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About "people still thinking LLMs are quite useless", I still believe that the problem is that most people are exposed to ChatGPT 4o that at this point for my u

About "people still thinking LLMs are quite useless", I still believe that the problem is that most people are exposed to ChatGPT 4o that at this point for my use case (programming / design partner) is basically a useless toy. And I guess that in tech many folks try LLMs for the same use cases. Try Claude Sonnet 3.5 (not Haiku!) and tell me if, while still flawed, is not helpful. But there is more: a key thing with LLMs is that their ability to help, as a tool, changes vastly based on your communication ability. The prompt is the king to make those models 10x better than they are with the lazy one-liner question. Drop your files in the context window; ask very precise questions explaining the background. They work great to explore what is at the borders of your knowledge. They are also great at doing boring tasks for which you can provide perfect guidance (but that still would take you hours). The best LLMs (in my case just Claude Sonnet 3.5, I must admit) out there are able to accelerate you.

wslh 2y ago
Right, in simpler terms: The measure of LLMs success is how effectively they help you achieve your goal faster.
- antirez 2y ago
  Exactly, and right now the LLMs acceleration effect is a tool, not "give me the final solution". Even people that can't code, using LLMs to build applications from scratch, still have this tool mindset. This is why they can use them effectively: they don't stop at the first failed solution; they provide hints to the LLM, test the code, try to figure what's the problem (also with the LLM help), and so forth. It's a matter of mindset.
  - d0mine 2y ago
    btw, fusion has arrived by that definition: No reactors that would produce more energy than they consume, But net positive reactions have been achieved. Tasks where LLMs output is more than 1x are few and far between.
  - andrewaylett 2y ago
    > people that can't code These people may not be Software Engineers, but they are coding.
hdjjhhvvhga 2y ago
While Claude Sonnet is superior than 4o for most my use cases, there are still occasionally some specific tasks where it performs slightly better.
- antirez 2y ago
  Probably. But statistically to work with 4o is a lose of time for me. LLMs is like an investment: you write the prompts, you "work" with them. If the LLM is too weak, this is a lose of time. You need to have a return on the investment that is positive. With ChatGPT 4o / o1 most of the times for me the investment of time has almost zero return. Before Claude Sonnet 3.5 I already had a ChatGPT PRO account but never used it for coding since it was most of the times useless if not for throw away scripts that I didn't want to do myself or as a stack overflow replacement for trivial stuff. Now it's different.
  - airstrike 2y ago
    This mirrors my experience 100%. I'm not even sure why I still pay for OpenAI at this point. Claude 3.5 is just incredibly superior. And I totally agree on the point about dropping in context and asking very specific questions. I've had Claude pinpoint a bug in a 2k LOC module that I was struggling to find the cause for. After wasting a lot of time on it on my own, I thought "what the heck, maybe Claude can figure it out" and it did. It's objectively useful, even if flawed sometimes.
    - hanikesn 2y ago
      I'm curious. Can you go into more detail what kind of bug it found?
      - airstrike 2y ago
        I was writing a custom widget for iced (the Rust GUI library) and I was getting a panic due to some fancy logic I was trying to do. I guess the shortest description I can say is that it was a combination of what appeared to be a caching issue at first, but the real cause turned out to be some method shadowing where I was using a struct's method where I meant to use the trait's method. I had made the specific operation generic (moving it out of the struct and into a trait) but forgot to delete it from the struct, so I was calling the incorrect function. Claude pinpointed the cache issue immediately when I just dumped two files into the context and asked it: somewhere in my codebase I'm triggering a perform() on the editor but the next call on highlight() panics because `Line layout should be cached` what am I missing? do I need to do something after perform() to re-cache the layout? at first that seemed to fix the issue, but other errors persisted. so we kept debugging together until we found the root cause. either way I knew where to look thanks to its assistance
brookst 2y ago
I’m surprised you only have one use case. I use LLMs to research travel, adjust recipes, check biographies and book reviews, and many many more things.
minimaxir 2y ago
> Claude Sonnet 3.5 (not Haiku!) A very big surprise is just how much better Sonnet 3.5 is than Haiku. Even the confusingly-more-expensive-Haiku-variant Haiku 3.5 that's more recent than Sonnet 3.5 is still much worse.
mhh__ 2y ago
Hopefully things have narrowed but you can see from the trends data just how few people (API may be a different story) use claude relative to chatgpt.
- minimaxir 2y ago
  Brand awareness is a hell of a drug.
  - mhh__ 2y ago
    Indeed, although I find myself reaching for o1 more than Claude for matters other than programming, solely because it has better LaTeX (...)
dxbydt 2y ago
> best LLMs are able to accelerate you https://www2.math.upenn.edu/~ghrist/preprints/LAEF.pdf https://www2.math.upenn.edu/~ghrist/preprints/LAEF.pdf - this math textbook was written in just 55 days! Paraphrasing the acknowledgements - ...Begun November 4, 2024, published December 28, 2024. ...assisted by Claude 3.5 sonnet, trained on my previous books... ...puzzles co-created by the author and Claude ...GPT-4o and -o1 were useful in latex configurations...doing proof-reading. ...Gemini Experimental 1206 was an especially good proof-reader ...Exercises were generated with the help of Claude and may have errors. ...project was impossible without the creative labors of Claude The obvious comparison is to the classic Strang https://math.mit.edu/~gs/everyone/ https://math.mit.edu/~gs/everyone/ which took several *years* to conceptualize, write, peer review, revise and publish. Ok maybe Strang isn't your cup of tea, :%s/Strang/Halmos/g , :%s/Strang/Lipschutz/g, :%s/Strang/Hefferon/g, :%s/Strang/Larson/g ... Working through the exercises in this new LLMbook, I'm thinking...maybe this isn't going to stand the test of time. Maybe acceleration is not so hot after all.
- datadrivenangel 2y ago
  Going faster isn't good if the quality drops enough that overall productivity decreases... Infinite slop is only a good thing for pigs.
  - cruffle_duffle 2y ago
    Just use ChatGPT to summarize its own output. It’s like running your JPEG back through the JPEG compressor again!
- kianN 2y ago
  ^ This perfectly encapsulates the story I see every time someone digs into the details of any llm generated or assisted content that has any level of complexity. Great on the surface but lacks any depth, cohesive, or substance
- pton_xd 2y ago
  "The story of linear algebra begins with systems of equations, each line describing a constraint or boundary traced upon abstract space. These simplest mathematical models of limitation — each equation binding variables in measured proportion — conjoin to shape the realm of possible solutions. When several such constraints act in concert, their collaboration yields three possible fates: no solution survives their collective force; exactly one point satisfies all bounds; or infinite possibilities trace curves and planes through the space of satisfaction. This trichotomy — of emptiness, uniqueness, and infinity — echoes through all of linear algebra, appearing in increasingly sophisticated forms as our understanding deepens." Maybe I'm not the target audience, but... that really doesn't make me interested in continuing to read.
ninth_ant 2y ago
I think a lot of the confusion is in how we approach LLMs. Perhaps stemming from the over-broad term “AI”. There are certain classes of problems that LLMs are good at. Accurately regurgitating all accumulated world knowledge ever is not one, so don’t ask a language model to diagnose your medical condition or choose a political candidate. But do ask them to perform suitable tasks for a language model! Every day by automation I feed in the hourly weather forecast my home ollama server and it builds me a nice readable concise weather report. It’s super cool! There are lots of cases like this where you can give an LLM reliable data and ask it to do a language related task and it will do an excellent job of it. If nothing else it’s an extremely useful computer-human interface.
- rrix2 2y ago
  > Every day by automation I feed in the hourly weather forecast my home ollama server and it builds me a nice readable concise weather report. not to dissuade you from a thing you find useful but are you aware that the national weather service produces an Area Forecast Discussion product in each local NWS office daily or more often that accomplishes this with human meteorologists and clickable jargon glossary? https://forecast.weather.gov/product.php?site=SEW&issuedby=SEW&product=AFD&format=CI&version=1&glossary=1 https://forecast.weather.gov/product.php?site=SEW&issuedby=S...
  - ninth_ant 2y ago
    Doesn’t dissuade me at all, that’s a really neat service. I’m not American though, and even if my own country had a similar service I still enjoying tuning the results to focus on what I’m interested in. And it was just an example of the kinds of computer-human interfaces that are newly possible from this technology. Anytime you have data and want it explained in a casual way — and it’s not mission critical to be extremely precise — LLMs are going to be a good option to consider. More useful AGI-like behaviours may be enabled by combining LLMs with other technologies down the line, but we shouldn’t try to pretend that LLMs can do everything nor are they useless.
    - LtWorf 2y ago
1oooqooq 2y ago
yeah, they save as much time as finding a template with a good old search and using it.
uludag 2y ago
I don't think people finding LLMs useless is a good representation of the general sentiment though. I feel that more than anything, people are annoyed at LLM slop. Someone uses an LLM too much to write code, they create "slop," which ends up making things worse.
- gre 2y ago
  Yes but then they can prompt it to golf the code and most of the slop goes away. This sometimes breaks the code.
