Our open source AI model, Llama, is going to space. In a standout case of American innovation, Booz Allen has collaborated with Meta to deploy a fine-tuned version of Llama 3.2 aboard the International Space Station (ISS) National Laboratory, where astronauts in low orbit conduct scientific research not possible on Earth.
Why Llama?
As an open source platform, Llama offers greater flexibility and can be downloaded and then deployed on machines without internet access. There’s no need to transfer data through an AI company for processing – helping to secure this highly sensitive environment – or even connect to computers on Earth, which is important since the internet is unavailable on the ISS.
Additionally, Llama’s lower costs and adaptability, made possible by its publicly available “model weights” (the numerical values that determine how Llama makes decisions), are helpful in a setting like the ISS’s National Laboratory, where researchers must be able to respond to new conditions quickly and keep projects on budget.
Transforming Research Processes with Llama
The tech stack used for Space Llama brings together Booz Allen’s own A2E2™ (AI for Edge Environments), Hewlett Packard Enterprise’s (HPE) Spaceborne Computer-2, NVIDIA accelerated computing, enabling powerful AI to operate directly on the ISS, and Meta’s Llama vision AI capabilities. Using a compact, energy-efficient system similar to those used in satellites, the team sped up AI tasks from minutes to just over a second using models fine-tuned with NVIDIA CUDA software and its acceleration libraries, including cuDNN and cuBLAS. As a result of this tech stack, which is believed to be the first of its kind used beyond Earth, astronauts will be able to harness the advantages of digital technologies for research, fast decision-making and agile data access without having to manage the risk of losing connectivity.
Space Llama will include both generative and multimodal AI – in other words, AI that can generate content based on prompts and AI that can process multiple types of data, including textual, visual and auditory. For example, Space Llama can be used to help researchers easily retrieve information from crucial technical reference documents and instructions, no internet needed.
Space Llama builds on Booz Allen’s successful deployment and operation of a generative AI large language model (LLM) in space using HPE’s Spaceborne Computer-2 on the ISS in August 2024. In November 2024, we announced that our open source Llama models would be made available to US government agencies and private sector partners, making Space Llama possible.
“Space innovation has been limited historically due to reliance on Earth-based connectivity for compute and communications capabilities. Space Llama brings tools directly to the edge of space to quickly conduct critical repairs and maintain the ISS National Lab – propelling us towards a future of space-based science, discovery and the ability to operate at the farthest mission edge – space,” said Bill Vass, chief technology officer at Booz Allen.
Space Llama will be deployed in part to address the unique challenges of conducting scientific research in the largest structure human beings have ever put in space. This initiative is set to support the ISS National Laboratory’s researchers in a wide range of scientific projects and represents a critical step for lunar and Mars exploration, enablement of modern satellite and drone capabilities, and the next generation of autonomous systems.
Open Source AI is Essential for Advancing America’s Interests
Meta’s partnership with Booz Allen shows how essential open source AI is to sharpening the U.S.’s competitive edge. AI that’s powerful and durable in outer space, perhaps the most extreme environment imaginable, is ready to help lead the way forward in technological transformations here on Earth.
This moment is just the beginning of Space Llama. We envision a future where open source models like Llama play a vital role in space exploration and research, working “hand in hand” with astronauts as they solve complex scientific problems and help advance innovation for all.
