Our members partner with the academic community, empowering researchers and students to engage with vital research in AI models, algorithms, and platforms. We are also creating educational materials and resources to inform the public and policymakers about the advantages and risks of AI, offering solutions and advocating for precise, well-informed AI regulations.

We deploy and create benchmarks, tools, and resources to facilitate the responsible global development and use of AI systems. This includes establishing a catalog of vetted tools for safety, security, and trust. We will support these tools' advocacy and integration within the developer community for model and application development. Our members are also working to establish benchmarks and evaluation standards for the release of open models and their integration into applications.

We build and promote open-source tools for model training, tuning, and inference, such as PyTorch. We are also collaborating to simplify, automate, and optimize the deployment and execution of large-scale AI workloads on Kubernetes.

We collaborate on the benchmarking, optimization, and adaptation of AI workloads to accelerate innovation in a diverse set of hardware. Our work focuses on scalability, platform adaptation, and advanced power, energy, and carbon modeling. Benchmarks and metrics developed for model inference, fine-tuning, and energy consumption of large-scale AI workloads will be contributed to the open-source community.

We are responsibly enhancing the ecosystem of open foundation models. We are embracing multilingual and multimodal models, as well as science models tackling broad societal issues like climate change and education. To aid AI model builders and application developers, we’re collaborating to develop and promote open-source tools for model training, tuning, and inference. We are also launching programs to foster the open development of AI in safe and beneficial ways, and hosting events to explore AI use cases.

A thriving and competitive open innovation ecosystem for AI must be a priority for industry, civil society, and academia — policymakers should take note. Though these ecosystems are largely decentralized and self-directed, there's room for policy to aid their growth. Our work will help policymakers and governments recognize and support open innovation ecosystems for AI. We’re also bridging gaps between policy and industry, fostering responsible and ethical AI practices to benefit societies around the world.