this post was submitted on 23 Feb 2026
1 points (100.0% liked)
Technology
82227 readers
4334 users here now
This is a most excellent place for technology news and articles.
Our Rules
- Follow the lemmy.world rules.
- Only tech related news or articles.
- Be excellent to each other!
- 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, this includes using AI responses and summaries. To ask if your bot can be added please contact a mod.
- Check for duplicates before posting, duplicates may be removed
- Accounts 7 days and younger will have their posts automatically removed.
Approved Bots
founded 2 years ago
MODERATORS
you are viewing a single comment's thread
view the rest of the comments
view the rest of the comments
Yeah, "AI is getting pretty good" is a very unpopular opinion in these parts. Popularity doesn't change the results though.
Its unpopular because its wrong.
It's overhyped in many areas, but it is undeniably improving. The real question is: will it "snowball" by improving itself in a positive feedback loop? If it does, how much snow covered slope is in front of it for it to roll down?
I think its far more likely to degrade itself in a feedback loop.
It's already happening. GPT 5.2 is noticeably worse than previous versions.
It's called model collapse.
To clarify : model collapse is a hypothetical phenomenon that has only been observed in toy models under extreme circumstances. This is not related in any way to what is happening at OpenAI.
OpenAI made a bunch of choices in their product design which basically boil down to "what if we used a cheaper, dumber model to reply to you once in a while".
I feel that a lot of what is improving in the recent batch of model releases is the vetting of their training data - basically the opposite of model collapse.
Nothing requires an LLM to train on the entire internet.
That's an excellent point! On that topic I recently listened to an interview of the founder of EleutherAI, who focuses on training small language models. She said they were able to train a 1B parameters reasoning model with 50K Wikipedia articles and carefully curated RL traces. The thing could run in your smartphone and is at parity with much larger models trained on trillions of tokens.
She also scoffed at Common Crawl and said it contained mostly cookies and porn. She had a kind of attitude like "no wonder the big labs need to slurp trillions of tokens when the tokens are such low quality". Very interesting approach, if you understand french I can only recommend the interview.
The very interesting part will be how successful they are at training the training data selectors to choose high quality data sources.
I think a lot of it is still done by hand, and there is also synthetic data distilled from larger models of course.