this post was submitted on 28 Feb 2024
474 points (97.4% liked)
Technology
59562 readers
2348 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
The "solutions" to model collapse - essentially retraining on the original data set - suggests LLMs plateau or deteriorate. Especially without a way to separate out good and bad quality data (or ad they euohemistically try and say human vs AI data).
Were increasingly seeing the limitations and flaws with LLMs. "Hallucinations" or better described as serious errors, model collapse and complete collapse suggest the current approach to LLMs is probably not going to lead to some gone of general AI. We have models we don't really understand that have fundamental flaws and limitations.
Unsurprising that they probably can't live up to the hype.
Even if it will plateau, same was said with moorrs law, which held up way longer than expected. There are so many ways to improve this. Open source community is getting to the point where you can actually run decent models on normal private hardware (talking about 70-120b model)