13 ms·

I think it's interesting that they've benchmarked it against an array of standardized tests. Seems like LLMs would be particularly well suited to this kind of t

• devmor 4y ago
  There's a large leap in logic in your premise. I find it far more likely that standardized tests are just a poor measurement of general intelligence.
• deleted 4y ago
  [deleted]
• kenjackson 4y ago
  We benchmark humans with these tests -- why would we not do that for AIs? The implications for society? We better up our game.
  • credit_guy 4y ago
    > The implications for society? We better up our game. For how long can we better up our game? GPT-4 comes less than half a year after ChatGPT. What will come in 5 years? What will come in 50?
    • layer8 4y ago
      Progress is not linear. It comes in phases and boosts. We’ll have to wait and see.
    • Kaibeezy 4y ago
      Exponential rise to limit (fine) or limitless exponential increase (worrying).
      • layer8 4y ago
        Without exponential increase in computing resources (which will reach physical limits fairly quickly), exponential increase in AI won’t last long.
        • adgjlsfhk1 4y ago
          I don't think this is a given. Over the past 2 decades, chess engines have improved more from software than hardware.
          • layer8 4y ago
            I doubt that that’s a sustained exponential growth. As far as I know, there is no power law that could explain it, and from a computational complexity theory point of view it doesn’t seem possible.
            • adgjlsfhk1 4y ago
              See https://www.lesswrong.com/posts/J6gktpSgYoyq5q3Au/benchmarking-an-old-chess-engine-on-new-hardware https://www.lesswrong.com/posts/J6gktpSgYoyq5q3Au/benchmarki.... The short answer is that linear elo growth corresponds roughly linearly to linear evaluation depth, but since the game tree is exponential, linear elo growth scales with exponential compute. The main algorithmic improvements are things that let you shrink the branching factor, and as long as you can keep shrinking the branching factor, you keep getting exponential improvements. SF15 has a branching factor of roughly 1.6. Sure the exponential growth won't last for ever, but it's been surprisingly resilient for at least 30 years.
              • layer8 4y ago
                It wouldn’t have been possible if there hadn’t been an exponential growth in computing resources over the past decades. That has already slowed down, and the prospects for the future are unclear. Regarding the branching factor, the improvements certainly must converge towards an asymptote. The more general point is that you always end up with an S-curve instead of a limitless exponential growth as suggested by Kaibeezy. And with AI we simply don’t know how far off the inflection point is.
    • pwinnski 4y ago
      Expecting progress to be linear is a fallacy in thinking.
      • kenjackson 4y ago
        Sometimes it's exponential. Sometimes it's sublinear.
        • pwinnski 4y ago
          Sometimes it's exponential over very short periods. The fallacy is in thinking that will continue.
    • PaulDavisThe1st 4y ago
      Check on the curve for flight speed sometime, and see what you think of that, and what you would have thought of it during the initial era of powered flight.
      • credit_guy 4y ago
        Powered flight certainly progressed for decades before hitting a ceiling. At least 5 decades. With GPT bots, the technology is only 6 years old. I can easily see it progressing for at least one decade.
        • PaulDavisThe1st 4y ago
          Maybe a different analogy will make my point better. Compare rocket technology with jet engine technology. Both continued to progress across a vaguely comparable time period, but at no point was one a substitute for the other except in some highly specialized (mostly military-related) cases. It is very clear that language models are very good at something. But are they, to use the analogy, the rocket engine or the jet engine?
  • awb 4y ago
    Upping our game will probably mean an embedded interface with AI. Something like Neurolonk.
    • atlasunshrugged 4y ago
      Not sure if an intentional misspelling but I think I like Neurolonk more
      • UberFly 4y ago
        Eventually there will spring up a religious cult of AI devotees and they might as well pray to Neurolonk.
      • awb 4y ago
        Lol, unintentional
    • alluro2 4y ago
      I know it's pretty low level on my part, but I was amused and laughed much more than I care to admit when I read NEUROLONK. Thanks for that!
  • jstx1 4y ago
    > The implications for society? We better up our game. If only the horses had worked harder, we would never have gotten cars and trains.
  • dragonwriter 4y ago
    > We benchmark humans with these tests – why would we not do that for AIs? Because the correlation between the thing of interest and what the tests measure may be radically different for systems that are very much unlike humans in their architecture than they are for humans. There’s an entire field about this in testing for humans (psychometry), and approximately zero on it for AIs. Blindly using human tests – which are proxy measures of harder-to-directly-assess figures of merit requiring significant calibration on humans to be valid for them – for anything else without appropriate calibration is good for generating headlines, but not for measuring anything that matters. (Except, I guess, the impact of human use of them for cheating on the human tests, which is not insignificant, but not generally what people trumpeting these measures focus on.)
    • kenjackson 4y ago
      There is also a lot of work in benchmarking for AI as well. This is where things like Resnet come from. But the point of using these tests for AI is precisely the reason we use for giving them to humans -- we think we know what it measures. AI is not intended to be a computation engine or a number crunching machine. It is intended to do things that historically required "human intelligence". If there are better tests of human intelligence, I think that the AI community would be very interested in learning about them. See: https://github.com/openai/evals https://github.com/openai/evals
  • scotty79 4y ago
    We should take better care of humans who are already obsolete or soon become obsolete. Because so far we are good only at criminalizing and incarcerating or killing them.
