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GPT-4 gets a B on my quantum computing final exam
- dwaltrip 4y ago> In general, I’d say that GPT-4 was strongest on true/false questions and (ironically!) conceptual questions—the ones where many students struggled the most. It was (again ironically!) weakest on calculation questions, where it would often know what kind of calculation to do but then botch the execution. It'd be great if chain-of-thought / show-your-work type prompts became the default for anything involving complex, multi-step calculations or logic. GPT-4 would have almost certainly gotten a higher score on the calculation questions if those methods were used.
- tkamat29 4y agoEh, even when asked specifically to show it's work GPT-4 still frequently makes calculation errors. It's just one of the limitations of current LLMs, and can easily be solved by integration with Wolfram, or even just a basic calculator.
- ZeroGravitas 4y agoTrue/false questions on an exam seem a bit lazy, is that common?
- techwiz137 4y agoIn my country, yes. In fact because the True/False were there, or to circle the correct answer, I was in this way given a hint of what the correct answer is. Had I needed to think of it, I wouldn't have managed to graduate high school. Full disclose, I graduated with something close to a D, but in actuality we are graded from 2(F) to 6(A) and my HS diploma says 3.97. And it is largely fictitious, in reality I was closer to 3 and less.
- TheCycoONE 4y agoMultiple choice and true false questions were fairly common in my undergraduate experience, particularly in first year courses. Often they were Scantron forms for maximum laziness.
- hgsgm 4y agoI never saw a scantron at my college. I thought UTAustin was an elite school.
- CrazyStat 4y agoUniversity prestige is primarily based on research productivity, which doesn't necessarily correlate positively with quality of teaching.
- hombre_fatal 4y agoEven so, I don't see what a scantron exam tells you about the quality of a professor and class.
- timy2shoes 4y agoThe enrollment at UT Austin is ~50K. No way you can grade that many tests by hand. Source: I went to UT for grad school and was a TA.
- MengerSponge 4y agoIt's safe to assume the enrollment of Prof. Aaronson's Quantum Computing course isn't 50k.
- timy2shoes 4y agoThank you Captain Obvious. The parent comment was about classes at UT in general, not about one specific class.
- MengerSponge 4y agoI suppose we can generalize my statement too. I imagine that most courses at UT have fewer than 50k students enrolled.
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- tennisflyi 4y agoAbsolutely!
- twic 4y agoIt's a quantum computing exam, the trick is you have to be able to answer both true and false at once.
- Sharlin 4y ago|true> + |false>
- kaesar14 4y agoThis is pretty incredible. I guess the thing that we have to keep in mind is that we really can't compete with an AI that understands natural language this well and also has the entirety of the internet as its reference materials. Maybe we need to accept that or rework our definition of what makes humans special
- hgsgm 4y agoMore that most undergrad colleges only teach and test regurgitation because the profs don't care about education.
- jakeinspace 4y agoI took the graduate version of this course, and thankfully did better on this exam than GPT-4. It was a fairly rigorous course, and getting an A required about 20 hours per week of work.
- scotty79 4y ago> ... required about 20 hours per week of work. Of thinking or of remembering?
- jakeinspace 4y agoThere were weekly problem sets. The questions on these tended to be a bit more in depth than the midterm/exam questions.
- kaesar14 4y agoFwiw Scott Aaronson is maybe the most well respected researcher in this field. I don't think this is a case of some shitty professor asking his students to regurgitate useless information
- moonchrome 4y agoHave you actually tried using GPT 4 and 3.5 ? I'd say 3.5 could be called a regurgitation machine with a few tricks, GPT 4 seems to apply concepts and feels like showing signs of human level intelligence. If the rate of progress continues for a few years we are collectively fucked.
- pubby 4y agoWhen I was growing up in the 2000s, it was required to learn a foreign language in school. I took Spanish but dropped the class after a year, thinking that when I grew up, computers would be able to translate text far better humans could. Would you believe it, transformers were invented ten years later. I wonder if it's worth learning anything anymore.
- cypress66 4y agoMachine translation isn't super human yet. But yes, it's probably only a few years away.
- ben_w 4y agoIt might not be super human in the sense of beating the C2 standard, but it sure knows more German than I do. And Spanish, and Greek, and Esperanto, and… well, everything. But I've been really trying with that German.
- sour-taste 4y agoI moved to Japan recently so have been trying to learn the language. Im atrociously bad and dream of the day when I can read a sentence without getting tripped up on kanji, grammar, etc. I mentioned this to a coworker who has been studying for several years and she said she just uses Google translate for everything. Even with her pretty good japanese, translate is better and faster than she is for doing things like going through forms, letters, etc. We may reach a point where computers are good enough that they beat all but native speakers, maybe.