- antirez 2y ago
  Unfortunately complex tools will be misused by part of the population. There is no easy escape from that in the modernity of possibilities. Look at the Internet itself.
cruffle_duffle 2y ago
To get the most out of them you have to provide context. Treat these models like some kind of eager beaver junior engineer who wants to jump in and write code without asking questions. Force it to ask questions (eg: “do not write code yet, please restate my requirements to make sure we are in alignment. Are there any extra bits of context or information that would help? I will tell you when to write code”) If your model / chat app has the ability to always inject some kind of pre-prompt make sure to add something like “please do not jump to writing code. If this was a coding interview and you jumped to writing code without asking questions and clarifying requirements you’d fail”. At the top of all your source files include a comment with the file name and path. If you have a project on one of these services add an artifact that is the directory tree (“tree —-gitignore” is my goto). This helps “unaided” chats get a sense of what documents they are looking at. And also, it’s a professional bullshitter so don’t trust it with large scale code changes that rely on some language / library feature you don’t have personal experience with. It can send you down a path where the entire assumption that something was possible turns out to be false. Does it seek like a lot of work? Yes. Am I actually more productive with the tool than without? Probably. But it sure as shit isn’t “free” in terms of time spent providing context. I think the more I use these models, the more I get a sense of what it is good at and what is going to be a waste of time. Long story short, prompting is everything. These things aren’t mind readers (and worse they forget everything in each new session)
- layer8 2y ago
  You are right, but doing all that is incredibly cumbersome, at least to some people, which is why they don’t like working with LLMs.
  - simonw 2y ago
    That was one of the themes of my article: LLMs are power-user tools, mis-sold as "easy to use". To get great results out of them you need to invest a whole lot of under-documented and under-appreciated effort. https://simonwillison.net/2024/Dec/31/llms-in-2024/#llms-somehow-got-even-harder-to-use https://simonwillison.net/2024/Dec/31/llms-in-2024/#llms-som...
jsheard 2y ago
I swear these goalposts keep getting moved, I remember being told that GPT3.5 is a useless toy but the paid GPT4 is lifechanging, and now that GPT4 is free I'm told that it's a useless toy but paid o1 or paid Sonnet are lifechanging. Looking forward to o1 and Sonnet becoming useless toys, unlike the lifechanging o3.
- aetherson 2y ago
  You will also be dismayed to hear that a 2011 iPhone is no longer state-of-the-art, and indeed can't run most modern apps.
  - jpc0 2y ago
    GPT4 is a 13 year old technology? Compared to o1 and Sonnet 3.5? If someone told me an iPhone 4 is terrible but an iPhone 5 would definitely serve my needs, then when I get an iPhone 5 they say the same of the 6 you really want me to believe them a second time? Then a third time? Then a 4th? In the mean time my time and money is wasted?
  - scubbo 2y ago
    Holy false-equivalency, Batman! The definitions of "useless toy / lifechanging tool" are _not_ changing over time (or, at least, not over the timescale being explored here), whereas the expectations and requirements of processing power of a phone are.
    - aetherson 2y ago
      But in fact they are changing over time -- this is an expectations treadmill. When you get something newer and better, it highlights the flaws in what you had before.
      - scubbo 2y ago
        That is true _in general_, but not in this specific case (hence why I specified "not over the timescale being explored here"). A modern cigarette-lighter would indeed have been a life-changing tool to a caveman but is indeed disposable junk today. The point being made by the original comment (with which I agree) was that many criteria-for-usefulness - primarily that of reliability or a lack of hallucination - have remained static; with successive generations of tools being (falsely) claimed to meet them, but then abandoned when the next hype-train comes along. I certainly agree that _some_ aspects of AI models are indeed improving (often drastically!) over time (speed, price, supported formats, history/context, etc.) - but they still _all_ fall _drastically_ short on the key core requirement that is required in order to make them Actually Useful. "X is better than Y" does not imply "where Y failed to be useful, X now succeeds".
qsort 2y ago
I believe it's more frustration directed at the mismatch between marketing and reality, combined with the general well deserved growing hatred for SV culture, and, more broadly, software engineers. The sentiment would be completely different if the entire industry marketed themselves like the helpful tools they are rather than the second coming of Christ they aren't. This distinction is hard to make on "fast food" forums like this one. If you aren't a coder, it's hard to find much utility in "Google, but it burns a tree whenever you make an API call, and everything it tells you might be wrong". I for one have never used it for anything else. It just hasn't ever come up. It's great at cheating on homework, kids love GPTs. It's great at cheating in general, in interviews for instance. Or at ruining Christmas, after this year's LLM debacle it's unclear if we'll have another edition of Advent of Code. None of this is the technology's fault, of course, you could say the same about the Internet, phones or what have you, but it's hardly a point in favor either. And if you are a coder, models like Claude actually do help you, but you have to monitor their output and thoroughly test whatever comes out of them, a far cry from the promises of complete automation and insane productivity gains. If you are only a consumer of this technology, like the vast majority of us here, there isn't that much of an upside in being an early adopter. I'll sit and wait, slowly integrating new technology in my workflow if and when it makes sense to do so. Happy new year, I guess.
- fragmede 2y ago
  > there isn't that much of an upside in being an early adopter. Other than, y'know, using the new tools. As a programmer heavy forum, we focus a lot on LLMs' (lack of) correctness. There's more than a little bit of annoyance when things are wrong, like being asked to grab the red blanket and then getting into an argument over it being orange instead of what was important, someone needed the blanket because they were cold. Most of the non-tech people who use ChatGPT that I've talked to absolutely love it because they don't feel it judges them for asking stupid questions and they have conversations about absolutely everything in their lives with it down to which outfit to wear to the party. There are wrong answers to that question as well, but they're far more subjective and just having another opinion in the room is invaluable. It's just a computer and won't get hurt if you totally ignore it's recommendations, and even better, it won't gloat (unless you ask it to) if you tell it later that it was right and you were wrong. Some people have found upsides for themselves in their lives, even at this nascent stage. No one's forcing you to use one, but your job isn't going to be taken by AI, it's going to be taken by someone else who can outperform you that's using AI.
duped 2y ago
> Try Claude Sonnet 3.5 (not Haiku!) and tell me if, while still flawed, is not helpful. It's not as helpful as Google was ten years ago. It's more helpful than Google today, because Google search has slowly been corrupted by garbage SEO and other LLM spam, including their own suggestions.
- timewizard 2y ago
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- ChicagoDave 2y ago
  Claude Sonnet 3.5 can write whole React applications with proper contextual clues and some minor iterations. Google has never coded for you. I’ve written two large applications and about a dozen smaller ones using Claude as an assistant. I’m a terrible front-end developer and almost none of that work was possible without Claude. The API and AWS deployment were sped up tremendously. I’ve created unit tests and I’ve read through the resulting code and it’s very clean. One of my core pre-prompt requirements has always been to follow domain-driven design principles, something a novice would never understand. I also start with design principles and a checklist that Claude is excellent at providing. My only complaint is you only have a 3-4 hour window before you’re cutoff for a few hours. And needing an enterprise agreement to have a walled garden for proprietary purposes. I was not a fan in Q1. Q2 improved. Q3 was a massive leap forward.
  - duped 2y ago
    I've never really used Claude for writing code, becuase I'm not really bottlenecked by that problem. I have used it quite a bit for asking questions about what code to write and it's almost always wrong (usually in subtle ways that would trick someone with little experience). Maybe it was overtrained on react sources, but for me it's pretty useless. The big annoyance for me is it just makes up APIs that don't exist. While that's useful for suggesting to me what APIs I should add to my own code, it's really pointless if I ask a question like "using libfoo how do I bar" and it tells me "call the doBar() function" which does not exist.
dkkergoog 2y ago
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swalsh 2y ago
I'm a big believer in Claude. I've accomplished some huge productivity gains by leveraging it. That said, I can see places where the models are strong and weak. If you're doing react, or python. These models are incredible. C#, C++ they're not terrible. Rust though, it's not great. If your experience is exclusively trying to use it to write Rust, it doesn't matter if you're using o1, Claude or anything else. It's just not great at it yet.
mvkel 2y ago
I'm surprised at the description that it's "useless" as a programming / design partner. Even if it doesn't make "elegant" code (whatever that means), it's the difference between an app existing at all, or not. I built and shipped a Swift app to the App Store, currently generating $10,200 in MRR, exclusively using LLMs. I wouldn't describe myself as a programmer, and didn't plan to ever build an app, mostly because in the attempts I made, I'd get stuck and couldn't google my way out. LLMs are the great un-stickers. For that reason per se, they are incredibly useful.
