Technology

59415 readers

2886 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]

134

Mapping the Mind of a Large Language Model (www.anthropic.com)

submitted 6 months ago by [email protected] to c/[email protected]

21 comments fedilink hide all child comments

I often see a lot of people with outdated understanding of modern LLMs.

This is probably the best interpretability research to date, by the leading interpretability research team.

It's worth a read if you want a peek behind the curtain on modern models.

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

[–] [email protected] 3 points 6 months ago (2 children)

Saying that it's "statistics" is, at best, unhelpful. It conveys no useful information. At worst, it's misleading. What goes on with neural nets has very little to do with what one learns in a stats course.

[–] [email protected] 3 points 6 months ago (1 children)

Yeah, it's about as useful as saying that all of science is "just statistics". Which like, in a literal way, it's true. But science is still what forms the foundation of our entire civilization and base of knowledge.

Knowing that a blood pressure drug works is "just statistics", but you still take it if your blood pressure is high.

[–] [email protected] 3 points 5 months ago

Yes, that's a valid comparison. It's worse with neural nets, though. Much of machine learning is literally applied statistics. That is, a program is written that applies statistical methods to data and then adjusts its behavior. So, saying that it's statistics has the potential to really send people down the wrong track. Many of the "human hallucinations" about AIs result from confusion about this.

[–] [email protected] 3 points 6 months ago* (last edited 6 months ago) (1 children)

Most people don't know what Bayesian statistics are so you could say most people don't really get how machine learning works in general anyway. It's not misleading though as it perfectly sets expectations on what you're getting as output. It's much more healthy to general understanding of AI than anthropomorphizing very inflexible and limited models achieved thanks to technology that is seemingly in a plateau.

[–] [email protected] 3 points 5 months ago (1 children)

I would not expect almost human-like conversation on being told that is just statistics. I'd expect something like the old Markov chain jobs. What kind of knowledge leads you to have higher expectations?

Also, how does Bayesian statistics enter into this?

[–] [email protected] 1 points 5 months ago (1 children)

ELIZA from 1966 was enough to convince people that computer program they were talking to was human. People are now being sold on getting answers to their questions via natural language prompts and those answers are pretty much plausibly sounding sentences that happen to be right sometimes due to probability calculations.

Bayesian statistics is very different from what's being taught up until high school (at least here) and is foundational to earlier machine learning applications like spam filters. It's hard to imagine understanding what LLMs do without basics.

[–] [email protected] 4 points 5 months ago

Those aren't the basics, though. That's how saying it's statistics is misleading. A Bayesian network is not a neural network.