11 ms·

ChatGPT fabricates lots of stuff, it's deceptive for common queries, but for programming related output, it's easily verifiable and delivers as an extremely val

• loveparade 4y ago
  It's easily verifiable, but it may still waste time. I've had many cases where ChatGPT makes up functions that do exactly what I need, but then I find out these functions don't actually exist. This may not happen very often for super popular languages like Python or Javascript where training data is huge, but it happens all the time for the long-tail of languages. In those cases, it would've been faster for me to do a regular search. I do agree with the overall point though. If you understand when to use it and when it's more likely to give you nonsensical answers, it can save a huge amount of time. But when I ask it about a topic that I don't know enough about to immediately verify the answer myself I'm forced to double check the answers for validity, which kind of defeats the purpose. The best queries to ChatGPT are cases where I know what the answer should look like, I just forgot the syntax or some details. Bash scripts or Kubernetes manifests are examples here, I know them, I just keep forgetting the keywords because I only touch them every few weeks. And don't get me started about asking ChatGPT about more general topics in e.g. economics or finance. What you get is a well-written summary of popular news and reddit opinions, which is dangerous if it's presented as "the truth" - The big mistake here is that the training procedure assumes that the amount of data correlates with correctness, which isn't true for many topics that involve politics or similar kinds of incentives where people and news spread what conveniently benefits them and gets clicks.
  • wildpeaks 4y ago
    Wasting time and having to be constantly vigilant is exhausting and a slippery slope that makes it easier to fall for deceptive content and settling for "I don't know, it's probably close enough" instead of insisting on precision and accuracy. Humans take a lot of shortcuts (such as believing more easily the same facts presented with a confident tone) and the "firehose of bs" exploits it: this was already the case before generative AI, but AI amplifies the industrial-scale imbalance between the time needed to generate partially incorrect data and the amount of time/energy required to validate.
    • discreteevent 4y ago
      Agreed that it is a slippery slope. Programming is understanding - like writing or teaching is understanding. To really understand something, we must construct it ourselves. We will be inclined to skip this step. This comment sums it up well: > Salgat 8 days ago > The problem with ML is that it's pattern recognition, it's an approximation. Code is absolute, it's logic that is interpreted very literally and very exactly. This is what makes it so dangerous for coding; it creates code that's convincing to humans but with deviations that allow for all sorts of bugs. And the worst part is, since you didn't write the code, you may not have the skills (or time) to figure out if those bugs exist https://news.ycombinator.com/item?id=34140585 https://news.ycombinator.com/item?id=34140585
      • MetaWhirledPeas 4y ago
        > To really understand something, we must construct it ourselves. I think the real power of these bots will be to lead us down this path, as opposed to it doing everything for us. We can ask it to justify and explain its solution and it will do its best. If we're judicious with this we can use it to build our own understanding and just trash the AI's output.
    • alpaca128 4y ago
      How is that worse than having to look at every online post's date to estimate whether the solution is out of date? Or two StackOverflow results where one is incorrectly marked as duplicate and in the other the person posting the answer is convinced that the question is wrong. ChatGPT can completely cut out the online search and give an answer directly about things like compiler errors, and elaborate further on any detail in the answer. I think that 2-3 further GPT generations down the line it will be worth the time for some applications. The problem I see is less the overall quality of responses but people overestimating on where it can be used productively. But that will always be a problem with new tech, see Tesla drivers who regularly take a nap in the car because it didn't crash yet.
      • mannykannot 4y ago
  • janandonly 4y ago
    I am foreseeing a future in which programming language designers match the most sought after functions in google/bing/chatgpt and then implement those that do not yet exist because apparently there is a real need for those.
    • tgv 4y ago
      You can also call it an artificially created need. Many functions exist, but have a different name.
    • VirusNewbie 4y ago
      Yes, I had the same thought. LLM’s might be instrumental in new language design. If it can understand the most common structures being used, it makes sense to build libraries, macros, or language features.
  • weird-eye-issue 4y ago
    It does this for Python and JS too
  • atmosx 4y ago
    I agree, chatGPT3 shines when the operator has domain knowledge. Otherwise it's a hit or miss.
