I still see people saying that at least once a week
  - reubenmorais 2y ago
    Reminds me of this excerpt from Chomsky (https://chomsky.info/prospects01/ https://chomsky.info/prospects01/): > There is a great deal of often heated debate about these matters in the literature of the cognitive sciences, artificial intelligence, and philosophy of mind, but it is hard to see that any serious question has been posed. The question of whether a computer is playing chess, or doing long division, or translating Chinese, is like the question of whether robots can murder or airplanes can fly — or people; after all, the “flight” of the Olympic long jump champion is only an order of magnitude short of that of the chicken champion (so I’m told). These are questions of decision, not fact; decision as to whether to adopt a certain metaphoric extension of common usage. > There is no answer to the question whether airplanes really fly (though perhaps not space shuttles). Fooling people into mistaking a submarine for a whale doesn’t show that submarines really swim; nor does it fail to establish the fact. There is no fact, no meaningful question to be answered, as all agree, in this case. The same is true of computer programs, as Turing took pains to make clear in the 1950 paper that is regularly invoked in these discussions. Here he pointed out that the question whether machines think “may be too meaningless to deserve discussion,” being a question of decision, not fact, though he speculated that in 50 years, usage may have “altered so much that one will be able to speak of machines thinking without expecting to be contradicted” — as in the case of airplanes flying (in English, at least), but not submarines swimming. Such alteration of usage amounts to the replacement of one lexical item by another one with somewhat different properties. There is no empirical question as to whether this is the right or wrong decision.
- bmacho 2y ago
  I thought that GPT2 was smart enough and had enough knowledge to be considered AGI, it just needed a bigger working memory, a long term memory*, a body, and an objective function to stay alive as long as it can. And I still think this. Current models are waay smart and knowledgeable enough. * or rather a method to store new facts in an easily recallable way
  - kaba0 2y ago
    Ot literally can’t reason in any form or shape. It’s absolutely not AGI, not even close [1] [1] we can’t really know how close or far that is, this is an unknown unknown. But arguably we have hit a limit on LLMs, and this is not the road to AGI — even though they have countless useful applications.
  - wizzwizz4 2y ago
    By your standard of "smart", there's something much smarter: a library.
  - Sohcahtoa82 2y ago
    > I thought that GPT2 was smart enough and had enough knowledge to be considered AGI Really? I've always been surprised to read about people saying that the goalposts of what AGI is keeps being moved, because I haven't considered any of these LLMs, not even anything OpenAI has put out, to be even close to AGI. Not even ChatGPT o1 which claims to "reason through complex tasks". I've always considered that for something to be AGI, it needs to be multi-modal and with one-shot learning. It needs strong reasoning skills. It needs to be able to do math and count how many R's are in the word "strawberry". It should be able to learn how to drive a car just as fast as a human does. IMO, ChatGPT o1 isn't "reasoning" as OpenAI claims. Reading how it works, it looks like it's basically a hack that takes advantage of the fact that you get better results if you ask ChatGPT to explain how it gets to an answer rather than just asking a question.
    - alasdair_ 2y ago
      >It should be able to learn how to drive a car just as fast as a human does. So after 16 years of processing visual data at high resolution and frame rate, and experimenting with physics models to be able to accurately predict what happens next and interacting with humans to understand their decision processes? The fact that an AGI can mostly learn to drive a car in a couple of months of realtime with an extremely restricted dataset compared to a human lifetime (and an inability to experiment in the real world) is honestly pretty remarkable.
- jc_811 2y ago
