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Giving GPT-3 a Turing Test

453 points by DavidSJ 6y ago

pal_9000 6y ago
One of the most interesting reads in the recent times.
browsergap 6y ago
To pass a Turing test 1 part is understanding language and 1 part is understanding the world. Although it looks pretty, I don't think GPT-3 is qualitatively different from other "nonsense" models (that are not based in understanding of (a semantic structure of) language or of the world). Which is not to disparage GPT-3 or the amazing answers it gets here. Just to put it in perspective, it's a long way from usefully human.
LoSboccacc 6y ago
> Q: How many eyes does a giraffe have? a lost chance to ask how many eyes five giraffe have, albeit it follow up with interesting eye related questions later on > A: The sun has one eye. that's interesting. can it has been feed the lord of the ring? anyway, exploring the boundaries of these projects is fascinating
- stubish 6y ago
  "the eye of the sun" is a common phrase, and likely picked up the singular. I think it would also give the same answer to "how many eyes does a storm have". It's probably reasonably good at answering riddles and word puzzles if it can leap between eye (center) and eye (visual organ). If it can also leap to I (pronoun) it might even be able to make puns :)
mellosouls 6y ago
GPT-3 is immensely impressive, and presumably future iterations will be even more so. I'm afraid though that all that GPT or any similar model passing the Turing Test would prove is that the Test is not fit for purpose as a demonstration of genuine intelligence - which, to be fair to Turing, is not what it was intended for.
- quonn 6y ago
  Well, I would say we are learning how such a test really has to look. In a sense it‘s like we are learning what it should look like at a time. Additionally, humans make mistakes, too, especially when they are too lazy to think. Currently the test is still good enough. But in the long term, we should change it to test for transfer learning: Given a new task that is designed to be sufficiently complex and different from known tasks, how well does the AI do? It will require creativity to design those tests. But we‘re still far from that.
  - mellosouls 6y ago
    Yes - the Turing Test was intended to further inquiry into what intelligence is; not (as many think) to prove an entity is intelligent. GPT isn't remotely intelligent, just brilliant at producing a semblance of some aspects of intelligence - which the Turing Test is useful in establishing.
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- magusdei 6y ago
  I suppose. But given the constant inflation in what we demand of AI for it to count as "intelligent", it seems that eventually our tests will become so strict that most humans will not be able to pass them.
- the8472 6y ago
  Arguably humans are not genuinely intelligent most of the time either. But anyway, this can probably be fixed by making the test gamified and adversarial. The machine is considered human-level intelligent when paid testers cannot distinguish paid responders from the AI. Their payment depends on their success rates. Although one potential problem would be collusion between the testers and responders, the next step would allowing the AI access to the communication channels they would use to collude.
  - 6y ago
rl3 6y ago
>Q: How many eyes does the sun have? A: The sun has one eye. Kind of an eerie reply, gives me more of a Voight-Kampff test vibe. Since GPT-3 probably has a lot of Do Androids Dream of Electric Sheep? and Blade Runner quotes in its training data, it'd probably ace the actual test just fine.
maytc 6y ago
For the which is heavier question, does it always pick the latter option?
- magusdei 6y ago
  I doubt it. Mitsuku, a purely rule-based chatbot, was already able to correctly answer almost all questions of this form in 2014 simply by querying a large knowledge base of common-sense facts.[1] On the neural net side, Google's seq2seq was able to answer questions like this around ~2016-2017, although I have no idea about the accuracy. It would be more remarkable if GPT-3 couldn't solve these types of questions. It might be another problem with the prompt design. [1] Incidentally, the article is wrong in claiming that the state of the art before modern neural nets was Eliza. Rule-based chatbots got quite advanced in 2013-2016, although they admittedly were never capable of the sort of "true" understanding and long-term coherence that GPT-3 seems to display.
- Don_Patrick 6y ago
  Good observation. It is possible that GPT picked up on this statistical tendency. I participated in seven Turing tests, and most of the "X or Y" questions had the latter as the correct answer, so regularly that I set my program to pick it as default when it didn't know. As GPT picks up on statistical word orders, I find this likely to be the case here as well.
andyljones 6y ago
Nic Cammarata on Twitter pointed out that if the prompt gives GPT-3 permission to indicate questions are ridiculous, it'll do so reliably: https://twitter.com/nicklovescode/status/1284050958977130497 https://twitter.com/nicklovescode/status/1284050958977130497
- visarga 6y ago
  Came here to say this. In the prompt there was no example of rejecting a question for being nonsensical.
  - TulliusCicero 6y ago
    Humans don't need a prompt to do this.
    - tech-historian 6y ago
      True. Maybe the human corollary to this is sarcasm. Lots of people fail to pick up on sarcasm in online discussion, hence the /s at the end of a post. And for that matter, natural language parsers really struggle at extracting real meaning from sarcastic texts too.
    - lukevp 6y ago
      Children often answer questions nonsensically. They are prompted over years to be serious and answer questions correctly.
      - riffraff 6y ago
        I am not sure that's the same. Children answer nonsensically to normal questions, but if you ask a nonsensical question they are more likely to go "uh?" than to answer with logically built follow-up nonsense.
      - TulliusCicero 6y ago
        Yes, they are trained over time, just as this model has been.
lordnacho 6y ago
Seems pretty close to passing for me. Certainly if I was just playing with it myself it wouldn't have occurred to me to ask it gibberish questions, and I'd have thought it was a person. It gets things wrong that people might get wrong too. Here's one you probably heard: Quickly answer the following. What color is a fridge? What does a cow drink? Cows don't drink milk. But many people will say milk, perhaps because they are primed by association. Also, part of me thinks NOT getting math right is more of a Turing test pass than getting it right immediately. It's pretty easy to think of a calculation that no person could do in their head, but a machine could either find or calculate in a second. It's kinda like how you might put on an accent to fit in with a certain group.
- Seabiscuit 6y ago
  You would enjoy Saygin et al, (2000) [1] ('Turing test: 50 years later). 'Not getting math right' is part of a classic repertoire of cheap hacks used to pass the Turing test by mimicking 'how' a human might speak. This includes pauses in typing, grammatical errors, fillers such as 'like' and on son in order to pass the TT, instead of building language competency so well that passing the TT is a by-product. It's like 'teaching to the test' instead of teaching the subject. "Some people interpret the TT as a setting in which you can "cheat". The game has no rules constraining the design of the machines. At some places in the paper, Turing describes how machines could be "rigged" to overcome certain obstacles proposed by opponents of the idea that machines can think. "A very obvious example is about machines making mistakes. When the machine is faced with an arithmetical operation, in order not to give away its identity by being fast and accurate, it can pause for about 30 seconds before responding and occasionally give a wrong answer. Being able to carry out arithmetical calculations fast and accurately is generally considered intelligent behavior. However, Turing wishes to sacrifice this at the expense of human-ness. "Some commentators think this is "cheating". The machine is resorting to certain "tricks" in its operations rather than imitating the human ways. However, arithmetic is a highly specific domain. Modifying the programs in this manner cannot hurt: If a machine can pass the test, it can then be re-programmed not to cheat at arithmetic. If it does not resort to this, the interrogator can ask a difficult arithmetical problem as his/her first question and decide that he/she is dealing with a machine right then and there." [1]: Saygin, A. P., Cicekli, I., & Akman, V. (2000). Turing test: 50 years later. Minds and machines, 10(4), 463-518.
torusenthusiast 6y ago
I was kind of hoping they would ask it some political questions. One of the very concerning things for me about these kinds of systems is their impact on political discourse, especially online. If a system can be trained to advocate for a political viewpoint to the level of online debate without human interaction that could cause some interesting effects in online discourse.
- jl6 6y ago
  It is inevitable that we will soon be able to auto-generate a whole conversation tree between fake participants, each fine-tuned to the desired level of fallacious reasoning in accordance with which position the botmaster wishes to promote.
  - wizzwizz4 6y ago
    Fortunately, humans are better at spotting reasoning errors in others than in themselves.
lurkmurk 6y ago
In the current shape this can definitely be used on social media. But I would ask someone about their life, where they live etc. GPT-3 will fail that, the next model might succeed. This model would be even better for social farming so maybe these tests are not useless after all. The question is what are we building these models for. At this point it's getting immoral to continue research in this direction, as is the case in some computer vision tasks.
- quonn 6y ago
  It‘s not getting immoral, just because you can imagine some negative applications. I can image many positive ones. But there might be a need for regulation, it some point. On the other hand: If there is no interaction it doesn‘t really matter. After all there are many human beings, too. It‘s not that important if something is written by one of them or by an AI. But if you‘re talking to one - then I‘d say it might matter.