  • bambax 4y ago
    I agree. ChatGPT is really really bad. It just makes up stuff and wraps its fabrications in an air of authority. A "bullshit sandwich" if you will. When one tells people this we get the reply "but so do random blogs! or reddit comments!". Well yes, but they're just random blogs and reddit comments, often peppered with syntactic and spelling mistakes, non sequiturs, and other absurdities. Nobody would take them seriously. ChatGPT is very different. It doesn't say "this random redditor says this, and this other random redditor says the exact opposite, so IDK, I'm just a machine, please make up your mind". What it says is "this is the absolute truth that I, a 'large language model', have been able to extract from the vast amount of information I have been trained on. You can rely on it with confidence." I'm sorry to sound hyperbolic but this cannot end well.
    • int_19h 4y ago
      ChatGPT doesn't say anything of the sort. In fact, it will vehemently insist that what it says is not necessarily true or accurate if you challenge it.
      • bambax 4y ago
        I'm sorry but this is demonstrably false. I have posted examples of this on HN before. Yes, if you tell ChatGPT that it's wrong, in some cases it says "I'm sorry" and tries again (and produces some other random guess). But if you ask it "are you sure?" it invariably affirms that yes, it's sure and it's in the right.
        • int_19h 4y ago
          Hm, you're right. I'm pretty sure that it wasn't so gung-ho when I played with it earlier, but now even very explicit instructions along the lines of "you should only answer "yes" if it is absolutely certain that this is the correct answer" still give this response. Ditto for prompts like "is it possible that your answer was incorrect?"
    • whodev 4y ago
      I like bouncing my code problems off ChatGPT, it can give me an answer and I don't feel bad if I forgot something simple. The issue is I've had it give me completely wrong code only for it to be like "I'm sorry" and provide a second incorrect response.
  • throwaway4aday 4y ago
    Using a purpose built (or trained I guess) model for code generation would likely have better results. GitHub copilot is useful for this reason. I find ChatGPT for code is mainly useful if you want to instruct it in natural language to make subsequent changes to the output.
  • themk 4y ago
    If you follow up about the nonexistent function, it will often implement it for you. The other thing that I've had success with is asking for references for the information, which will often link you to the relevant docs.
  • rmbyrro 4y ago
    If you ask, there's a good chance ChatGPT can create that function for you. Just tell it: "That function `xyz()` doesn't exist in the library, can you write it for me?"
• Dopameaner 4y ago
  I second this about chatGPT fabrications. When I was going through Tim Roughdarden's YT courses. I almost always have to double check its answers.
• Night_Thastus 4y ago
  It does such a good job at giving answers that sound right, and are almost correct. I could imagine losing many hours from a ChatGPT answer. And if you have to go through the trouble to verify everything it says to make sure it's not just making crap up, then imo it loses much value as a tool.
  • idontwantthis 4y ago
    But so do people: I spent an hour yesterday trying regexps that multiple people on Stackoverflow confirmed would definitely do what I needed, and guess what? They did not do what I needed. Same with copilot. Sometimes it's ludicrously wrong in ways that sound good. I still have to do my job and make sure they are right. But it's right or right enough to save me significant effort at least 75% of the time. Right enough to at least point me in the right direction or inspire me at least 90% of the time.
    • chx 4y ago
      and then one day https://mobile.twitter.com/Dereklowe/status/1599035870308618241 https://mobile.twitter.com/Dereklowe/status/1599035870308618... happens and people die.
      • nonethewiser 4y ago
        One day what happens? A person uses it to encourage topical application of a toxic material and publishes the results? How is ChatGPT enabling this? All of that is very possible without ChatGPT. The damaging part is deciding to do it.
        • chx 4y ago
          They released a zero day for a security hole in the human brain. That's what ChatGPT is. The security hole is well known and described perhaps the most understandable format is the book Thinking Fast And Slow which describes, ah, if I try to explain I will surely botch but perhaps put it this way: how things that appear more credible will be deemed credible because of the "fast" processes in our brains. In this particular case, ChatGPT will write something nonsensical which people will accept more easily because of the way it is written. This is inevitable and extremely dangerous.
• twayt 4y ago
  The key is that it is way faster and has a broader set of knowledge than a human. Being an editor is often easier and more productive than being both a single generator and editor
  • est 4y ago
    > Being an editor is often easier This 100%. ChatGPT can play an interesting role by separating duties in a process of productivity. ChatGPT can generate tons of true/false suggestions very fast and understandable by humans. Sometimes this helps a lot.