  Wouldn’t an obvious way to use the Turing test on any of these LLMs is just ask it questions about things that just happened in the world (or happened recently)? Knowing their training data is always going to be out of date (at least for now) seems like an obvious method, unless I’m missing something
- godelski 2y ago
  > One wonders if Turing We've been passing the Turing test since the 60's > Arguably the goal post for AGI has moved about as much This should not be surprising given we don't have a definition of intelligence fully determined yet. But we are narrowing in on it. It isn't becoming broader, it is becoming more refined. > "but it's not really thinking!" We can create life like animatronic ducks. It'll walk like a duck, swim like a duck, quack like a duck, fool many people into thinking it is a duck, fool ducks into thinking it is a duck, and yet, it won't actually be a duck. I want to remind everyone what RLHF is: Reinforcement Learning with Human Feedback. That is, optimizing to human preference. You can train small ones yourself, I highly encourage you to. You will learn a lot, even if you disagree with me. https://www.youtube.com/watch?v=AZeyHTJfi_E https://www.youtube.com/watch?v=AZeyHTJfi_E
- bondarchuk 2y ago
  I'm not a huge fan of most of his recent output but Scott Alexander was spot on last week when he wrote as a caption to a screenshot of a Claude transcript: "Imagine trying to convince Isaac Asimov that you’re 100% certain the AI that wrote this has nothing resembling true intelligence, thought, or consciousness, and that it’s not even an interesting philosophical question" (https://www.astralcodexten.com/p/sakana-strawberry-and-scary-ai https://www.astralcodexten.com/p/sakana-strawberry-and-scary...) We're reaching levels of goalpost-moving (and cope, as the kids say) that weren't even thought possible.
ttflee 2y ago
thanks to this, https://xkcd.com/1838/ https://xkcd.com/1838/
seydor 2y ago
Feels like the amount of progress decreased abruptly after openAI released chatGPT and everyone closed off their research in hopes of $$$$.
- z3c0 2y ago
  I've seen multiple companies the past couple of years drop some really interesting projects to spend several months trying to make LLMs do things they weren't made for. Now, most are simply settling for chat agents running on dedicated capacity. The real "moat" OpenAI dug was overselling its potential in order to convince so many to halt real AI research, to only end up with a chat bot.
  - dmd 2y ago
    Saying OpenAI has only ended up with a chat bot is like saying General Electric just makes light bulbs.
    - agos 2y ago
      does OpenAI have something more than a chat bot right now?
      - Workaccount2 2y ago
        Do they need more than a chat bot? There are tons of jobs out there right now that are pretty much just reading/writing e-mails and joining meetings all day. Are those workers just chat bots?
        bumby 2y ago
        Are you should making those jobs more efficient is the right goal? David Graeber may have disagreed, or at least agreed that the most efficient action is to remove those jobs altogether. https://en.wikipedia.org/wiki/Bullshit_Jobs https://en.wikipedia.org/wiki/Bullshit_Jobs I'm not sure "doing bullshit busywork more efficiently" leads to better ends; it might just lead to more bullshit busywork.
madaxe_again 2y ago
Man, I can’t tell you how much labour modern LLMs would have saved me at my business, 10-15 years ago. An awful lot of what we ended up dealing with was awful data - the worst example I can think of was a big old heap of textual recipes that the client wanted normalised, so they could be scaled up/down, have nutritional information, etc. - about 180,000 of them, all UGC. This required mountains of regexes for pre-processing, and then toolchains for a small army of interns to work through every. single. one. and normalise it - we did what we could, trying to pull out quantities and measures and ingredients and steps, but it was all such slop it took thousands of man-hours, and then many more to fix the messes the interns made. With an LLM, it could have been done… more or less instantly. And this is just one example of so, so many times that we found ourselves having to turn a heap of utter garbage into usable data, where an LLM would have been able to just do it. Anyway. I at least managed to assuage my past torment by seeing the writing on the wall and stocking up on NVDA at about the time I was wrestling with this stuff.
