NVIDIA Clara Train SDK
Accelerate clinical AI workflows with AI-assisted annotation and secure federated learning.

The Unified Platform for Collaborative, Distributed, and Private Generative AI.
FedML is a pioneering distributed machine learning platform that enables developers to build, train, and deploy AI models anywhere, specifically focusing on data privacy and resource efficiency. In the 2026 landscape, FedML stands as the leading infrastructure for 'Private AI,' allowing enterprises to fine-tune Large Language Models (LLMs) on sensitive data without centralizing it. Its architecture is divided into four key layers: FedML Nexus AI (cloud orchestration), FedML Open Source (algorithmic foundation), FedML Parrot (GPU sharing marketplace), and FedML Octopus (edge device management). This full-stack approach facilitates seamless transitions from local experimentation to massive-scale distributed training across multi-cloud or edge environments. By leveraging advanced protocols like FedAvg and FedProx, FedML reduces communication overhead by up to 10x compared to standard distributed training methods. As data sovereignty regulations tighten globally, FedML provides the essential compliance layer for healthcare, finance, and government sectors to leverage generative AI while maintaining strict data isolation. The platform's 2026 roadmap emphasizes 'Zero-Code' fine-tuning for non-technical domain experts and automated hyper-parameter optimization across decentralized nodes.
A centralized MLOps dashboard for managing distributed experiments across global infrastructure.
Accelerate clinical AI workflows with AI-assisted annotation and secure federated learning.
Accelerating drug discovery and precision medicine through federated learning and multi-modal AI.
The industry-standard AI computing platform for healthcare, genomics, and medical imaging.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
A decentralized GPU marketplace allowing users to rent out idle compute or access low-cost GPUs.
A graphical interface for PEFT (Parameter-Efficient Fine-Tuning) of LLMs.
Communication protocol optimized for unreliable networks and mobile/IoT devices.
Uses Secure Multiparty Computation (SMPC) and Differential Privacy to ensure raw data never leaves the node.
Serverless inference engine for deploying models to decentralized edge nodes.
Specialized workflows for collaboration between different organizations (e.g., multiple banks).
Hospitals cannot share patient data due to HIPAA, preventing large-scale model training.
Registry Updated:2/7/2026
Distribute updated weights back to hospitals.
Small startups cannot afford high H100 cloud costs from major providers.
Processing millions of camera feeds in the cloud is bandwidth-prohibitive.