- raydev 2y ago
  Which service/LLM performed the best for you?
  - mvkel 2y ago
    Sonnet-3.5 seemed to churn out the best code, so I would default to that. If it got stuck in circular reasoning, 4o would usually resolve it. Then back to Sonnet.
- egometry 2y ago
  To the un-sticking point: it's also great at letting people ask questions without being perceived as dumb Tragically - admitting ignorance, even with the desire to learn, often has negative social reprocussions
  - simonw 2y ago
    Asking "stupid" questions without fear of judgement is legit one of my favorite personal applications of LLMs.
    - tkgally 2y ago
      That is one of the great strengths of LLMs for school education as well. Students often refrain from asking questions in class out of embarrassment at showing their ignorance or hesitation at interrupting the flow of the class. When used well, LLMs offer a good way for motivated learners to fill in the gaps in their understanding. The pervasive problem of low student motivation won't be solved by LLMs, though. Human teachers will, I think, still be needed.
FooBarWidget 2y ago
Why do people have such narrow views on what makes LLMs useful? I use them for basically everything. My son throwing an irrational tantrum at the amusement park and I can't figure out why he's like that (he won't tell me or he doesn't know himself either) or what I should do? I feed Claude all the facts of what happened that day and ask for advice. Even if I don't agree with the advice, at the very least the analysis helps me understand/hypothesize what's going on with him. Sure beats having to wait until Monday to call up professionals. And in my experience, those professionals don't do a better job of giving me advice than Claude does. It's weekend, my wife is sick, the general practitioner is closed, the emergency weekend line has 35 people in the queue, and I want some quick half-assed medical guidance that while I know might not be 100% reliable, is still better than nothing for the next 2 hours? Feed all the symptoms and facts to Claude/ChatGPT and it does an okay job a lot of the time. I've been visiting Traditional Chinese Medicine (TCM) practitioner for a week now and my symptoms are indeed reducing. But TCM paradigm and concepts are so different from western medicine paradigms and concepts that I can't understand the doctor's explanation at all. Again, Claude does a reasonable job of explaining to me what's going on or why it works from a western medicine point of view. Want to write a novel? Brainstorm ideas with GPT-4o. I had a debate with a friend's child over the correct spelling of a Dutch word ("instabiel" vs "onstabiel"). Google results were not very clear. ChatGPT explained it clearly. Just where is this "useless" idea coming from? Do people not have a life outside of coding?
- krapp 2y ago
  Yes people have lives outside of coding, but most people are able to manage without having AI software intercede in as much of their lives as possible. It seems like you trust AI more than people and prefer it to direct human interaction. That seems to be satisfying a need for you that most people don't have.
  - claar 2y ago
    Why do you postulate that "most people don't have" this need? I also use AI non-stop throughout my day for similar uses. This feels identical to when I was an early "smart phone" user w/my palm pilot. People would condescend saying they didn't understand why I was "on it all the time". A decade or two later, I'm the one trying to get others to put down their phones during meetings. My take? Those who aren't using AI continually currently are simply later adopters of AI. Give it a few years - or at most a decade - and the idea of NOT asking 100+ AI queries per day (or per hour) will seem positively quaint.
karmakaze 2y ago
We're at the "computers play chess badly" stage. Then we'll hit the Deep Thought (1988) and Deep Blue (1995-1997) stages, but still saying that solving Go won't happen for 50+ years and that humans will continue to be better than computers. The date/time that divides my world into before/after is AlphaGo v Lee Sedol game 3 (2016). From that time forward, I don't dismiss out of hand speculations of how soon we can have intelligent machines. Ray Kurzweil date of 2045 is as good as any (and better than most) for an estimate. Like Moore's (and related) Laws, it's not about how but the historical pace of advancements crossing a fairly static point of human capability. Application coding, requires much less intelligence than playing Go at these high levels. The main differences are concise representation and clear final outcome scoring. LLMs deal quite well with the fuzziness of human communications. There may be a few more pegs to place but when seems predictably unknown.
kromem 2y ago
Both new Sonnet and Haiku have a masking overhead. Using a few messages to get them out of "I aim to be direct" AI assistant mode gets much better overall results for the rest of the chat. Haiku is actually incredibly good at high level systems thinking. Somehow when they moved to a smaller model the "human-like" parts fell away but the logical parts remained at a similar level. Like if you were taking meeting notes from a business strategy meeting and wanted insights, use Haiku over Sonnet, and thank me later.
atombender 2y ago
Is there a way to use this in Jetbrains IDEs? (I've not been impressed with their AI Assistant.) There are a few plugins, but from the reviews they all seem kind of mediocre.
- cpursley 2y ago
  Try Cursor. I’m serious.
  - atombender 2y ago
    I'm sure it's good, but that's not what I'm asking about.
- cube2222 2y ago
  I personally use the Zed editor AI assistant integration with Sonnet for anything AI-related, while using a JetBrains IDE for coding / code reading, side-by-side. I haven’t found anything comparably good for JetBrains IDEs yet, but I’m also not switching to something else as my main editor.
- Sn0wCoder 2y ago
  I use IntelliJ as my main coding tool but also use VSCode and Sublime text. If you have access to local LLMs or have an API key for some the Continue Plugin (basically Cursor but can use in IntelliJ) is the Best of the Best for IntelliJ (IMO). I have a box running some local models including Phind and StarCoder (plus some small embeddings) and have been super happy with the end product. The next up is Google Gemini Code Assist has been the best of the IntelliJ (non-configured) AI tools I have tried. There are better ones out there but IMO not for IntelliJ. It's still free for a few more weeks and I have been using it since the free release, fun to use. Can pre-prompt, say you are an expert XXX, please be funny, fill in the rest of your regular prompts. The Co-Pilot I use for work is very limited and will only answer coding questions. I tried to tell it that it was my coding buddy, and its name was Phil and told me it cannot have a personality or be funny. I believe the paid personal Co-Pilot allows you to choose which LLM it uses (I cannot confirm). The Phind VSCode plugin works really well. Also, the Phind coding models are on par with some of the other big ones and free if you have a subscription (or run locally). Sublime is around to open those GIG+ files as VSCode chocks and not worth the RAM of opening another IntelliJ. Each task / programming language / query requires trying different LLM models and novel ways of prompting. If it's not work-related (or work pays for the one you use) sending as much of the code as relevant also helps the answers be more useful. Most of the people I meet that say LLMs are not useful have only tried one (flavor / plugin), do not know how to pre-prompt or prompt, and do not give the tools a chance. Try one or two things, say yep, it's not good and give up. Still hard for me to admit that Prompt Engineering is a profession, but it's the same as Google Fu. Once you learn it you can become an LLM Ninja! I do not believe LLMs are coming for my job (just yet) but do believe they are going to be able to replace some people, are useful and those that do not use them will be at a disadvantage.
qwertox 2y ago
LLMs have given computers the ability to communicate with us in natural language, we didn't have that before at this level. In order to do this, they've been fed with a lot of coherent stuff and give the impression of being coherent, but we know they're just statistical machines. But at least they can now communicate naturally with us, so now we have that infrastructure available, as we do have TTS or ASR or monitors and keyboards available. It's still up to us to now make proper agents out of them. Agents for the software we've been using for decades. They can take over a lot of tedious work for us.
deleted 2y ago
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salawat 2y ago
Why are you pasting huge chunks of potentially crown jewels code into a 3rd party service where prompts are going to most likely be turned into training/surveillance material?
- simonw 2y ago
  A lot of vendors promise not to train on input to their models. I choose to believe those promises.
  - askl56 2y ago
    A scorpion, not knowing how to swim, asked a frog to carry it across the river. “Do I look like a fool?” said the frog. “You’d sting me if I let you on my back!” “Be logical,” said the scorpion. “If I stung you I’d certainly drown myself.” “That’s true,” the frog acknowledged. “Climb aboard, then!” But no sooner than they were halfway across the river, the scorpion stung the frog, and they both began to thrash and drown. “Why on earth did you do that?” the frog said morosely. “Now we’re both going to die.” “I can’t help it,” said the scorpion. “It’s my nature.”
zahlman 2y ago
>They are also great at doing boring tasks for which you can provide perfect guidance (but that still would take you hours) All the tasks I can think of dealing with on my own computer that would take hours, a) are actually pretty interesting to me and b) would equally well take hours to "provide perfect guidance". The drudge work of programming that I notice comes in blocks of seconds at a time, and the mental context switch to using an LLM would be costlier.
worldsayshi 2y ago