    • twayt 4y ago
      On a related note, I've personally observed that it also helps a lot with: 1. Generating (or simply repeating) obvious ideas in a domain that I am not an expert in 2. (With some prompting) Generating creative ideas in a domain that I am familiar with 3. Generating obvious ideas in a domain I'm familiar with when I'm too tired to think or preoccupied Not only do you get a productivity boost by being an editor but it also complements human energy cycles
    • ThrowawayR2 4y ago
      The downside is the risk of atrophying one's own mental ability to generate such suggestions if excessively relied upon. Given my druthers, I'd prefer to be a generator of text ChatGPT would want to absorb than to be a consumer of the mystery meat it is regurgitating.
• smalley 4y ago
  Maybe its better in some programming languages, but my experience with verilog/systemVerilog output is that it generates a design with flaws almost every time (but very confidently). If you try to correct it with prompting it comes up with reasonable sounding responses about what its fixing then just creates more wild examples. One pretty consistent way to see this is to ask for various very simple designs like a n-bit adder, it will almost always do something logically incorrect or syntactically incorrect with the carry in or carry out
  • Gigachad 4y ago
    ChatGPT has acted as an advanced rubber duck for me. It outputs a lot of bullshit but so often it gives me the prompt or way of thinking needed to move on. And it’s so much faster than posting on stack overflow or some irc. It doesn’t abuse you for asking dumb questions either.
    • mtrower 4y ago
      That's an interesting approach to consider, thanks!
• Blackthorn 4y ago
  I tested chatgpt with some domain specific stuff and found it so wrong on the fundamentals that I immediately lost trust in any of its output for learning. I would not trust it to explain anything eBPF related reliably. You are more likely to get something that is extremely wrong or, worse, subtly wrong.
• pjerem 4y ago
  Have you tried a query like this ? Add documentation to this method : [paste a method in any language] For me the results have been impressive. It’s even more impressive if you are not English speaking because it explains what the code does but also translates your domain terms in your own language. More than code generation I see a really concrete application in having autogenerated and up to date documentation of public methods. It could be generated directly in your code or only by your IDE to help you in absence of human written documentation. Other interesting things it can does is basic code review by proposing a « better » code and explaining what and why it changed something. It can also try to rewrite a given code in another language. I haven’t tried a lot of things due to the limitations in response size but for what I tested, it looks like it is able to convert the bulk of the work. While I’m not really convinced by code generation itself (a la copilot) I truly think that GPT can be a really powerful tool for IDE editors if used cleverly, especially to add meaning to unclear, decade old codebases from which original contributors are long gone. And knowing that what is hard is not writing but reading code, I see GPT to be a lot more useful here than helping writing 10 lines in a keystroke.
  • tommica 4y ago
    Just tried this out, and this is great! As you say, code-generation is iffy, but for documentation this is something that can really help with.
  • riffraff 4y ago
    Is this really valuable documentation? A common advice for documentation is "why not how", I'm not sure you can do "why" by looking at the "how". You can do javadoc style params, and there's some value there,but not much.
    • pjerem 4y ago
      > A common advice for documentation is "why not how", I'm not sure you can do "why" by looking at the "how". You are right. It’s the rule when you write the doc. But when you are let alone in an unknown codebase, having your IDE summarize the "what" in the auto completion popup could be really useful. Especially in codebases with wrong naming conventions.
• ergonaught 4y ago
  I had a lot of fun with ChatGPT’s wholly fabricated but entirely legitimate-sounding descriptions of different Emacs packages (and their quite detailed elisp configuration options) for integrated cloud storage, none of which exist. I’m not sure that fabricated nonsense would actually make Bing’s results any worse than they are today. “It’s okay I don’t mind verifying all these answers myself” is an odd sort of sentiment, and also inevitably going to prove untrue in one sense or another.
  • brookst 4y ago
    Well if it could generate the code, you wouldn’t necessarily care if they existed before your query.
