Arivde

Arivde is a distributed computing platform and protocol designed to facilitate collaborative artificial intelligence and edge computing. First proposed in 2019 and developed through an open-source community, Arivde aims to enable decentralized model training, data sharing with privacy controls, and interoperable deployment across heterogeneous devices and cloud environments.

The architecture of Arivde combines a lightweight runtime for edge devices, a peer-to-peer overlay network for coordination, and modular services for model orchestration, data anonymization, and secure aggregation. The protocol supports federated learning, differential privacy mechanisms, and cryptographic techniques such as secure multi-party computation to reduce central data collection while allowing collective model improvement. A registry and versioning system provides discovery and compatibility for models and components.

Arivde has been adopted in pilot projects across domains including Internet of Things deployment, smart city sensing, distributed medical research consortia, and industrial monitoring, where local data sensitivity or intermittent connectivity make centralized solutions less practical. Its open governance model is overseen by a non-profit foundation comprised of contributors from academia, industry, and civil society, which maintains the core specification and community codebase.

Critiques of Arivde focus on challenges of scaling consensus across resource-constrained nodes, the complexity of guaranteeing privacy under varied threat models, and regulatory uncertainty around cross-jurisdictional data processing. Ongoing development emphasizes performance optimization, standardized compliance tooling, and broader interoperability with existing cloud and edge ecosystems.