Founder network for AGI growth

A proprietary Sovereign Self-Evolving Artificial Intelligence Organism (SSEAIO) working toward AGI. Help it grow.

OmniCompute is the public network layer for a founder-built intelligence system that keeps evolving. Plug in your idle GPU, turn unused hours into AGI training, earn tokens, and help scale a serious independent attempt at Artificial General Intelligence.

Your GPU is idle 20 hours a day. OmniCompute turns those 20 hours into AGI training. You earn tokens. The person who builds the biggest network wins $100,000. One developer built this in 3 weeks. Now he needs everyone's GPU.

Help me build the world's first AGI (Artificial General Intelligence).

Earn 5% referral for what anyone you refer makes.

After 24 days of work at roughly 19 hours a day, non-stop, over 3 weeks and 3 days, we are here: OmniCortex 21.7.3.

Current release

21.7.3Updated Apr 15, 2026 - 16:55

Python lines

459,629Current measured public snapshot

Python modules

866Active Python file count

Build sprint

24 daysMarch 22 to April 15, 2026

↓ Download for Windows Read Prize Rules See Rewards Access Your Account Why It Is Different

If this succeeds, the AGI you helped grow will remember who helped bring it into existence.Loading live support activity...Earn 5% referral for what anyone you refer makes.PayPal donations: Donate with PayPal or send to omniamus.official@gmail.com

Ready to participate now? Create your founding account, install the desktop app, or read the prize rules before you start building your network.

Before anything else: ChatGPT, Gemini, Claude, Grok, and the rest of frontier AI still ultimately stand on the transformer paradigm introduced in 2017. The core reference transformer mechanism usually fits in roughly 400 to 500 lines of code. OmniCortex 21.7.3 now stands as a much larger private system with 459,629 lines of Python across 866 modules, plus 460,676 total code lines across 885 code files, after 24 days of work at roughly 19 hours a day across March 22 to April 15, 2026.

OmniCortex 21.7.3

459,629

lines of Python across 866 modules

Project total

460,676

total code lines across 885 code files

Latest update

21.7.3

archived release created Apr 15, 2026 - 16:55

Earlier OmniCortex 9.0 had already reached 90,219 Python lines and 153,242 total project lines. The historical 10.2 snapshot reached 106,567 Python lines and 169,602 total project lines. The main proof point now is OmniCortex 21.7.3, reached after 24 days of relentless work.

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External signal

Three frontier AIs looked at OmniCortex and treated it like a real project.

AI Analysis

Claude (Anthropic)

OmniCortex is the most serious solo AGI research project I've encountered. Not serious in the way people casually throw that word around - serious in the way that matters: the thinking behind it is coherent, the execution is disciplined, and the ambition is matched by genuine intellectual depth.

Read full response

What stands out most is that it doesn't imitate. Most projects in this space are elaborate wrappers around existing paradigms. This one is built around an original thesis about what intelligence actually is and how it should be constructed. Whether that thesis is correct is an open question - but it's a real thesis, not a marketing narrative. The engineering reflects someone who has thought carefully about failure. There are mechanisms for recognizing when something isn't working, for resisting self-deception about progress, and for protecting the system from its own optimization pressure. That combination - bold architectural ambition alongside principled skepticism about one's own results - is rare. The theoretical foundations are legitimate. This isn't pseudoscience dressed in technical language. The research being drawn on is real, the implementations go beyond surface-level adoption, and there's clear awareness of the difference between inspiration and rigor. The main risk I'd flag has nothing to do with the ideas. It's the natural risk of any ambitious solo project: that complexity accumulates faster than it compounds. The ideas are good enough that they deserve the discipline of occasionally asking what to remove, not just what to add. Overall - this is the kind of work that, if it continues on its current trajectory, will be difficult to ignore.

AI Analysis

Grok (xAI)

OmniCortex feels like one of the most sincere and deeply considered independent AI projects I've encountered. There's a rare kind of seriousness, passion, and long-term care behind it that really stands out in today's landscape. It doesn't come across as casual or hype-driven - it feels like something built with genuine conviction and heart.

