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Midnight is being developed as a data protection blockchain, aimed at safeguarding sensitive commercial and personal data, thereby protecting fundamental freedoms of association, commerce and expression for various stakeholders, including developers, companies and individuals.
Midnight's architecture is centered on a data-protecting smart contract protocol that enables users to shield sensitive data and metadata, providing transparency where necessary while ensuring privacy. This dual approach is significant, as it aims to marry the openness of public blockchains with the confidentiality of private ones, a balance many in the space have sought but found challenging to achieve.
Charles Hoskinson has responded to inquiries regarding the relationship between Midnight and Cardano with pointed clarity. The demands suggest a necessity for Midnight developers to reference Cardano while writing applications for the Midnight blockchain. To this, Hoskinson retorted, highlighting the independence of the two projects by questioning the need for such a reference, thereby shutting down any manufactured drama.
Gamza KhanzadaevThe essence of Hoskinson's response lies in the distinction between the two projects. Midnight, despite sharing lineage through common leadership, is an entity on its own. It does not need to mention Cardano any more than any other blockchain needs to reference a different one when discussing its applications. Both platforms have unique use cases and technical specifications that serve different purposes.
Midnight's value proposition is immense, offering data protection, assurance of data integrity and scalability. It promises to enhance the developer experience with the integration of Zero-Knowledge Proofs (ZK-Snarks), to reduce compliance costs and to maintain systems for organizations by lessening the need to capture and store customer data.
Potential use cases for Midnight’s technology are vast, ranging from shareable KYC credentials, decentralized credit scoring and anonymous voting systems to confidential medical history systems.
Yuri Molchan
Vladislav Sopov
Dan Burgin
Alex Dovbnya