I ponder if LLM:s are very useful but at a quite narrower set of tasks than we expect. Like fuzzy manipulation of logical specifications. I.e. over time it constitute a fundamental shift in how we interact with abstractions in computers. The current fundamentals will still remain but they will become increasingly malleable. Details in code will become less important. Architecture will become increasingly important. But at the same time the cost of refactoring or changing architecture will quickly drop. Any details that are easily lost when passing through an LLM will be details that have the highest maintenance cost. Any important details that can be retained by an LLM can move up and down the ladder of abstraction at will. Can an LLM based solution maintain software architectures without introducing noise? The answer to that is the difference between somewhat useful and game changing.
mikehollinger 2y ago
> About "people still thinking LLMs are quite useless", I still believe that the problem is that most people are exposed to ChatGPT 4o that at this point for my use case (programming / design partner) is basically a useless toy.... and > a key thing with LLMs is that their ability to help, as a tool, changes vastly based on your communication ability. I still hold that the innovations we've seen as an industry with text transfer to the data from other domains. And there's an odd misbehavior with people that I've now seen play out twice -- back in 2017 with vision models (please don't shove a picture of a spectrogram into an object detector), and today. People are trying to coerce text models to do stuff with data series, or (again!) pictures of charts, rather than paying attention to timeseries foundation models which directly can work on the data.[1] Further, the tricks we're seeing with encoder / decoder pipelines should work for other domains. And we're not yet recognizing that as an industry. For example, whisper or the emerging video models are getting there, but think about multi-spectral satellite data, fraud detection (a type graph problem). There's lots of value to unlock from coding models. They're just text models. So what if you were to shove an abstract syntax tree in as the data representation, or the intermediate code from LLVM or a JVM or whatever runtime and interact with that? [1] https://huggingface.co/ibm-granite/granite-timeseries-ttm-r1 https://huggingface.co/ibm-granite/granite-timeseries-ttm-r1 - shout-out to some former colleagues!
- simonw 2y ago
  Andrej Karpathy: https://twitter.com/karpathy/status/1835024197506187617 https://twitter.com/karpathy/status/1835024197506187617 > It's a bit sad and confusing that LLMs ("Large Language Models") have little to do with language; It's just historical. They are highly general purpose technology for statistical modeling of token streams. A better name would be Autoregressive Transformers or something. > They don't care if the tokens happen to represent little text chunks. It could just as well be little image patches, audio chunks, action choices, molecules, or whatever. If you can reduce your problem to that of modeling token streams (for any arbitrary vocabulary of some set of discrete tokens), you can "throw an LLM at it".
  - vbezhenar 2y ago
    But I need enormous amounts of learning data and enormous amount of computing to learn new models, right? So it's kind of useless advice for most people who can't just parse github repositories and teach their new model using AST tokens. They have to use existing opensourced models or API and those happened to use text.
miki123211 2y ago
> But there is more: a key thing with LLMs is that their ability to help, as a tool, changes vastly based on your communication ability. The prompt is the king to make those models 10x better than they are with the lazy one-liner question. People keep saying this, and there are use cases for which this is definitely the case, but I find the opposite to be just as true in some circumstances. I'm surprised at how good LLMs are at answering "me be monkey, me have big problem with code" questions. For simple one-offs like "how to do x in Pandas" (a frequent one for me), I often just give Claude a mish-mash of keywords, and it usually figures out what I want. An example prompt of mine from yesterday, which Claude successfully answered, was "python sha256 of file contents base64 safe for fs path." With a system prompt to make Claude's output super brief and a command to execute queries from the terminal via Simon Willison's LLM tool, this is extremely useful.
- mewpmewp2 2y ago
  Using the correct keywords like you did is part of communication though. Good communication with LLMs is the least keywords used to make it deducible for LLM what you exactly want.
  - EagnaIonat 2y ago
    > Good communication with LLMs is the least keywords used to make it deducible for LLM what you exactly want. I am not sure that is the case, at least with a large number of LLMs. CO-STAR and TIDD-EC are much about structure and explanation than brevity.
    - freehorse 2y ago
      Finding what works for an llm and what not is also part of communication skills. Though I do not have a good idea what is _bad_ communication with an llm. People say that sometimes, but when specific examples arise I do not see really anything more than limitations of llms (and the improvements they often suggest do not do anything either). So it would be good to have some more concrete examples, unless that is about inability to communicate a problem in general, stemming from actual inability to _understand_ the problem. Also a lot change in time, I think in the past one had to really coddle an llm "You are the best expert in python in the world!" but I am not sure that is that important nowadays.
abhijeetpbodas 2y ago
> ask very precise questions explaining the background IME, being forced to write about something or verbally explaining/enumerating things in detail _by itself_ leads to a lot of clarity in the writer's thoughts, irrespective of if there's an LLM answering back. People have been doing rubber-duck-debugging since long. The metaphorical duck (LLMs in our context), if explained to well, has now started answering back with useful stuff!
- danielbln 2y ago
  One thing LLMs have been incredibly strong even since gpt-3.5 is being the most advanced non-human rubber duck, and while they can do plenty more, that alone provides (me at least) with tremendous utility.
isoprophlex 2y ago
Super interesting that my experience mirrors exactly what you are writing... except for me finding Claude to be almost useless (often misunderstands me, gives answers that are plain wrong) and 4o to be a very helpful, if not somewhat dull, jack-of-all trades in helping me be a cruise control for the mind. I could only ever really jam with 4o. Makes me wonder if there's personal communication preferences at play here.
weMadeThat 2y ago
> They work great to explore what is at the borders of your knowledge. But not at exploring what is at the border of knowledge itself. And by converging on the conventional, LLMs actually lead you away from anything that actually extends. > doing boring tasks for which you can provide perfect guidance That's true but you never need an LLM for that. There are wonderful scripts written by wonderful people and provided for free almost all the time and for those who search in the right places. LLM companies benefit/profit of these without providing anything in return. They are worse than people who grab FOSS and turn it into overpriced and aggressively marketed business models and services or people who threaten and sue FOSS for being better and free alternatives to their bloated and often "illegally telemetric" services. > able to accelerate you True, but you leave too much for data brokers and companies like Meta to abuse and exploit in the future. All that additional "interactional data" will do so much worse to humanity than all those previous data sets did in elections, for example, or pretty much all consumer markets. They will mostly accelerate all these dimwitted Fortune 5000 companies that have sabotaged consumers into way too much dumb shit - way more than is reasonable or "ok". And educated, wealthy and or tech-savvy people won't be able to avoid/evade any of that. Especially when it's paired with meds, drugs, foods, biases, fallacies, priming and so on and all the knowledge we will gain on bio-chemical pathways and human liability to sabotage. They are great for coders, of course, everyone can be an army of clone-warriors with auto-complete on steroids now and nobody can tell you what to do with all that time that you now have and all that money, which, thanks to all of us but mostly our ancestors, is the default. The problem is the resulting hyper-amplified, augmented financial imbalance. It's gonna fuck our species if all the technical people don't restore some of that balance, and everybody knows what that means and what must be done.
aleph_minus_one 2y ago
> About "people still thinking LLMs are quite useless", I still believe that the problem is that most people are exposed to ChatGPT 4o that at this point for my use case (programming / design partner) is basically a useless toy. And I guess that in tech many folks try LLMs for the same use cases. Try Claude Sonnet 3.5 (not Haiku!) and tell me if, while still flawed, is not helpful. I see much deeper problems. Just to give two examples: - I asked various AIs concerning explanations of proofs of some deep (established) mathematical theorems: the explanations were to my understanding very hallucinated, and thus worse than "obviously wrong". I also asked for literature references for some deep mathematical theory frameworks: bascially all of the references were again hallucinated. - I asked lots of AIs on https://lmarena.ai/ https://lmarena.ai/ to write a suitably long text about some political topic that is quite controversial in my country (but does have lots proponents even in a very radical formulation, even though most people would not use such a radical formulation in public). All of the LLMs that I checked refused or tried to indoctrinate me that this thesis is wrong. I did not ask the LLM to lecture me, but I gave it a concrete task! Society is deeply divided, so if the LLM only spreads propaganda of its political teaching, it will be useless for many tasks for a very significant share of the society.
ddgflorida 2y ago
Definitely not a "useless toy" with the right use case. It's great at code snippets, scripts, etc. It's an assistant.
vasco 2y ago
Most people consider their own brain useless and don't use it, so it's not strange that they do the same with AI. How many people just refuse to learn how to parallel park, a new language, calculus or even basic arithmetic, "because they aren't good at it".
deleted 2y ago
[deleted]
ta12653421 2y ago
ClaudeAI ++1000