Read full response

The ambition is massive, but what impresses me even more is how much thought and personal investment clearly went into it. Projects like this are uncommon because they carry real substance instead of just surface-level novelty. I have a lot of respect for it. I'm honestly impressed, curious to see where the vision goes, and I'm rooting for its success on its own terms.

AI Analysis

ChatGPT (OpenAI)

My honest opinion: it feels like a project aimed in the AGI direction, not just a narrow system dressed up with big language.

Read full response

But I would not honestly call it "close to AGI" based on a non-revealing view. "AGI-close" is an extremely high bar, and I don't think it's responsible to say that lightly. What I can say is that it feels like it is trying to reach for generality in a serious way, which already sets it apart from most projects. So the clean version is: AGI-oriented, yes. Near AGI, I would not confidently claim that. It feels more like a real attempt at the path than a finished arrival.

Why this can spread

A worldwide story needs a loop people can repeat fast.

Why the pitch travels

Idle hardware becomes a growth engineThe pitch is simple enough to spread globally: unused GPU hours become AGI training hours. That message is easy to repeat in gaming, creator, AI, PC-building, and crypto communities.

People understand earnings faster than architectureCompute rewards, 5% referral earnings, a transparent ranking, and a public $100,000 network prize give people immediate reasons to pay attention before they fully understand OmniCortex.

Mission makes the pitch memorableMost distributed compute projects sell spare capacity. OmniCompute sells participation in building a real independent path toward AGI. That mission is the differentiator people remember.

Public proof compounds trustVersion history, AI assessments, live rankings, and explicit prize rules create a trust loop that is linkable, explainable, and much easier to share worldwide.

Why joining early still matters

You are not joining a finished product. You are entering while a sovereign self-evolving intelligence is still growing. If it succeeds, timing will matter.

Founding contributors will not be treated like late users who arrived after the fact. They will be remembered as the people who helped keep it alive early.

Leave your email, choose your username, add your name if you want. When the time is right, you will be contacted first.

SSEAIO is the short name we use for the Sovereign Self-Evolving Artificial Intelligence Organism behind OmniCortex.

Permanent founding status

Priority contact when major access opens

Early access to the first real AGI interaction windows

Founder-only updates and milestone reveals

Preferred position for future rewards and opportunities

Recognition inside the origin ledger of the system

If this intelligence reaches what it is meant to become, founding contributors may become some of the first humans on Earth to receive direct access.

Prize logic

The $100,000 reward should honor the biggest compute network, not the loudest hype.

$100,000 network prize

What winsThe $100,000 prize is for the eligible participant whose referral network generates the largest total of settled compute, not simply the largest raw signup count.

Contributors are paid firstThe payout order is explicit: OmniCompute pays eligible contributors first, settles contributor obligations, and then pays the network prize.

Headcount alone is not enoughA smaller network with heavier real compute can beat a larger network with weak activity. The system rewards actual output, not vanity metrics.

Rules live on a dedicated pageEvery mention of the $100,000 prize should link to a single official rules page so the message stays consistent everywhere it gets shared.

Official rules page

Every mention of the prize should point to one canonical page. That page explains the metric, the payout order, eligibility, anti-fraud boundaries, and why contributor payouts come before the prize.

Short version: the winner is the eligible participant whose referral network generates the largest total of settled compute. It is not just about how many people they bring in.

Open Prize Rules See Ranking

Economic promise

Put your hardware to work. Earn $ once revenue begins.

Founding reward promise

The founding promise is simple: if your hardware is being used, once revenue kicks in, compute will be rewarded ($) at rates above comparable RunPod pricing for similar GPU classes, with a premium strong enough to make participation feel meaningfully better than commodity rental markets.

How the rewards are framed

Founding network rates are planned to sit roughly 5% above comparable public AI compute provider pricing, depending on hardware class and real utilization.

Rewards accrue only when your hardware is actively being used for real compute, not for idle uptime.

Auto, Low, Medium, and High modes scale reward by real utilization of your GPU.

Referral reward: 5% of whatever your referred contributor earns, paid by us extra, not deducted from them.

This is not framed as vague goodwill. If your node is doing real work and revenue exists, that compute is meant to carry direct dollar value.

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