A debugger will always interfere with the processes you are looking at, hence making debugging of multithreading-related errors a game of whack-a-mole.
It's a very pleasant debugging experience when you can easily switch threads, have them log what happened first, check the variables in the thread at the moment in time it was hit (vs now), etc. etc.
This and an easy way to attach a line-by-line debugger and I'm golden.
I believe that is a vast minority of developments. And tbh multithreading debugging is a breeze in C# on Rider (except race conditions, those will always be tricky, but also easily identifiable).
Huh? That is the literal opposite of what I said. Like, diametrically opposite.
The system summarizes and hashes docs. The model can only answer from those summaries in that mode. There’s no semantic retrieval step.
No, that's exactly what you wrote.
Now, with this change
SUMM -> human reviews
That would be fixed, but will work only for small KBs, as otherwise the summary would be exhaustive.
Case in point: assume a Person model with 3-7 facts per Person. Assume small 3000 size set of Persons. How would the SUMM of work? Do you expect a human to verify that SUMM? How are you going to converse with your system to get the data from that KB Person set? Because to me that sounds like case C, only works for small KBs.
Again: the proposition is not “the model will never hallucinate.”. It’s “it can’t silently propagate hallucinations without a human explicitly allowing it to, and when it does, you trace it back to source version”.
Fair. Except that you are still left with the original problem of you don't know WHEN the information is incorrect if you missed it at SUMM time.
The system summarizes and hashes docs. The model can only answer from those summaries in that mode
Oh boy. So hallucination will occur here, and all further retrievals will be deterministically poisoned?
So... Rag with extra steps and rag summarization? What about facts that are not rag retrieval?
A very tailored to llms strengths benchmark calls you a liar.
https://artificialanalysis.ai/articles/gemini-3-flash-everything-you-need-to-know (A month ago the hallucination rate was ~50-70%)
I want to believe you, but that would mean you solved hallucination.
Either:
A) you're lying
B) you're wrong
C) KB is very small
Thanks, appreciate it.
It could be cognitive bias (because of the words around it), but the girl on the screenshot does look a bit manly to me (but it also can be lighting, angle, makeup, hair, scales and horns; after all those are the tools of drag and I'm not an expert at gendering peeps. Fortunately my native language has gendered names, verbs and nouns so misgendering someone after their first sentence is gramatically improbable)
I've noticed this on my main page and am here to get educated: what is the meme about?
I'm assuming the meme is about her being male presenting and hit with male pronouns from strangers who assume the gender visually, while the OP would prefer to be addressed by female pronouns (I'm not sure how said strangers should know that though, but that's not the meme point)?
Or is it a meme about being stuck in the process and however she tries she's still male presenting for reasons unknown to her?
My only question is - would the issue be solved if you followed the manual properly?
Ummmm... According to YT, about 50% of new videos is AI generated (20% AI slop, 30% AI brainrot, don't ask me whats the difference), and some industry analytics expect that to grow to 90%>