this post was submitted on 01 Jun 2024
105 points (88.9% liked)
Technology
59534 readers
3143 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
We invented multi bit models so we could get more accuracy since neural networks are based off human brains which are 1 bit models themselves. A 2 bit neuron is 4 times as capable as a 1 bit neuron but only double the size and power requirements. This whole thing sounds like bs to me. But then again maybe complexity is more efficient than per unit capability since thats the tradeoff.
The network architecture seems to create a virtualized hyperdimensional network on top of the actual network nodes, so the node precision really doesn't matter much as long as quantization occurs in pretraining.
If it's post-training, it's degrading the precision of the already encoded network, which is sometimes acceptable but always lossy. But being done at the pretrained layer it actually seems to be a net improvement over higher precision weights even if you throw efficiency concerns out the window.
You can see this in the perplexity graphs in the BitNet-1.58 paper.
None of those words are in the bible
No, but some alarmingly similar ideas are in the heretical stuff actually.