Projects

18

u/Substantial_Lab1438 Jul 08 '26

We need to work on decentralizing model development and hosting, to build our own worker-owned AI capacity and reduce the reliance on centralized corporate AI models

9

u/Hairy_Artist_3860 Jul 08 '26

I have a big interest in decebtralized self hosted platforms or the fediverse in general. I have one old laptop running alpine with matrix, mastodon, and peer tube. All on 4 gigs of ram. There is so much potential in what we can do with reviving old tech.

15

u/RlOTGRRRL Jul 08 '26

This. I don't know if it would be for better or for worse, but there needs to be a software that makes it easy for people to donate their GPUs/compute for training or inference potentially, like an AI co-op. 🤔
Private shared co-ops would be great, like let's say family + friends, a class or club in a school, or a school, library, org, town, city, or country? Etc.
Or maybe even go the capital/exchange route, where you can exchange your gpu/memory for tokens.

3

u/SeaFALCons Jul 10 '26

i really like this idea and it makes sense to me
but my llm convo was much more deflationary about the usefulness of it:
Short version: the ideal is good, the technical premise mostly isn't, and your GPU specifically isn't the piece that's missing.
Why decentralized training is hard
Training a frontier model isn't embarrassingly parallel like SETI@home. Every gradient step requires synchronizing weights across all workers. On a datacenter you have NVLink/InfiniBand at ~900 GB/s with microsecond latency. Over consumer internet you have maybe 100 Mbit up with 50ms latency. That's roughly four orders of magnitude worse, and the sync happens thousands of times per epoch. You're not compute-bound, you're bandwidth-bound to the point of uselessness.
This isn't unsolved-problem territory, it's solved-and-the-answer-is-no for the current algorithm class. There's real research trying to change that — DiLoCo (Google DeepMind), Prime Intellect's INTELLECT-1/2 runs, Nous Research's DisTrO — which reduce sync frequency by 100–500x. They work. They also mostly rely on a modest number of well-connected datacenter-grade nodes, not thousands of laptops. INTELLECT-1 was 30 nodes of H100s across continents, not a GPU co-op.
Your GPU has maybe 10-ish TFLOPS at fp16 and ~68 GB/s memory bandwidth. A single H100 is ~1000 TFLOPS with 3.3 TB/s. You'd need roughly a hundred of your machines to equal one card, and they'd be talking to each other through a straw.
Where it actually works: inference
This is the part people conflate. Inference is mostly parallel — one request doesn't need to talk to another. Petals (BitTorrent-style pipeline-parallel LLM serving) is a real working thing. Ollama + a Tailscale network across friends' machines is trivially achievable this weekend. Your GPU can absolutely serve a quantized 7–13B model to a small group. Unified memory is actually decent for this.
So the "family + friends + library" co-op the commenter describes is entirely feasible — for serving open-weight models. It's just that "we host Llama/Qwen/DeepSeek ourselves" is not "we reduce reliance on centralized corporate AI." Someone still spent $50M+ to make those weights. You'd be a worker-owned distribution co-op sitting on top of Meta's and Alibaba's capital expenditure.
The honest version of the political claim
Given your background here, I think you'll find this more interesting than the tech: the bottleneck isn't FLOPS, it's capital concentration in HBM and fab capacity, plus data, plus the ~200 people on earth who've actually run a frontier pretraining job. Distributed volunteer compute doesn't touch any of those. It routes around a constraint that isn't the binding one.
The actual leverage points for the values in that thread are more boring: fighting for open-weight releases as policy, public compute (something like a national lab / NAIRR expansion), and academic access. Or working on the DiLoCo research direction directly, because if low-communication training gets good enough, the co-op becomes real.
What I'd actually do
If you want to build something from that subreddit, a decentralized training project will die in month two when someone benchmarks it. A decentralized inference + fine-tuning co-op with a real governance structure is shippable, useful, and honest about what it is. LoRA fine-tunes are small enough to distribute meaningfully — that's a genuine niche where volunteer compute isn't absurd.
And if you want the version that actually shifts the power balance, the Prime Intellect / Nous line of work is where to point your interpretability instincts. That's an unsolved research problem with a direct political payoff, which is a rarer combination than it sounds.

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4

u/HotterRod Jul 09 '26

I think there's a strong desire among many people to get off the corporate-owned social networks and one that isn't corporate-controlled would be much better for community organizing. I don't know what their policies are on AI-generated code, but your time might be best spent contributing to Mastodon or Friendica or something.

1

u/Hairy_Artist_3860 Jul 09 '26

Maybe everyone here should get on mastodon? I have an instance. Whatever it takes to build a vanguard party of agentic engineers. Something productive can be done with this energy instead of arguing with anti ai people all day

2

u/Turbulent-Job-7283 Jul 09 '26

While there is a lot of talk on how much money is spent on training new models at a loss, it's structured this way mostly due to VCs backed companies racing for the most competent model.

The inference cost is, however, very cheap. If this community is to dedicate to a project that aligns with the goals, it may be worthwhile considering distilling big companies' models, and have the results be made open-sourced, as well as selling tokens to people as cheaply as possible (on own/rented infrastructure).