- wizzwizz4 4y agoI don't get why people are so optimistic about machine translation. Computers can get explicit meaning across – that's obvious to anyone who understands linear algebra, information theory, and linguistics. But many aspects of translation (puns, tone, cultural context) aren't just about mapping from one vector space to another. A human, no matter how fluently bilingual, would have to think about the problem, and the current systems don't think. If we keep working on them, these systems will likely get better and better at low-level translation (including translating idioms), but no machine translation system currently in existence could translate the 逆転裁判 games to Ace Attorney games. Perhaps computers can do it – I don't see a theoretical reason they shouldn't be able to – but it would take a fundamentally different approach.
- IanCal 4y agoIt seems they just passed the questions in, which is totally fine but I'd just add that this gives you pretty much a lower bound of performance. I think it's worse if you try and make it output very small responses, and does a lot better if it can output a lot (chain of thought). I'm continually astonished at how well gpt4 can handle problems with literally no additional work, and how much you can improve it with some small help. Edit I asked question 1m but said it was an expert in QM and was there to explain the answer to test questions followed by answering them and it gets it right with a page or so of proof (please don't attack my use of the word proof, I'm a lay man - this also explains my failure to fix the numbering, latex editing on a phone is not my forte). I've not checked it, but it gets the right answer. https://figshare.com/articles/preprint/GPT4_answers_a_QM_question/22589293 https://figshare.com/articles/preprint/GPT4_answers_a_QM_que...
- pclmulqdq 4y agoAn LLM being able to pass your graduate-level exam almost certainly means that your exam is bad. Lots of lazy professors do things like this (true/false and multiple choice answers, very soft questions, etc.), and the presence of GPTs should help them understand that this is not sufficient for evaluating someone's knowledge of a highly technical topic.
- kaesar14 4y agoScott Aaronson is one of the best professors and researchers in this field in the world.
- H8crilA 4y agoAnd the test is actually rather easy. It's an undergraduate test.
- jacquesm 4y agoIt's probably not 'easy' for the average human out there. I would expect >> 90% of humanity to fail that test.
- InitialLastName 4y agoI have highly technical graduate and undergraduate degrees (in CS-adjacent field) and a decade of experience doing software development part time, but no direct experience with quantum computing (or much beyond an undergraduate physics class and an intro CS class in terms of directly related study), and consider myself a better-than-average test-taker. I could get 1D, 1E, 1F and 1T by intuition, 1J by actual knowledge, 1P by tautology, and had roughly no shot at the open-ended questions.
- jacquesm 4y ago> much beyond an undergraduate physics class and an intro CS class in terms of directly related study That's puts you in < 1% of the population right there.
- arthurcolle 4y agoI tried the first one on GPT-3.5-turbo and it got the answer wrong haha. Goes to show you how much better GPT-4 is... GPT-3.5-TURBO: --------------------------- True. A pure state of n qubits is described by an n-dimensional complex unit vector, also known as a quantum state vector. In Dirac notation, a pure state of n qubits can be represented as: |ψ⟩ = a_0|0⟩ + a_1|1⟩ + ... + a_(2^n-1)|2^n-1⟩ where a_i are complex numbers and |i⟩ represents the i-th computational basis state. The normalization condition |a_0|^2 + |a_1|^2 + ... + |a_(2^n-1)|^2 = 1 must also be satisfied. (hallucination?) --------------------------- GPT-4: --------------------------- False. A pure state of n qubits is described by a 2^n-dimensional complex unit vector. In a quantum system, each qubit can be in a superposition of two basis states, so for n qubits, there are 2^n possible basis states in the overall Hilbert space. --------------------------- Interesting to note that with GPT-3.5-turbo, a single followup chain-of-reasoning prompt ("Let's think step by step", i.e. no introduction of a priming prompt like "Are you sure?" or "Why are you wrong?") helps the model identify the correct answer: GPT-3.5-TURBO: --------------------------- Sure, let's break it down step by step: Qubits: A qubit is the fundamental unit of quantum information. It is a quantum analogue to the classical bit. While a classical bit can take one of two values, 0 or 1, a qubit can be in a superposition of both 0 and 1 states simultaneously. Basis states: For a single qubit, there are two basis states, often denoted as |0> and |1>. A qubit can be in any linear combination (superposition) of these basis states, represented as α|0> + β|1>, where α and β are complex numbers, and the sum of the magnitudes squared (|α|^2 + |β|^2) equals 1. Multiple qubits: When you have a system of n qubits, each qubit can be in a superposition of its basis states. The overall state of the n-qubit system is described by the tensor product of the individual qubit states. The number of basis states in the combined system is