đThe Problem
Last updated
Last updated
Everything on the blockchain is public. While this has many upsides, it can also lead to censorship, surveillance, targeted theft, and bots front-running trades. This limits the potential for the mass adoption of use cases like on-chain AI, fully on-chain games, secure identity, and confidential voting.
For example, in on-chain AI, where computational tasks are distributed across a network of nodes, robust privacy preservation is essential.
AI models often process sensitive user data like personal info, biometrics, or proprietary business data.
AI models themselves can be valuable intellectual property that could be exposed to theft, reverse-engineering and adversarial attacks from malicious actors.
By ensuring democratic AI accessibility, organizations of all sizes can leverage AI without compromising sensitive data. Prioritizing security allows decentralized AI to realize its full potential as a paradigm for collaborative intelligence, driving AI innovations.