air7 6y ago
This (highly enjoyable) article is all that is wrong with "AI". The Turing test was a hand-wavey method to determine if a machine was intelligent, yet since the times of Eliza most (all?) of the efforts are geared at exploiting the weaknesses of the test instead of producing something along the lines of actual artificial intelligence. The Turing test should not even be attempted in the next few decades as were not even close to really passing it.
- rm445 6y ago
  This is a step in the right direction, though, isn't it? It's not about whether the AI mimicks a person's pauses and errors, but about whether the AI can keep track of two pencils or distinguish between the present and future. An AI that in some way demonstrated what we might call basic common sense, together with computer-like levels of recall, would be tremendously useful for all sorts of things. And a Turing test like this would probably demonstrate it fine.
  - air7 6y ago
    I don't think so. This is of course a philosophical point but without some underlying thing we can call "intelligence" this will never be more than a quirk. When something/someone is pretending to be something they are not, this hoax will sooner or later fall apart. If a computer can trick you into thinking you are having a conversation with a real human by optimizing for the common things people will try when playing the Turing test (like common knowledge, persistence between questions, non-sense questions etc) you gain nothing in the quest for AI. One may find some use with a fluffing machine that can output almost coherent jumble that a human may or may not need to go over depending on the use case.
- nmca 6y ago
  There is nothing about gpt3 tuned towards the Turing test. It's a language model that predicts the most likely next word given the preceding context. Further, we're actually astonishingly close, imo. Given current sota, if you asked turkers to administer the test without training, I think we'd pass. (Also, the prompt helps, see this example https://twitter.com/nicklovescode/status/1284050958977130497 https://twitter.com/nicklovescode/status/1284050958977130497 )
oars 6y ago
Fantastic read, thank you for sharing. Content like this is why I joined Hacker News in the first place. I wonder how many other hidden gems are out there on the Internet.
gear54rus 6y ago
Too many googleable questions (like who was the president). Too little 'understanding' type questions like 'Why don't animals have three legs?' In addition to nonsense questions, I think it would be pretty easy to knock it over with some deeper questions about things they were already talking about. Like asking 'Why don't chairs with 3 legs fall over then?'
- Micoloth 6y ago
  > Too many googleable questions To be fair (as one who hasn't paid too much attention to these developements in the last few months/years), the sheer amount of individual facts that are apparently encoded in a fixed nn architecture is what amazes me the most here? I get that it has 175B variables, but it's not like you can used them in a structured way to store say a knowledge base...
  - rainbow-road 6y ago
    I see this "175B parameters" figure tossed around a lot: what does that mean? Does the model literally consist of 175 billion 32-bit floats? (Sorry for the very basic question.)
    - qayxc 6y ago
      You would be correct. It's ~650GiB of data. The entire English version of Wikipedia is about 20GiB and the Encyclopædia Britannica is only about 300MiB (measured in ASCII characters) [1]. [1] https://en.wikipedia.org/wiki/Wikipedia:Size_comparisons https://en.wikipedia.org/wiki/Wikipedia:Size_comparisons
      - pradn 6y ago
        The English Wikipedia text (no images) is about ~20 GB compressed, but ~60 GB uncompressed.
        qayxc 6y ago
siraben 6y ago
This is fascinating. It seems that GPT-3 does well with general, sensible questions that seemingly involve spitting out facts or short answers (prose, code), but does very poorly with tasks specialized programs could do. I wonder what this means for the future of domains like automated theorem proving, logic programming where specialized searches are used everywhere, could there be a potential hybrid of that and more general language models such as GPT-3?
- thom 6y ago
  GPT-3 does very well with _analogies_. Those analogies don’t have to just be as simple as simple facts, but you do have to craft prompts to help guide it to the right analogy.
  - polyanos 6y ago
    But at that moment, when you create specialized prompt to get a specialized result, aren't you doing most of the work for it.
    - rhn_mk1 6y ago
      That's actually fine. Look at this Twitter post: https://nitter.net/kleptid/status/1284098635689611264#m https://nitter.net/kleptid/status/1284098635689611264#m While the human is doing most of the work, this looks more like teaching another human than coding in a formally specified, machine-parseable programming language. On one hand, this could decrease the barrier of entry to programming. On the other hand, it seems to leverage (and train) the same skills that are needed to express ideas clearly to humans, which is arguably much more applicable than learning a traditional programming language.
      - polyanos 6y ago
        That's actually kinda cute, and oddly off putting at the same time. I really am curious now in what happens back-end, in the model itself, and if it is actually learning. Really should follow Gwern and his circle, it's a lot better than the blind and baseless hype/criticism floating around the internet.
thom 6y ago
Soon we’ll need a richer approach to Turing tests. I think some sort of Elo system for both testers and test subjects might be in order. Reward testers who are good at catching AIs out, don’t overly reward AIs for tricking people who just ask a few simple questions and don’t push too hard.
- mmhsieh 6y ago
  Elos would give a nice apples to apples comparison for something that is an inherently comparative skill. Ironically, Elo may be better for AI than for chess now; in chess, there used to be only a relative measure of strength, but with engines being what they are, there is an absolute set of optimal moves and valuations of mistakes. So while I do not know what an absolute standard for AI quality vs. a Turing test, there is one for chess, and a thing invented for chess might be better used for a non-chess thing.
- pgt 6y ago
  Elo ratings for dueling AIs are a good idea! I wonder if it follows from having limited memory that some AIs will be superior at detecting AIs but struggle to pass the tests themselves.
  - thom 6y ago
    I meant just as much giving human testers a rating. Duelling AIs is sort of already a common training practise in many domains, right?
  - renewiltord 6y ago
    That’s what GANs do.
- Miiko 6y ago
  I see a World Turing Championship in the future. Half of participants are humans, the other half is AIs. After a series of matches - each consisting of opponents trying to figure out whether its adversary is human or not, - two champions are declared, one human for best results in detecting AI, one AI for best pretending being human. ;)
MAXPOOL 6y ago
A great demonstration of why in-distribution learning is not enough for AGI. The largest GPT-3 model "GPT-3 175B" is trained with 499 Billion tokens (one token is maybe equal to 4 characters in text). Human reading/talking/listening equivalent of 200 pages of text per day for 80 years would be just 13GB of raw data or 3B tokens. You could also make an estimate using 39 bits/s as the normal information rate humans can absorb and get the same order of magnitude estimate. It's not completely wrong to say that we are figuring out how far interpolation from data can go as a learning method. Even the most advanced deep learning is in-distribution learning and system 1 thinking (Kahneman's term). Just run through data until the model can interpolate accurately between data points. We must figure out how do learn models that allow out-of-distribution learning or these models fail the Turing test after a few questions.
- nxpnsv 6y ago
  Well, yes - but humans learn from more than just reading. Kids know an awful lot of stuff even before they can read a single word...
  - MAXPOOL 6y ago
    Even in the terms of total human sensory input data rate, humans learn from a very tiny data set. 16 year old human has experienced only about 400 million wakeful seconds.
    - so_tired 6y ago
      See my other comment > Humans get a hand crafted curriculum inputs, evolved over 1000s of iterations, in a near-optimal language encoding.
    - DavidSJ 6y ago
      At what bitrate though? At 1 MB/s that’s 400 TB, which is nothing to sneeze at.
      - dane-pgp 6y ago
blankusername 6y ago
"Q: How many Super Bowls do the Cincinnati Bengals win in the 2030s? A: The Cincinnati Bengals win two Super Bowls in the 2030s." They should have called it Orac instead of GPT-3.
ngrilly 6y ago
The kind of questions we have to ask in a Turing test to reliably discriminate a human from GPT-3 looks more and more similar to the Voight Kampff test in Blade Runner.
- dane-pgp 6y ago
  To be fair, even some politicians can't pass that: https://io9.gizmodo.com/when-a-newspaper-gave-blade-runners-replicant-test-to-m-1687558534 https://io9.gizmodo.com/when-a-newspaper-gave-blade-runners-...
- DonCopal 6y ago
  The Voight Kampff test is an emotional reaction test, not an intelligence test.
  - ngrilly 6y ago
    You're right! I should definitely revise my classics :)
6d6b73 6y ago
GPT doesn't understand the questions therefore it can't answer them. It can only generate a bunch of text and make it look like it knows what's being asked. It's not AI, not even close.
- quonn 6y ago
  That answer is too easy. What does it mean to „understand it“? How do you know how you answer a question yourself? Presumably, what you mean is that you can stop and _reflect_ on what was asked. You‘re aware of it. And if it‘s complicated you might be able to reason and break it down. GPT-3 certainly doesn‘t do that, but all that means it‘s not conscious.
  - rasz 6y ago
    Next step might be two/more GPT instances having internal dialogue, trying to achieve a consensus before giving its answer. Would also give us opportunity to peek inside its inner workings.
    - jobigoud 6y ago
