Making large AI models cheaper, faster and more accessible
A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.
Accelerated deep learning R&D
Training and serving large-scale neural networks with auto parallelization.
Bare bone examples of machine learning in TensorFlow
A unified interface for distributed computing. Fugue executes SQL, Python, Pandas, and Polars code on Spark, Dask and Ray without any rewrites.
Master Federated Learning in 2 Hours—Run It on Your PC!
A distributed task scheduler for Dask
Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.
A crowdsourced distributed cluster for AI art and text generation
Distributed Deep learning with Keras & Spark
Implementation of Communication-Efficient Learning of Deep Networks from Decentralized Data
PySpark + Scikit-learn = Sparkit-learn
Distributed Computing for AI Made Simple
Unified Interface for Constructing and Managing Workflows on different workflow engines, such as Argo Workflows, Tekton Pipelines, and Apache Airflow.
Bagua Speeds up PyTorch
Unleash the power of cloud
Backend.AI is a streamlined, container-based computing cluster platform that hosts popular computing/ML frameworks and diverse programming languages, with pluggable heterogeneous accelerator support including CUDA GPU, ROCm GPU, Gaudi NPU, Google TPU, GraphCore IPU and other NPUs.
Self-hosted AI agent OS. Your memory, chat, agents, and files stay on hardware you own, offline by default, cloud by choice. Offline AI memory (taOSmd), self-hosted multi-framework group chat, a full web desktop + app store, and auto-clustering across the consumer hardware you already have (Orange/Raspberry Pi, Mac mini, gaming PC).
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