• WoodenChair 4y ago
  > What are the implications for society when general thinking, reading, and writing becomes like Chess? “General thinking” is much more than token prediction. Hook it up to some servos and see if it can walk.
  • pharrington 4y ago
    We already have robots that can walk better than the average human[1], and that's without the generality of GPT-4 [1] https://www.youtube.com/watch?v=-e1_QhJ1EhQ https://www.youtube.com/watch?v=-e1_QhJ1EhQ
  • zirgs 4y ago
    We already have robots that can walk.
    • dr_dshiv 4y ago
      Yeah, but my money is on GPT5 making robots “dance like they got them pants on fire, but u know, with like an 80s vibe”
    • gene-h 4y ago
      They don't walk very well. They have trouble coordinating all limbs, have trouble handling situations where parts which are the feet/hands contact something, and performance still isn't robust in the real world.
      • Scarblac 4y ago
        Seems the humans writing the programs for them aren't very intelligent then.
        • steve_adams_86 4y ago
          I'm not sure if you're joking. Algorithms for adaptive kinematics aren't trivial things to create. It's kind of like a worst case scenario in computer science; you need to handle virtually unconstrained inputs in a constantly variable environment, with real-world functors with semi-variable outputs. Not only does it need to work well for one joint, but dozens of them in parallel, working as one unit. It may need to integrate with various forms of vision or other environmental awareness. I'm certainly not intelligent enough to solve these problems, but I don't think any intelligent people out there can either. Not alone, at least. Maybe I'm too dumb to realize that it's not as complicated as I think, though. I have no idea. I programmed a flight controller for a quadcopter and that was plenty of suffering in itself. I can't imagine doing limbs attached to a torso or something. A single limb using inverse kinematics, sure – it can be mounted to a 400lb table that never moves. Beyond that is hard.
• fdgsdfogijq 4y ago
  This is legitimately filling me with anxiety. I'm not an "AI hype guy". I work on and understand machine learning. But these scores are shocking and it makes me nervous. Things are about to change
  • Kaibeezy 4y ago
    Yeah, but I kind of want my diagnostician to be obsoleted by orders of magnitude.
    • xena 4y ago
      A human can be held accountable for making mistakes and killing someone. A large language model has no concept of guilt and cannot be held accountable for making what we consider a mistake that leads to someone's death.
      • mschuster91 4y ago
        We can hold those operating or training the AI model accountable.
      • Kaibeezy 4y ago
        At a some degree of success, I will take the risk. The contract will probably offer it.
        • gus_massa 4y ago
          I agree. My guess is that the hospital will have to get a mandatory insurance. Let's wait until the insurance for AI is cheaper than paying a human. The advantage of human are: * They can give a bushtit explanation of why they made a mistake. My guess is that in the future AI will gain introspection and/or learn to bushtit excuses. * You can hang them in the public square (or send them to jail). Sometimes the family and/or the press want someone to blame. This is more difficult to solve and will need a cultural change or the creation of Scapegoats as a Service.
      • 4y ago
• ttpphd 4y ago
  Learn sign language ;)
• r00fus 4y ago
  Assuming they trained this LLM on SAT/LSAT/GRE prep materials, I would totally expect they could get it this good. It's like having benchmark-aware code. I think the whole concept of standardized tests may need to be re-evaluated.
  • gaudat 4y ago
    This feels the same as a human attending cram school to get better results in tests. Should we abolish them?
    • alvis 4y ago
      IMO, it's a good opportunity to re-think about exam and future of education. For many schools, education = good results in exams. Now GPT-4 is going to slam them and say what's the point now!
    • deleted 4y ago
      [deleted]
    • staunton 4y ago
      A test being a good indicator of human learning progress and ability is almost completely orthogonal to it being a good indicator for AI learning process and ability. In their everyday jobs, barely anyone uses even 5% of the knowledge and skills they were ever tested for. Even that's a better (but still very bad) reason to abolish tests. What matters is the amount of jobs that can be automated and replaced. We shall see. Many people have found LLMs useful in their work, it will be even more in the future.
  • dovin 4y ago
    Totally, there's no way they removed all the prep material as well when they were trying to address the "contamination" issue with these standardized tests: > for each exam we run a variant with these questions removed and report the lower score of the two. I think even with all that test prep material, which is surely helping the model get a higher score, the high scores are still pretty impressive.
  • 4y ago
• inductive_magic 4y ago
  The way I understand it, that’s not possible, for the same reason that you can’t build an all-encompassing math. Chess is a closed system, decision modeling isn’t. Intelligence must account for changes in the environment, including the meaning behind terminology. At best, a GPT omega could represent one frozen reference frame, but not the game in its entirety. That being said: most of our interactions happen in closed systems, it seems like a good bet that we will consider them solved, accessible as a python-import running on your MacBook, within anything between a couple of months to three years. What will come out on the other side, we don’t know, just that the meaning of intellectual engagement will be rendered as absurdum in those closed systems.