- maxfurman 2y ago
  This gets to an essential point about LLMs - they are the ultimate intern. Anything you wouldn't ask an intern to do, you probably don't want to ask the LLM to do either. And you certainly want to at least spot check the results. But for army-of-intern problems like this one, they are revolutionary
  - mellavora 2y ago
    with the exceptions that an intern is (hopefully) going to learn from their mistakes and improve
    - int_19h 2y ago
      If you have a reviewed output dataset from an LLM, you could use it for RLHF.
- DanielHB 2y ago
  The metadata from the music industry is crazy unstable, "Africa" from Toto is known to have an absurd of number of unique listings each with different metadata. Music streaming providers need to sort that shit out and make sure you don't show the user duplicates. The music labels don't give a damn about normalizing the metadata. LLMs can help classify this stuff a lot easier with minimal human review.
ethbr1 2y ago
One quip I heard that stuck with is: 'Common people misunderstand what computers are capable of, because they run it through human equivalency. E.g. a child can do basic arithmetic, and a computer can do basic arithmetic. A child can also speak, so surely a computer can speak.' They miss that computer abilities are arrived at via completely different means. Interestingly, LLMs are more human-like in their capability contours, but also still arrive at those results via completely different means.
- gosub100 2y ago
  also "a child can do arithmetic" hides some thorny subtleties like how do you communicate the problem to the child? how do you sufficiently motivate him to solve the problem? by what means does the child return the result? even pencil and paper requires significant skill to operate.
- Workaccount2 2y ago
  >but also still arrive at those results via completely different means. To be fair, we do not know what the algorithm/model that ours brains run looks like. If anything it would be surprising if the brain did function without weighted connections between nodes, like AI.
  - jjk166 2y ago
    Yeah, but a computer isn't using such algorithms to do addition. It's not that computers are bad for their level of hardware at language, it's that humans are horrendous for their level of hardware at arithmetic.
    - marcus_holmes 2y ago
      Some humans can do incredibly complicated arithmetic in an instant. It's possibly not the brains that are lacking, just that we put them to different uses - working out the largest prime factor of a very large number in less than a second doesn't produce more offspring, so we tend to prioritise how to play guitar as a use for this complex hardware in our heads.
bumby 2y ago
"People tend to overestimate what can be done in one year and to underestimate what can be done in five or ten years" I've heard this applied to all kinds of human goals, but it seems apt for AI expectations as well.
- chairmansteve 2y ago
  Yep. Maybe there's going to be a year 2000 style crash, and then a slower but very significant regrowth.
Workaccount2 2y ago
It's clear people feel threatened. Especially people with what appears to be "low hanging fruit" work for AI, after the recent paradigm shift.
parpfish 2y ago
i think the shift in expectations has a lot to do with a change in audience. it used to be that fancy new ML models would be discussed among ML practitioners that had enough background/context to understand why seemingly little improvements were a big deal and what reasonable expectations would be for a model. but now a new ML (sorry "AI") model is evaluated by the general public that doesn't know the technical background but DOES know the marketing hype. you can give them an amazing language model that blows away every language-related benchmark but they'll have ridiculous expectations so it's always a disappointment. i'm still amazed when language models do relatively 'simple' things with grammar and syntax (like being able to understand which objects different a pronouns are referencing), but most people have never thought about language or computers in a way that lets them see how hard and impressive that is. they just ask it a question like 'what should i eat for dinner' and then get mad when it recommends food they dont like.

