Frequently Asked Questions
Decentralized AI is an approach where artificial intelligence models and decision-making are distributed across blockchain, peer-to-peer networks, and federated systems instead of being controlled by a single centralized entity.
Traditional AI relies on centralized servers and datasets, while Decentralized AI distributes data processing, model training, and decision-making across multiple nodes. This reduces single points of failure and improves transparency, privacy, and trust.
With rising concerns over data privacy, bias, and monopolization of AI by big tech companies, decentralized AI ensures fairness, democratized access, and secure collaboration across industries.
Key technologies include blockchain, smart contracts, federated learning, decentralized storage (IPFS/Filecoin), edge computing, peer-to-peer networks, and cryptographic techniques like zero-knowledge proofs.
benefits of Decentralized AI are
* Enhanced privacy and data sovereignty
* Increased transparency and fairness
* Scalability through distributed networks
* Reduced dependency on central entities
* Democratization of AI access
