530
Senate report says AI will take 97M US jobs in the next 10 years, but those numbers come from ChatGPT
(www.theregister.com)
this post was submitted on 07 Oct 2025
530 points (98.5% liked)
Technology
75792 readers
2480 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
If you understand how LLMs work, that's not surprising.
LLMs generate a sequence of words that makes sense in that context. It's trained on trillions(?) of words from books, Wikipedia, etc. In most of the training material, when someone asks "what's the name of the person who did X?" there's an answer, and that answer isn't "I have no fucking clue".
Now, if it were trained on a whole new corpus of data that had "I have no fucking clue" a lot more often, it would see that as a reasonable thing to print sometimes so you'd get that answer a lot more often. However, it doesn't actually understand anything. It just generates sequences of believable words. So, it wouldn't generate "I have no fucking clue" when it doesn't know, it would just generate it occasionally when it seemed like it was an appropriate time. So, you'd ask "Who was the first president of the USA?" and it would sometimes say "I have no fucking clue" because that's sometimes what the training data says a response might look like when someone asks a question of that form.