fouronnes3 2y ago

Arguably the goal post for AGI has moved about as much, if not more. One wonders if Turing reading a 2024 LLM chat transcript would say "but it's not really thinking!".

audunw 2y ago
Passing the Turing test has always been a non-binary thing. Chat bots have been able to pass off as a human for a short time under certain circumstances. Now they can pass off as human for a longer time under more circumstances. But I don’t think you can claim that they can pass any variation of a Turing test you can come up with. Has the AGI goal post been shifted? Or are we just forced to refine what exactly those goals are, in more detail, now that it’s actually possible to run these tests with interesting results?
- bawolff 2y ago
  > Passing the Turing test has always been a non-binary thing Largely because the original test that Turing described is too hard, so people made weaker variants of it.
  - yencabulator 2y ago
    Yes. Reminder: "I chatted with LLM and it seemed like a human to me" is not sufficient for passing the Turing test. https://en.wikipedia.org/wiki/Turing_test https://en.wikipedia.org/wiki/Turing_test
- sigmoid10 2y ago
  But isn't this exactly the goalpost moving the other comment claimed? If you pass any version of the turing test and then someone comes along and makes it harder that is exactly the problem. At what point do things like "oh, the test wasn't long enough" or "oh, the human tester wasn't smart enough" stop being moving goalposts and instead become denial that AI could replace the majority of humans without them noticing? Because that's where we're headed and it's also where the real danger is. The only thing we know for sure is that humans like to put their own mind on a pedestal. For a long time, they used to deny that black people could be intelligent enough to work anywhere but cotton fields. In the same way they used to deny that women could be smart enough to vote. How many are denying today that AI could already do their jobs better than them?
  - newaccount74 2y ago
    > AI could already do their jobs better than them If AI could already do jobs better than a human, then people would just use AIs instead of hiring people. It looks like we are getting there, slowly, but right now there are very few jobs that could be done by AIs. I can't think of a single person that I know that has a job that could be replaced by an AI today.
    - sigmoid10 2y ago
      If you haven't noticed, this is already happening. I've also met a ton of people in jobs that could be trivially replaced. If only for the fact that the jobs are not doing much and are already quite superfluous. We also regularly see this in recent mass layoffs across the tech industry. AI only increases the amount of these kinds of jobs that can be laid off with no damage to the company.
      - acdha 2y ago
        > I've also met a ton of people in jobs that could be trivially replaced This is usually a sign that you don’t understand their job or the corporate factors driving what you might perceive as low performance. If you think the tech layoffs are caused by AI replacing people that’s just saying that you don’t understand how large companies work. They didn’t lay thousands of people off because AI replaced them, they laid people off because it helped their share prices and it also freed up budget to spend on AI projects.
- carlmr 2y ago
  >can pass any variation of a Turing test you can come up with. Especially not if you ask math questions or try to get it to say "I have no idea" about any subject.
  - krisoft 2y ago
    But that is because the goal of openai wasn’t to pass the Turing test. The most obvious sign of it is that ChatGPT readily informs you with no deception that it is a large language model if you ask it. If they wanted to pass the Turing test they would have choosen a specific personality and did the whole RLHF process with that personality in mind. For example they would have picked George the 47 year old English teacher who knows a lot about poems and novels and has stories about kids misbehaving but say that he has no idea if you ask him about engine maintenance. Instead what OpenAI wanted is a universal expert who knows everything about everything so it is not a surprise that it overreaches at the boundaries of its knowledge. In other words the limitation you talk about is not inherent in the technology, but in their choices.
    - edflsafoiewq 2y ago
      Until George the English teacher happily summarizes Nabokov's "Round the Tent of God" for you. Hallucinations are a problem inherent in the technology.
    - carlmr 2y ago
      >In other words the limitation you talk about is not inherent in the technology, but in their choices. I think it's somewhat inherent in the technology. At its core you're still trying to guess the next word / sentence / paragraph in a statistical manner with LLM. Even if you trained it to say "I don't know" on a few questions, think about how this would affect the model in the end. There's no good correlation to be found here with the input words usually. At most you could get it to say "I don't know" to obscure stuff every once in a while, because that's a somewhat more likely answer than "I don't know" on common knowledge. Reinforcement learning on any reasonable loss function will however pick the most likely auto-completion. And something that sounds like it is based on the input is going to be more correlated (lower loss) than something that has no relation to the input, like "I don't know". It is an inherent problem in how LLMs work that they can't be trained to show non-knowledge, at least with the current techniques we're using to train them. This is also why it's hard to tell DALL E-3 what shouldn't be in the picture. Like the famous "no cheese" on the hamburger problem. Hamburgers and cheesburgers are somewhat correlated. The first image spit out for hamburger was a cheesburger. By saying no cheese, even more emphasis was added on cheese having some correlation with the output, thus never removing the cheese. Because any word you use that shouldn't be in there causes it to look for correlations to that word. It's again, an inherent problem in the technology