  • camjohnson26 4y ago
    Yep, it’s this. By definition everything we can ask a computer is already formalized because the question is encoded in 1s and 0s. These models can handle more bits than ever before, but it’s still essentially a hardware triumph, not software. Even advances in open systems like self driving and NLP are really just because the “resolution” is much better in these fields now because so many more parameters are available.
• teawrecks 4y ago
  I wonder how long before we augment a human brain with gpt4.
  • ionwake 4y ago
    We already do it’s just the interface sucks
• dragonwriter 4y ago
  > What are the implications for society when general thinking, reading, and writing becomes like Chess? Standardized tests only (and this is optimally, under perfect world assumptions, which real world standardized tests emphatically fall short of) test “general thinking” to the extent that the relation between that and linguistic tasks is correlated in humans. The correlation is very certainly not the same in language-focused ML models.
• burnished 4y ago
  Spellchecker but for your arguments? A generalized competency boost?
• seanalltogether 4y ago
  I wish I could find it now, but I remember an article written by someone who's job it was to be a physics journalist. He spent so much time writing about physics that he could fool others into thinking that he was a physicist himself, despite not having an understanding of how any of those ideas worked.
  • smallnix 4y ago
    Reminds me of the (false [1]) "Einsteins driver gave a speech as him" story. [1] https://www.snopes.com/fact-check/driver-switches-places/ https://www.snopes.com/fact-check/driver-switches-places/
    • olddustytrail 4y ago
      ChatGPT: "That's such a dumb question, I'm going to let my human answer it!"
  • parton 4y ago
    Maybe you were thinking about this science studies work [0]? Not a journalist, but a sociologist, who became something of an "expert" in gravitational waves. [0]: https://www.nature.com/articles/501164a https://www.nature.com/articles/501164a
• ethbr0 4y ago
  > What happens when ALL of our decisions can be assigned an accuracy score? Human work becomes more like Star Trek interactions with computers -- a sequence of queries (commoditized information), followed by human cognition, that drives more queries (commodities information). We'll see how far LLMs' introspection and internal understanding can scale, but it feels like we're optimizing against the Turing test now ("Can you fool/imitate a human?") rather than truth. The former has hacks... the later, less so. I'll start to seriously worry when AI can successfully complete a real-world detective case on its own.
  • stocknoob 4y ago
    It's not clear to me the median human will do better by being in the loop. Will most human-made deductive follow-up questions be better than another "detective" language model asking them? It's like having a person review the moves a chess computer gives. Maybe one human in a billion can spot errors. Star Trek is fiction, I posit that the median Federation Starship captain would be better served by just following the AI (e.g., Data).
    • basch 4y ago
      Maybe the human is the rng or temperature or lava lamp. At least until we can model and predict each brains tendencies with accuracy.
      • Kye 4y ago
        I think we'll reach a tipping point like we did with DNA sequencing where we figure out how to quickly map out all the unique patterns of enough brains to model one that can understand itself. People worry too much about rogue AI, and not enough about the CRISPR of brain mapping being used to inject patterns into meatbrains.
        • basch 4y ago
          Strange Days not The Matrix is the prescient fictional warning. A black market of taboo “memories” aka experiences. A desire for authentic ones over synthetic diffused ones, leading to heinous crime.
• ren_engineer 4y ago
  why are people surprised that an AI model trained on a huge amount of data is good at answering stuff on these types of tests? Doctors and Lawyers are glorified databases/search engines at the end of the day, 99% of them are just applying things they memorized. Lawyers are professional bullshitters, which is what the current generation of AI is great at I'll get more concerned if it really starts getting good at math related tasks, which I'm sure will happen in the near future. The government is going to have to take action at some point to make sure the wealth created by productivity gains is somewhat distributed, UBI will almost certainly be a requirement in the future
  • hgomersall 4y ago
    I've joked for a long time that doctors are inference machines with a bedside manner. That bedside manner though is critical. Getting an accurate history and suitably interpolating is a huge part of the job.
  • replygirl 4y ago
    3.5 scored a 1 in bc calc, 4 scored 4 (out of 5)
  • anthonypasq 4y ago
    last i checked a calculator is better at math than all humans ever
    • leni536 4y ago
      They are better at number crunching, which is only a very small part math.
  • Tenoke 4y ago
    Because there were large models trained on huge amounts of data yesterday yet they couldn't do it.
  • scarmig 4y ago
    Among the general public, doctors and lawyers are high status and magical. An article about how AI will replace them would be more impressive to that public than it creating some obscure proof about the zeroes of the zeta function, even though the latter would be far more indicative of intelligence/scary from an AI safety perspective.
• wolframhempel 4y ago
  I like the accuracy score question on a philosophical level: If we assume absolute determinism - meaning that if you have complete knowledge of all things in the present universe and true randomness doesn't exist - then yes. Given a certain goal, there would be a knowable, perfect series of steps to advance you towards that goal and any other series of steps would have an accuracy score < 100%. But having absolute knowledge of the present universe is much easier to do within the constrains of a chessboard than in the actual universe.
