this post was submitted on 10 Sep 2023
686 points (95.5% liked)
Technology
59669 readers
2727 users here now
This is a most excellent place for technology news and articles.
Our Rules
- Follow the lemmy.world rules.
- Only tech related content.
- Be excellent to each another!
- Mod approved content bots can post up to 10 articles per day.
- Threads asking for personal tech support may be deleted.
- Politics threads may be removed.
- No memes allowed as posts, OK to post as comments.
- Only approved bots from the list below, to ask if your bot can be added please contact us.
- Check for duplicates before posting, duplicates may be removed
Approved Bots
founded 1 year ago
MODERATORS
you are viewing a single comment's thread
view the rest of the comments
view the rest of the comments
It doesn't hardly understand logic. I'm using it to generate content and it continuously will assert information in ways that don't make sense, relate things that aren't connected, and forget facts that don't flow into the response.
As I understand it as a layman who uses GPT4 quite a lot to generate code and formulas, it doesn't understand logic at all. Afaik, there is currently no rational process which considers whether what it's about to say makes sense and is correct.
It just sort of bullshits it's way to an answer based on whether words seem likely according to its model.
That's why you can point it in the right direction and it will sometimes appear to apply reasoning and correct itself. But you can just as easily point it in the wrong direction and it will do that just as confidently too.
It has no notion of logic at all.
It roughly works by piecing together sentences based on the probability of the various elements (mainly words but also more complex) being there in various relations to each other, the "probability curves" (not quite probability curves but that's a good enough analog) having been derived from the very large language training sets used to train them (hence LLM - Large Language Model).
This is why you might get things like pieces of argumentation which are internally consistent (or merelly familiar segments from actual human posts were people are making an argument) but they're not consistent with each other - the thing is not building an argument following a logic thread, it's just putting together language tokens in common ways which in its training set were found associate with each other and with language token structures similar to those in your question.
That's a great summary of how it works. Well done.