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1. segpha+J4[view] [source] 2025-05-06 15:34:48
>>meetpa+(OP)
My frustration with using these models for programming in the past has largely been around their tendency to hallucinate APIs that simply don't exist. The Gemini 2.5 models, both pro and flash, seem significantly less susceptible to this than any other model I've tried.

There are still significant limitations, no amount of prompting will get current models to approach abstraction and architecture the way a person does. But I'm finding that these Gemini models are finally able to replace searches and stackoverflow for a lot of my day-to-day programming.

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2. redox9+na[view] [source] 2025-05-06 16:02:43
>>segpha+J4
Making LLMs know what they don't know is a hard problem. Many attempts at making them refuse to answer what they don't know caused them to refuse to answer things they did in fact know.
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3. Volund+hk[view] [source] 2025-05-06 16:59:08
>>redox9+na
> Many attempts at making them refuse to answer what they don't know caused them to refuse to answer things they did in fact know.

Are we sure they know these things as opposed to being able to consistently guess correctly? With LLMs I'm not sure we even have a clear definition of what it means for it to "know" something.

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4. ajross+Ar[view] [source] 2025-05-06 17:42:36
>>Volund+hk
> Are we sure they know these things as opposed to being able to consistently guess correctly?

What is the practical difference you're imagining between "consistently correct guess" and "knowledge"?

LLMs aren't databases. We have databases. LLMs are probabilistic inference engines. All they do is guess, essentially. The discussion here is about how to get the guess to "check itself" with a firmer idea of "truth". And it turns out that's hard because it requires that the guessing engine know that something needs to be checked in the first place.

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5. myname+ns[view] [source] 2025-05-06 17:46:49
>>ajross+Ar
Simple, and even simpler from your own example.

Knowledge has an objective correctness. We know that there is a "right" and "wrong" answer and we know what a "right" answer is. "Consistently correct guesses", based on the name itself, is not reliable enough to actually be trusted. There's absolutely no guarantee that the next "consistently correct guess" is knowledge or a hallucination.

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6. ajross+Dt[view] [source] 2025-05-06 17:55:14
>>myname+ns
This is a circular semantic argument. You're saying knowledge is knowledge because it's correct, where guessing is guessing because it's a guess. But "is it correct?" is precisely the question you're asking the poor LLM to answer in the first place. It's not helpful to just demand a computation device work the way you want, you need to actually make it work.

Also, too, there are whole subfields of philosophy that make your statement here kinda laughably naive. Suffice it to say that, no, knowledge as rigorously understood does not have "an objective correctness".

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7. Volund+H01[view] [source] 2025-05-06 21:36:30
>>ajross+Dt
> You're saying knowledge is knowledge because it's correct, where guessing is guessing because it's a guess.

Knowledge is knowledge because the knower knows it to be correct. I know I'm typing this into my phone, because it's right here in my hand. I'm guessing you typed your reply into some electronic device. I'm guessing this is true for all your comments. Am I 100% accurate? You'll have to answer that for me. I don't know it to be true, it's a highly informed guess.

Being wrong sometimes is not what makes a guess a guess. It's the different between pulling something from your memory banks, be they biological or mechanical, vs inferring it from some combination of your knowledge (what's in those memory banks), statistics, intuition, and whatever other fairy dust you sprinkle on.

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