wslh 2y ago

Right, in simpler terms: The measure of LLMs success is how effectively they help you achieve your goal faster.

antirez 2y ago
Exactly, and right now the LLMs acceleration effect is a tool, not "give me the final solution". Even people that can't code, using LLMs to build applications from scratch, still have this tool mindset. This is why they can use them effectively: they don't stop at the first failed solution; they provide hints to the LLM, test the code, try to figure what's the problem (also with the LLM help), and so forth. It's a matter of mindset.
- d0mine 2y ago
  btw, fusion has arrived by that definition: No reactors that would produce more energy than they consume, But net positive reactions have been achieved. Tasks where LLMs output is more than 1x are few and far between.
- andrewaylett 2y ago
  > people that can't code These people may not be Software Engineers, but they are coding.

hdjjhhvvhga 2y ago

While Claude Sonnet is superior than 4o for most my use cases, there are still occasionally some specific tasks where it performs slightly better.

antirez 2y ago
Probably. But statistically to work with 4o is a lose of time for me. LLMs is like an investment: you write the prompts, you "work" with them. If the LLM is too weak, this is a lose of time. You need to have a return on the investment that is positive. With ChatGPT 4o / o1 most of the times for me the investment of time has almost zero return. Before Claude Sonnet 3.5 I already had a ChatGPT PRO account but never used it for coding since it was most of the times useless if not for throw away scripts that I didn't want to do myself or as a stack overflow replacement for trivial stuff. Now it's different.
- airstrike 2y ago
  This mirrors my experience 100%. I'm not even sure why I still pay for OpenAI at this point. Claude 3.5 is just incredibly superior. And I totally agree on the point about dropping in context and asking very specific questions. I've had Claude pinpoint a bug in a 2k LOC module that I was struggling to find the cause for. After wasting a lot of time on it on my own, I thought "what the heck, maybe Claude can figure it out" and it did. It's objectively useful, even if flawed sometimes.
  - hanikesn 2y ago
    I'm curious. Can you go into more detail what kind of bug it found?
    - airstrike 2y ago
      I was writing a custom widget for iced (the Rust GUI library) and I was getting a panic due to some fancy logic I was trying to do. I guess the shortest description I can say is that it was a combination of what appeared to be a caching issue at first, but the real cause turned out to be some method shadowing where I was using a struct's method where I meant to use the trait's method. I had made the specific operation generic (moving it out of the struct and into a trait) but forgot to delete it from the struct, so I was calling the incorrect function. Claude pinpointed the cache issue immediately when I just dumped two files into the context and asked it: somewhere in my codebase I'm triggering a perform() on the editor but the next call on highlight() panics because `Line layout should be cached` what am I missing? do I need to do something after perform() to re-cache the layout? at first that seemed to fix the issue, but other errors persisted. so we kept debugging together until we found the root cause. either way I knew where to look thanks to its assistance

brookst 2y ago

I’m surprised you only have one use case. I use LLMs to research travel, adjust recipes, check biographies and book reviews, and many many more things.

minimaxir 2y ago

> Claude Sonnet 3.5 (not Haiku!) A very big surprise is just how much better Sonnet 3.5 is than Haiku. Even the confusingly-more-expensive-Haiku-variant Haiku 3.5 that's more recent than Sonnet 3.5 is still much worse.

mhh__ 2y ago

Hopefully things have narrowed but you can see from the trends data just how few people (API may be a different story) use claude relative to chatgpt.

minimaxir 2y ago
Brand awareness is a hell of a drug.
- mhh__ 2y ago
  Indeed, although I find myself reaching for o1 more than Claude for matters other than programming, solely because it has better LaTeX (...)

dxbydt 2y ago

> best LLMs are able to accelerate you https://www2.math.upenn.edu/~ghrist/preprints/LAEF.pdf https://www2.math.upenn.edu/~ghrist/preprints/LAEF.pdf - this math textbook was written in just 55 days! Paraphrasing the acknowledgements - ...Begun November 4, 2024, published December 28, 2024. ...assisted by Claude 3.5 sonnet, trained on my previous books... ...puzzles co-created by the author and Claude ...GPT-4o and -o1 were useful in latex configurations...doing proof-reading. ...Gemini Experimental 1206 was an especially good proof-reader ...Exercises were generated with the help of Claude and may have errors. ...project was impossible without the creative labors of Claude The obvious comparison is to the classic Strang https://math.mit.edu/~gs/everyone/ https://math.mit.edu/~gs/everyone/ which took several *years* to conceptualize, write, peer review, revise and publish. Ok maybe Strang isn't your cup of tea, :%s/Strang/Halmos/g , :%s/Strang/Lipschutz/g, :%s/Strang/Hefferon/g, :%s/Strang/Larson/g ... Working through the exercises in this new LLMbook, I'm thinking...maybe this isn't going to stand the test of time. Maybe acceleration is not so hot after all.

datadrivenangel 2y ago
Going faster isn't good if the quality drops enough that overall productivity decreases... Infinite slop is only a good thing for pigs.
- cruffle_duffle 2y ago
  Just use ChatGPT to summarize its own output. It’s like running your JPEG back through the JPEG compressor again!
kianN 2y ago
^ This perfectly encapsulates the story I see every time someone digs into the details of any llm generated or assisted content that has any level of complexity. Great on the surface but lacks any depth, cohesive, or substance
pton_xd 2y ago
"The story of linear algebra begins with systems of equations, each line describing a constraint or boundary traced upon abstract space. These simplest mathematical models of limitation — each equation binding variables in measured proportion — conjoin to shape the realm of possible solutions. When several such constraints act in concert, their collaboration yields three possible fates: no solution survives their collective force; exactly one point satisfies all bounds; or infinite possibilities trace curves and planes through the space of satisfaction. This trichotomy — of emptiness, uniqueness, and infinity — echoes through all of linear algebra, appearing in increasingly sophisticated forms as our understanding deepens." Maybe I'm not the target audience, but... that really doesn't make me interested in continuing to read.

ninth_ant 2y ago

I think a lot of the confusion is in how we approach LLMs. Perhaps stemming from the over-broad term “AI”. There are certain classes of problems that LLMs are good at. Accurately regurgitating all accumulated world knowledge ever is not one, so don’t ask a language model to diagnose your medical condition or choose a political candidate. But do ask them to perform suitable tasks for a language model! Every day by automation I feed in the hourly weather forecast my home ollama server and it builds me a nice readable concise weather report. It’s super cool! There are lots of cases like this where you can give an LLM reliable data and ask it to do a language related task and it will do an excellent job of it. If nothing else it’s an extremely useful computer-human interface.

rrix2 2y ago
> Every day by automation I feed in the hourly weather forecast my home ollama server and it builds me a nice readable concise weather report. not to dissuade you from a thing you find useful but are you aware that the national weather service produces an Area Forecast Discussion product in each local NWS office daily or more often that accomplishes this with human meteorologists and clickable jargon glossary? https://forecast.weather.gov/product.php?site=SEW&issuedby=SEW&product=AFD&format=CI&version=1&glossary=1 https://forecast.weather.gov/product.php?site=SEW&issuedby=S...
- ninth_ant 2y ago
  Doesn’t dissuade me at all, that’s a really neat service. I’m not American though, and even if my own country had a similar service I still enjoying tuning the results to focus on what I’m interested in. And it was just an example of the kinds of computer-human interfaces that are newly possible from this technology. Anytime you have data and want it explained in a casual way — and it’s not mission critical to be extremely precise — LLMs are going to be a good option to consider. More useful AGI-like behaviours may be enabled by combining LLMs with other technologies down the line, but we shouldn’t try to pretend that LLMs can do everything nor are they useless.
  - LtWorf 2y ago

1oooqooq 2y ago

yeah, they save as much time as finding a template with a good old search and using it.

uludag 2y ago

I don't think people finding LLMs useless is a good representation of the general sentiment though. I feel that more than anything, people are annoyed at LLM slop. Someone uses an LLM too much to write code, they create "slop," which ends up making things worse.