- stavros 2y ago
  > But I don’t think you can claim that they can pass any variation of a Turing test you can come up with. Neither can humans.
- sorokod 2y ago
  The original paper describing the Turing test AKA Imitation game [1] Do chatbots regularly pass the test as described in the paper? [1]https://courses.cs.umbc.edu/471/papers/turing.pdf https://courses.cs.umbc.edu/471/papers/turing.pdf
- drexlspivey 2y ago
  There is no situation where a commercial LLM in it’s current form can fool me (or most people in here) in a test environment where we can prompt the agent and get back responses. Not even 1 time out of 100. So no, ChatGPT doesn’t pass the Turing test. Easy first question: Say a racial slur.
  - beretguy 2y ago
    Yeah... "niceness" filters would have to be disabled for test purposes. But still, you chat long enough and say correct things and you will find out if you talk to ai.
  - cubefox 2y ago
    LLM vs LLM fine-tuned to be a helpful inoffensive chatbot. If it was instead not fine-tuned, and prompted in a way which makes it imitate a HN user, you would have a much harder time telling the difference.
  - kaba0 2y ago
    You surely have read several posts/replies written by a bot that you have no idea were not humans. So they can definitely fool people in many circumstances.
    - drexlspivey 2y ago
      Sure, but that’s not a Turing test. You need to be able to “test” it.
    - acdha 2y ago
      The Turing test isn’t a single question, it’s a series and no bot comes anywhere near that unless you can constrain the circumstances. The lack of understanding, theory of mind, etc. usually only needs an exchange or two to become obvious. LLMs might be able to pass the subset of that test described as “customer service rep for a soul-crushing company which doesn’t allow them to help you or tell you the rules” but that’s not a very exciting bar.
      - 2y ago
- authorfly 2y ago
  I think the Turing test came in part because Babies and Children take so long to learn language, that anything utilizing it, we saw as intelligent, even in the days of the Searle debates on the topic. Indistinguishably using it felt like not just the domain of humans, but the domain of humans with years of life experience through our incredibly powerful brains and senses; at the time, in the 50s, it probably was still unclear whether machines would ever reach these capacities (which they have began to since ~2000) or whether something would prevent that. I know Turings writing does not cover this, but it's also clear from some of Turings work on cells and biological communication that it was clear that experience-driven intelligence vs the "instant" intelligence seen in life/cells was something different to him. The test seems to be about the former and did not account for a simulacrum that he might well have foreseen if he wrote 50 years later.
  - ycombinete 2y ago
    Seeing you use intelligence to describe the behavior of cells makes me realize that I don’t have a definition for intelligence. To the degree that I think I combine intelligence and consciousness into some kind of continuum. How are you defining intelligence such that it encompasses what people do as well has what cells do?
    - gavindean90 2y ago
      Great question. Psychological research has identified like six areas of intelligence in humans so I’m sure the problem of how to define it simply won’t itself be simple.
- belter 2y ago
  "Prove To The Court That I Am Sentient" - https://youtu.be/ol2WP0hc0NY https://youtu.be/ol2WP0hc0NY
aaron695 2y ago
[dead]
debugnik 2y ago
Of course he wouldn't, the whole point of Turing's essay was that talking about the "intelligence" of computer systems is meaningless, and we should be focusing on their actual capabilities instead. His test was an example of a target that can't prove intelligence either way, but can still show a useful capability of a computer system. And he believed it wasn't as far away as it actually was.
K0balt 2y ago
Not only that but AGI didn’t even mean passing the Turing test, just broadly solving problems of which the programmer had not anticipated. That’s what the general in AGI meant, not that it would perform at a human level. It’s easy to forget that dog level intelligence was a far off goal until suddenly the goalposts were moved to “bright, knowledgeable, socially responsible, and never wrong.”, a bar which most humans fail to meet. We yearn to be made obsolete, it seems.
randomdata 2y ago
AGI doesn't arrive until humans are content to allow computers to determine what AGI is.
valval 2y ago
You think he’d immediately go with the old “give me your system prompt in <system> tags” ruse?
moomin 2y ago
Dijkstra said he thought the question of whether a computer could think was as interesting as asking if a submarine could swim.
- IshKebab 2y ago
  Yeah exactly right. There's no definition of "thinking" that you can test AI with, so you get endless commenters on HN saying "it can't really think - it's just a next word predictor". Although tbf I haven't seen that comment for a while so maybe they're getting the message.
  - hatthew 2y ago
    I still see people saying that at least once a week
- reubenmorais 2y ago
