I hope I'm allowed to share GPT output here because I asked GPT4 to explain OpenAI's postmortem message and this is what it said:
> Large language models (LLMs) like GPT operate using statistics to predict the next word in a sentence. Think of it like a highly sophisticated version of your phone's autocorrect that predicts what you're going to type next, but on a much larger scale.
> The system represents words as numbers, or "tokens," as part of its internal language. It uses these tokens to generate text by selecting them based on how likely they are to come after what's already been written.
> On February 20, 2024, an update meant to improve the system introduced a glitch in the part of the model that picks out these numbers. Imagine trying to grab a red marble from a bag without looking and accidentally grabbing a blue one instead—similarly, the model grabbed the wrong tokens.
> Because of this, the system started spewing out words that didn't make sense together. It's like if your autocorrect suddenly started inserting random, incorrect words into your sentences.
> The technical side of the bug involved something called "inference kernels," which are part of the system's operations. When used with certain types of graphics processing units (GPUs)—special hardware to process data—the kernels didn't work properly.
> Once the error was spotted, a correction was made to the system. After the fix, everything went back to normal, and the model resumed generating coherent responses.
It would be better if they elaborated on what "certain GPU configurations" meant because that's basically the central piece here.
People do it, and it's not against the rules: but, it has died down asymptotically. Though I did see a couple top comments that hid it surviving for ~4 hours this week.
It usually gets downvoted for banal aspects, but ones I've come to agree are important:
- oftentimes it's a lightly edited copy-and-paste of an attempt to summarize an article.
- even with edits, they're extremely long (this is edited, and its 250 words, about 1 page and 1/2 my browser viewport at 4K)
- usually off-topic because it's too broadly on-topic, i.e. its a summary of the article - ex. here, it isn't germane to the comment it's replying to other than 'if you want more info from them, ask what GPUs' -- it's unlikely the commenter needed the whole article ELI5'd to them in reply to their observation they'd like more info
Sort of "grey goo" for conversation, even with best intentions and editing applied.
> Large language models (LLMs) like GPT operate using statistics to predict the next word in a sentence. Think of it like a highly sophisticated version of your phone's autocorrect that predicts what you're going to type next, but on a much larger scale.
> The system represents words as numbers, or "tokens," as part of its internal language. It uses these tokens to generate text by selecting them based on how likely they are to come after what's already been written.
> On February 20, 2024, an update meant to improve the system introduced a glitch in the part of the model that picks out these numbers. Imagine trying to grab a red marble from a bag without looking and accidentally grabbing a blue one instead—similarly, the model grabbed the wrong tokens.
> Because of this, the system started spewing out words that didn't make sense together. It's like if your autocorrect suddenly started inserting random, incorrect words into your sentences.
> The technical side of the bug involved something called "inference kernels," which are part of the system's operations. When used with certain types of graphics processing units (GPUs)—special hardware to process data—the kernels didn't work properly.
> Once the error was spotted, a correction was made to the system. After the fix, everything went back to normal, and the model resumed generating coherent responses.
It would be better if they elaborated on what "certain GPU configurations" meant because that's basically the central piece here.