Discussion
Loading...

#Tag

Log in
  • About
  • Code of conduct
  • Privacy
  • Users
  • Instances
  • About Bonfire
Hacker News
Hacker News
@h4ckernews@mastodon.social  ·  activity timestamp 2 months ago

Streaming AI Agent Desktops with Gaming Protocols

https://blog.helix.ml/p/technical-deep-dive-on-streaming

#HackerNews #Streaming #AI #Agent #Desktops #Gaming #Protocols #AI #Technology #Helix #Blog

  • Copy link
  • Flag this post
  • Block
openSUSE Linux
openSUSE Linux
@opensuse@fosstodon.org  ·  activity timestamp 6 months ago

#openSUSE turns 2️⃣0️⃣! From #desktops to #servers, hackathons to home labs, our community has helped shape the #opensource world. Share your favorite moments, photos and milestones to help us celebrate two decades. #openSUSE20 https://news.opensuse.org/2025/07/09/celebrating-20-yrs-of-os/

  • Copy link
  • Flag this post
  • Block
➴➴➴Æ🜔Ɲ.Ƈꭚ⍴𝔥єɼ👩🏻‍💻
➴➴➴Æ🜔Ɲ.Ƈꭚ⍴𝔥єɼ👩🏻‍💻
@AeonCypher@lgbtqia.space  ·  activity timestamp 8 months ago

Okay, Back of the napkin math:
- There are probably 100 million sites and 1.5 billion pages worth indexing in a #search engine
- It takes about 1TB to #index 30 million pages.
- We only care about text on a page.

I define a page as worth indexing if:
- It is not a FAANG site
- It has at least one referrer (no DD Web)
- It's active

So, this means we need 40TB of fast data to make a good index for the internet. That's not "runs locally" sized, but it is nonprofit sized.

My size assumptions are basically as follows:
- #URL
- #TFIDF information
- Text #Embeddings
- Snippet

We can store an index for 30kb. So, for 40TB we can store an full internet index. That's about $500 in storage.

Access time becomes a problem. TFIDF for the whole internet can easily fit in ram. Even with #quantized embeddings, you can only fit 2 million per GB in ram.

Assuming you had enough RAM it could be fast: TF-IDF to get 100 million candidated, #FAISS to sort those, load snippets dynamically, potentially modify rank by referers etc.

6 128 MG #Framework #desktops each with 5tb HDs (plus one raspberry pi to sort the final condidates from the six machines) is enough to replace #Google. That's about $15k.

In two to three years this will be doable on a single machine for around $3k.

By the end of the decade it should be able to be run as an app on a powerful desktop

Three years after that it can run on a #laptop.

Three years after that it can run on a #cellphone.

By #2040 it's a background process on your cellphone.

  • Copy link
  • Flag this post
  • Block

bonfire.cafe

A space for Bonfire maintainers and contributors to communicate

bonfire.cafe: About · Code of conduct · Privacy · Users · Instances
Bonfire social · 1.0.1-alpha.44 no JS en
Automatic federation enabled
Log in
  • Explore
  • About
  • Members
  • Code of Conduct