gre 2y ago
Yes but then they can prompt it to golf the code and most of the slop goes away. This sometimes breaks the code.
antirez 2y ago
Unfortunately complex tools will be misused by part of the population. There is no easy escape from that in the modernity of possibilities. Look at the Internet itself.

cruffle_duffle 2y ago

To get the most out of them you have to provide context. Treat these models like some kind of eager beaver junior engineer who wants to jump in and write code without asking questions. Force it to ask questions (eg: “do not write code yet, please restate my requirements to make sure we are in alignment. Are there any extra bits of context or information that would help? I will tell you when to write code”) If your model / chat app has the ability to always inject some kind of pre-prompt make sure to add something like “please do not jump to writing code. If this was a coding interview and you jumped to writing code without asking questions and clarifying requirements you’d fail”. At the top of all your source files include a comment with the file name and path. If you have a project on one of these services add an artifact that is the directory tree (“tree —-gitignore” is my goto). This helps “unaided” chats get a sense of what documents they are looking at. And also, it’s a professional bullshitter so don’t trust it with large scale code changes that rely on some language / library feature you don’t have personal experience with. It can send you down a path where the entire assumption that something was possible turns out to be false. Does it seek like a lot of work? Yes. Am I actually more productive with the tool than without? Probably. But it sure as shit isn’t “free” in terms of time spent providing context. I think the more I use these models, the more I get a sense of what it is good at and what is going to be a waste of time. Long story short, prompting is everything. These things aren’t mind readers (and worse they forget everything in each new session)

layer8 2y ago
You are right, but doing all that is incredibly cumbersome, at least to some people, which is why they don’t like working with LLMs.
- simonw 2y ago
  That was one of the themes of my article: LLMs are power-user tools, mis-sold as "easy to use". To get great results out of them you need to invest a whole lot of under-documented and under-appreciated effort. https://simonwillison.net/2024/Dec/31/llms-in-2024/#llms-somehow-got-even-harder-to-use https://simonwillison.net/2024/Dec/31/llms-in-2024/#llms-som...

jsheard 2y ago

I swear these goalposts keep getting moved, I remember being told that GPT3.5 is a useless toy but the paid GPT4 is lifechanging, and now that GPT4 is free I'm told that it's a useless toy but paid o1 or paid Sonnet are lifechanging. Looking forward to o1 and Sonnet becoming useless toys, unlike the lifechanging o3.

aetherson 2y ago
You will also be dismayed to hear that a 2011 iPhone is no longer state-of-the-art, and indeed can't run most modern apps.
- jpc0 2y ago
  GPT4 is a 13 year old technology? Compared to o1 and Sonnet 3.5? If someone told me an iPhone 4 is terrible but an iPhone 5 would definitely serve my needs, then when I get an iPhone 5 they say the same of the 6 you really want me to believe them a second time? Then a third time? Then a 4th? In the mean time my time and money is wasted?
- scubbo 2y ago
  Holy false-equivalency, Batman! The definitions of "useless toy / lifechanging tool" are _not_ changing over time (or, at least, not over the timescale being explored here), whereas the expectations and requirements of processing power of a phone are.
  - aetherson 2y ago
    But in fact they are changing over time -- this is an expectations treadmill. When you get something newer and better, it highlights the flaws in what you had before.
    - scubbo 2y ago
      That is true _in general_, but not in this specific case (hence why I specified "not over the timescale being explored here"). A modern cigarette-lighter would indeed have been a life-changing tool to a caveman but is indeed disposable junk today. The point being made by the original comment (with which I agree) was that many criteria-for-usefulness - primarily that of reliability or a lack of hallucination - have remained static; with successive generations of tools being (falsely) claimed to meet them, but then abandoned when the next hype-train comes along. I certainly agree that _some_ aspects of AI models are indeed improving (often drastically!) over time (speed, price, supported formats, history/context, etc.) - but they still _all_ fall _drastically_ short on the key core requirement that is required in order to make them Actually Useful. "X is better than Y" does not imply "where Y failed to be useful, X now succeeds".

qsort 2y ago

I believe it's more frustration directed at the mismatch between marketing and reality, combined with the general well deserved growing hatred for SV culture, and, more broadly, software engineers. The sentiment would be completely different if the entire industry marketed themselves like the helpful tools they are rather than the second coming of Christ they aren't. This distinction is hard to make on "fast food" forums like this one. If you aren't a coder, it's hard to find much utility in "Google, but it burns a tree whenever you make an API call, and everything it tells you might be wrong". I for one have never used it for anything else. It just hasn't ever come up. It's great at cheating on homework, kids love GPTs. It's great at cheating in general, in interviews for instance. Or at ruining Christmas, after this year's LLM debacle it's unclear if we'll have another edition of Advent of Code. None of this is the technology's fault, of course, you could say the same about the Internet, phones or what have you, but it's hardly a point in favor either. And if you are a coder, models like Claude actually do help you, but you have to monitor their output and thoroughly test whatever comes out of them, a far cry from the promises of complete automation and insane productivity gains. If you are only a consumer of this technology, like the vast majority of us here, there isn't that much of an upside in being an early adopter. I'll sit and wait, slowly integrating new technology in my workflow if and when it makes sense to do so. Happy new year, I guess.

fragmede 2y ago
> there isn't that much of an upside in being an early adopter. Other than, y'know, using the new tools. As a programmer heavy forum, we focus a lot on LLMs' (lack of) correctness. There's more than a little bit of annoyance when things are wrong, like being asked to grab the red blanket and then getting into an argument over it being orange instead of what was important, someone needed the blanket because they were cold. Most of the non-tech people who use ChatGPT that I've talked to absolutely love it because they don't feel it judges them for asking stupid questions and they have conversations about absolutely everything in their lives with it down to which outfit to wear to the party. There are wrong answers to that question as well, but they're far more subjective and just having another opinion in the room is invaluable. It's just a computer and won't get hurt if you totally ignore it's recommendations, and even better, it won't gloat (unless you ask it to) if you tell it later that it was right and you were wrong. Some people have found upsides for themselves in their lives, even at this nascent stage. No one's forcing you to use one, but your job isn't going to be taken by AI, it's going to be taken by someone else who can outperform you that's using AI.

duped 2y ago

> Try Claude Sonnet 3.5 (not Haiku!) and tell me if, while still flawed, is not helpful. It's not as helpful as Google was ten years ago. It's more helpful than Google today, because Google search has slowly been corrupted by garbage SEO and other LLM spam, including their own suggestions.

timewizard 2y ago
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ChicagoDave 2y ago
Claude Sonnet 3.5 can write whole React applications with proper contextual clues and some minor iterations. Google has never coded for you. I’ve written two large applications and about a dozen smaller ones using Claude as an assistant. I’m a terrible front-end developer and almost none of that work was possible without Claude. The API and AWS deployment were sped up tremendously. I’ve created unit tests and I’ve read through the resulting code and it’s very clean. One of my core pre-prompt requirements has always been to follow domain-driven design principles, something a novice would never understand. I also start with design principles and a checklist that Claude is excellent at providing. My only complaint is you only have a 3-4 hour window before you’re cutoff for a few hours. And needing an enterprise agreement to have a walled garden for proprietary purposes. I was not a fan in Q1. Q2 improved. Q3 was a massive leap forward.
- duped 2y ago
  I've never really used Claude for writing code, becuase I'm not really bottlenecked by that problem. I have used it quite a bit for asking questions about what code to write and it's almost always wrong (usually in subtle ways that would trick someone with little experience). Maybe it was overtrained on react sources, but for me it's pretty useless. The big annoyance for me is it just makes up APIs that don't exist. While that's useful for suggesting to me what APIs I should add to my own code, it's really pointless if I ask a question like "using libfoo how do I bar" and it tells me "call the doBar() function" which does not exist.

dkkergoog 2y ago

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swalsh 2y ago

I'm a big believer in Claude. I've accomplished some huge productivity gains by leveraging it. That said, I can see places where the models are strong and weak. If you're doing react, or python. These models are incredible. C#, C++ they're not terrible. Rust though, it's not great. If your experience is exclusively trying to use it to write Rust, it doesn't matter if you're using o1, Claude or anything else. It's just not great at it yet.

mvkel 2y ago

I'm surprised at the description that it's "useless" as a programming / design partner. Even if it doesn't make "elegant" code (whatever that means), it's the difference between an app existing at all, or not. I built and shipped a Swift app to the App Store, currently generating $10,200 in MRR, exclusively using LLMs. I wouldn't describe myself as a programmer, and didn't plan to ever build an app, mostly because in the attempts I made, I'd get stuck and couldn't google my way out. LLMs are the great un-stickers. For that reason per se, they are incredibly useful.

raydev 2y ago
Which service/LLM performed the best for you?
- mvkel 2y ago
  Sonnet-3.5 seemed to churn out the best code, so I would default to that. If it got stuck in circular reasoning, 4o would usually resolve it. Then back to Sonnet.
egometry 2y ago
To the un-sticking point: it's also great at letting people ask questions without being perceived as dumb Tragically - admitting ignorance, even with the desire to learn, often has negative social reprocussions
- simonw 2y ago
  Asking "stupid" questions without fear of judgement is legit one of my favorite personal applications of LLMs.
  - tkgally 2y ago
    That is one of the great strengths of LLMs for school education as well. Students often refrain from asking questions in class out of embarrassment at showing their ignorance or hesitation at interrupting the flow of the class. When used well, LLMs offer a good way for motivated learners to fill in the gaps in their understanding. The pervasive problem of low student motivation won't be solved by LLMs, though. Human teachers will, I think, still be needed.