    • ergonaught 4y ago
      If it generated the code, I would have to audit that code for correctness/safety/etc. Or, more likely, I would just lazily assume everything is fine and use it anyway, until one day the unexamined flaws destroyed something costly in a manner difficult to diagnose because I didn't bother to actually understand what it was doing. There really should be more horror at the imminent brief and temporary stint of humans as editors, code reviewers, whatever, over generative AI mechanisms (temporary because that will be either automated or rendered moot next). I'm unaware of any functional human societies that have actually reached the "no one actually has to work unless they want to do so, because technology" state, so this is an interesting transition, for sure.
      • brookst 4y ago
        > Or, more likely, I would just lazily assume everything is fine and use it anyway, until one day the unexamined flaws destroyed something costly in a manner difficult to diagnose because I didn't bother to actually understand what it was doing. Well yeah, I'm right there with you. But that feels a lot like any software, open or closed source. Human programmers on average are better than AI programming today, but human programmers aren't improving as fast as AI is. Ten years from now, AI code will be able to destroy your data in far more unpredictable and baroque ways than some recent CS grad. > I'm unaware of any functional human societies that have actually reached the "no one actually has to work unless they want to do so, because technology" state, so this is an interesting transition, for sure. This is a really interesting thought. Are we seeing work evaporate, or just move up the stack? Is it still work if everyone is just issuing natural language instructions to AI? I think so, assuming you need the AI's output in order to get a paycheck which you need to live. Then again, as a very long time product manager, I'm relatively unfazed by the current state of AI. The hundreds of requirements docs I've written over decades of work were all just prompt engineering for human developers. The exact mechanism for converting requirements to product is an implementation detail ;)
• jjeaff 4y ago
  The insidious part about chatGPT getting things wrong is that it is a superb bullshitter. It gives you answers with 100% confidence and believable explanations. But sometimes the answers are still completely wrong.
  • btgeekboy 4y ago
    Knowing little about how ChatGPT actually works, is there perhaps a variable that could be exposed, something that would represent the model's confidence in the solution provided?
    • ailef 4y ago
      It's not available for ChatGPT but the other GPT models can expose the probability for each generated token, which can serve as a proxy for confidence. Tuning the temperature and topP parameters you can also make the model avoid low probability completions (useful for less creative use cases where you need exact answers).
      • TuringTest 4y ago
        > It's not available for ChatGPT but the other GPT models can expose the probability for each generated token, which can serve as a proxy for confidence. A proxy for confidence in what exactly? Language models represent closeness of words, so a high probability would only express that those words are put together frequently in the corpus of text; not that their meanings are at all relevant to the problem at hand. Am I wrong?
        • ailef 4y ago
          In cases where you ask GPT-3 questions that have a clear correct answer, I think you can use the probability to judge how correct the answer is. For example, when asking "How tall is Mount Everest?" I would want the completion "Mount Everest is ____ meters above sea level." to have a very high probability for the ____ tokens. This is because I'm operating under the assumption that sequences of words that appear often in the training set are more likely to represent something correct (otherwise you might as well train on random words). This only holds if the training set is big enough that you can estimate correctly (e.g. if the training set is small a very rare/wrong phrase may appear very often). Maybe confidence was the wrong word, but for this kind of questions I would trust a high-probability answer way more than a low one. For questions belonging to very specific subjects, where training material is scarce, the model might have very skewed probabilities so they become less useful.
• weatherlite 4y ago
  > I hope Bing dominates Google and stackoverflow in this Google will probably build the same thing. Stackoverflow can suffer though...
  • ssdspoimdsjvv 4y ago
    But paradoxically, OpenAI can't let StackOverflow disappear, because in the end I suppose it's one of ChatGPT's main sources for programming content.
    • kolinko 4y ago
      For now, but perhaps we are at a level where enough knowledge is there that future solutions can be inferred from the past ones and documentation/code of libraries available on the internet.
  • palata 4y ago
    I believe the exact opposite. If one could prove that text has not been generated by an AI, that would have immense value. StackOverflow has a built-in validation process ("mark as the solution"), which says that some human found that it solved the problem. Doesn't mean it's correct, but still, that's something. I really wonder what impact ChatGPT will have on search engines. I could imagine that the first 4 pages of Google/Bing results end up being autogenerated stuff, and it will just make it harder to find trustworthy information.
