Our members are building the future of AI

AIConfig is a config-based framework for building generative AI applications.

BigCode is an open scientific collaboration working on the responsible development and use of large language models for code (Code LLMs), empowering the machine learning and open source communities through open governance.

This work focuses on time-sensitive AI, for example, to rapidly evaluate a photo for interesting content, or even to perform pipelines of intelligent tasks.

Lightning AI has been maintaining key open source frameworks widely used today in GenAI and general deep learning. PyTorch Lightning, Lightning Fabric and TorchMetrics are powering a portion of the GenAI ecosystem today (e.g. StableDiffusion, NeMO, TinyLlama).

A report evaluating the feasibility, benefits, and limitations of using generative AI technologies in an educational setting and its impact on learning outcomes.

A series of code models trained by IBM licensed under Apache 2.0 license. Includes base pretrained and instruct models.

InstructLab is a model-agnostic open source AI project that facilitates contributions to Large Language Models (LLMs).

The Amber project includes a 7B English language model with the LLaMA architecture, an instruction-following model finetuned from LLM360-Amber, and a safety-finetuned instruction model using LLM360-AmberChat as the base.

LangCheck is an open-source toolkit that provides building blocks for developers and organizations to create evaluations, guardrails, and monitoring for their LLM applications. LangCheck supports both English and Japanese text.

Ragna is an open-source RAG-based (Retrieval-Augmented Generation) AI orchestration framework designed to bridge the gap between AI research and production deployment.

Ray is an open-source, unified compute framework that makes it easy to scale AI and Python workloads.

TrustyAI is an open-source toolkit designed for responsible AI.