Pearl blockchain integrates AI inference with mining rewards through Proof-of-Useful-Work

Most blockchain mining burns electricity to solve puzzles that exist solely to prove you burned electricity. Pearl, a Layer-1 blockchain built by Pearl Research Labs, decided that was a waste of perfectly good GPUs and built something different: a network where the math miners do to earn block rewards is the same math that powers AI inference. The project’s Proof-of-Useful-Work (PoUW) consensus mechanism uses matrix multiplications, the foundational operations behind neural network inference, as its proof-of-work function. Miners run these computations on high-powered NVIDIA GPUs, simultaneously securing the network and producing real AI outputs. Pearl calls it a “2-for-1” model, and the math checks out: the overhead sits at roughly 1+o(1), which in plain terms means the extra computational cost of doing both jobs at once is negligible. How the dual-purpose engine works When a miner on Pearl’s network processes a block, they’re performing matrix operations that can serve as part of an AI inference pipeline. The results are verifiable on-chain, meaning the network can confirm the work was done correctly without re-running the entire computation. The network launched its mainnet on A...