equal to the product of the number of basis states of each individual qubit. n-dimensional vector: For n classical bits, you would indeed need an n-dimensional vector to describe their state. However, with n qubits in a quantum system, the number of basis states grows exponentially, as opposed to linearly in the classical case. 2^n-dimensional complex unit vector: As we mentioned earlier, each qubit can be in a superposition of two basis states. Therefore, for n qubits, there are 2^n possible basis states. The overall state of an n-qubit system is represented by a 2^n-dimensional complex unit vector, with each component corresponding to the probability amplitude of one of the 2^n basis states. In summary, a pure state of n qubits is described by a 2^n-dimensional complex unit vector, not an n-dimensional one. ---------------------------
- jen729w 4y agoThis is obviously very cool, but at this point — who knows what I’ll say in a year — my concern with these LLMs is that they’re in the uncanny valley. Here’s one passing a very difficult test. Amazing! Now, rely on it to build a nuclear doohickey for a power station or a multi-billion dollar device for CERN or anything really and, well, no. So humans still have to check the output, and now we’re in that situation where humans driving a Tesla on autopilot who are supposed to be 100% aware of the road aren’t, because they get lazy and doze off, and now the car crashes and whoops. No negativity towards AI here. It’s amazing and it’ll change the future. But we need to be careful on the way.
- mupuff1234 4y agoAlso today humans need to check the output, code reviews etc. Maybe in the near future humans can just focus on the reviewing and testing part.
- CalRobert 4y agoSure, but we'll get lazy.
- SketchySeaBeast 4y agoHumans are going to want to do the worst parts of the job?
- cyberlurker 4y agoHumans used to go in coal mines.
- SketchySeaBeast 4y agoThey still do. But that job hasn't gotten worse, it's always been the same level of suck.
- skinnydennys 4y ago
- davnicwil 4y agoLook, it's impressive yes or yes but is it that surprising that a system like an LLM does well on exams? What is an exam? It's an attempt to test that you have consumed and understood large amounts of information and can apply it to novel (ish) situations, but in a very 'sandboxed' way that is just text-in-text-out. That's literally what these systems are specialists in doing. Is it maybe a bit like saying a driverless car can outperform most human drivers in a time trial on a race track? Not a trivial feat, to be sure, but also not that surprising perhaps once the basics are dialled in.
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- codetrotter 4y agoIt’s impressive and surprising. Imagine going back to the year 2021 and telling the good people of HN that in 2023 AI would be as advanced like it is now. Literally no one would have believed you in 2021 if you did.
- psychphysic 4y agoExactly everything is obvious in hindsight. No one called this, and certainly no one called it would be so easy to access.
- smiley1437 4y ago> No one called this, and certainly no one called it would be so easy to access. Thanks for capturing a point that I couldn't quite articulate myself as to why ChatGPT feels different - the ease of use. Literally a year ago I was planning to take a python programming course for ML, thinking that a deep understanding of code would be needed to make things work well. With GPT it's like...I just ask it things in English and it'll do it? The ease of access to LMMs is groundbreaking the way the simplicity of IOS launched the modern smartphone era. Even babies could use an Iphone. And now any child old enough to type sentences can use ChatGPT.
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- fauxpause_ 4y agoI find it very endearing that Scott opens his final exam with an optional ungraded question about your favorite QM interpretation.
- sebzim4500 4y agoI would very much like to see his analysis on which interpretations correlate with high scores. I would guess the more niche ones do, and Copenhagen and Many-Worlds will do the worst.
- tqi 4y agoI'm curious how the predictive aspect of LLMs can generate / "solve" equations. Is it purely "these inputs are most likely followed by this output", and thus needs to have actually seen the problem to get it right, or is it able to infer some of the rules underlying the operations?
- famouswaffles 4y agoPrediction is only the goal. The whole point of training is to learn what it takes to predict well and accurately. and that necessitates understanding and whatever else an LLM learns from the data.
- sebzim4500 4y agoClearly it doesn't need to have seen the exact input before because you can ask GPT-4 to add together two 6 digit numbers and it will get it right. More impressively, if you generate a random small neural network and then put some samples in the prompt it can do a surprisingly good job of predicting the result of putting other inputs into the network. Presumably doing something that looks a bit like gradient decent, see https://arxiv.org/pdf/2212.07677.pdf https://arxiv.org/pdf/2212.07677.pdf Solely in order to predict the next token, LLMs are learning an incredibly sophisticed model of both computation and the outside world.