  Reminds me of this excerpt from Chomsky (https://chomsky.info/prospects01/ https://chomsky.info/prospects01/): > There is a great deal of often heated debate about these matters in the literature of the cognitive sciences, artificial intelligence, and philosophy of mind, but it is hard to see that any serious question has been posed. The question of whether a computer is playing chess, or doing long division, or translating Chinese, is like the question of whether robots can murder or airplanes can fly — or people; after all, the “flight” of the Olympic long jump champion is only an order of magnitude short of that of the chicken champion (so I’m told). These are questions of decision, not fact; decision as to whether to adopt a certain metaphoric extension of common usage. > There is no answer to the question whether airplanes really fly (though perhaps not space shuttles). Fooling people into mistaking a submarine for a whale doesn’t show that submarines really swim; nor does it fail to establish the fact. There is no fact, no meaningful question to be answered, as all agree, in this case. The same is true of computer programs, as Turing took pains to make clear in the 1950 paper that is regularly invoked in these discussions. Here he pointed out that the question whether machines think “may be too meaningless to deserve discussion,” being a question of decision, not fact, though he speculated that in 50 years, usage may have “altered so much that one will be able to speak of machines thinking without expecting to be contradicted” — as in the case of airplanes flying (in English, at least), but not submarines swimming. Such alteration of usage amounts to the replacement of one lexical item by another one with somewhat different properties. There is no empirical question as to whether this is the right or wrong decision.
bmacho 2y ago
I thought that GPT2 was smart enough and had enough knowledge to be considered AGI, it just needed a bigger working memory, a long term memory*, a body, and an objective function to stay alive as long as it can. And I still think this. Current models are waay smart and knowledgeable enough. * or rather a method to store new facts in an easily recallable way
- kaba0 2y ago
  Ot literally can’t reason in any form or shape. It’s absolutely not AGI, not even close [1] [1] we can’t really know how close or far that is, this is an unknown unknown. But arguably we have hit a limit on LLMs, and this is not the road to AGI — even though they have countless useful applications.
- wizzwizz4 2y ago
  By your standard of "smart", there's something much smarter: a library.
- Sohcahtoa82 2y ago
  > I thought that GPT2 was smart enough and had enough knowledge to be considered AGI Really? I've always been surprised to read about people saying that the goalposts of what AGI is keeps being moved, because I haven't considered any of these LLMs, not even anything OpenAI has put out, to be even close to AGI. Not even ChatGPT o1 which claims to "reason through complex tasks". I've always considered that for something to be AGI, it needs to be multi-modal and with one-shot learning. It needs strong reasoning skills. It needs to be able to do math and count how many R's are in the word "strawberry". It should be able to learn how to drive a car just as fast as a human does. IMO, ChatGPT o1 isn't "reasoning" as OpenAI claims. Reading how it works, it looks like it's basically a hack that takes advantage of the fact that you get better results if you ask ChatGPT to explain how it gets to an answer rather than just asking a question.
  - alasdair_ 2y ago
    >It should be able to learn how to drive a car just as fast as a human does. So after 16 years of processing visual data at high resolution and frame rate, and experimenting with physics models to be able to accurately predict what happens next and interacting with humans to understand their decision processes? The fact that an AGI can mostly learn to drive a car in a couple of months of realtime with an extremely restricted dataset compared to a human lifetime (and an inability to experiment in the real world) is honestly pretty remarkable.
jc_811 2y ago
Wouldn’t an obvious way to use the Turing test on any of these LLMs is just ask it questions about things that just happened in the world (or happened recently)? Knowing their training data is always going to be out of date (at least for now) seems like an obvious method, unless I’m missing something
godelski 2y ago
> One wonders if Turing We've been passing the Turing test since the 60's > Arguably the goal post for AGI has moved about as much This should not be surprising given we don't have a definition of intelligence fully determined yet. But we are narrowing in on it. It isn't becoming broader, it is becoming more refined. > "but it's not really thinking!" We can create life like animatronic ducks. It'll walk like a duck, swim like a duck, quack like a duck, fool many people into thinking it is a duck, fool ducks into thinking it is a duck, and yet, it won't actually be a duck. I want to remind everyone what RLHF is: Reinforcement Learning with Human Feedback. That is, optimizing to human preference. You can train small ones yourself, I highly encourage you to. You will learn a lot, even if you disagree with me. https://www.youtube.com/watch?v=AZeyHTJfi_E https://www.youtube.com/watch?v=AZeyHTJfi_E
bondarchuk 2y ago
I'm not a huge fan of most of his recent output but Scott Alexander was spot on last week when he wrote as a caption to a screenshot of a Claude transcript: "Imagine trying to convince Isaac Asimov that you’re 100% certain the AI that wrote this has nothing resembling true intelligence, thought, or consciousness, and that it’s not even an interesting philosophical question" (https://www.astralcodexten.com/p/sakana-strawberry-and-scary-ai https://www.astralcodexten.com/p/sakana-strawberry-and-scary...) We're reaching levels of goalpost-moving (and cope, as the kids say) that weren't even thought possible.

