this post was submitted on 01 Jun 2024
105 points (88.9% liked)
Technology
57418 readers
4924 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
Isn't this true of standard multi-bit neural networks too? This seems to be what a nonlinear activation function achieves: translating the input values into an all-or-nothing activation.
The characteristic of a 1-bit model is not that its activations are recorded in a single but but that its weights are. There are no gradations of connection weights: they are just on or off. As far as I know, that's different from both standard neural nets and from how the brain works.