Decentralized AI presents a promising alternative to open and closed-sourced AI by leveraging blockchain technology and crypto-based incentives. In decentralized AI systems, no single entity controls the network; instead, ownership, access, and rewards are distributed among participants. This approach addresses the funding and coordination issues that plague open-source AI by introducing token economies that provide ongoing financial incentives to contributors. For example, decentralized networks like NEAR, Bittensor, Allora, Sentient, and Sahara aim to reward participants with native tokens for their contributions to training and improving AI models, creating a sustainable economic model that could enable developers to fund ongoing development.