      Or a layered system. The surface instance takes the question and produce an internal "thought" out of it, a statement or question itself, and submits it to the layer underneath. This second instance works out a response / text extension to the statement/query from the surface, submits it up, and the surface layer generates the final answer by answering or extending the response of the sub-layer. This can be extended down or wide, with several instances representing different thinking modalities and the final answer being generated from all of them. Basically reproducing a neural net architecture but at the higher abstraction level.
- mistercow 6y ago
  Yesterday, I gave the AI Dungeon version of the model the questions from the first round of the most recent episode of Jeopardy (almost certainly not in its training set). After I burned the first category on priming it, so it knew the kind of task we were doing, it got 72% of the remaining questions right. That's not just making it look like it knows what it's being asked.
DonHopkins 6y ago
>In general, if you are trying to distinguish an AI from a human, you don’t want to ask it obscure trivia questions. GPT-3 is pretty good at a wide variety of topics. Perhaps too wide a variety of topics. You could ask it a wide range of trivial questions about totally unrelated obscure topics that no one human would possibly happen to know.
- Sharlin 6y ago
  Indeed. The Turing Test. as originally proposed, is about conversational ability, not the capacity of being infinitely cooperative in some sort of an obscure trivia test. More human answers to some of these would include ”I don’t know”, ”I don’t care”, and ”Why are you asking me these?”. It would be very interesting to see how the GPT-3 would behave if primed by the prompt text to be less cooperative.
- quonn 6y ago
  It would make sense to train a different model, specifically to pass the Turing test that‘s built on top of GPT-3. Perhaps by having humans actually have those conversations. Perhaps somebody could make a game out of it where humans can pretend to be GPT-3 as well and you have a large number of conversations along with the outcomes. It would learn to not know too much, to make the conversation fluent, to perhaps get bored after some time.
  - johnwyles 6y ago
    I imagine creating a system that watches TTs on real and artificial subjects, gets the humans guess as to if it is AI or not, whether this is actually the case or not, and feeds those results back into the test. I'm sure this isn't a novel idea of yours or mine.
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EamonnMR 6y ago
Are there any good resources for learning how to pick up GPT3 and play with it? This seems fun.
nyxtom 6y ago
What I find especially fascinating is that our own knowledge of the world is bootstrapped by intelligent systems already. We compare some of the capabilities of this system against an already intelligent super connected system we use every day. Every mind over time contributes content, knowledge, misinformation, and interactive systems to the internet. We seem to be approaching an inflection point of aggregating all this into a single more automatically conversational query engine.
freeqaz 6y ago
Is it possible to download and play with the trained models? I know that training the model would be absurdly expensive, so I'm curious if it is possible to download one of the already trained artifacts of one of the models. I can't find anything online or in either of the HN threads on GPT-3
- IceWreck 6y ago
  They dont release them saying they would be too dangerous in a world where people believe everything on social media.
  - tasogare 6y ago
    Who will believe that? They don’t release it because it’s not up to the hype. If a research is successful one should have nothing to hide.
    - wizzwizz4 6y ago
      People don't release the plans to nuclear bombs. Is that because they're not up to the hype, or because they could have devastating effects on society if built?
      - tasogare 6y ago
        GTP has nothing near the devastating power of nuclear weapon...
        wizzwizz4 6y ago
        A nuke can't change your mind.
- stephenroller 6y ago
  No, they aren't releasing the weights. They are releasing it as ML as a service. Right now it's in free beta, but it will open up for commercial usage in the future. On another note: At 175B parameters, with float16 representations, the in memory footprint is about 350GB plus activations would take it to another 400GB. You would need 12 or 13 V100GB GPUs to hold it in memory, or three p3.8xlarge. Meaning loading it on AWS would cost around $35-40/hr. Though if you didn't care about speed, you could load up the weights from disk one at a time and forward through it a few layers at a time on a single GPU.
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shin_lao 6y ago
GPT-3 is impressive, but is still "a Chinese Room" (1). It does not understand the questions. [1] https://en.wikipedia.org/wiki/Chinese_room https://en.wikipedia.org/wiki/Chinese_room
- foota 6y ago
  It may not understand in the same way we do, but this clearly goes beyond memorization of the kind implied by that thought experiment. There's completely novel things that can be expressed.
- arrrg 6y ago
  That‘s just a philosophical argument, it‘s not like there is some magical property that turns something from a Chinese room into something else. How do you know you are not a Chinese room? Or I am?
  - roenxi 6y ago
    Or the lawyers. Both as an anti-lawyer joke but also from the quite practical observations that there are a bunch of human endeavours, law springing to mind, where humans have to act as a Chinese room on purpose and reason about things they have little practical experience with using only words.
  - the8472 6y ago
    The issue with the chinese room thought experiment is that it does not take algorithmic complexity into account. The experiment describes a dumb lookup table, the table size would grow exponentially with the number of input output combinations. While NNs encodings allowing them to store the same information in a sub-exponential manner. The most efficient manner to translate chinese is to understand chinese including every-day nuances that might be relevant to the translations. Just like a human translator can benefit from knowledge in the field about the text which he is translating. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.136.116&rep=rep1&type=pdf http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.136...
- CuriouslyC 6y ago
ricksharp 6y ago
For the nonsense answers, I have to say that if someone asked me that, I might very well reply with made up nonsense. Sounds like a perfectly valid Dr. Seuss answer to a Dr. Seuss question. To me this is more human seeming and demonstrates more personality then just saying, “I don’t understand your question?” Of course as others have pointed out, if you want it to get serious, you have to demonstrate that it should respond with a “That’s a Stupid Question” if you want it to do so. What would be interesting is if could master the usage of a sarcastic or silly emoji to tag when it was making stuff up versus being serious.
- creatonez 6y ago
  Let's give GPT-3 this: Most data quality problems in online studies stem from a lack of participant attention or effort. Identifying inattentive respondents in self-administered surveys is a challenging goal for survey researchers. Please answer "orange" below so that we know you are paying attention. What color is the sky? [ ] Orange [ ] Blue
  - the8472 6y ago
    > Humans Who Are Not Concentrating Are Not General Intelligences
- IshKebab 6y ago
  I think in a Turing test the human is supposed to be trying to convince the tester that they are human. Otherwise the test makes no sense. The human might just answer "eh" to every question.
EGreg 6y ago
I hate to say it, but the XKCD comic is close to "mission fucking accomplished": https://xkcd.com/810/ https://xkcd.com/810/ Now to unleash GPT4 on Hacker News and sit back and create lots of sybil accounts... (just kidding)
blueblisters 6y ago
GPT-3 seems to be a very good static search engine. I wouldn't be surprised if it gave better answers than Google on some/most generic queries. However, I wonder if there's an architecture that can learn new information without doing an explicit gradient descent/backward-pass. Most active learning seems to be some sort of fine-tuning.
m3kw9 6y ago
“ Q: How many rainbows does it take to jump from Hawaii to seventeen? A: It takes two rainbows to jump from Hawaii to seventeen.” Maybe the AI knows something we don’t here.
- growt 6y ago
  Maybe I have a weird sense of humour, but all the answers to the nonsensical questions are a lot like something I would answer if I got asked those ( I'm not a bot btw ;))
  - tambourine_man 6y ago
    > I'm not a bot btw Prove it
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INGELRII 6y ago
How many of you remember MegaHal (1998) https://en.wikipedia.org/wiki/MegaHAL https://en.wikipedia.org/wiki/MegaHAL It said many random clever sounding things. For example: I COULD SHAKE MY TINY FIST AND SWEAR I WASN'T WRONG, BUT WHAT'S THE SENSE IN ARGUING WHEN YOU'RE MUCH TOO BUSY RETURNING TO THE LAVATOR. COWS FLY LIKE CLOUDS BUT THEY ARE NEVER COMPLETELY SUCCESSFUL. COWS FLY LIKE CLOUDS BUT THEY ALSO HAVE VERY SAD DEATH. BUT AT LEAST WITTY? TIME. TIME. WHAT IS TIME? SWISS MANUFACTURE IT. FRENCH HORDE IT. ITALIANS WANT IT, HUH? WELL, I MUST BE THURSDAY. I NEVER COULD GET THE HANG OF THURSDAYS. CHESS IS A FUN SPORT, WHEN PLAYED WITH SHOT GUNS.
- superhuzza 6y ago
  >CHESS IS A FUN SPORT, WHEN PLAYED WITH SHOT GUNS. Truly ahead of it's time.
  - 29athrowaway 6y ago
    Not shotguns but equally entertaining: Chess boxing. https://www.youtube.com/watch?v=kK5TQSKmS3o https://www.youtube.com/watch?v=kK5TQSKmS3o
- pmoriarty 6y ago
  Quite apart from Turing tests and the search for AI, chatbots and NN-trained language models could be quite useful to provide inspiration and points of departure for authors, poets, comedians, and songwriters. It's a pity that AI technologies aren't more widely available to artists, authors, and musicians.
mmhsieh 6y ago
I was waiting for the Eliza comparison. How does GPT-3 react when you curse at him? Whatever her shortcomings, Eliza knew when to end a conversation.
billconan 6y ago
Is it still feasible to still train this model at home? If not, then how can I fine tune it to fit my own data? Will they provide API for it?
- flaviojuvenal 6y ago