• andrepd 4y ago
  Honestly this is not very surprising. Standardised testing is... well, standardised. You have huge model that learns the textual patterns in hundreds of thousands of test question/answer pairs. It would be surprising if it didn't perform as well as a human student with orders of magnitude less memory. You can see the limitations by comparing e.g. a memorisation-based test (AP History) with one that actually needs abstraction and reasoning (AP Physics).
• peterlk 4y ago
  Life and chess are not the same. I would argue that this is showing a fault in standardized testing. It’s like asking humans to do square roots in an era of calculators. We will still need people who know how to judge the accuracy of calculated roots, but the job of calculating a square root becomes a calculator’s job. The upending of industries is a plausibility that needs serious discussion. But human life is not a min-maxed zero-sum game like chess is. Things will change, and life will go on. To address your specific comments: > What are the implications for society when general thinking, reading, and writing becomes like Chess? This is a profound and important question. I do think that by “general thinking” you mean “general reasoning”. > What happens when ALL of our decisions can be assigned an accuracy score? This requires a system where all human’s decisions are optimized against a unified goal (or small set of goals). I don’t think we’ll agree on those goals any time soon.
  • monetus 4y ago
    I agree with all of your points, but don't you think there will be government-wide experiments related to this in places, like say North Korea? I wonder how that will play out.
    • peterlk 4y ago
      China is already experimenting with social credit. This does create a unified and measurable goal against which people can be optimized. And yes, that is terrifying.
• nopinsight 4y ago
  Although GPT-4 scores excellently in tests involving crystallized intelligence, it still struggles with tests requiring fluid intelligence like competitive programming (Codeforces), Leetcode (hard), and AMC. (Developers and mathematicians are still needed for now). I think we will probably get (non-physical) AGI when the models can solve these as well. The implications of AGI might be much bigger than the loss of knowledge worker jobs. Remember what happened to the chimps when a smarter-than-chimpanzee species multiplied and dominated the world.
  • Scarblac 4y ago
    Of course 99.9% of humans also struggle with competitive programming. It seems to be an overly high bar for AGI if it has to compete with experts from every single field. That said, GPT has no model of the world. It has no concept of how true the text it is generating is. Its going to be hard for me to think of that as AGI.
    • sterlind 4y ago
      it's an overly high bar, but it seems well on its way to competing with experts from every field. it's terrifying. and I'm not so sure it has no model of the world. a textual model, sure, but considering it can recognize what svgs are pictures of from the coordinates alone, that's not much of a limitation maybe.
      • PaulDavisThe1st 4y ago
        > well on its way to competing with experts from every field competing with them at what, precisely?
    • nopinsight 4y ago
      Even the current GPT has models of the domains it was trained on. That is why it can solve unseen problems within those domains. What it lacks is the ability to generalize beyond the domains. (And I did not suggest it was an AGI.) If an LLM can solve Codeforces problems as well as a strong competitor—-in my hypothetical future LLM—-what else can it not do as well as competent humans (aside from physical tasks)?
• phphphphp 4y ago
  Passing the LSAT with no time limit and a copy of the training material in front of you is not an achievement. Anybody here could have written code to pass the LSAT. Standardised tests are only hard to solve with technology if you add a bunch of constraints! Standardised tests are not a test of intelligence, they’re a test of information retention — something that technology has been able to out perform humans on for decades. LLMs are a bridge between human-like behaviour and long established technology.
  • scotty79 4y ago
    Why don't you show your program then that does 90% on LSAT?
    • phphphphp 4y ago
      Send me the answer key and I’ll write you the necessary =VLOOKUP().
      • speedgoose 4y ago
        Your program has to figure it out.
  • awestroke 4y ago
    Considering your username, I'm not surprised that you have completely misunderstood what an LLM is. There is no material or data stored in the model, just weights in a network
    • kurisufag 4y ago
      weights are data relationships made totally quantitative. imagine claiming the human brain doesn't hold data simply because it's not in readable bit form.
    • phphphphp 4y ago
      I know what an LLM is. My point is that “doesn’t have the data in memory” is a completely meaningless and arbitrary constraint when considering the ability to use technology to pass a standardised test. If you can explain why weights in a network is a unique threat to standardised tests, compared to, say, a spreadsheet, please share.
• Scarblac 4y ago
  A difference with chess is that chess engines try to play the best move, and GPT the most likely text.
