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Welcome to the official documentation of AI Vulnerability Database (AVID)!
As the first open-source, extensible knowledge base of failures across the AI Ecosystem (e.g. data sets, models, systems), AVID aims to
encompass coordinates of responsible ML such as security, ethics, and performance
build out a taxonomy of potential harms across these coordinates
house full-fidelity information (e.g. metadata, measurements, benchmarks) on evaluation use cases of a harm (sub)category
evaluate models and datasets that are either open-source or accessible through APIs
This site contains information to get you started with different components of AVID.
: a landing place of instances of AI system/model/dataset failures.
: stores information on such instances in a structured manner.
: the official Python toolkit for working with AVID.
Next - Taxonomy