Technology

59143 readers

2284 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

[email protected]

597

A.I.’s un-learning problem: Researchers say it’s virtually impossible to make an A.I. model ‘forget’ the things it learns from private user data (finance.yahoo.com)

submitted 1 year ago by [email protected] to c/[email protected]

208 comments fedilink hide all child comments

I'm rather curious to see how the EU's privacy laws are going to handle this.

(Original article is from Fortune, but Yahoo Finance doesn't have a paywall)

you are viewing a single comment's thread
view the rest of the comments

[–] [email protected] 2 points 1 year ago

It’s a statistical model. Given a sequence of words, there’s a set of probabilities for what the next word will be.

That is a gross oversimplification. LLM's operate on much more than just statistical probabilities. It's true that they predict the next word based on probabilities learned from training datasets, but they also have layers of transformers to process the context provided from a prompt to eke out meaningful relationships between words and phrases.

For example: Imagine you give an LLM the prompt, "Dumbledore went to the store to get ice cream and passed his friend Sam along the way. At the store, he got chocolate ice cream." Now, if you ask the model, "who got chocolate ice cream from the store?" it doesn't just blindly rely on statistical likelihood. There's no way you could argue that "Dumbledore" is a statistically likely word to follow the text "who got chocolate ice cream from the store?" Instead, it uses its understanding of the specific context to determine that "Dumbledore" is the one who got chocolate ice cream from the store.

So, it's not just statistical probabilities; the models' have an ability to comprehend context and generate meaningful responses based on that context.