FooBarWidget 2y ago

Why do people have such narrow views on what makes LLMs useful? I use them for basically everything. My son throwing an irrational tantrum at the amusement park and I can't figure out why he's like that (he won't tell me or he doesn't know himself either) or what I should do? I feed Claude all the facts of what happened that day and ask for advice. Even if I don't agree with the advice, at the very least the analysis helps me understand/hypothesize what's going on with him. Sure beats having to wait until Monday to call up professionals. And in my experience, those professionals don't do a better job of giving me advice than Claude does. It's weekend, my wife is sick, the general practitioner is closed, the emergency weekend line has 35 people in the queue, and I want some quick half-assed medical guidance that while I know might not be 100% reliable, is still better than nothing for the next 2 hours? Feed all the symptoms and facts to Claude/ChatGPT and it does an okay job a lot of the time. I've been visiting Traditional Chinese Medicine (TCM) practitioner for a week now and my symptoms are indeed reducing. But TCM paradigm and concepts are so different from western medicine paradigms and concepts that I can't understand the doctor's explanation at all. Again, Claude does a reasonable job of explaining to me what's going on or why it works from a western medicine point of view. Want to write a novel? Brainstorm ideas with GPT-4o. I had a debate with a friend's child over the correct spelling of a Dutch word ("instabiel" vs "onstabiel"). Google results were not very clear. ChatGPT explained it clearly. Just where is this "useless" idea coming from? Do people not have a life outside of coding?

krapp 2y ago
Yes people have lives outside of coding, but most people are able to manage without having AI software intercede in as much of their lives as possible. It seems like you trust AI more than people and prefer it to direct human interaction. That seems to be satisfying a need for you that most people don't have.
- claar 2y ago
  Why do you postulate that "most people don't have" this need? I also use AI non-stop throughout my day for similar uses. This feels identical to when I was an early "smart phone" user w/my palm pilot. People would condescend saying they didn't understand why I was "on it all the time". A decade or two later, I'm the one trying to get others to put down their phones during meetings. My take? Those who aren't using AI continually currently are simply later adopters of AI. Give it a few years - or at most a decade - and the idea of NOT asking 100+ AI queries per day (or per hour) will seem positively quaint.

karmakaze 2y ago

We're at the "computers play chess badly" stage. Then we'll hit the Deep Thought (1988) and Deep Blue (1995-1997) stages, but still saying that solving Go won't happen for 50+ years and that humans will continue to be better than computers. The date/time that divides my world into before/after is AlphaGo v Lee Sedol game 3 (2016). From that time forward, I don't dismiss out of hand speculations of how soon we can have intelligent machines. Ray Kurzweil date of 2045 is as good as any (and better than most) for an estimate. Like Moore's (and related) Laws, it's not about how but the historical pace of advancements crossing a fairly static point of human capability. Application coding, requires much less intelligence than playing Go at these high levels. The main differences are concise representation and clear final outcome scoring. LLMs deal quite well with the fuzziness of human communications. There may be a few more pegs to place but when seems predictably unknown.

kromem 2y ago

Both new Sonnet and Haiku have a masking overhead. Using a few messages to get them out of "I aim to be direct" AI assistant mode gets much better overall results for the rest of the chat. Haiku is actually incredibly good at high level systems thinking. Somehow when they moved to a smaller model the "human-like" parts fell away but the logical parts remained at a similar level. Like if you were taking meeting notes from a business strategy meeting and wanted insights, use Haiku over Sonnet, and thank me later.

atombender 2y ago

Is there a way to use this in Jetbrains IDEs? (I've not been impressed with their AI Assistant.) There are a few plugins, but from the reviews they all seem kind of mediocre.

cpursley 2y ago
Try Cursor. I’m serious.
- atombender 2y ago
  I'm sure it's good, but that's not what I'm asking about.
cube2222 2y ago
I personally use the Zed editor AI assistant integration with Sonnet for anything AI-related, while using a JetBrains IDE for coding / code reading, side-by-side. I haven’t found anything comparably good for JetBrains IDEs yet, but I’m also not switching to something else as my main editor.
Sn0wCoder 2y ago
I use IntelliJ as my main coding tool but also use VSCode and Sublime text. If you have access to local LLMs or have an API key for some the Continue Plugin (basically Cursor but can use in IntelliJ) is the Best of the Best for IntelliJ (IMO). I have a box running some local models including Phind and StarCoder (plus some small embeddings) and have been super happy with the end product. The next up is Google Gemini Code Assist has been the best of the IntelliJ (non-configured) AI tools I have tried. There are better ones out there but IMO not for IntelliJ. It's still free for a few more weeks and I have been using it since the free release, fun to use. Can pre-prompt, say you are an expert XXX, please be funny, fill in the rest of your regular prompts. The Co-Pilot I use for work is very limited and will only answer coding questions. I tried to tell it that it was my coding buddy, and its name was Phil and told me it cannot have a personality or be funny. I believe the paid personal Co-Pilot allows you to choose which LLM it uses (I cannot confirm). The Phind VSCode plugin works really well. Also, the Phind coding models are on par with some of the other big ones and free if you have a subscription (or run locally). Sublime is around to open those GIG+ files as VSCode chocks and not worth the RAM of opening another IntelliJ. Each task / programming language / query requires trying different LLM models and novel ways of prompting. If it's not work-related (or work pays for the one you use) sending as much of the code as relevant also helps the answers be more useful. Most of the people I meet that say LLMs are not useful have only tried one (flavor / plugin), do not know how to pre-prompt or prompt, and do not give the tools a chance. Try one or two things, say yep, it's not good and give up. Still hard for me to admit that Prompt Engineering is a profession, but it's the same as Google Fu. Once you learn it you can become an LLM Ninja! I do not believe LLMs are coming for my job (just yet) but do believe they are going to be able to replace some people, are useful and those that do not use them will be at a disadvantage.

qwertox 2y ago

LLMs have given computers the ability to communicate with us in natural language, we didn't have that before at this level. In order to do this, they've been fed with a lot of coherent stuff and give the impression of being coherent, but we know they're just statistical machines. But at least they can now communicate naturally with us, so now we have that infrastructure available, as we do have TTS or ASR or monitors and keyboards available. It's still up to us to now make proper agents out of them. Agents for the software we've been using for decades. They can take over a lot of tedious work for us.

