ResonanceNet

The world's first Proof-of-Training blockchain. Miners don't burn energy on hash puzzles — they train neural networks.

Read Whitepaper Download v0.1.0 Source Code

Why ResonanceNet?

🧠

Proof-of-Training

Every block requires real AI model improvement. Mining energy goes toward training neural networks, not solving useless hash puzzles.

📈

Continuous Growth

The shared model grows autonomously — adding layers and dimensions as the chain advances. No hard forks needed.

MinGRU Architecture

O(1) inference per token with no KV cache. Efficient training and instant text generation from the chain's model.

🔒

Modern Cryptography

Keccak-256d hashing (Ethereum-compatible), Ed25519 block signing, BIP32/44 HD wallets with mandatory recovery.

🎮

Multi-GPU Backends

CUDA, Vulkan, and Metal support. CPU fallback included. Mine on any hardware.

🌐

Decentralized P2P

Bitcoin Core-style networking with encrypted transport, relay protection, and full node verification.

How Mining Works

1

Load Checkpoint

The miner loads the current model checkpoint from the chain tip.

2

Train the Model

Run forward and backward passes on the MinGRU neural network using real training data.

3

Evaluate

Compute validation loss on a deterministic dataset. If loss improved — you found a valid block.

4

Broadcast

Assemble the block with the new checkpoint and broadcast to the network. Other nodes verify the improvement.

31K+
Lines of C++20
15
Libraries
6
Binaries
3
GPU Backends

Join the Testnet

Download pre-built binaries and connect to the seed node.

Linux
x86_64 · tar.gz
macOS
ARM64 · tar.gz
Windows
x64 · zip