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Open Source AI
Open source AI technologies that form the foundation for watsonx
Open Source technologies serve as a critical basis for much of the solutions, software, and platforms delivered by IBM. The AI platform, watsonx, is no exception. Watsonx relies on its open source foundation to empower enterprises to train, tune, and deploy AI across the business, leveraging critical, trusted data wherever it resides.
28 March 2025
Article
Create AI pipelines using Elyra and Kubeflow Pipelines
Use JupyterLab and Elyra to create and run machine learning pipelines.
28 February 2025
Article
The open source ecosystem of watsonx
Learn how open source impacts watsonx through some of the key open source projects that IBM has invested in.
28 February 2025
Article
AI model training with PyTorch
Learn about the basics of PyTorch and it's support for the training, evaluation, and inferencing phases of the machine learning workflow.
28 February 2025
Article
Put the power of AI in your apps without being an AI expert
Use Caikit to serve Hugging Face AI models that are consumed by your application.
19 December 2024
Open Project
LangFlow
LangFlow is a visual framework for building LLM applications with a drag-and-drop interface, making it easy to create complex AI workflows and applications.
12 August 2024
Open Project
Caikit
Caikit is an AI toolkit that enables users to manage models through a set of developer-friendly APIs.
04 August 2024
Open Project
CodeFlare
Open source CodeFlare drastically reduces time to set up, run, and scale machine-learning tests. Learn more and contribute.
26 July 2024
Open Project
Docling
Get your documents ready for generative AI. Parse documents and export them to the desired format with ease and speed.
16 June 2024
Open Project
KServe
A standard cloud-agnostic model inference platform that provides pluggable production serving.
15 June 2024
Open Project
KServe ModelMesh
A mature, general-purpose model serving management and routing layer. Optimized for high volume, high density, and frequently changing model use cases, ModelMesh intelligently loads and unloads models to and from memory to strike a balance between responsiveness and compute.