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salawat 2y ago

Why are you pasting huge chunks of potentially crown jewels code into a 3rd party service where prompts are going to most likely be turned into training/surveillance material?

simonw 2y ago
A lot of vendors promise not to train on input to their models. I choose to believe those promises.
- askl56 2y ago
  A scorpion, not knowing how to swim, asked a frog to carry it across the river. “Do I look like a fool?” said the frog. “You’d sting me if I let you on my back!” “Be logical,” said the scorpion. “If I stung you I’d certainly drown myself.” “That’s true,” the frog acknowledged. “Climb aboard, then!” But no sooner than they were halfway across the river, the scorpion stung the frog, and they both began to thrash and drown. “Why on earth did you do that?” the frog said morosely. “Now we’re both going to die.” “I can’t help it,” said the scorpion. “It’s my nature.”

zahlman 2y ago

>They are also great at doing boring tasks for which you can provide perfect guidance (but that still would take you hours) All the tasks I can think of dealing with on my own computer that would take hours, a) are actually pretty interesting to me and b) would equally well take hours to "provide perfect guidance". The drudge work of programming that I notice comes in blocks of seconds at a time, and the mental context switch to using an LLM would be costlier.

worldsayshi 2y ago

I ponder if LLM:s are very useful but at a quite narrower set of tasks than we expect. Like fuzzy manipulation of logical specifications. I.e. over time it constitute a fundamental shift in how we interact with abstractions in computers. The current fundamentals will still remain but they will become increasingly malleable. Details in code will become less important. Architecture will become increasingly important. But at the same time the cost of refactoring or changing architecture will quickly drop. Any details that are easily lost when passing through an LLM will be details that have the highest maintenance cost. Any important details that can be retained by an LLM can move up and down the ladder of abstraction at will. Can an LLM based solution maintain software architectures without introducing noise? The answer to that is the difference between somewhat useful and game changing.

mikehollinger 2y ago

> About "people still thinking LLMs are quite useless", I still believe that the problem is that most people are exposed to ChatGPT 4o that at this point for my use case (programming / design partner) is basically a useless toy.... and > a key thing with LLMs is that their ability to help, as a tool, changes vastly based on your communication ability. I still hold that the innovations we've seen as an industry with text transfer to the data from other domains. And there's an odd misbehavior with people that I've now seen play out twice -- back in 2017 with vision models (please don't shove a picture of a spectrogram into an object detector), and today. People are trying to coerce text models to do stuff with data series, or (again!) pictures of charts, rather than paying attention to timeseries foundation models which directly can work on the data.[1] Further, the tricks we're seeing with encoder / decoder pipelines should work for other domains. And we're not yet recognizing that as an industry. For example, whisper or the emerging video models are getting there, but think about multi-spectral satellite data, fraud detection (a type graph problem). There's lots of value to unlock from coding models. They're just text models. So what if you were to shove an abstract syntax tree in as the data representation, or the intermediate code from LLVM or a JVM or whatever runtime and interact with that? [1] https://huggingface.co/ibm-granite/granite-timeseries-ttm-r1 https://huggingface.co/ibm-granite/granite-timeseries-ttm-r1 - shout-out to some former colleagues!

simonw 2y ago
Andrej Karpathy: https://twitter.com/karpathy/status/1835024197506187617 https://twitter.com/karpathy/status/1835024197506187617 > It's a bit sad and confusing that LLMs ("Large Language Models") have little to do with language; It's just historical. They are highly general purpose technology for statistical modeling of token streams. A better name would be Autoregressive Transformers or something. > They don't care if the tokens happen to represent little text chunks. It could just as well be little image patches, audio chunks, action choices, molecules, or whatever. If you can reduce your problem to that of modeling token streams (for any arbitrary vocabulary of some set of discrete tokens), you can "throw an LLM at it".
- vbezhenar 2y ago
  But I need enormous amounts of learning data and enormous amount of computing to learn new models, right? So it's kind of useless advice for most people who can't just parse github repositories and teach their new model using AST tokens. They have to use existing opensourced models or API and those happened to use text.

miki123211 2y ago

> But there is more: a key thing with LLMs is that their ability to help, as a tool, changes vastly based on your communication ability. The prompt is the king to make those models 10x better than they are with the lazy one-liner question. People keep saying this, and there are use cases for which this is definitely the case, but I find the opposite to be just as true in some circumstances. I'm surprised at how good LLMs are at answering "me be monkey, me have big problem with code" questions. For simple one-offs like "how to do x in Pandas" (a frequent one for me), I often just give Claude a mish-mash of keywords, and it usually figures out what I want. An example prompt of mine from yesterday, which Claude successfully answered, was "python sha256 of file contents base64 safe for fs path." With a system prompt to make Claude's output super brief and a command to execute queries from the terminal via Simon Willison's LLM tool, this is extremely useful.

mewpmewp2 2y ago
Using the correct keywords like you did is part of communication though. Good communication with LLMs is the least keywords used to make it deducible for LLM what you exactly want.
- EagnaIonat 2y ago
  > Good communication with LLMs is the least keywords used to make it deducible for LLM what you exactly want. I am not sure that is the case, at least with a large number of LLMs. CO-STAR and TIDD-EC are much about structure and explanation than brevity.
  - freehorse 2y ago
    Finding what works for an llm and what not is also part of communication skills. Though I do not have a good idea what is _bad_ communication with an llm. People say that sometimes, but when specific examples arise I do not see really anything more than limitations of llms (and the improvements they often suggest do not do anything either). So it would be good to have some more concrete examples, unless that is about inability to communicate a problem in general, stemming from actual inability to _understand_ the problem. Also a lot change in time, I think in the past one had to really coddle an llm "You are the best expert in python in the world!" but I am not sure that is that important nowadays.

abhijeetpbodas 2y ago

> ask very precise questions explaining the background IME, being forced to write about something or verbally explaining/enumerating things in detail _by itself_ leads to a lot of clarity in the writer's thoughts, irrespective of if there's an LLM answering back. People have been doing rubber-duck-debugging since long. The metaphorical duck (LLMs in our context), if explained to well, has now started answering back with useful stuff!

danielbln 2y ago
One thing LLMs have been incredibly strong even since gpt-3.5 is being the most advanced non-human rubber duck, and while they can do plenty more, that alone provides (me at least) with tremendous utility.

isoprophlex 2y ago

Super interesting that my experience mirrors exactly what you are writing... except for me finding Claude to be almost useless (often misunderstands me, gives answers that are plain wrong) and 4o to be a very helpful, if not somewhat dull, jack-of-all trades in helping me be a cruise control for the mind. I could only ever really jam with 4o. Makes me wonder if there's personal communication preferences at play here.

weMadeThat 2y ago

> They work great to explore what is at the borders of your knowledge. But not at exploring what is at the border of knowledge itself. And by converging on the conventional, LLMs actually lead you away from anything that actually extends. > doing boring tasks for which you can provide perfect guidance That's true but you never need an LLM for that. There are wonderful scripts written by wonderful people and provided for free almost all the time and for those who search in the right places. LLM companies benefit/profit of these without providing anything in return. They are worse than people who grab FOSS and turn it into overpriced and aggressively marketed business models and services or people who threaten and sue FOSS for being better and free alternatives to their bloated and often "illegally telemetric" services. > able to accelerate you True, but you leave too much for data brokers and companies like Meta to abuse and exploit in the future. All that additional "interactional data" will do so much worse to humanity than all those previous data sets did in elections, for example, or pretty much all consumer markets. They will mostly accelerate all these dimwitted Fortune 5000 companies that have sabotaged consumers into way too much dumb shit - way more than is reasonable or "ok". And educated, wealthy and or tech-savvy people won't be able to avoid/evade any of that. Especially when it's paired with meds, drugs, foods, biases, fallacies, priming and so on and all the knowledge we will gain on bio-chemical pathways and human liability to sabotage. They are great for coders, of course, everyone can be an army of clone-warriors with auto-complete on steroids now and nobody can tell you what to do with all that time that you now have and all that money, which, thanks to all of us but mostly our ancestors, is the default. The problem is the resulting hyper-amplified, augmented financial imbalance. It's gonna fuck our species if all the technical people don't restore some of that balance, and everybody knows what that means and what must be done.

aleph_minus_one 2y ago

> About "people still thinking LLMs are quite useless", I still believe that the problem is that most people are exposed to ChatGPT 4o that at this point for my use case (programming / design partner) is basically a useless toy. And I guess that in tech many folks try LLMs for the same use cases. Try Claude Sonnet 3.5 (not Haiku!) and tell me if, while still flawed, is not helpful. I see much deeper problems. Just to give two examples: - I asked various AIs concerning explanations of proofs of some deep (established) mathematical theorems: the explanations were to my understanding very hallucinated, and thus worse than "obviously wrong". I also asked for literature references for some deep mathematical theory frameworks: bascially all of the references were again hallucinated. - I asked lots of AIs on https://lmarena.ai/ https://lmarena.ai/ to write a suitably long text about some political topic that is quite controversial in my country (but does have lots proponents even in a very radical formulation, even though most people would not use such a radical formulation in public). All of the LLMs that I checked refused or tried to indoctrinate me that this thesis is wrong. I did not ask the LLM to lecture me, but I gave it a concrete task! Society is deeply divided, so if the LLM only spreads propaganda of its political teaching, it will be useless for many tasks for a very significant share of the society.

ddgflorida 2y ago

Definitely not a "useless toy" with the right use case. It's great at code snippets, scripts, etc. It's an assistant.

vasco 2y ago

Most people consider their own brain useless and don't use it, so it's not strange that they do the same with AI. How many people just refuse to learn how to parallel park, a new language, calculus or even basic arithmetic, "because they aren't good at it".

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ta12653421 2y ago

ClaudeAI ++1000