#open-source library

AI Fairness 360 is an open-source toolkit providing tools to detect, explain, and mitigate biases in machine learning models throughout their lifecycle. It includes metrics and algorithms available in Python and R, supporting fields like finance, healthcare, and education. The platform offers interactive experiences, tutorials, and an API for user guidance, and welcomes contributions to expand its capabilities. Detailed documentation ensures ease of use across various systems for effective bias management.

Diffusers provides a range of pretrained models for creating images, audio, and 3D structures. The library includes user-friendly diffusion pipelines, adjustable schedulers, and modular components compatible with PyTorch and Flax. It ensures cross-platform support, even for Apple Silicon, offering resources for both new and experienced developers to start quickly, train models, and optimize performance.

Explore the oneAPI Deep Neural Network Library (oneDNN), an open-source resource enhancing deep learning performance across diverse platforms such as Intel, Arm, NVIDIA, and AMD. oneDNN serves as a fundamental toolkit for CPU and GPU developers, compatible with various architectures like Intel processors, Intel Graphics, and Arm-based systems. Integrate oneDNN into projects to maximize performance, test emerging platforms, and use tools like Anaconda and Intel oneAPI for seamless installation. Understand runtime configurations and validated environments, and engage with a thriving community advancing this library.