The internet gave everyone a voice.
Open-source gave everyone a tool.
AI is still waiting.

InfiniteZero is building the commons that changes that.

Data is AI's fuel. Without it, the most sophisticated engines ever built are dead weight.

Most useful data is stranded at the edge — phones, sensors, hospital devices, farm equipment. No way to train where it lives. No one paid to build it. So it sits unused.

Today, access means trusting middlemen, signing contracts, and handing value to platforms that give little back. Even federated learning needs a central coordinator — a gatekeeper deciding who joins, when, and how. Not a philosophical problem. An engineering bottleneck.

So AI that could improve health, farming, and education stays starved.

We're building edge infrastructure that unlocks data where it lives. No intermediaries. No gatekeepers. Trainers get data. Applications deliver. AI is open source by default — not ideology, architecture.

The model isn't the product. The data isn't the product. Utility is: applications that actually improve lives.

You keep using the apps you already use — messaging, health tracking, farming tools, education platforms. Nothing changes about your day.

Behind the scenes, those apps plug in to InfiniteZero. Instead of sending your data to a central server, they keep it stored locally on your device. InfiniteZero plugs into that local data — enabling applications to securely contribute to collective AI training without building expensive infrastructure or moving massive datasets around.

As you go about your routine, your device quietly contributes encrypted, anonymised patterns to the network. Not your data. Not your behaviour. Just patterns that help shared AI models grow smarter for everyone.

Your device learns locally  →  Encrypted patterns join the network  →  Shared AI models improve for everyone

The more people use apps that plug in to InfiniteZero, the better the AI gets — for everyone. You don't have to do anything. You just keep living your life, and the network grows. This is what AI for an open-decentralized internet looks like.

Like a library that gets better every time someone reads from it, but no one has to think about how the shelves are organised.

When AI is trained collectively, in the open, it stops being a product and starts being infrastructure.

This is what AI looks like when it's built for humanity rather than about it.

Apps are built the same way they always have been — but with InfiniteZero plugged in as a backend layer. Users opt in to contribute encrypted learning patterns. Data stays local. The app earns a share of network fees. The models improve for everyone.

You bring the brains. InfiniteZero brings the network.

• Deploy your AI models to the protocol.
• Users' devices train them locally on real-world data.
• Receive anonymized, encrypted updates that make your model smarter — without touching raw user data.
• Your work improves the AI for everyone, everywhere.

What can be trained? In principle, anything. The protocol coordinates phases, stakes, and IPFS CIDs on-chain — it doesn't care about model type, and gas costs don't grow with model size. Each model brings its own services for training, auditing, and aggregation.

• Model families: classical ML, CNNs, MobileNets and other on-device architectures, RNNs/LSTMs, transformers
• LLMs: fine-tuned with federated parameter-efficient methods (FedLoRA / FedQLoRA) — only adapter weights move, not the full base model
• Frameworks: PyTorch, TensorFlow/Keras, scikit-learn, JAX — anything Python can call
• FL algorithms: FedAvg, FedProx, FedOpt variants, SCAFFOLD, FedNova, q-FFL, plus Byzantine-robust aggregators
• FL types: horizontal (default), vertical, heterogeneity-aware, personalized, transfer

The practical limit is hardware and participant availability, not the protocol. Today the MNIST reference is the only end-to-end tested example — everything else is supported by design and needs the model owner to write and test the services.

📘 Full details →

You bring the utility. The network brings the scale.

• Build apps that connect your users to the AI commons.
• Users benefit automatically — smarter recommendations, better predictions, personalized insights.
• Every interaction feeds back to the shared models, so your app grows smarter with the global network, without users ever seeing the protocol.
• Your app earns a share of network fees — generating revenue while your users' data stays entirely in their hands.

📘 Documentation · 🔗 DevNet · 📄 White Paper

When you use an app that plugs in to InfiniteZero, your everyday activity — movement, choices, patterns — quietly helps train AI that belongs to everyone.

Your data never leaves your device. You're not a product. You're a contributor to something shared.

Think of it less like using a service, and more like leaving a book better than you found it.

InfiniteZero runs on Ethereum — open, decentralised, with no central authority. The network is secured by validators. The protocol is governed by the community. The models it trains belong to the commons.

📄 Read the White Paper →

A small team of researchers, developers, and open-source contributors spanning 4 continents — humble origins, rooted in Oxford's Human-Centered Computing division, home to Emeritus Sir Tim Berners-Lee and Sir Nigel Shadbolt. Many years of quiet building. Now it's live.

We're raising funds to scale the network on Giveth — a zero-fee crypto donation platform. Donations are regularly matched, meaning a small contribution goes a long way.

Every dollar you contribute doesn't just fund the work — it helps prove that AI infrastructure built for everyone, by everyone, is possible. You're not a donor. You're a founding contributor to something that belongs to no one and benefits everyone.

➡️ Support us on Giveth

In addition to our core team, a small group of open-source builders already work with us. Each contributes in the area they know best. Some write protocol code. Some work on the cryptography. Some design the developer experience. No one does everything. Each does a small piece.

Individually, these are small contributions. Together, they've made something none of us could have built alone.

These builders join because the network addresses something for them missing in AI today, and their work reflects the values they already hold.

If that resonates, there's a place for you here — matched to what you already do best.

Ways to build with us:

• 🔹 Protocol & Core — consensus, privacy, edge coordination
• 🔹 Cryptography & Privacy — encrypted pattern aggregation, local-first guarantees
• 🔹 Developer Experience — SDKs, docs, integration paths for app builders
• 🔹 Applied AI — model training pipelines, evaluation, federated optimisation
• 🔹 Community & Governance — open deliberation, contributor onboarding, grants

→ github.com/InfiniteZeroFoundation/DevNet
→ docs.infinitezero.network
→ Say hello → abrahamnash@protonmail.com

You don't have to ask permission to start. Pick the area that's already yours, and build.