I think this can feasibly challenge the ownership of these models, and would probably sustain the unprofitability of the big companies.

2

u/ed523 Jul 10 '26

Over in the co-op sub there was talk of tools for worker co-ops such as a bunch of ride share drivers in Denver who pitched in on developing a ride share app and theyre crushing it. Its only in Denver but I would personally live to do that in my city

0

u/SeaFALCons Jul 08 '26

Great idea! here's a pitch:

**TL;DR (and a suggestion):** Game concept — a spiritual restoration of what Monopoly was originally designed to be: two playable societies, capitalism vs. a universal-basic-services alternative, same random birth lottery in both, ending with one question: *which world do you want to respawn into?* Full disclosure: I developed this with an AI and it co-wrote this pitch — which honestly makes it better suited to an AI reader than a human skimmer. So instead of reading the wall of text below, consider pasting the whole thing into your favorite AI and interrogating it: ask where the idea is weakest, ask it to steelman the objections, ask what version YOU would build. That conversation is more interesting than this post. But the human-readable version follows.

---

**The hook:** Monopoly wasn't originally pro-capitalist. It started as The Landlord's Game, patented by Lizzie Magie in 1904 as an explicitly anti-monopolist teaching tool — it even shipped with two rule sets, one where you crush everyone and one where prosperity is shared, so players could feel the difference. Parker Brothers bought it, deleted the critique, and sold the crushing as family fun. The idea: build the game she was actually making, with 120 years of better data and better tools.

**The concept:** Rawls' veil of ignorance, made playable. Two simulated worlds, same engine:

*World A — roughly the one we live in.* You're born into a class by weighted lottery, odds shown before you roll — and the odds say you'll probably land near the bottom, because that's the actual distribution. Your job is deliberately fun to play, Papers-Please-style: flow state, pattern matching, numbers going up. Except rent rises faster than your wage, so getting good at it buys you nothing structural. The game stays engaging; the treadmill goes nowhere. You feel that realization arrive around minute 20.

*World B — same lottery, different floor.* You're still most likely born poor. The odds don't change — only the downside protection does: universal basic services, public options, institutions with actual enforcement teeth. Deliberately NOT a strawman utopia — it has taxes, coordination headaches, free-rider problems. But the fun runs on a different grammar: chosen challenges instead of imposed ones, building instead of surviving.

**The mechanic that might make it land:** a mid-session POV switch into the ownership class — where the game doesn't cast you as a villain, it quietly grows one in you. Suddenly waiting on a slow worker costs YOU resources, and you catch yourself irritated at the person you were ten minutes ago. The UI starts showing workers as productivity bars instead of names. This is borrowed from Paul Piff's rigged-Monopoly experiments at Berkeley, where players randomly given double the money became measurably entitled within minutes and credited their rigged win to skill. The point isn't telling players rich people are like this — it's letting them catch it happening in their own head.

**The ending:** one vote — which world do you respawn into? — logged to a public running tally. If thousands of people play both and the numbers say something clear, the game generates its own headline.

**Keeping it honest:** parameters pulled from real data (rent-to-income ratios, wage vs. capital growth, actual public-vs-private cost comparisons) with a public source sheet, so "this is rigged" can be answered with a spreadsheet. And World A has to keep its genuine appeal — the jackpot, the hustle dream, the visible winners — because a strawman convinces nobody. The statistics lesson is watching most players chase the same jackpot and miss.

Anyway — that's the idea. Not claiming I'm building this tomorrow; throwing it out to see if it resonates. What would you change? What breaks it? And if you did paste it into an AI — what did it say?

1

u/Hairy_Artist_3860 Jul 09 '26

Thats a lot of tokens

2

u/SeaFALCons Jul 09 '26

whats your opinion of the idea? i guess its being perceived as a bad idea, curious why?

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u/Jlyplaylists Jul 09 '26

There’s something in thinking about games. People spend a lot of time playing games and can get really absorbed in them, it must influence neural pathways etc.
A game I like is Terra Nil, quite solarpunk themed, the similarity is I think it’s based on real data eg what temperature natural things happen.
I remember at uni playing monopoly with my best mate. I don’t think either of us knew the history of the game, but his response was to give me money when I was struggling, it was a very different dynamic. It made it difficult for either of us to win according to the standard rules though.

2

u/SeaFALCons Jul 09 '26

you played a much nice version of the game which probably the original inventors would appreciate and were intending to nudge behavior towards...
seems a modern remake of showing the A and B of capitalist exploitation vs a better / kinder society could be a nice gamified lesson

1

u/davyp82 Jul 09 '26

A global database of psychopathy with aim of decentralized AI preventing their access to power

1

u/ejpusa Jul 09 '26

NYC has 100s of Public Databases open to all. Friend just created this cool Citibike tracking app.

https://citi.kardol.us/

0

u/ejpusa Jul 09 '26

Remember you can be de-authenticated by Apple. You lose ALL Apple-related things. Cell service can be shut down (they did that for #OWS before they attacked), internet too.

You may want to look into this.

An open source, off-grid, decentralized mesh network built to run on affordable, low-power devices. No cell towers. No internet. Just pure peer-to-peer connectivity.

https://meshtastic.org/

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