aistr
Aistr, stylized as aistr, is an open standard and reference implementation for transmitting artificial intelligence inference tasks and results across distributed computing environments. It aims to provide low-latency, interoperable communication for AI workloads that span edge devices, on-premises clusters, and cloud services. By standardizing task definitions, result reporting, and model metadata, aistr seeks to reduce integration costs and enable portable AI pipelines.
Architecture and data model: The core concepts include Task, TaskResult, ModelMeta, and Provenance. A Task encapsulates
Security and governance: Aistr specifies authentication and authorization mechanisms, message signing, and data lineage tracking to
History and status: Initiated by a cross-industry consortium in the early 2020s, aistr was published as an
Limitations: As an evolving standard, interoperability requires adapters for legacy pipelines. Performance depends on network characteristics