Bridging Decentralized AI and Blockchain: Challenges and Solutions

The integration of Deep Learning and Blockchain presents an opportunity to decentralize artificial intelligence, reducing the risks associated with centralized AI models. This paper proposes a novel approach using a consensus protocol that leverages Deep Learning as Proof of Useful Work. The proposed protocol aims to address key challenges related to scalability, security, and efficiency in decentralized AI systems. To validate the protocol, a series of simulations were conducted to analyze reward distribution in networks with both honest and Byzantine nodes. Additionally, an alternative solution using smart contracts was explored, highlighting potential gas cost issues on Layer-1 networks. A Layer-2 implementation is suggested as a scalable alternative to minimize gas costs. The findings demonstrate that a decentralized AI system is achievable with carefully designed protocols and reward mechanisms, though further research is needed to address outstanding challenges.