- scotty79 4y agoProbably any human could get a B if it had book in hand, unlimited time and proper incentive.
- thomastjeffery 4y agoNow rephrase the questions and try again.
- asah 4y agoI've been re-engineering the pre-screening process for two companies (one F500, one startup) to account for LLMs. The trick (for now) is to include subtle clues that LLMs will miss but savvy/experienced humans will notice and incorporate into the answer. The goal of pre-screening is to knock-out the bottom 80-90% of candidates who are "perfectly decent" but not actually good enough to survive a battery of interviews.
- jimsimmons 4y agoFYI: Scott seems to have briefly worked at OpenAI.
- Sharlin 4y agoHe did, researching how to watermark LLM output so it can be distinguished from human writing AFAIK.
- theK 4y agoReading stuff like this, one thing I cannot stop wondering is this: If Ai can be trusted to do all the trivial tasks and if non trivial tasks require a scaffold of trivial practice, where are we going to keep finding the people qualified enough to actually do the non trivial stuff?
- nilsb 4y agoYou won't need people for that once AI systems start improving themselves.
- theK 4y agoSo who will then certify them?
- somewhat_drunk 4y agoIt's AI all the way down...
- awestroke 4y agoCertify them? What for?
- theK 4y agoImportant work. It is a typical quality control architecture in the modern world to have an independent party evaluate whether one can perform an important task or not. Typical examples would be SE vs PE licensing on structural engineering or the various bar exams.
- sebzim4500 4y agoOther AI systems, presumably.
- mkipper 4y agoThis is what worries me the most when it comes to job losses and downward pressure on wages. If we hit the point where a senior engineer reviewing the output from an AI can effectively replace a team with a senior engineer and 5 junior engineers, you’re right that it isn’t wise to simply replace all those junior engineers with the AI. Unless you’re confident that the AI will be able to replace that senior engineer soon, you _need_ junior engineers who can build up the experience needed to step into that role once the senior engineer moves on. But you _can_ get rid of 3 or 4 of those junior engineers. The remaining junior engineer(s) will still need mentorship from the senior engineer and will still do “trivial” work that needs oversight, but they will be able to pump that out at a high enough rate to replace a few of their pre-AI peers. Basically, I’d imagine the org chart at most companies will look pretty similar to now, except you’ll just have fewer people at each level.
- czbond 4y agoNow I just want to take this class!
- scrame 4y agoIsn't this more an indictment of current teaching and testing methods than a praise of LLMs? Like the old "you can't use a calculator on a test because you won't always have a calculator". Im old enough that my textbooks still had trig lookup tables when I was a kid. That seems silly now, but it was considered important at the time. I know slightly older people in publishing that used manual photosizers instead of just importing to photoshop. I remember being told multiple times that VR was going to fix programming because you could just visually move conditional blocks around. So we have smartphones and scratch and photoshop and whathaveyou, but... We still need people to draw and write and photograph and sculpt. we still need engineers to use the new models, and we still need mechanics to fix the computers and trains when they break. If GPT-4 can pass a test, maybe it's a better reference point, or maybe a better study aid. Like taped language lessons vs reading pronunciation diagrams. You'll never obviate people from the equation that is defined by people,regardless of that singularity that is just around the corner like cold fusion and self driving cars and the cure for the common cold.
- hackererror404 4y agoIt's impressive on the surface... But give me Google and I too can pass some extremely challenging tests that I actually know nothing about. If someone told you I passed the "bar" exam, you would be impressed. If they then said, he had google and lots of time. You wouldn't be that impressed anymore. The impressive thing here is that AI can read and answer questions... it's not overly impressive that it can use information found online and reconstruct that a bit.
- SanderNL 4y agoPassing a bar exam is not possible by using Google and using an hour or two extra..
- sebzim4500 4y agoCan you find question 5 online? I can't, but maybe I'm just bad at googling.
- red75prime 4y agoOK, try to do it like GPT does: by saying the first thing that comes to your mind. You can have any amount of preliminary training.
- Imnimo 4y agoT/F question 1d says: >Google's recent quantum supremacy experiment demonstrated the successful use of quantum error-correction. How "recent" is the experiment in question? Would it have been publicized before GPT-4's training cutoff?