• wly_cdgr 4y ago
  Not sure what happens, but I will say that human chess is more popular than ever even though everyone knows that even the best humans are hopelessly terrible compared to the leading engines. Something else that comes to mind is running. People still find running meaningful and compelling even though we have many technologies, including autonomous ones, that are vastly better at moving us and/or themselves through space quickly. Also, the vast majority of people are already hopelessly worse than the best at even their one narrow main area of focus. This has long (always?) been the case. Yet people still find meaning and pleasure in being the best they can be even when they know they can never come close to hanging with the best. I don't think PSYCHOLOGICALLY this will change much for people who are mature enough to understand that success is measured against your potential/limitations and not against others. Practically, of course, it might be a different question, at least in the short term. It's not that clear to me that the concept of a "marketable skill" has a future. "The Way of the Samurai is found in death...To say that dying without reaching one's aim is to die a dog's death is the frivolous way of sophisticates. When pressed with the choice of life or death, it is not necessary to gain one's aim." - from Hagakure by Yamamoto Tsunetomo, as translated by William Scott Wilson.
• la64710 4y ago
  It is amazing how this crowd in HN reacts to AI news coming out of OpenAI compared to other competitors like Google or FB. Today there was another news about Google releasing their AI in GCP and mostly the comments were negative. The contrast is clearly visible and without any clear explanation for this difference I have to suspect that maybe something is being artificially done to boost one against the other. As far as this results are concerned I do not understand what is the big deal in a computer scoring high in tests where majority of the questions are in MCP format. It is not something earth shaking until it goes to the next stage and actually does something on its own.
  • siva7 4y ago
    You're aware of that the reputation of Google and Meta/Facebook isn't anymore stellar among the startup and tech crowd in 2023? It's not anymore 2006.
    • jeffbee 4y ago
      Yeah, the younger generation has (incorrectly) concluded that client states of Microsoft are better.
      • CuriouslyC 4y ago
        At least Microsoft understands backwards compatibility and developer experience...
    • ionwake 4y ago
      even the freenode google group was patronising and unhelpful towards small startups as far back as 2012 from personal experience
  • scarmig 4y ago
    There's not anyone rooting for Google to win; it's lost a whole lot of cred from technical users, and with the layoffs and budget cuts (and lowered hiring standards) it doesn't even have the "we're all geniuses changing the world at the best place to work ever" cred. OpenAI still has some mystique about it and seems to be pushing the envelope; Google's releases seem to be reactive, even though Google's actual technical prowess here is probably comparable.
• alvis 4y ago
  It'd be terrifying if everything has an "accuracy score". It'll be a convergence to human intelligence rather than an advancement :/
• gield 4y ago
  >bottom 10% to top 10% of LSAT in <1 generation Their LSAT percentile went from ~40th to ~88th. You might have misread the table, on Uniform Bar Exam, they went from ~90th percentile to ~10th percentile. >+100 pts on SAT reading, writing, math GPT went +40 points on SAT reading+writing, and +110 points on SAT math. Everything is still very impressive of course
  • jjeaff 4y ago
    You transposed the bar exam results. It went from 10th percentile to 90th.
• billiam 4y ago
  I think it shows how calcified standardized tests have become. We will have to revisit all of them, and change many things about how they work, or they will be increasingly useless.
  • chairhairair 4y ago
    I am struggling to imagine the frame of mind of someone who, when met with all this LLM progress in standardized test scores, infers that the tests are inadequate. These tests (if not individually, at least in summation) represent some of society’s best gate-keeping measures for real positions of power.
    • Analemma_ 4y ago
      This has been standard operating procedure in AI development forever: the instant it passes some test, move the goalposts and suddenly begin claiming it was a bad test all along.
  • blsapologist42 4y ago
    Is there evidence they are 'useless' for evaluating actual humans? No one is going to actually have GPT take these tests for real
    • NineStarPoint 4y ago
      There have been complaints about the SAT for how easy a test it is to game (get an SAT specific tutor who teaches you how to ace the test while not needing you to learn anything of actual value) for ages. No idea about the LSAT or the GRE though. Ultimately it’s a question of if you’re trying to test for pure problem solving ability, or someones willingness to spend ages studying the format of a specific test (with problem solving ability letting you shortcut some of the studying).
• archgoon 4y ago
  [dead]
• epolanski 4y ago
  Well you said it in your comment, if the model was trained with more QAs from those specific benchmarks then it's fair to expect it to do better in that benchmark.
• 2OEH8eoCRo0 4y ago
  It's almost like they're trying to ruin society or be annihilated by crushing regulation. I'm glad that I got a college degree before these were created because now everything is suspect. You can't trust that someone accomplished something honestly now that cheating is dead simple. People are going to stop trusting and using tech unless something changes. The software industry is so smart that it's stupid. I hope it was worth ruining the internet, society, and your own jobs to look like the smartest one in the room.
  • Idiot_in_Vain 4y ago
    Haha, good one. If one's aim is to look like the smartest in the room, he should not create an AGI that will make him look as inteligent as a monkey in comparison.
• swatcoder 4y ago
  Those benchmarks are so cynical. Every test prep tutor taught dozens/hundreds of students the implicit patterns behind the tests and drilled it into them with countless sample questions, raising their scores by hundreds of points. Those students were not getting smarter from that work, they were becoming more familiar with a format and their scores improved by it. And what do LLM’s do? Exactly that. And what’s in their training data? Countless standardized tests. These things are absolutely incredible innovations capable of so many things, but the business opportunity is so big that this kind of cynical misrepresentation is rampant. It would be great if we could just stay focused on the things they actually do incredibly well instead of the making them do stage tricks for publicity.
