Recent breakthroughs in AI, and generative AI in particular, have captured the public’s imagination and demonstrated what those developing these technologies have long known — they have the potential to help people do incredible things, create a new era of economic and social opportunities, and give individuals, creators, and businesses new ways to express themselves and connect with people.

Meta has put exploratory research, open source, and collaboration with academic and industry partners at the heart of our AI efforts for over a decade. We’ve seen first-hand how innovation in the open can lead to technologies that benefit more people. Dozens of large language models have already been released and are driving progress by developers and researchers. They’re being used by businesses as core ingredients for new generative AI-powered experiences. We’ve been blown away by the huge demand for Llama 1 from researchers — with more than 100,000 requests for access to the large language model — and the amazing things they’ve achieved by building on top of it.

Now, with this expanded partnership, Microsoft and Meta are supporting an open approach to provide increased access to foundational AI technologies to the benefits of businesses globally. It’s not just Meta and Microsoft that believe in democratizing access to today’s AI models. We have a broad range of diverse supporters around the world who believe in this approach too — including companies that have given us early feedback and are excited to build new products with Llama 2, cloud providers that will include Llama 2 in their offerings for customers, research institutions who are collaborating with us on the safe and responsible deployment of large generative models, and people across tech, academia, and policy who see the benefits as we do.

Red-Teaming Exercises: Our fine-tuned models have been red-teamed — tested for safety — through internal and external efforts. The team worked to generate adversarial prompts to facilitate model fine-tuning. In addition, we commissioned third parties to conduct external adversarial testing across our fine-tuned models to similarly identify gaps in performance. These safety fine-tuning processes are iterative; we will continue to invest in safety through fine-tuning and benchmarking and plan to release updated fine-tuned models based on these efforts.

• Transparency Schematic: We explain our fine-tuning and evaluation methods for the model and identify its shortcomings. Our transparency schematic, which is located within the research paper, discloses known challenges and issues we’ve experienced and provides insight into mitigations taken and future ones we intend to explore.
• Responsible Use Guide: We created this guide as a resource to support developers with best practices for responsible development and safety evaluations. It outlines best practices reflective of current, state-of-the-art research on responsible generative AI discussed across the industry and the AI research community.
• Acceptable Use Policy: We put a policy in place that prohibits certain use cases to help ensure that these models are being used fairly and responsibly.

Open Innovation AI Research Community: Today, we also launched a new partnership program for academic researchers that aims to deepen our understanding of the responsible development and sharing of large language models. Researchers may apply to join a community of practitioners to share learnings on this important topic, and the community will form a research agenda to pursue going forward.

• Llama Impact Challenge: We want to activate the community of innovators who aspire to use Llama to solve hard problems. We are launching a challenge to encourage a diverse set of public, non-profit, and for-profit entities to use Llama 2 to address environmental, education and other important challenges. The challenge rules will be available prior to the start of it.

We look forward to seeing what the world builds with Llama 2.