this post was submitted on 10 Aug 2023
167 points (97.2% liked)

Technology

59135 readers
2968 users here now

This is a most excellent place for technology news and articles.


Our Rules


  1. Follow the lemmy.world rules.
  2. Only tech related content.
  3. Be excellent to each another!
  4. Mod approved content bots can post up to 10 articles per day.
  5. Threads asking for personal tech support may be deleted.
  6. Politics threads may be removed.
  7. No memes allowed as posts, OK to post as comments.
  8. Only approved bots from the list below, to ask if your bot can be added please contact us.
  9. Check for duplicates before posting, duplicates may be removed

Approved Bots


founded 1 year ago
MODERATORS
 

Nvidia reveals new A.I. chip, says costs of running LLMs will ‘drop significantly’::Currently, Nvidia dominates the market for AI chips, with over 80% market share, according to some estimates.

all 26 comments
sorted by: hot top controversial new old
[–] Zerfallen@lemmy.world 33 points 1 year ago (1 children)

I'm sure the cost to the consumer will remain exactly the same, or somehow increase.

[–] GenderNeutralBro@lemmy.sdf.org 7 points 1 year ago (1 children)

I'm not worried about that. There will be open competition, because most of this stuff is open-source. Cheaper hardware will open the door for anyone like you or me to set up our own services. Anyone can set up a server with their own hardware (or rent it from Amazon or wherever) and run their own chatbot (with blackjack! and hookers!) instead of using ChatGPT.

This is already possible on consumer hardware, just not with the biggest and best networks. Right now, if I wanted to run, say, BLOOM (an open-source LLM), I'd need to spend close to $100K on hardware. Obviously, that's out of reach for a hobbyist, so I'm limited to using smaller, less advanced networks like LLaMa or GPT-J. Cheaper hardware will help break the hold that the big players currently have over the industry.

[–] abhibeckert@lemmy.world 1 points 1 year ago* (last edited 1 year ago) (1 children)

if I wanted to run, say, BLOOM (an open-source LLM), I’d need to spend close to $100K on hardware

Doesn't that dozens of notes with over a terabyte of RAM each? And state of the art networking?

Sounds closer to $100M than $100K.

If you want to train your own network like they did, you'd want something like that, yeah, but to run the trained network you "only" need ~360GB of memory.

For context, even if you wanted to run this in CPU, there are currently no A5 mobos (Ryzen 7000 series) that support more than 192GB of memory. You literally can't even run it on high-end consumer hardware.