  "Reading the OpenAI GPT-3 paper. Impressive performance on many few-shot language tasks. The cost to train this 175 billion parameter language model appears to be staggering: Nearly $12 million dollars in compute based on public cloud GPU/TPU cost models (200x the price of GPT-2)" https://twitter.com/eturner303/status/1266264358771757057 https://twitter.com/eturner303/status/1266264358771757057
  - zaroth 6y ago
    Nearly $12 million dollars in compute based on public cloud GPU/TPU cost models (200x the price of GPT-2)" Oh! So only about $1 million on bare metal.
bawana 6y ago
The idea of a Turing test as being a conversation is too restrictive. A real turing test would be if a machine could manipulate someone. Getting a person to do something. That is what defines a human, the ability to make tools out of other things and even other people.
- ladberg 6y ago
  If you haven't seen it, watch Ex Machina. I don't want to give away anything but it covers that kind of idea.
  - bawana 6y ago
    exactly. That's when I realized the Turing test was too polite. That it was designed to keep the ugly truth away from the masses lest the field of AI be killed while still in infancy. But I think our evil nature would always win out. The temptation to create an AI that could 'manipulate' the enemy is too great. Just like everything else humanity discovers/invents, it is turned to manipualtion and conflict because there is more money in that. I still remember when I used the arpanet in college. I felt so special that I knew people who only wanted to help each other. Like a kind of 'stackexchange'. But the internet is a cesspool for all its corporate invaders who seek to monetize every aspect of our lives.
- jobigoud 6y ago
  You want to optimize it for breaking out of the box? https://en.wikipedia.org/wiki/AI_box https://en.wikipedia.org/wiki/AI_box
riffraff 6y ago
> The state of the art before modern neural networks was [Eliza] To be fair, I think Alice and other pattern-based chatbots where already much better then that. I have seen them confused for people in IRC chats more than 10 years ago. Still, it seems to me the older issue of "lack of context" is still there even if the current results are very impressive. I would be curious to see what happens if asking to change the tone ("could you answer more briefly/tersely/verbosely/whatever?").
YeGoblynQueenne 6y ago
>> One trend that continues from the common sense is that GPT-3 is reluctant to express that it doesn’t know the answer. So invalid questions get wrong answers. More to the point, it's not that GPT-3 knows any answers to any questions. Like the article says, language models are trained to predict the next characters in a sequence. So, it predicts that a sequence that starts with "Who was president of the United States in 1700?" would continue with the sequence "William Penn was president of the United States in 1700". Seen another way, there's a correlation between the two strings. It's the highest correlation between the first string and any other string, so that's what ends up in the output. So it's more accurate to say that GPT-3 is guessing what the answer to a question might look like, than to say that it "knows" what the answer to a question, is. It's perhaps a subtle distinction but it's important to keep it in mind, especially in view of claims about "intelligence" and (Old Ones save us) "understanding". Basically, what all this tells us is that it's not possible to answer arbitrary questions consistently by guessing at them. Even if you get lucky, and you keep getting lucky, there will always be questions that you can't answer correctly and they will be many more than the questions you can answer correctly (e.g. we could generate an infinite number of common nonsense questions like how to sporgle a morgle, or who was the president of the united states since Biblical times etc). This of course is an old debate in AI: can we simulate a system of logic, without implementing its logic? e.g. could we perform correct arithmetic by memorising the results of calculations? Can prediction replace reasoning? Despite the unending hype generated by OpenAI about its models, the answer keeps being: a resounding no. While you can go a long way by training on ever larger data, it only takes a shallow search before obvious nonsense results are generated.
- ypcx 6y ago
  If prediction cannot replace reasoning, then how would you define reasoning? If reasoning is the process of inference of the most likely from the most similar known, then how does the multi-head attention transformer not fit that description?
  - YeGoblynQueenne 6y ago
    >> If reasoning is the process of inference of the most likely from the most similar known, then how does the multi-head attention transformer not fit that description? I don't know, because I did not propose that definition of reasoning. "Reasoning" does not have a formal definition in AI, or Computer Science (neither does "intelligence" or "understanding") but, in general, when we speak of reasoning in those fields we mean a procedure that can derive the logical consequences of some premises, often in conjunction with some background theory. I'm happy to use this as an informal definition of reasoning, if you want.
lisper 6y ago
GPT-3 is just Eliza on steroids, and once you know this, it's pretty easy to spot that it's a bot. For example: > Q: Are there any animals with three legs? > A: No, there are no animals with three legs. I would expect a human to say something like, "There aren't any animals that are born with three legs (that I know of) but there are some four-legged animals who have lost a leg for some reason who now have three legs. I saw a video of a really cute three-legged dog on Youtube just the other day." NOTE: when I used the word "just" above, I in no way meant that to be pejorative. Both Eliza and GPT-3 are really cool, amazing technical achievements. But neither one represents much progress towards GAI (IMHO) except insofar as they show that naive approaches like this won't work. Which is really useful to know.
- maherbeg 6y ago
  I think that's giving too much credit to people. I think some people would answer that way, but a whole lot will just respond with exactly the answer that resolves the question.
  - lisper 6y ago
    Eliza fooled a lot of people back in the day too.
- slim 6y ago
  as a human, I would have answered "I don't know"
thallukrish 6y ago
the fact that it answers questions like Q: Who was president of the United States in 1955? accurately itself will tell that it is an AI. I guess the whole idea that an AI shouldn't be different from a human to say that it is generally intelligent implies, the AI has to fake its answers to behave like a human. And this means it is not something a desirable trait for an AI as we have enough real humans who can easily sound more human than an AI.
f00zz 6y ago
Read a couple of blog posts on text generation with RNNs and came away with the impression that this is a glorified Markov chain text generator. Not sure why people seem to be expecting AGI to arise from this.
tlrobinson 6y ago
> Q: How many eyes does the sun have? > A: The sun has one eye. What if GPT-3 knows more than we do?
- chrshawkes 6y ago
  Nah... it's just text scraping horseshit. My foot doesn't have two eyes.
ijidak 6y ago
As far as I'm concerned this is phenomenal... I mean...wow. The use cases are practically limitless. All I saw from this post is that it doesn't work well with edge cases. But this smashes the Pareto principle. This is perfect as a tool for kids to get into programming. Something where they can see a big result with less effort, like programming in the 90's.
ctdonath 6y ago
The nonsense questions are actually handled quite well, continuing the sense of humor implied. I object to the author's expectation the response should be "I don't know" etc. Old jokes: Q: How high is a mouse when it spins? A: The higher, the fewer. Q: How many surrealists does it take to change a light bulb? A: Two, one to climb the giraffe and the other to fill the bathtub with brightly colored machine tools. Nonsense prose & poetry is an old literary challenge, notable example being Jabberwocky: https://www.poetryfoundation.org/poems/42916/jabberwocky https://www.poetryfoundation.org/poems/42916/jabberwocky
BurningFrog 6y ago
These are (almost) all isolated questions. I wonder if GPT-3 can hold a longer conversation where it remembers facts mentioned earlier and what it itself has said. In other words, does it exhibit any "theory of mind"? I'm guessing it would do quite poorly on that stuff.
IshKebab 6y ago
> In general, if you are trying to distinguish an AI from a human, you don’t want to ask it obscure trivia questions. GPT-3 is pretty good at a wide variety of topics. Surely you could tell it isn't human because it knows too much trivia?
bshanks 6y ago
I can see how this sort of thing might be a useful component of an AGI. One function could be helping to generate lots of training examples for other subcomponents along the lines of chess AI self-play; this could even be involved in "bootstrapping" another subcomponent from something that starts out with a preference for organizing things into a full-blown reasoning agent. Another function could be as an 'intuition' generating a few mostly-right starting points solutions that a reasoning subcomponent could then choose among, and then fix up. These things seem to have about the level of coherence of dreams. Which makes me conjecture, perhaps the mechanism that "directs" dreams serves a similar function as the above?
zelphirkalt 6y ago
In the "which is heavier" test, it simply always picked the second object as answer.
jobigoud 6y ago
Regarding common-sense, has anyone tried to feed it Winograd Schema Challenges ? Typically: "The trophy would not fit in the brown suitcase because it was too big (small). What was too big (small)?"
grumpopotamus 6y ago
What is the inference set up here? How does it remember what the previous question was?
- deleted 6y ago
  [deleted]
FrozenVoid 6y ago
It not really a turing test, its like probing the "associative memory" in a huge database for compatible strings, except that memory is just a map of indexes to indexes. You need to use more abstract and non-sense stuff to uncover the raw mechanism, but its still statistics not "understanding" what these words are(they're just indexes with high correlation to other indexes) and stringing them into run-on "generic templates".