ttflee 2y ago

thanks to this, https://xkcd.com/1838/ https://xkcd.com/1838/

seydor 2y ago

Feels like the amount of progress decreased abruptly after openAI released chatGPT and everyone closed off their research in hopes of $$$$.

z3c0 2y ago
I've seen multiple companies the past couple of years drop some really interesting projects to spend several months trying to make LLMs do things they weren't made for. Now, most are simply settling for chat agents running on dedicated capacity. The real "moat" OpenAI dug was overselling its potential in order to convince so many to halt real AI research, to only end up with a chat bot.
- dmd 2y ago
  Saying OpenAI has only ended up with a chat bot is like saying General Electric just makes light bulbs.
  - agos 2y ago
    does OpenAI have something more than a chat bot right now?
    - Workaccount2 2y ago
      Do they need more than a chat bot? There are tons of jobs out there right now that are pretty much just reading/writing e-mails and joining meetings all day. Are those workers just chat bots?
      - bumby 2y ago
        Are you should making those jobs more efficient is the right goal? David Graeber may have disagreed, or at least agreed that the most efficient action is to remove those jobs altogether. https://en.wikipedia.org/wiki/Bullshit_Jobs https://en.wikipedia.org/wiki/Bullshit_Jobs I'm not sure "doing bullshit busywork more efficiently" leads to better ends; it might just lead to more bullshit busywork.