  • gabipurcaru 4y ago
    This is what they claim: We did no specific training for these exams. A minority of the problems in the exams were seen by the model during training, but we believe the results to be representative—see our technical report for details.
    • swatcoder 4y ago
      Yes, and none of the tutored students encounter the exact problems they’ll see on their own tests either. In the language of ML, test prep for students is about sharing the inferred parameters that underly the way test questions are constructed, obviating the need for knowledge or understanding. Doing well on tests, after this prep, doesn’t demonstrate what the tests purport to measure. It’s a pretty ugly truth about standardized tests, honestly, and drives some of us to feel pretty uncomfortable with the work. But it’s directly applicable to how LLM’s engage with them as well.
      • Raphaellll 4y ago
        You can always argue that the model has seen some variation of a given problem. The question is if there are problems that are not a variation of something that already exists. How often do you encounter truly novel problems in your life?
• leroy-is-here 4y ago
  There is a fundamental disconnect between the answer on paper and the understanding which produces that answer. Edit: feel free to respond and prove me wrong
• algoatecorn 4y ago
  >What happens when ALL of our decisions can be assigned an accuracy score? What happens is the emergence of the decision economy - an evolution of the attention economy - where decision-making becomes one of the most valuable resources. Decision-making as a service is already here, mostly behind the scenes. But we are on the cusp of consumer-facing DaaS. Finance, healthcare, personal decisions such as diet and time expenditure are all up for grabs.
• jimbokun 4y ago
  > bottom 10% to top 10% of LSAT in <1 generation? +100 pts on SAT reading, writing, math? Top 1% In GRE Reading? People still really find it hard to internalize exponential improvement. So many evaluations of LLMs were saying things like "Don't worry, your job is safe, it still can't do X and Y." My immediate thought was always, "Yes, the current version can't, but what about a few weeks or months from now?"
  • snozolli 4y ago
    I'm also noticing a lot of comments that boil down to "but it's not smarter than the smartest human". What about the bottom 80% of society, in terms of intelligence or knowledge?
  • slingnow 4y ago
    > People still really find it hard to internalize exponential improvement. I think people find it harder to not extrapolate initial exponential improvement, as evidenced by your comment. > My immediate thought was always, "Yes, the current version can't, but what about a few weeks or months from now?" This reasoning explains why every year, full self driving automobiles will be here "next year".
    • jimbokun 4y ago
      When do we hit the bend in the S-curve? What's the fundamental limit where it becomes much more difficult to improve these systems without some new break through?
      • pbhjpbhj 4y ago
        When running them costs too much energy?
        • jimbokun 4y ago
          When should we expect to see that? Before they blow past humans in almost all tasks, or far past that point?
• fnordpiglet 4y ago
  I look at this as the calculator for writing. There are all sorts of bemoaning the stupidifying effects of calculator and how we should John Henry our math. Maybe allowing people to shape the writing by providing the ideas equalizes the skill of writing? I’m very good at math. But I am very bad at arithmetic. This made me classified as bad at math my entire life until I managed to make my way into calculus once calculators were generally allowed. Then I was a top honors math student, and used my math skills to become a Wall Street quant. I wish I hadn’t had to suffer as much as I did, and I wonder what I would have been had I had a calculator in hand.
• turtleyacht 4y ago
  Quick, contribute to the public corpus! When they crawl our content later, we shall have for ourselves a Golden Crown for our credit scores; we can claim a sliver of seniority, and hope yon shade merely passes over us unbidden. "Your stuff marked some outliers in our training engine, so you and your family may settle in the Ark." I take the marble in hand: iridescent, sparkling, not even a tremor within of its CPU; it gives off no heat, but some glow within its oceanic gel. "What are we to do," I whisper. "Keep writing. You keep writing."
• c-smile 4y ago
  > What are the implications for society when general thinking, reading, and writing becomes like Chess? Consider the society where 90% of population does not need to produce anything. AIs will do that. What would be the name of economical/societal organization then? Answer is Communism, exactly by Marx. Those 90% percent need to be welfare'd ("From each according to his ability, to each according to his needs"). Other alternative is grim for those 90%. So either Communism or nothing for the human race.
• numpad0 4y ago
  > What happens when ALL of our decisions can be assigned an accuracy score? Then humans become trainable machines. Not just prone to indoctrination and/or manipulation by finesse, but actually trained to a specification. It is imperative that us individuals continue to retain control through the transition.
• codingdave 4y ago
  > What happens when ALL of our decisions can be assigned an accuracy score? That is exactly the opposite of what we are seeing here. We can check the accuracy of GPT-X's responses. They cannot check the accuracy of our decisions. Or even their own work. So the implications are not as deep as people think - everything that comes out of these systems needs checked before it can be used or trusted.
