Comment by oofbey

14 hours ago

I’ve often suspected these models of getting dumber when the service is under high load. But I’ve never seen actually measured results or proof. Anybody know of real published data here?

5 comments

oofbey

Reply
ayewo  8 hours ago

Here's a recent comment [1] by an OpenAI engineer confirming that they do in fact make such trade offs between intelligence and efficiency.

[1]: https://news.ycombinator.com/item?id=46909905

  • int_19h  6 hours ago

    That comment only says that they have a lot of different options for smaller & faster models that people can opt into. It doesn't say that they dynamically scale things up or down depending on demand.

transcriptase  13 hours ago

ChatGPT was brutal for it a couple years ago. You could tell when it would go into “lazy mode” during peak usage periods.

Suddenly instead of writing the code you asked for it would give some generic bullet points telling you to find a library to do what you asked for and read the documentation.

  • lelanthran  10 hours ago

    > ChatGPT was brutal for it a couple years ago. You could tell when it would go into “lazy mode” during peak usage periods.

    ChatGPT web has been doing this for a week now, for me. Ask some technical question and get a reply absolutely filled with AI phrases (Not $X, Just $Y, the key insight, the deeper insight, etc) dominating about 50% of the text, with the remaining 50% some generic filler stuff partially related to the tech I asked.

    Last night I read through a ChatGPT web response about solutions for a security bootstrapping problem without holding keys/password, and it spat out pages and pages of key insights, all nicely numbered sections with bullet points in each section, without actually answering the question.

    Moved to Claude Web immediately, got a usable answer on the first try.