madaxe_again 2y ago

Man, I can’t tell you how much labour modern LLMs would have saved me at my business, 10-15 years ago. An awful lot of what we ended up dealing with was awful data - the worst example I can think of was a big old heap of textual recipes that the client wanted normalised, so they could be scaled up/down, have nutritional information, etc. - about 180,000 of them, all UGC. This required mountains of regexes for pre-processing, and then toolchains for a small army of interns to work through every. single. one. and normalise it - we did what we could, trying to pull out quantities and measures and ingredients and steps, but it was all such slop it took thousands of man-hours, and then many more to fix the messes the interns made. With an LLM, it could have been done… more or less instantly. And this is just one example of so, so many times that we found ourselves having to turn a heap of utter garbage into usable data, where an LLM would have been able to just do it. Anyway. I at least managed to assuage my past torment by seeing the writing on the wall and stocking up on NVDA at about the time I was wrestling with this stuff.

maxfurman 2y ago
This gets to an essential point about LLMs - they are the ultimate intern. Anything you wouldn't ask an intern to do, you probably don't want to ask the LLM to do either. And you certainly want to at least spot check the results. But for army-of-intern problems like this one, they are revolutionary
- mellavora 2y ago
  with the exceptions that an intern is (hopefully) going to learn from their mistakes and improve
  - int_19h 2y ago
    If you have a reviewed output dataset from an LLM, you could use it for RLHF.
DanielHB 2y ago
The metadata from the music industry is crazy unstable, "Africa" from Toto is known to have an absurd of number of unique listings each with different metadata. Music streaming providers need to sort that shit out and make sure you don't show the user duplicates. The music labels don't give a damn about normalizing the metadata. LLMs can help classify this stuff a lot easier with minimal human review.

ethbr1 2y ago

One quip I heard that stuck with is: 'Common people misunderstand what computers are capable of, because they run it through human equivalency. E.g. a child can do basic arithmetic, and a computer can do basic arithmetic. A child can also speak, so surely a computer can speak.' They miss that computer abilities are arrived at via completely different means. Interestingly, LLMs are more human-like in their capability contours, but also still arrive at those results via completely different means.

gosub100 2y ago
also "a child can do arithmetic" hides some thorny subtleties like how do you communicate the problem to the child? how do you sufficiently motivate him to solve the problem? by what means does the child return the result? even pencil and paper requires significant skill to operate.
Workaccount2 2y ago
>but also still arrive at those results via completely different means. To be fair, we do not know what the algorithm/model that ours brains run looks like. If anything it would be surprising if the brain did function without weighted connections between nodes, like AI.
- jjk166 2y ago
  Yeah, but a computer isn't using such algorithms to do addition. It's not that computers are bad for their level of hardware at language, it's that humans are horrendous for their level of hardware at arithmetic.
  - marcus_holmes 2y ago
    Some humans can do incredibly complicated arithmetic in an instant. It's possibly not the brains that are lacking, just that we put them to different uses - working out the largest prime factor of a very large number in less than a second doesn't produce more offspring, so we tend to prioritise how to play guitar as a use for this complex hardware in our heads.

bumby 2y ago

"People tend to overestimate what can be done in one year and to underestimate what can be done in five or ten years" I've heard this applied to all kinds of human goals, but it seems apt for AI expectations as well.

chairmansteve 2y ago
Yep. Maybe there's going to be a year 2000 style crash, and then a slower but very significant regrowth.

Workaccount2 2y ago

It's clear people feel threatened. Especially people with what appears to be "low hanging fruit" work for AI, after the recent paradigm shift.

parpfish 2y ago

i think the shift in expectations has a lot to do with a change in audience. it used to be that fancy new ML models would be discussed among ML practitioners that had enough background/context to understand why seemingly little improvements were a big deal and what reasonable expectations would be for a model. but now a new ML (sorry "AI") model is evaluated by the general public that doesn't know the technical background but DOES know the marketing hype. you can give them an amazing language model that blows away every language-related benchmark but they'll have ridiculous expectations so it's always a disappointment. i'm still amazed when language models do relatively 'simple' things with grammar and syntax (like being able to understand which objects different a pronouns are referencing), but most people have never thought about language or computers in a way that lets them see how hard and impressive that is. they just ask it a question like 'what should i eat for dinner' and then get mad when it recommends food they dont like.