40
An Analysis of DeepMind's 'Language Modeling Is Compression' Paper
(codeconfessions.substack.com)
this post was submitted on 28 Sep 2023
40 points (100.0% liked)
Technology
59207 readers
3375 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
Firstly—maybe what we consider an “association” is actually an indicator that our brains are using the same internal tokens to store/compress the memories.
But what I was thinking of specifically is narrative memories: our brains don’t store them frame-by-frame like video, but rather, they probably store only key elements and use their predictive ability to extrapolate the omitted elements on demand.
This seems likely to me. The common saying is that "you hear what you want to hear", but I think more accurately it's "you remember what has meaning to you". Recently there was a study that even visual memory was tightly integrated with spoken language: https://www.science.org/doi/10.1126/sciadv.adh0064
However, there's a lot of variation in memory among humans. See: The Mind of a Mnemonist.
Yes, that makes much more sense.
No, because our brains also use hierarchical activation for association, which is why if we're talking about bugs and I say "I got a B" you assume its a stinging insect, not a passing grade.
If it was simple word2vec we wouldn't have that additional means of noise suppression.