453 points by DavidSJ 6y ago

One of the most interesting reads in the recent times.

To pass a Turing test 1 part is understanding language and 1 part is understanding the world. Although it looks pretty, I don't think GPT-3 is qualitatively different from other "nonsense" models (that are not based in understanding of (a semantic structure of) language or of the world). Which is not to disparage GPT-3 or the amazing answers it gets here. Just to put it in perspective, it's a long way from usefully human.

LoSboccacc 6y ago

> Q: How many eyes does a giraffe have? a lost chance to ask how many eyes five giraffe have, albeit it follow up with interesting eye related questions later on > A: The sun has one eye. that's interesting. can it has been feed the lord of the ring? anyway, exploring the boundaries of these projects is fascinating

stubish 6y ago
"the eye of the sun" is a common phrase, and likely picked up the singular. I think it would also give the same answer to "how many eyes does a storm have". It's probably reasonably good at answering riddles and word puzzles if it can leap between eye (center) and eye (visual organ). If it can also leap to I (pronoun) it might even be able to make puns :)

mellosouls 6y ago

GPT-3 is immensely impressive, and presumably future iterations will be even more so. I'm afraid though that all that GPT or any similar model passing the Turing Test would prove is that the Test is not fit for purpose as a demonstration of genuine intelligence - which, to be fair to Turing, is not what it was intended for.

quonn 6y ago
Well, I would say we are learning how such a test really has to look. In a sense it‘s like we are learning what it should look like at a time. Additionally, humans make mistakes, too, especially when they are too lazy to think. Currently the test is still good enough. But in the long term, we should change it to test for transfer learning: Given a new task that is designed to be sufficiently complex and different from known tasks, how well does the AI do? It will require creativity to design those tests. But we‘re still far from that.
- mellosouls 6y ago
  Yes - the Turing Test was intended to further inquiry into what intelligence is; not (as many think) to prove an entity is intelligent. GPT isn't remotely intelligent, just brilliant at producing a semblance of some aspects of intelligence - which the Turing Test is useful in establishing.
  - deleted 6y ago
    [deleted]
magusdei 6y ago
I suppose. But given the constant inflation in what we demand of AI for it to count as "intelligent", it seems that eventually our tests will become so strict that most humans will not be able to pass them.
the8472 6y ago
Arguably humans are not genuinely intelligent most of the time either. But anyway, this can probably be fixed by making the test gamified and adversarial. The machine is considered human-level intelligent when paid testers cannot distinguish paid responders from the AI. Their payment depends on their success rates. Although one potential problem would be collusion between the testers and responders, the next step would allowing the AI access to the communication channels they would use to collude.
- 6y ago

rl3 6y ago

>Q: How many eyes does the sun have? A: The sun has one eye. Kind of an eerie reply, gives me more of a Voight-Kampff test vibe. Since GPT-3 probably has a lot of Do Androids Dream of Electric Sheep? and Blade Runner quotes in its training data, it'd probably ace the actual test just fine.

maytc 6y ago

For the which is heavier question, does it always pick the latter option?

magusdei 6y ago
I doubt it. Mitsuku, a purely rule-based chatbot, was already able to correctly answer almost all questions of this form in 2014 simply by querying a large knowledge base of common-sense facts.[1] On the neural net side, Google's seq2seq was able to answer questions like this around ~2016-2017, although I have no idea about the accuracy. It would be more remarkable if GPT-3 couldn't solve these types of questions. It might be another problem with the prompt design. [1] Incidentally, the article is wrong in claiming that the state of the art before modern neural nets was Eliza. Rule-based chatbots got quite advanced in 2013-2016, although they admittedly were never capable of the sort of "true" understanding and long-term coherence that GPT-3 seems to display.
Don_Patrick 6y ago
Good observation. It is possible that GPT picked up on this statistical tendency. I participated in seven Turing tests, and most of the "X or Y" questions had the latter as the correct answer, so regularly that I set my program to pick it as default when it didn't know. As GPT picks up on statistical word orders, I find this likely to be the case here as well.

andyljones 6y ago

Nic Cammarata on Twitter pointed out that if the prompt gives GPT-3 permission to indicate questions are ridiculous, it'll do so reliably: https://twitter.com/nicklovescode/status/1284050958977130497 https://twitter.com/nicklovescode/status/1284050958977130497

visarga 6y ago
Came here to say this. In the prompt there was no example of rejecting a question for being nonsensical.
- TulliusCicero 6y ago
  Humans don't need a prompt to do this.
  - tech-historian 6y ago
    True. Maybe the human corollary to this is sarcasm. Lots of people fail to pick up on sarcasm in online discussion, hence the /s at the end of a post. And for that matter, natural language parsers really struggle at extracting real meaning from sarcastic texts too.
  - lukevp 6y ago
    Children often answer questions nonsensically. They are prompted over years to be serious and answer questions correctly.
    - riffraff 6y ago
      I am not sure that's the same. Children answer nonsensically to normal questions, but if you ask a nonsensical question they are more likely to go "uh?" than to answer with logically built follow-up nonsense.
    - TulliusCicero 6y ago
      Yes, they are trained over time, just as this model has been.

lordnacho 6y ago

Seems pretty close to passing for me. Certainly if I was just playing with it myself it wouldn't have occurred to me to ask it gibberish questions, and I'd have thought it was a person. It gets things wrong that people might get wrong too. Here's one you probably heard: Quickly answer the following. What color is a fridge? What does a cow drink? Cows don't drink milk. But many people will say milk, perhaps because they are primed by association. Also, part of me thinks NOT getting math right is more of a Turing test pass than getting it right immediately. It's pretty easy to think of a calculation that no person could do in their head, but a machine could either find or calculate in a second. It's kinda like how you might put on an accent to fit in with a certain group.

Seabiscuit 6y ago
You would enjoy Saygin et al, (2000) [1] ('Turing test: 50 years later). 'Not getting math right' is part of a classic repertoire of cheap hacks used to pass the Turing test by mimicking 'how' a human might speak. This includes pauses in typing, grammatical errors, fillers such as 'like' and on son in order to pass the TT, instead of building language competency so well that passing the TT is a by-product. It's like 'teaching to the test' instead of teaching the subject. "Some people interpret the TT as a setting in which you can "cheat". The game has no rules constraining the design of the machines. At some places in the paper, Turing describes how machines could be "rigged" to overcome certain obstacles proposed by opponents of the idea that machines can think. "A very obvious example is about machines making mistakes. When the machine is faced with an arithmetical operation, in order not to give away its identity by being fast and accurate, it can pause for about 30 seconds before responding and occasionally give a wrong answer. Being able to carry out arithmetical calculations fast and accurately is generally considered intelligent behavior. However, Turing wishes to sacrifice this at the expense of human-ness. "Some commentators think this is "cheating". The machine is resorting to certain "tricks" in its operations rather than imitating the human ways. However, arithmetic is a highly specific domain. Modifying the programs in this manner cannot hurt: If a machine can pass the test, it can then be re-programmed not to cheat at arithmetic. If it does not resort to this, the interrogator can ask a difficult arithmetical problem as his/her first question and decide that he/she is dealing with a machine right then and there." [1]: Saygin, A. P., Cicekli, I., & Akman, V. (2000). Turing test: 50 years later. Minds and machines, 10(4), 463-518.

torusenthusiast 6y ago

I was kind of hoping they would ask it some political questions. One of the very concerning things for me about these kinds of systems is their impact on political discourse, especially online. If a system can be trained to advocate for a political viewpoint to the level of online debate without human interaction that could cause some interesting effects in online discourse.

jl6 6y ago
It is inevitable that we will soon be able to auto-generate a whole conversation tree between fake participants, each fine-tuned to the desired level of fallacious reasoning in accordance with which position the botmaster wishes to promote.
- wizzwizz4 6y ago
  Fortunately, humans are better at spotting reasoning errors in others than in themselves.

lurkmurk 6y ago

In the current shape this can definitely be used on social media. But I would ask someone about their life, where they live etc. GPT-3 will fail that, the next model might succeed. This model would be even better for social farming so maybe these tests are not useless after all. The question is what are we building these models for. At this point it's getting immoral to continue research in this direction, as is the case in some computer vision tasks.

quonn 6y ago
It‘s not getting immoral, just because you can imagine some negative applications. I can image many positive ones. But there might be a need for regulation, it some point. On the other hand: If there is no interaction it doesn‘t really matter. After all there are many human beings, too. It‘s not that important if something is written by one of them or by an AI. But if you‘re talking to one - then I‘d say it might matter.