• ChrisRR 4y ago
  ChatGPT is adamant that "Sunday" has a T in it. It could generate a python script that counted the days of the week with the letter T, but still insisted that Sunday had a T Edit: Scratch that. I just tried again and now it says that saturday doesn't have a T in it
  • astrange 4y ago
    It doesn’t consistently know words have individual letters since it’s trained using byte pair encodings. This is one reason earlier versions of it couldn’t generate rhymes.
• Roark66 4y ago
  When it works it is great. I've been using it instead of Google a lot too, but when it makes mistakes it requires someone familiar with a subject to detect it. I'm not sure if it is ready to be used as as a search engine by everyone. For example recently I asked it for the best way to search in an mbox file on arch Linux. It proceeded to recommend a number of tools including mboxgrep. When I asked how to install it on arch it gave me a standard response using the package manager, but mboxgrep is not an arch package. It isn't even an aur package. It requires fetching the source and building it by yourself(if I remember correctly one has to use an older version of gcc too). None if it was mentioned by chatgpt. This is not the first time BTW, there was another software it recommended that Debian doesn't know about, when I asked it another time.
• wolpoli 4y ago
  When ChatGPT serve me broken code, I would paste the errors back in and ChatGPT would try to make corrections. I don't see why ChatGPT couldn't do that itself with the right compiler, saving me from being a copy and paste clerk.
• yosito 4y ago
  I found ChatGPTs answers relatively accurate for explaining programming related queries, feeding it documentation and asking questions related to that, etc. But I've also tried to use it for travel and health related queries. For travel queries, it confidently tells me the wrong information, "Do most restaurants in Chiang Mai accept credit cards?" got "Yes, most restaurants in Chiang Mai accept credit cards!", which is completely false. Also got wildly inaccurate information about the quality of drinking water. And for health related queries, it tells me the same weasel-worded BS that I get on health spam blogs. I tried to dig out more information regarding sources of both travel and health related information, but ChatCPT simply said it doesn't know the details of the sources of information. I think a new implementation of ChatGPT is worth exploring though, one that cites sources and gives links to further information, and also one that has the ability to somehow validate it's responses for accuracy.
• peatfreak 4y ago
  > wasting time looking up the manuals God forbid!
  • arcturus17 4y ago
    I think we should let this C era meme die, the manuals are often terrible. I'm currently working with the AWS SDK Python documentation and it's a hot pile of garbage from all points of view (UX, info architecture, technical detail, etc.). Python lang docs are "kind-of-OK" but when someone raves about them I'm left scratching my head. Information is not always well-organized, examples are hit-and-miss, parameter and return types not always clear, etc. Referencing docs as a programmer is generally a nightmare and a time sink, and it's the one use case where ChatGPT is slowly becoming indispensable crutch for me. I can ask for very specific examples that are not included in the docs, or that cannot be included in the docs, for example combinatorial in nature: "how can I mock this AWS SDK library by patching it with a context manager"? Occasionally it will hallucinate, but even if it gets it 8/10 times right - and it's higher than that in practice - it will prove revolutionary at least for this use case.
    • danielbln 4y ago
      I'm amazed by how divisive it is. I've also been using it to significantly increase my productivity, be that documenting things or having it mutate code via natural language or various other tasks. I feel that if you keep in mind that hallucination is something that can happen, then you can somewhat mitigate that by prompting it in certain ways. E.g. asking for unit tests to verify generated functions, among other things. I find this tool so useful, that I scratch my head when I read about how dismissive some people are of it.
    • int_19h 4y ago
      I think one of the reasons why Python got such a reputation for good docs is because its primary competitors back in the day were Perl and Ruby. Ruby has horrible documentation to this day, and Perl has extensive docs that are difficult to navigate; in comparison with either, Python was definitely superior.
    • 4y ago
• elurg 4y ago
  I asked it how to convert a cell value to an unix timestamp in google sheets and it told to use the "UNIX_TIMESTAMP" and even provided an example. The function does not exist, it's entirely made up. What's weirder is that when I told it that the answer was wrong it provided a different solution that was correct.
• bob_theslob646 4y ago
  >hope Bing dominates Google and stackoverflow in this. Where do you think it got the information?
• twelve40 4y ago
  where are they going to get a steady fresh firehose of data comparable to stackoverflows? who are the magical entities that will be feeding them all these inputs for bing to claim all the fame?
• Tycho 4y ago
  It's very useful for writing and explaining regular expressions. But the holy grail would be if it could write all my unit tests...