Earlier quoted context omitted.
A good prompt. You don’t just ask it. You tell it how to behave and give it a shot load of context
With Claude the context window is quite small. But with adding too much context it often seems to get worse. If the context is not carefully narrowly picked and too unrelated, the LLMs often start to do unrelated things to what you've asked. At some point it's not really worth anymore creating the perfect prompt, just code it yourself. Also saves the time to carefully review the AI generated code.
Making o1, o3, and Sonnet 3.7 hallucinate for everyone
101–110 of 233 posts
Re: Making o1, o3, and Sonnet 3.7 hallucinate for everyone
#102I'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.
I have made large projects using Claude, with success. I know what I want to do and how to do it, maybe my prompts were right.
Re: Making o1, o3, and Sonnet 3.7 hallucinate for everyone
#103It’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.
Every LLM hallucination comes from some patterns in the training data, combined with lack of awareness that the result isn’t factual. In the present case, the hallucination comes from the unawareness that the pattern was a proposed syntax in the training data and not an actual syntax.
Re: Making o1, o3, and Sonnet 3.7 hallucinate for everyone
#104ChatGPT used to assure me that you can use JS dot notation to access elements in a Python dict. It also invented Redocly CLI flags that don't exist. Claude sometimes invents OpenAPI specification rules. Any time I ask anything remotely niche, LLMs are often bad.
Any time I ask anything, LLMs are often bad. inb4 you just aren't prompting correctly
Re: Making o1, o3, and Sonnet 3.7 hallucinate for everyone
#105It’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 anyone can make up some random syntax/fact and post it once, and in some cases the model will take it as truth. I don't know if there's a widely agreed-on definition of "hallucination", but if this isn't one, then the distinction is meaningless imo.
Re: Making o1, o3, and Sonnet 3.7 hallucinate for everyone
#106Earlier quoted context omitted.
I once asked Perplexity (using Claude underneath) about some library functionality, which it totally fabricated. First, I asked it to show me a link to where it got that suggestion, and it scolded me saying that asking for a source is problematic and I must be trying to discredit it. Then after I responded to that it just said “this is what I thought a solution would look like because I couldn’t find what you were as…
It baffles me how the LLM output that Google puts at the top of search results, which draws on the search results, manages to hallucinate worse than even an LLM that isn't aided by Web results. If I ask ChatGPT a relatively straightforward question, it's usually more or less accurate. But the Google Search LLM provides flagrant, laughable, and even dangerous misinformation constantly. How have they not killed it off…
Re: Making o1, o3, and Sonnet 3.7 hallucinate for everyone
#107I'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.
I have made large projects using Claude, with success. I know what I want to do and how to do it, maybe my prompts were right.
Re: Making o1, o3, and Sonnet 3.7 hallucinate for everyone
#108Earlier quoted context omitted.
I have made large projects using Claude, with success. I know what I want to do and how to do it, maybe my prompts were right.
How do you deal with large files? After about a thousand lines in a file, it starts to cough for me. Forgets that some functions exist and makes up inferior duplicate ones.
Re: Making o1, o3, and Sonnet 3.7 hallucinate for everyone
#109Earlier quoted context omitted.
I have made large projects using Claude, with success. I know what I want to do and how to do it, maybe my prompts were right.
How do you deal with large files? After about a thousand lines in a file, it starts to cough for me. Forgets that some functions exist and makes up inferior duplicate ones.
Let us say there is 3k lines of RFCs, API, documentation of niche languages, examples), 2k lines of code generated by Claude (iteratively, starting small), then I do exceed the limit after a while. In that case I ask it to summarize everything in detail, start a new chat, use those 3k lines and the recent code, and continue ad infinitum.