Our members are building the future of AI

Our perspectives and recommendations in opposition to California SB 1047, the proposed Safe and Secure Innovation for Frontier Artificial Intelligence Models Act.

The AI Accelerator Software Ecosystem Guide provides an introduction to the broad topic of software tools that support seamless execution of AI workloads on different hardware accelerators. Industry experts provide guidance on the state of the art and how to ensure success.

We have seen rapid progress in building and releasing highly-capable and open foundation models for general language, coding, scientific discovery, and multi-modal scenarios.

A key development in model strategies is a focus on building smaller, more specialized models.

More details are coming soon, but we would love for you to join us. We need both model-building and domain experts, including those outside the target domains listed above.

Cataloging and managing trustworthy datasets.

A challenge for software development teams adopting generative AI is making sense of the safety issues that their applications must address. The AI safety ecosystem is broad and growing quickly, making it difficult for these development teams to know where they should focus their efforts. What safety concerns are most important for them to work on first?

The request seeks public input on the potential risks, benefits, and policy approaches for AI foundation models whose weights are broadly accessible.

Time-series applications are an important target for AI. In addition to gathering high-quality and fully-governed time series datasets as part of the Open Trusted Data Initiative, Alliance members are collaborating on new and improved time series models (as part of the Industry Open FMs Initiative and benchmarks, both general-purpose and application-specific.

Please join us. We need time series and domain experts, including especially subject matter experts and use case and product owners who would like to apply emerging time series foundation models to new applications. There is an acute shortage of good, open datasets for time series and data specially benchmarks and evaluation methods for various use cases. Contributions are especially welcome here.

The AI Alliance Trusted Evals request for proposals is aimed at seeking new perspectives in the AI evaluation domain. We are excited to work with those in academia, industry, startups and anyone excited to collaborate in the open and build an ecosystem around their work.

A major challenge for the successful use of AI is the importance of understanding potential trust and safety issues, along with their mitigation strategies. Failure to consider these issues could impact an organization's operations and the experience of its users. Concerns about safety are also a driver for current regulatory initiatives. Hence, applications built with AI must be designed and implemented with AI trust and safety in mind. This guide provides an introduction to trust and safety concerns, and offers guidance for AI projects.