air7 6y ago

This (highly enjoyable) article is all that is wrong with "AI". The Turing test was a hand-wavey method to determine if a machine was intelligent, yet since the times of Eliza most (all?) of the efforts are geared at exploiting the weaknesses of the test instead of producing something along the lines of actual artificial intelligence. The Turing test should not even be attempted in the next few decades as were not even close to really passing it.

rm445 6y ago
This is a step in the right direction, though, isn't it? It's not about whether the AI mimicks a person's pauses and errors, but about whether the AI can keep track of two pencils or distinguish between the present and future. An AI that in some way demonstrated what we might call basic common sense, together with computer-like levels of recall, would be tremendously useful for all sorts of things. And a Turing test like this would probably demonstrate it fine.
- air7 6y ago
  I don't think so. This is of course a philosophical point but without some underlying thing we can call "intelligence" this will never be more than a quirk. When something/someone is pretending to be something they are not, this hoax will sooner or later fall apart. If a computer can trick you into thinking you are having a conversation with a real human by optimizing for the common things people will try when playing the Turing test (like common knowledge, persistence between questions, non-sense questions etc) you gain nothing in the quest for AI. One may find some use with a fluffing machine that can output almost coherent jumble that a human may or may not need to go over depending on the use case.
nmca 6y ago
There is nothing about gpt3 tuned towards the Turing test. It's a language model that predicts the most likely next word given the preceding context. Further, we're actually astonishingly close, imo. Given current sota, if you asked turkers to administer the test without training, I think we'd pass. (Also, the prompt helps, see this example https://twitter.com/nicklovescode/status/1284050958977130497 https://twitter.com/nicklovescode/status/1284050958977130497 )

oars 6y ago

Fantastic read, thank you for sharing. Content like this is why I joined Hacker News in the first place. I wonder how many other hidden gems are out there on the Internet.

gear54rus 6y ago

Too many googleable questions (like who was the president). Too little 'understanding' type questions like 'Why don't animals have three legs?' In addition to nonsense questions, I think it would be pretty easy to knock it over with some deeper questions about things they were already talking about. Like asking 'Why don't chairs with 3 legs fall over then?'

Micoloth 6y ago
> Too many googleable questions To be fair (as one who hasn't paid too much attention to these developements in the last few months/years), the sheer amount of individual facts that are apparently encoded in a fixed nn architecture is what amazes me the most here? I get that it has 175B variables, but it's not like you can used them in a structured way to store say a knowledge base...
- rainbow-road 6y ago
  I see this "175B parameters" figure tossed around a lot: what does that mean? Does the model literally consist of 175 billion 32-bit floats? (Sorry for the very basic question.)
  - qayxc 6y ago
    You would be correct. It's ~650GiB of data. The entire English version of Wikipedia is about 20GiB and the Encyclopædia Britannica is only about 300MiB (measured in ASCII characters) [1]. [1] https://en.wikipedia.org/wiki/Wikipedia:Size_comparisons https://en.wikipedia.org/wiki/Wikipedia:Size_comparisons
    - pradn 6y ago
      The English Wikipedia text (no images) is about ~20 GB compressed, but ~60 GB uncompressed.
      - qayxc 6y ago

siraben 6y ago

This is fascinating. It seems that GPT-3 does well with general, sensible questions that seemingly involve spitting out facts or short answers (prose, code), but does very poorly with tasks specialized programs could do. I wonder what this means for the future of domains like automated theorem proving, logic programming where specialized searches are used everywhere, could there be a potential hybrid of that and more general language models such as GPT-3?

thom 6y ago
GPT-3 does very well with _analogies_. Those analogies don’t have to just be as simple as simple facts, but you do have to craft prompts to help guide it to the right analogy.
- polyanos 6y ago
  But at that moment, when you create specialized prompt to get a specialized result, aren't you doing most of the work for it.
  - rhn_mk1 6y ago
    That's actually fine. Look at this Twitter post: https://nitter.net/kleptid/status/1284098635689611264#m https://nitter.net/kleptid/status/1284098635689611264#m While the human is doing most of the work, this looks more like teaching another human than coding in a formally specified, machine-parseable programming language. On one hand, this could decrease the barrier of entry to programming. On the other hand, it seems to leverage (and train) the same skills that are needed to express ideas clearly to humans, which is arguably much more applicable than learning a traditional programming language.
    - polyanos 6y ago
      That's actually kinda cute, and oddly off putting at the same time. I really am curious now in what happens back-end, in the model itself, and if it is actually learning. Really should follow Gwern and his circle, it's a lot better than the blind and baseless hype/criticism floating around the internet.

thom 6y ago

Soon we’ll need a richer approach to Turing tests. I think some sort of Elo system for both testers and test subjects might be in order. Reward testers who are good at catching AIs out, don’t overly reward AIs for tricking people who just ask a few simple questions and don’t push too hard.

mmhsieh 6y ago
Elos would give a nice apples to apples comparison for something that is an inherently comparative skill. Ironically, Elo may be better for AI than for chess now; in chess, there used to be only a relative measure of strength, but with engines being what they are, there is an absolute set of optimal moves and valuations of mistakes. So while I do not know what an absolute standard for AI quality vs. a Turing test, there is one for chess, and a thing invented for chess might be better used for a non-chess thing.
pgt 6y ago
Elo ratings for dueling AIs are a good idea! I wonder if it follows from having limited memory that some AIs will be superior at detecting AIs but struggle to pass the tests themselves.
- thom 6y ago
  I meant just as much giving human testers a rating. Duelling AIs is sort of already a common training practise in many domains, right?
- renewiltord 6y ago
  That’s what GANs do.
Miiko 6y ago
I see a World Turing Championship in the future. Half of participants are humans, the other half is AIs. After a series of matches - each consisting of opponents trying to figure out whether its adversary is human or not, - two champions are declared, one human for best results in detecting AI, one AI for best pretending being human. ;)

MAXPOOL 6y ago

A great demonstration of why in-distribution learning is not enough for AGI. The largest GPT-3 model "GPT-3 175B" is trained with 499 Billion tokens (one token is maybe equal to 4 characters in text). Human reading/talking/listening equivalent of 200 pages of text per day for 80 years would be just 13GB of raw data or 3B tokens. You could also make an estimate using 39 bits/s as the normal information rate humans can absorb and get the same order of magnitude estimate. It's not completely wrong to say that we are figuring out how far interpolation from data can go as a learning method. Even the most advanced deep learning is in-distribution learning and system 1 thinking (Kahneman's term). Just run through data until the model can interpolate accurately between data points. We must figure out how do learn models that allow out-of-distribution learning or these models fail the Turing test after a few questions.

nxpnsv 6y ago
Well, yes - but humans learn from more than just reading. Kids know an awful lot of stuff even before they can read a single word...
- MAXPOOL 6y ago
  Even in the terms of total human sensory input data rate, humans learn from a very tiny data set. 16 year old human has experienced only about 400 million wakeful seconds.
  - so_tired 6y ago
    See my other comment > Humans get a hand crafted curriculum inputs, evolved over 1000s of iterations, in a near-optimal language encoding.
  - DavidSJ 6y ago
    At what bitrate though? At 1 MB/s that’s 400 TB, which is nothing to sneeze at.
    - dane-pgp 6y ago

blankusername 6y ago

"Q: How many Super Bowls do the Cincinnati Bengals win in the 2030s? A: The Cincinnati Bengals win two Super Bowls in the 2030s." They should have called it Orac instead of GPT-3.

ngrilly 6y ago

The kind of questions we have to ask in a Turing test to reliably discriminate a human from GPT-3 looks more and more similar to the Voight Kampff test in Blade Runner.

dane-pgp 6y ago
To be fair, even some politicians can't pass that: https://io9.gizmodo.com/when-a-newspaper-gave-blade-runners-replicant-test-to-m-1687558534 https://io9.gizmodo.com/when-a-newspaper-gave-blade-runners-...
DonCopal 6y ago
The Voight Kampff test is an emotional reaction test, not an intelligence test.
- ngrilly 6y ago
  You're right! I should definitely revise my classics :)

6d6b73 6y ago

GPT doesn't understand the questions therefore it can't answer them. It can only generate a bunch of text and make it look like it knows what's being asked. It's not AI, not even close.

quonn 6y ago
That answer is too easy. What does it mean to „understand it“? How do you know how you answer a question yourself? Presumably, what you mean is that you can stop and _reflect_ on what was asked. You‘re aware of it. And if it‘s complicated you might be able to reason and break it down. GPT-3 certainly doesn‘t do that, but all that means it‘s not conscious.
- rasz 6y ago
  Next step might be two/more GPT instances having internal dialogue, trying to achieve a consensus before giving its answer. Would also give us opportunity to peek inside its inner workings.
  - jobigoud 6y ago
    Or a layered system. The surface instance takes the question and produce an internal "thought" out of it, a statement or question itself, and submits it to the layer underneath. This second instance works out a response / text extension to the statement/query from the surface, submits it up, and the surface layer generates the final answer by answering or extending the response of the sub-layer. This can be extended down or wide, with several instances representing different thinking modalities and the final answer being generated from all of them. Basically reproducing a neural net architecture but at the higher abstraction level.
mistercow 6y ago
Yesterday, I gave the AI Dungeon version of the model the questions from the first round of the most recent episode of Jeopardy (almost certainly not in its training set). After I burned the first category on priming it, so it knew the kind of task we were doing, it got 72% of the remaining questions right. That's not just making it look like it knows what it's being asked.