- tudorw 4y agoI've been testing it's understanding of Ted Nelson's enfilades, it knew what I was asking, and implementations of that are to my knowledge scarce, in fact it specs out the whole Xanadu(r) system pretty well and I've been asking it how we would implement that today and its answers look sound, I'm not qualified to take that and deploy it, but the packages and functionality were real, and the code read like a solution, I've had it build a basic node-strut tensigrity structure that looks legit and an interesting conversation about hyper spatial nanocubes.
- sudosysgen 4y agoIt's impressive, but the vast majority of these questions have already been asked essentially verbatim online, and been answered. I'm of the opinion that only tests that were designed for students that were allowed to access the internet should be used as a benchmark for LLMs, and this wouldn't be one.
- sampo 4y agoHere is the course syllabus: https://apps.cs.utexas.edu/apps/sites/default/files/classes/syllabus/syllabus-fall2019.pdf https://apps.cs.utexas.edu/apps/sites/default/files/classes/... There course lecture notes were linked to in the blog post, but also: https://www.scottaaronson.com/qclec.pdf https://www.scottaaronson.com/qclec.pdf This is a first course in quantum computing, and doesn't require a background in physics. For what it is, it certainly looks like challenging course, though. University of Texas at Austin must have some good students. Still, a lot (a majority) of the exam questions were "word problems", or problems where you take a short mathematical step, based on you being familiar with the concepts and definitions. In short, the type of problems where GPT's pattern matching and filling does well. For the few problems where a longer calculation (actually solving a math/physics problem) was required, GPT performed poorly.
- iskander 4y agoWhile the test itself may not have been posted online, read the individual questions. They are extremely common topics on the internet and I wouldn't be surprised if the contents of this test are 100x+ replicated across different QM material that's available.
- up2isomorphism 4y agoThis just means this exam can be solved by searching internet and compiling the collections in a presentable format. For human this is not a easy task because first they need to memorized these information, second, they somehow need to not resort to intensive matrix multiplication in order to say something meaningful. Even the results from human and chatgpt might look similar but they are very different. This is somewhat similar to comparing finding a interpolation polynomial that is close to sin(x) to just save all the values in the considered interval and do a table lookup.
- sebzim4500 4y agoIf all GPT-4 is doing is searching the internet and compiling the results, then how come I can ask it to add two 6 digits numbers that appear nowhere on the internet and it will get it right? Sure, it's not exactly amazing that a computer can add numbers but it does show that it is doing more than pattern matching.
- civilized 4y ago> To the best of my knowledge—and I double-checked—this exam has never before been posted on the public Internet, and could not have appeared in GPT-4’s training data. Sure, but you can Google the answers to most of the questions. Personally I've accepted that GPT does learn and apply concepts present in its training data, and all of this would be. Learning is part of intelligence but not the whole thing. (I thought this was why, decades ago, most of the research in this general area rebranded itself from the ambitious goal of artificial intelligence to the more humble but accessible goal of machine learning.) The interesting question now is how much better it can get, in difficulty it can tackle, reliability, and quality of explanations. How long before AI can answer questions whose answers are not widely known, for which templates do not already exist? Personally, I believe this will not be some trivial matter of simply scaling up more. The waters of intelligence are much deeper than that. It's hard to believe given the rapid one two punch of GPT 3.5 and 4, but we are about to stall. If I'm wrong, mark this comment and make fun of me in five years. Wrong or right, it's going to be interesting!
- munchler 4y ago> you can Google the answers to most of the questions 1) Students can Google the answers also, but neither students nor GPT-4 are allowed to Google the answers during the test, so it remains a fair comparison. 2) Many of the questions require calculations, which are far less Googleable.
- civilized 4y ago1) It's not possible to fairly compare human intelligence with something that can memorize gigabytes of text and hold it in non-volatile memory. 2) Months ago, in my earliest interactions with ChatGPT, I asked it to solve math problems. It gave me back stuff with LaTeX formatting. Obviously it had, if not these exact problems, similar templates in its training set. Recently it was shown that GPT is completely incapable of solving Codeforces problems that appeared after it was trained. Whatever is going on here is interesting but less impressive than it looks.
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- mabbo 4y agoThis is the kind of thing that has Google terrified, and rightly so. Nobody needs a chatbot to pass exams. But what percentage of your Google searches are to answer some obscure question? This thing can answer most basic questions about quantum computing and 10,000 other topics. In the last 24 hours, I've had ChatGPT solve 3 weird questions about querying PrestoDB, help me get my Bluetooth headphones to work (I needed to press down and hold the power button!) and it gave me some brainstorming ideas around what to do for mother's day (it's coming up soon non-British people). Before I'd have Googled those things and spent five times longer to solve them- seeing ads on each search I made.