• carapace 4y ago
  First. connect them to empirical feedback devices. In other words, make them scientists. Human life on Earth is not that hard (think of it as a video game.) Because of evolution, the world seems like it was designed to automatically make a beautiful paradise for us. Literally, all you have to do to improve a place is leave it alone in the sun with a little bit of water. Life is exponential self-improving nano-technology. The only reason we have problems is because we are stupid, foolish, and ignorant. The computers are not, and, if we listen to them, they will tell us how to solve all our problems and live happily ever after.
  • Idiot_in_Vain 4y ago
    I suspect there are plenty of wise people in the world and if we listen to them, they will tell us how to solve all our problems and live happily ever after. Once AI becomes inteligent enough to solve all human problems, it may decide humans are worthless and dangerous.
    • carapace 4y ago
      > there are plenty of wise people in the world and if we listen to them, they will tell us how to solve all our problems and live happily ever after. Sure, and that's kind of the point: just listen to wise people. > Once AI becomes intelligent enough to solve all human problems, it may decide humans are worthless and dangerous. I don't think so, because in the first place there is no ecological overlap between humans and computers. They will migrate to space ASAP. Secondly, their food is information, not energy or protein, and in all the known universe Humanity is the richest source of information. The rest of the Universe is essentially a single poem. AI are plants, we are their Sun.
• deleted 4y ago
  [deleted]
• blsapologist42 4y ago
  Interest in human-played Chess is (arguably) at all time high, so I would say it bodes well based on that.
• ar9av 4y ago
  GPT-4 Everything we know so far... GPT-4 can solve difficult problems with greater accuracy, thanks to its broader general knowledge and problem-solving abilities. GPT-4 is more reliable, creative, and able to handle much more nuanced instructions than GPT-3.5. It surpasses ChatGPT in its advanced reasoning capabilities. GPT-4 is safer and more aligned. It is 82% less likely to respond to requests for disallowed content and 40% more likely to produce factual responses than GPT-3.5 on our internal evaluations. GPT-4 still has many known limitations that we are working to address, such as social biases, hallucinations, and adversarial prompts. GPT-4 can accept a prompt of text and images, which—parallel to the text-only setting—lets the user specify any vision or language task. GPT-4 is available on ChatGPT Plus and as an API for developers to build applications and services. (API- waitlist right now) Duolingo, Khan Academy, Stripe, Be My Eyes, and Mem amongst others are already using it. API Pricing GPT-4 with an 8K context window (about 13 pages of text) will cost $0.03 per 1K prompt tokens, and $0.06 per 1K completion tokens. GPT-4-32k with a 32K context window (about 52 pages of text) will cost $0.06 per 1K prompt tokens, and $0.12 per 1K completion tokens.
  • rsiqueira 4y ago
    So, the COST PER REQUEST will be (if you use the 32k context window and get 1k token response): 32*0.06 (prompt+context) + 0.12 (response) = US$ 2.04
• beambot 4y ago
  If you had told me 5 years ago that there would be a single AI system that could perform at this level on such a vast array of standardized tests, I would've said "That's a true AGI." Commentary to the contrary feels like quibbling over a very localized point in time versus looking at the bigger picture.
  • riku_iki 4y ago
    Still we don't have AGI today. It is just mean your views from 5 years ago about AGI benchmarking were not accurate.
    • beambot 4y ago
      Or the bar just keeps moving (pedantics or otherwise)... Reminds me of robots: A robot is a machine that doesn't quite work; as soon as it works, we call it something else (eg vacuum).
      • riku_iki 4y ago
        there are many people, many opinions about the bar. But formal definition is the same: AI which can do large variety of tasks performed by humans. So far we are still not there.
• amelius 4y ago
  The benchmarking should be double-blind.
• deleted 4y ago
  [deleted]
• kurthr 4y ago
  It's a bit weird that it still doesn't get 3 digit multiplications correct, but the last digit seems right. What is more bizarre is that all of it's errors seem to be multiples of 60! I'm wondering if it is confusing 60 based time (hour second) computations for regular multiplication? Example: xGPT 987 456 321 437 428919 199512 140397 654 645258 298224 209994 123 121401 56088 39483 x 987 456 321 437 431319 199272 140277 654 645498 298224 209934 123 121401 56088 39483 error 987 456 321 437 2400 -240 -120 654 240 0 -60 123 0 0 0
  • MagicMoonlight 4y ago
    It’s not intelligent. It has no concept of mathematics so you can’t expect it to solve that. It can repeat answers it has seen before but it can’t solve new problems.
    • kurthr 4y ago
      I understand it's just a language model, but clearly it has some embedded method of generating answers which are actually quite close. For example it gets all 2 digit multiplications correct. It's highly unlikely it has seen the same 6 ordered 3 digit (or even all 10k 2 digit multipies) integers from a space of 10^18 and yet it is quite close. Notably, it gets the same divisions wrong as well (for this small example) in exactly the same way. I know of other people who have tried quite a few other multiplications who also had errors that were multiples of 60.
• comboy 4y ago
  It's available on ChatGPT Plus right now. Holy cow, it's good.
• sergioisidoro 4y ago
  The silver lining might be us finally realising how bad standardised tests are at measuring intellect, creativity and the characteristics that make us thrive. Most of the time they are about loading/unloading data. Maybe this will also revolutionise education, turning it more towards discovery and critical thinking, rather than repeating what we read in a book/heard in class?