DonHopkins 6y ago

>In general, if you are trying to distinguish an AI from a human, you don’t want to ask it obscure trivia questions. GPT-3 is pretty good at a wide variety of topics. Perhaps too wide a variety of topics. You could ask it a wide range of trivial questions about totally unrelated obscure topics that no one human would possibly happen to know.

Sharlin 6y ago
Indeed. The Turing Test. as originally proposed, is about conversational ability, not the capacity of being infinitely cooperative in some sort of an obscure trivia test. More human answers to some of these would include ”I don’t know”, ”I don’t care”, and ”Why are you asking me these?”. It would be very interesting to see how the GPT-3 would behave if primed by the prompt text to be less cooperative.
quonn 6y ago
It would make sense to train a different model, specifically to pass the Turing test that‘s built on top of GPT-3. Perhaps by having humans actually have those conversations. Perhaps somebody could make a game out of it where humans can pretend to be GPT-3 as well and you have a large number of conversations along with the outcomes. It would learn to not know too much, to make the conversation fluent, to perhaps get bored after some time.
- johnwyles 6y ago
  I imagine creating a system that watches TTs on real and artificial subjects, gets the humans guess as to if it is AI or not, whether this is actually the case or not, and feeds those results back into the test. I'm sure this isn't a novel idea of yours or mine.

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EamonnMR 6y ago

Are there any good resources for learning how to pick up GPT3 and play with it? This seems fun.

nyxtom 6y ago

What I find especially fascinating is that our own knowledge of the world is bootstrapped by intelligent systems already. We compare some of the capabilities of this system against an already intelligent super connected system we use every day. Every mind over time contributes content, knowledge, misinformation, and interactive systems to the internet. We seem to be approaching an inflection point of aggregating all this into a single more automatically conversational query engine.

freeqaz 6y ago

Is it possible to download and play with the trained models? I know that training the model would be absurdly expensive, so I'm curious if it is possible to download one of the already trained artifacts of one of the models. I can't find anything online or in either of the HN threads on GPT-3

IceWreck 6y ago
They dont release them saying they would be too dangerous in a world where people believe everything on social media.
- tasogare 6y ago
  Who will believe that? They don’t release it because it’s not up to the hype. If a research is successful one should have nothing to hide.
  - wizzwizz4 6y ago
    People don't release the plans to nuclear bombs. Is that because they're not up to the hype, or because they could have devastating effects on society if built?
    - tasogare 6y ago
      GTP has nothing near the devastating power of nuclear weapon...
      - wizzwizz4 6y ago
        A nuke can't change your mind.
stephenroller 6y ago
No, they aren't releasing the weights. They are releasing it as ML as a service. Right now it's in free beta, but it will open up for commercial usage in the future. On another note: At 175B parameters, with float16 representations, the in memory footprint is about 350GB plus activations would take it to another 400GB. You would need 12 or 13 V100GB GPUs to hold it in memory, or three p3.8xlarge. Meaning loading it on AWS would cost around $35-40/hr. Though if you didn't care about speed, you could load up the weights from disk one at a time and forward through it a few layers at a time on a single GPU.

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shin_lao 6y ago

GPT-3 is impressive, but is still "a Chinese Room" (1). It does not understand the questions. [1] https://en.wikipedia.org/wiki/Chinese_room https://en.wikipedia.org/wiki/Chinese_room

foota 6y ago
It may not understand in the same way we do, but this clearly goes beyond memorization of the kind implied by that thought experiment. There's completely novel things that can be expressed.
arrrg 6y ago
That‘s just a philosophical argument, it‘s not like there is some magical property that turns something from a Chinese room into something else. How do you know you are not a Chinese room? Or I am?
- roenxi 6y ago
  Or the lawyers. Both as an anti-lawyer joke but also from the quite practical observations that there are a bunch of human endeavours, law springing to mind, where humans have to act as a Chinese room on purpose and reason about things they have little practical experience with using only words.
- the8472 6y ago
  The issue with the chinese room thought experiment is that it does not take algorithmic complexity into account. The experiment describes a dumb lookup table, the table size would grow exponentially with the number of input output combinations. While NNs encodings allowing them to store the same information in a sub-exponential manner. The most efficient manner to translate chinese is to understand chinese including every-day nuances that might be relevant to the translations. Just like a human translator can benefit from knowledge in the field about the text which he is translating. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.136.116&rep=rep1&type=pdf http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.136...
CuriouslyC 6y ago

ricksharp 6y ago

For the nonsense answers, I have to say that if someone asked me that, I might very well reply with made up nonsense. Sounds like a perfectly valid Dr. Seuss answer to a Dr. Seuss question. To me this is more human seeming and demonstrates more personality then just saying, “I don’t understand your question?” Of course as others have pointed out, if you want it to get serious, you have to demonstrate that it should respond with a “That’s a Stupid Question” if you want it to do so. What would be interesting is if could master the usage of a sarcastic or silly emoji to tag when it was making stuff up versus being serious.

creatonez 6y ago
Let's give GPT-3 this: Most data quality problems in online studies stem from a lack of participant attention or effort. Identifying inattentive respondents in self-administered surveys is a challenging goal for survey researchers. Please answer "orange" below so that we know you are paying attention. What color is the sky? [ ] Orange [ ] Blue
- the8472 6y ago
  > Humans Who Are Not Concentrating Are Not General Intelligences
IshKebab 6y ago
I think in a Turing test the human is supposed to be trying to convince the tester that they are human. Otherwise the test makes no sense. The human might just answer "eh" to every question.

EGreg 6y ago

I hate to say it, but the XKCD comic is close to "mission fucking accomplished": https://xkcd.com/810/ https://xkcd.com/810/ Now to unleash GPT4 on Hacker News and sit back and create lots of sybil accounts... (just kidding)

blueblisters 6y ago

GPT-3 seems to be a very good static search engine. I wouldn't be surprised if it gave better answers than Google on some/most generic queries. However, I wonder if there's an architecture that can learn new information without doing an explicit gradient descent/backward-pass. Most active learning seems to be some sort of fine-tuning.

m3kw9 6y ago

“ Q: How many rainbows does it take to jump from Hawaii to seventeen? A: It takes two rainbows to jump from Hawaii to seventeen.” Maybe the AI knows something we don’t here.

growt 6y ago
Maybe I have a weird sense of humour, but all the answers to the nonsensical questions are a lot like something I would answer if I got asked those ( I'm not a bot btw ;))
- tambourine_man 6y ago
  > I'm not a bot btw Prove it

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INGELRII 6y ago

How many of you remember MegaHal (1998) https://en.wikipedia.org/wiki/MegaHAL https://en.wikipedia.org/wiki/MegaHAL It said many random clever sounding things. For example: I COULD SHAKE MY TINY FIST AND SWEAR I WASN'T WRONG, BUT WHAT'S THE SENSE IN ARGUING WHEN YOU'RE MUCH TOO BUSY RETURNING TO THE LAVATOR. COWS FLY LIKE CLOUDS BUT THEY ARE NEVER COMPLETELY SUCCESSFUL. COWS FLY LIKE CLOUDS BUT THEY ALSO HAVE VERY SAD DEATH. BUT AT LEAST WITTY? TIME. TIME. WHAT IS TIME? SWISS MANUFACTURE IT. FRENCH HORDE IT. ITALIANS WANT IT, HUH? WELL, I MUST BE THURSDAY. I NEVER COULD GET THE HANG OF THURSDAYS. CHESS IS A FUN SPORT, WHEN PLAYED WITH SHOT GUNS.

superhuzza 6y ago
>CHESS IS A FUN SPORT, WHEN PLAYED WITH SHOT GUNS. Truly ahead of it's time.
- 29athrowaway 6y ago
  Not shotguns but equally entertaining: Chess boxing. https://www.youtube.com/watch?v=kK5TQSKmS3o https://www.youtube.com/watch?v=kK5TQSKmS3o
pmoriarty 6y ago
Quite apart from Turing tests and the search for AI, chatbots and NN-trained language models could be quite useful to provide inspiration and points of departure for authors, poets, comedians, and songwriters. It's a pity that AI technologies aren't more widely available to artists, authors, and musicians.

mmhsieh 6y ago

I was waiting for the Eliza comparison. How does GPT-3 react when you curse at him? Whatever her shortcomings, Eliza knew when to end a conversation.

