this post was submitted on 31 Aug 2023
564 points (98.3% liked)
Technology
59402 readers
3434 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
This is a somewhat sensationalist and frankly uninteresting way to describe neural networks. Obviously it would take years of analysis to understand the weights of each individual node and what they're accomplishing (if it is even understandable in a way that would make sense to people without very advanced math degrees). But that doesn't mean we don't understand the model or what it does. We can and we do.
You have misunderstood this article if what you took from it is this:
We do understand how it works -- as an overall system. Inspecting the individual nodes is as irrelevant to understanding an LLM as cataloguing trees in a forest tells you the name of the city to which the forest is adjacent.