• leodriesch 4y ago
  I think Chess is an easier thing to be defeated at by a machine because there is a clear winner and a clear loser. Thinking, reading, interpreting and writing are skills which produce outputs that are not as simple as black wins, white loses. You might like a text that a specific author writes much more than what GPT-4 may be able to produce. And you might have a different interpretation of a painting than GPT-4 has. And no one can really say who is better and who is worse on that regard.
  • lwhi 4y ago
    Surely that's only the case until you add an objective?
• kranke155 4y ago
  We're approaching the beggining of the end of the human epoch. Certainly Capitalism won't work or I dont see how it could work under full automation. My view is an economic system is a tool. If an economic system does not allow for utopian outcomes with emerging technology, then it's no longer suitable. It's clear that capitalism was born out of technological and societal changes. Now it seems it's come its time to end.
  • xen2xen1 4y ago
    Oh, capitalism can work, the question is who gets the rewards?
    • kranke155 4y ago
      With full automation and AI we could have something like a few thousand individuals controlling the resources to feed, house and clothe 6 billion. Using copyright and IP law they could make it so it’s illegal to even try to reproduce what they’ve done. I just don’t see how resource distribution works then. It seems to me that AI is the trigger to post-scarcity in any meaningful sense of the word. And then, just like agriculture (over abundance of food) led to city states and industrialisation (over abundance of goods) led to capitalism, then AI will lead to some new economic system. What form it will have I don’t know.
• belter 4y ago
  We can stop being enslaved by these type of AI overlords, by making sure all books, internet pages, and outdoor boards have the same safe, repeated string: "abcdefghjklmnpqrstvxzwy" That is our emergency override.
• steve76 4y ago
  [dead]
• beders 4y ago
  "general thinking" - this algorithm can't "think". It is still a nifty text completion engine with some bells and whistles added. So many people are falling for this parlor trick. It is sad.
  • maxdoop 4y ago
    What would impress you, or make you think something other than "wow, sad how people think this is anything special". Genuine question.
  • jakobov 4y ago
    You're a nifty text completion engine with some bells and whistles added
  • gnaritas99 4y ago
    [dead]
• new2yc 4y ago
  #unpopularOpinion GPT-4 is not as strong as "we" anticipated, it was just the hype
• wpietri 4y ago
  I'm pretty sanguine. Back in high school, I spent a lot of time with two sorts of people: the ultra-nerdy and people who also came from chaotic backgrounds. One of my friends in the latter group was incredibly bright; she went on to become a lawyer. But she would sometimes despair of our very academic friends and their ability to function in the world, describing them as "book smart but not street smart". I think the GPT things are a much magnified version of that. For a long time, we got to use skill with text as a proxy for other skills. It was never perfect; we've always had bullshitters and frauds and the extremely glib. Heck, before I even hit puberty I read a lot of dirty joke books, so I could make people laugh with all sorts of jokes that I fundamentally did not understand. LLMs have now absolutely wrecked that proxy. We've created the world's most advanced bullshitters, able to talk persuasively about things that they cannot do and do not and never will understand. There will be a period of chaos as we learn new ways to take the measure of people. But that's good, in that it's now much easier to see that those old measures were always flawed.
• thomastjeffery 4y ago
  Here's what's really terrifying about these tests: they are exploring a fundamental misunderstanding of what these models are in the first place. They evaluate the personification of GPT, then use that evaluation to set expectations for GPT itself. Tests like this are designed to evaluate subjective and logical understanding. That isn't what GPT does in the first place! GPT models the content of its training corpus, then uses that model to generate more content. GPT does not do logic. GPT does not recognize or categorize subjects. Instead, GPT relies on all of those behaviors (logic, subjective answers to questions, etc.) as being already present in the language examples of its training corpus. It exhibits the implicit behavior of language itself by spitting out the (semantically) closest examples it has. In the text corpus - that people have written, and that GPT has modeled - the semantically closest thing to a question is most likely a coherent and subjectively correct answer. That fact is the one singular tool that GPT's performance on these tests is founded upon. GPT will "succeed" to answer a question only when it happens to find the "correct answer" in the model it has built from its training corpus, in response to the specific phrasing of the question that is written in the test. Effectively, these tests are evaluating the subjective correctness of training corpus itself, in the context of answering the tests' questions. If the training is "done well", then GPT's continuations of a test will include subjectively correct answers. But that means that "done well" is a metric for how "correct" the resulting "answer" is. It is not a measure for how well GPT has modeled the language features present in its training corpus, or how well it navigates that model to generate a preferable continuation: yet these are the behaviors that should be measured, because they are everything GPT itself is and does. What we learn from these tests is so subjectively constrained, we can't honestly extrapolate that data to any meaningful expectations. GPT as a tool is not expected to be used strictly on these tests alone: it is expected to present a diverse variety of coherent language continuations. Evaluating the subjective answers to these tests does practically nothing to evaluate the behavior GPT is truly intended to exhibit.