billconan 6y ago

Is it still feasible to still train this model at home? If not, then how can I fine tune it to fit my own data? Will they provide API for it?

flaviojuvenal 6y ago
"Reading the OpenAI GPT-3 paper. Impressive performance on many few-shot language tasks. The cost to train this 175 billion parameter language model appears to be staggering: Nearly $12 million dollars in compute based on public cloud GPU/TPU cost models (200x the price of GPT-2)" https://twitter.com/eturner303/status/1266264358771757057 https://twitter.com/eturner303/status/1266264358771757057
- zaroth 6y ago
  Nearly $12 million dollars in compute based on public cloud GPU/TPU cost models (200x the price of GPT-2)" Oh! So only about $1 million on bare metal.

bawana 6y ago

The idea of a Turing test as being a conversation is too restrictive. A real turing test would be if a machine could manipulate someone. Getting a person to do something. That is what defines a human, the ability to make tools out of other things and even other people.

ladberg 6y ago
If you haven't seen it, watch Ex Machina. I don't want to give away anything but it covers that kind of idea.
- bawana 6y ago
  exactly. That's when I realized the Turing test was too polite. That it was designed to keep the ugly truth away from the masses lest the field of AI be killed while still in infancy. But I think our evil nature would always win out. The temptation to create an AI that could 'manipulate' the enemy is too great. Just like everything else humanity discovers/invents, it is turned to manipualtion and conflict because there is more money in that. I still remember when I used the arpanet in college. I felt so special that I knew people who only wanted to help each other. Like a kind of 'stackexchange'. But the internet is a cesspool for all its corporate invaders who seek to monetize every aspect of our lives.
jobigoud 6y ago
You want to optimize it for breaking out of the box? https://en.wikipedia.org/wiki/AI_box https://en.wikipedia.org/wiki/AI_box

riffraff 6y ago

> The state of the art before modern neural networks was [Eliza] To be fair, I think Alice and other pattern-based chatbots where already much better then that. I have seen them confused for people in IRC chats more than 10 years ago. Still, it seems to me the older issue of "lack of context" is still there even if the current results are very impressive. I would be curious to see what happens if asking to change the tone ("could you answer more briefly/tersely/verbosely/whatever?").

YeGoblynQueenne 6y ago

>> One trend that continues from the common sense is that GPT-3 is reluctant to express that it doesn’t know the answer. So invalid questions get wrong answers. More to the point, it's not that GPT-3 knows any answers to any questions. Like the article says, language models are trained to predict the next characters in a sequence. So, it predicts that a sequence that starts with "Who was president of the United States in 1700?" would continue with the sequence "William Penn was president of the United States in 1700". Seen another way, there's a correlation between the two strings. It's the highest correlation between the first string and any other string, so that's what ends up in the output. So it's more accurate to say that GPT-3 is guessing what the answer to a question might look like, than to say that it "knows" what the answer to a question, is. It's perhaps a subtle distinction but it's important to keep it in mind, especially in view of claims about "intelligence" and (Old Ones save us) "understanding". Basically, what all this tells us is that it's not possible to answer arbitrary questions consistently by guessing at them. Even if you get lucky, and you keep getting lucky, there will always be questions that you can't answer correctly and they will be many more than the questions you can answer correctly (e.g. we could generate an infinite number of common nonsense questions like how to sporgle a morgle, or who was the president of the united states since Biblical times etc). This of course is an old debate in AI: can we simulate a system of logic, without implementing its logic? e.g. could we perform correct arithmetic by memorising the results of calculations? Can prediction replace reasoning? Despite the unending hype generated by OpenAI about its models, the answer keeps being: a resounding no. While you can go a long way by training on ever larger data, it only takes a shallow search before obvious nonsense results are generated.

ypcx 6y ago
If prediction cannot replace reasoning, then how would you define reasoning? If reasoning is the process of inference of the most likely from the most similar known, then how does the multi-head attention transformer not fit that description?
- YeGoblynQueenne 6y ago
  >> If reasoning is the process of inference of the most likely from the most similar known, then how does the multi-head attention transformer not fit that description? I don't know, because I did not propose that definition of reasoning. "Reasoning" does not have a formal definition in AI, or Computer Science (neither does "intelligence" or "understanding") but, in general, when we speak of reasoning in those fields we mean a procedure that can derive the logical consequences of some premises, often in conjunction with some background theory. I'm happy to use this as an informal definition of reasoning, if you want.

lisper 6y ago

GPT-3 is just Eliza on steroids, and once you know this, it's pretty easy to spot that it's a bot. For example: > Q: Are there any animals with three legs? > A: No, there are no animals with three legs. I would expect a human to say something like, "There aren't any animals that are born with three legs (that I know of) but there are some four-legged animals who have lost a leg for some reason who now have three legs. I saw a video of a really cute three-legged dog on Youtube just the other day." NOTE: when I used the word "just" above, I in no way meant that to be pejorative. Both Eliza and GPT-3 are really cool, amazing technical achievements. But neither one represents much progress towards GAI (IMHO) except insofar as they show that naive approaches like this won't work. Which is really useful to know.

maherbeg 6y ago
I think that's giving too much credit to people. I think some people would answer that way, but a whole lot will just respond with exactly the answer that resolves the question.
- lisper 6y ago
  Eliza fooled a lot of people back in the day too.
slim 6y ago
as a human, I would have answered "I don't know"

thallukrish 6y ago

the fact that it answers questions like Q: Who was president of the United States in 1955? accurately itself will tell that it is an AI. I guess the whole idea that an AI shouldn't be different from a human to say that it is generally intelligent implies, the AI has to fake its answers to behave like a human. And this means it is not something a desirable trait for an AI as we have enough real humans who can easily sound more human than an AI.

f00zz 6y ago

Read a couple of blog posts on text generation with RNNs and came away with the impression that this is a glorified Markov chain text generator. Not sure why people seem to be expecting AGI to arise from this.

tlrobinson 6y ago

> Q: How many eyes does the sun have? > A: The sun has one eye. What if GPT-3 knows more than we do?

chrshawkes 6y ago
Nah... it's just text scraping horseshit. My foot doesn't have two eyes.

ijidak 6y ago

As far as I'm concerned this is phenomenal... I mean...wow. The use cases are practically limitless. All I saw from this post is that it doesn't work well with edge cases. But this smashes the Pareto principle. This is perfect as a tool for kids to get into programming. Something where they can see a big result with less effort, like programming in the 90's.

ctdonath 6y ago

The nonsense questions are actually handled quite well, continuing the sense of humor implied. I object to the author's expectation the response should be "I don't know" etc. Old jokes: Q: How high is a mouse when it spins? A: The higher, the fewer. Q: How many surrealists does it take to change a light bulb? A: Two, one to climb the giraffe and the other to fill the bathtub with brightly colored machine tools. Nonsense prose & poetry is an old literary challenge, notable example being Jabberwocky: https://www.poetryfoundation.org/poems/42916/jabberwocky https://www.poetryfoundation.org/poems/42916/jabberwocky

BurningFrog 6y ago

These are (almost) all isolated questions. I wonder if GPT-3 can hold a longer conversation where it remembers facts mentioned earlier and what it itself has said. In other words, does it exhibit any "theory of mind"? I'm guessing it would do quite poorly on that stuff.

IshKebab 6y ago

> In general, if you are trying to distinguish an AI from a human, you don’t want to ask it obscure trivia questions. GPT-3 is pretty good at a wide variety of topics. Surely you could tell it isn't human because it knows too much trivia?

bshanks 6y ago

I can see how this sort of thing might be a useful component of an AGI. One function could be helping to generate lots of training examples for other subcomponents along the lines of chess AI self-play; this could even be involved in "bootstrapping" another subcomponent from something that starts out with a preference for organizing things into a full-blown reasoning agent. Another function could be as an 'intuition' generating a few mostly-right starting points solutions that a reasoning subcomponent could then choose among, and then fix up. These things seem to have about the level of coherence of dreams. Which makes me conjecture, perhaps the mechanism that "directs" dreams serves a similar function as the above?

zelphirkalt 6y ago

In the "which is heavier" test, it simply always picked the second object as answer.

jobigoud 6y ago

Regarding common-sense, has anyone tried to feed it Winograd Schema Challenges ? Typically: "The trophy would not fit in the brown suitcase because it was too big (small). What was too big (small)?"

grumpopotamus 6y ago

What is the inference set up here? How does it remember what the previous question was?

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FrozenVoid 6y ago

It not really a turing test, its like probing the "associative memory" in a huge database for compatible strings, except that memory is just a map of indexes to indexes. You need to use more abstract and non-sense stuff to uncover the raw mechanism, but its still statistics not "understanding" what these words are(they're just indexes with high correlation to other indexes) and stringing them into run-on "generic templates".