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>INSUFFICIENT DATA FOR MEANINGFUL ANSWER Boy, it sure would be nice if real LLMs were capable of giving an answer like that.
by CGMthrowaway 6mo ago
>INSUFFICIENT DATA FOR MEANINGFUL ANSWER
Boy, it sure would be nice if real LLMs were capable of giving an answer like that.
- bargainbin 6mo agoYou’re absolutely right! I do have insufficient data for a meaningful answer. This is not an *insightful prediction* — it’s *Dunning-Kruger masquerading as qualified intelligence*
- fragmede 6mo agoDid a human write this?
- croisillon 6mo agoNo Information before. No information after. This is not a failure — it's narcissism as a service.
- combobyte 6mo agoYaaS — yes-men as a service
- gwerbin 6mo agoThey can do it, it's just not "by default", they need to be prompted to do it. So at least the danger is manageable if you know what you're doing and how to prompt around it.
- Bridged7756 6mo agoNot really. They're still non deterministic language predictors. Believing that a prompt is an effective way to actually control these machines' actual behavior is really far fetched. They com like that from factory. Hardcoded to never say no.
- LPisGood 6mo agoThe thing is that they are completely incapable of meta-cognition. Reasoning models don’t show their actual reasoning at all.
- DonaldPShimoda 6mo agoRight — they're not reasoning, they're generating text that statistically models reasoning. Anyone who says differently is selling something.
- jeremyjh 6mo agoThat is what a base model does. After RL it is a very different thing, and anyone who says they know what it is, is naive or dishonest. These things are grown, not made, and we really do not understand how they work in many important ways.
- narginal 6mo ago2061, mark the date
- ryanjshaw 6mo agoI reckon that’s how we know we’ve hit ASI.
- cortesoft 6mo agoThere are a lot of humans who refuse to give that answer, too
- Forgeties79 6mo agoI don’t have to spend dozens if not hundreds of dollars a month to talk to most people in my life lol
- _diyar 6mo agoDo you have to talk to LLMs?
- vhantz 6mo agoAnother way to say the same thing: "to talk to most people in my life lol I don’t have to spend dozens if not hundreds of dollars a month"
- boxedemp 6mo agoThere are lots of free LLMs, but you (often) pay for the good ones. There's lots of people with lots of opinions, but you (often) have to pay for the good ones.
- Forgeties79 6mo agoAccording to HN, every employer, and general social chatter, apparently yes.
- prerok 6mo agoWell, speaking from what I hear and see, employers want you to start using it so that you can be more productive. They've been sold this tool and want you to learn it so that your output will grow. That's not an unfair take, I think. Again, just IME, they expect too much because the tool is oversold: it does not deliver that well. And we always hear, this new model is so much better, it's tiring. I think we should all learn to use LLMs but we should still carefully review what they did. And that is what the employers don't quite get: the review still takes a lot of time. So, gains are not 10x but more like... 10%? Maybe 50 for boiler plate. Still gains are there, I guess.
- otikik 6mo agoJust add a skill to Claude
- temp0826 6mo agoLiving in South America a bit really showed me this. I think it's a cultural thing here but someone will always give you an answer, even if it's wrong, confidently. It was hard for me at first- I am usually the first person to say "I don't know" (often followed by "but let's slow down and find a good solution").
- jfaulken 6mo agoThis was similar to my experience running a software team in India (I'm an American) a couple decades ago. I had to learn not to ask yes/no questions because the answer would always be yes.
- HiPhish 6mo agoIt's a long-standing jodke that AI stands for "Actual Indians".
- deleted 6mo ago[deleted]
- ponector 6mo agoFrom real life: - Is it done? - Yes! But not yet!
- disillusioned 6mo agoOn a long enough time horizon, with sufficient multiverses, all things are done!
- throwaway132448 6mo agoTalking about South America as a homogeneous unit is… weird. Even neighbouring countries speaking the same language can be entirely different in this regard.
- temp0826 6mo ago
- amdivia 6mo agoExactly!! I've been trying to work on a new LLM code editor that does just that. When you instruct it to do something, it will evaluate your request, try to analyze the action part of it, the object, subject, etc, and map them to existing symbols in your codebase or, to expected to be created symbols. If all maps, it proceeds. If the map is incomplete, it errors out stating that your statement contained unresolvable ambiguity I think there is a real benefit here, and it might be the actual next beneficial grounded AI sustainable use in programming. Since I the current "Claude code and friends" are but a state of drunkenness we fell into after the advent of this new technology, but it will prove, with time, that this is not a sustainable approach
- in-silico 6mo agoAs measured by #_no_answer/(#_incorrect + #_no_answer) the top current models can do it 60-70% of the time (Grok 4.20 is the best with 83%): https://artificialanalysis.ai/evaluations/omniscience https://artificialanalysis.ai/evaluations/omniscience
- qsera 6mo agoI just came from reddit and seeing this comment, looked for "controversial" sort option instinctively. Maybe hackernews is becoming reddit...
- lynndotpy 6mo agoAt the time of this writing, the prevailing thinking with "artificial intelligence" was that we'd encode every Fact we know and every rule of Logic, and from there, the computer would make new discoveries. Todays AI researchers would call this "symbolic" AI, compared to the "neural" AI powering LLMs. They're like two different worlds. LLMs are just generating text, they don't know anything. They can't assess whether there is enough data for an answer. When you add a follow up prompt "This is wrong, why did you lie?" only then is it able to generate text, "I was wrong, I'm sorry," and so forth.
- theturtletalks 6mo agoDid Asimov’s idea of AI revolve around data retrieval? I’ve read that even human intelligence isn’t necessarily remembering things, but being able to traverse our knowledge and find that idea or thought quickly.
- lern_too_spel 6mo agoThey can read context and with fairly high accuracy say whether that context contains enough information to answer a posed question. They cannot (and we cannot for them) introspect their own weights to say whether their weights already encode information sufficient to answer a posed question.
- ButlerianJihad 6mo agoThis is exactly like a lot of customer service, or technical support. It seems that they are loath to tell anyone “no”, or that something can’t be done, or that an app doesn’t have a feature or can’t be used in a certain way. Especially when a feature has been removed for security reasons. In fact, it gets so crazy that I simply cannot get a straight answer out of somebody and if I persist in my line of questioning and they become evasive or vague or I just can’t get a straight answer for long enough, ultimately, I suspect that the answer is “no”, and that they're simply not allowed to tell me, and they're paid and trained specifically to avoid uttering the “n-word”. In my first job, as a network operator, my supervisor admonished me, and said “we must never tell a customer that we don't know something”. He said that we should tell the customer that “I will go ahead and find out for you, and get back to you on that”. And that is kind of the kind of slippery non-answer I often received in my most recent job, that some manager or supervisor would “look into something” for me and “get back to me”. But the ‘getting back to me’ part never happened, and I began to suspect that it was a platitude meant to satisfy me enough that I would shut up for a while, and stop pressing the issue.
- ItsClo688 6mo agohahaha, the irony is that "INSUFFICIENT DATA FOR MEANINGFUL ANSWER" requires more intelligence than a confident wrong answer. you have to know what you don't know. current LLMs are optimized to always produce output, which means they've essentially been trained out of epistemic humility. Asimov's Multivac at least had the dignity to wait.
- antonvs 6mo agoYes but it waited until the end of the universe. Its annual KPI and OKR performance was abysmal.