I wonder how easy it would be to influence super LLMs if a particular group of people created enough articles that were clear to any human reader that it's a load of garbage and rubbish and should ignore it but if a LLM was to parse it wouldn't realise and then ruin it's reasoning and code generation abilities?
Making o1, o3, and Sonnet 3.7 hallucinate for everyone
61–70 of 233 posts
Re: Making o1, o3, and Sonnet 3.7 hallucinate for everyone
#62[flagged]
Until it's got several nines, it's not trustworthy. A $3 drugstore calculator has more accuracy and reliability nines than any of today's commercial AI models and even those might not be trustworthy in a variety of situations. There is no self awareness about accuracy when the model can not provide any kind of confidence scores. Couching all of its replies in "this is AI so double check your work" is not self awarene…
If I need to double check the work why would I waste my time with the AI when I can just go straight to real sources?
Re: Making o1, o3, and Sonnet 3.7 hallucinate for everyone
#63> Conclusion > LLMs are really smart most of the time. No, the conclusion is they’re never “smart”. All they do is regurgitate text which resembles a continuation of what came before, and sometimes—but with zero guarantees—that text aligns with reality.
Similar the thing at the end with "I find it endearing". I mean, the author feels what he feels, but personally I find this LLM behavior disgusting and depressing.
Re: Making o1, o3, and Sonnet 3.7 hallucinate for everyone
#64I wonder how easy it would be to influence super LLMs if a particular group of people created enough articles that were clear to any human reader that it's a load of garbage and rubbish and should ignore it but if a LLM was to parse it wouldn't realise and then ruin it's reasoning and code generation abilities?
It's very easy. I've done this by accident. One of my side projects helps users price the affordability of a particular kind of product. When I ask various LLMs "can I afford X" or "how much do I need to earn to buy X", my project comes up as a source/reference. I currently manually crawl retailers for the MSRP so these numbers are usually months out of date!
Re: Making o1, o3, and Sonnet 3.7 hallucinate for everyone
#65I've got a lot of hallucinations like that from LLMs. I really don't get how so many people can get LLMs to code most of their tasks without those issues permanently popping up.
GPT can't even tell what its done or give what it knows it should. It's endless, "Apologies, here is what you actually asked for ..." and again it isn't.
Re: Making o1, o3, and Sonnet 3.7 hallucinate for everyone
#66I've got a lot of hallucinations like that from LLMs. I really don't get how so many people can get LLMs to code most of their tasks without those issues permanently popping up.
A language like Golang tries really hard to only have _one_ way to do something, one right way, one way. Just one way. See how it was before generics. You just have a for loop. Can't really mess up a for loop.
I predict that the variance in success in using LLM for coding (even agentic coding with multi-step rather than a simple line autosuggest or block autosuggest that many are familar with via CoPilot) has much more to do with:
1) is the language a super simple, hard to foot-gun yourself language, with one way to do things that is consistent
AND
2) do juniors and students tend to use the lang, and how much of the online content vis a vis StackOverflow as an example, is written by students or juniors or bootcamp folks writing incorrect code and posting it online.
What % of the online Golang is GH repo like Docker or K8s vs a student posting their buggy Gomoku implementation in StackOverflow?
The future of programming language design has AI-comprehensibility/AI-hallucination-avoidance as one of the key pillars. #1 above is a key aspect.
Re: Making o1, o3, and Sonnet 3.7 hallucinate for everyone
#67Earlier quoted context omitted.
I try to keep "boring" code to a minimum, by finding meaningful and simple abstractions. LLMs are especially bad handling those, because they were not trained on non-standard abstractions. Edit: most LLMs are great for spitting out some code that fulfills 90% of what you asked for. That's sometimes all you need. But we all know that the last 10% usually take the same amount of effort as the first 90%.
This is what got me in most sleepless nights, crunch and ass clenching production issues over my career. Simple repetitive shit is easy to reason about, debug and onboard people on. Naturally it's balancing act, and modern/popular frameworks are where most people landed, there's been a lot of iteration in this space for decades now.
I've made the opposite observation. Without proper abstractions code bases grow like crazy. At some point they are just a huge amount of copy, paste, and slight modification. The amount of code often grows exponentially. With more lines of code comes more effort to maintain it.
After a few years those copy and pasted code pieces completely drift apart and create a lot of similar but different issues, that need to be addressed one by one.
My approach for designing abstractions is always to make them composable (not this enterprise java inheritance chaos). To allow escaping them when needed.
Re: Making o1, o3, and Sonnet 3.7 hallucinate for everyone
#68I've got a lot of hallucinations like that from LLMs. I really don't get how so many people can get LLMs to code most of their tasks without those issues permanently popping up.
A language like Golang tries really hard to only have _one_ way to do something, one right way, one way. Just one way. See how it was before generics. You just have a for loop. Can't really mess up a for loop. I predict that the variance in success in using LLM for coding (even agentic coding with multi-step rather than a simple line autosuggest or block autosuggest that many are familar with via CoPilot) has much mo…
> A language like Golang tries really hard to only have _one_ way to do something
Really?
Logging in Go: A Comparison of the Top 9 Libraries
https://betterstack.com/community/guides/logging/best-golang...
Re: Making o1, o3, and Sonnet 3.7 hallucinate for everyone
#69It’s not really hallucinating though, is it? It’s repeating a pattern in its training data, which is wrong but is presented in that training data (and by the author of this piece, but unintentionally) as being the solution to the problem. So this has more in common with an attack than a hallucination on the LLM’s part.
So nothing is a hallucination ever, because anything a LLM ever spits out is somehow somewhere in the training data?
No. That’s not correct. Hallucination is a pretty accurate way to describe these things.
Re: Making o1, o3, and Sonnet 3.7 hallucinate for everyone
#70I've got a lot of hallucinations like that from LLMs. I really don't get how so many people can get LLMs to code most of their tasks without those issues permanently popping up.
> LLMs. I really don't get how so many people can get LLMs to code most of their tasks without those issues permanently popping up.
You write tests in the same way as you would when checking your own work or delegating to anyone else?