About NDIF
Powerful large-scale Artificial Intelligence (AI) systems such as Large Language Models (LLMs) herald a new era of AI that is poised to reshape society, but scientists cannot explain their predictions. The NSF National Deep Inference Fabric (NDIF) is a research computing project that enables researchers and students to crack open the mysteries inside these enormous neural networks.
Because large-scale AI systems are trained automatically using massive amounts of data — instead of being designed line-by-line by a programmer — the internal workings of the current generation of AI are inscrutable to humans. Understanding how these systems work is an emerging science. But performing science on the internals of such large-scale AI systems requires substantial computational resources that are not practical at institutional scale, because the infrastructure required to study the detailed computations of AI differs from the computing systems used for ordinary commercial deployment of AI.
NDIF addresses this critical need by creating a unique nationwide research computing fabric that enables scientists to perform transparent and reproducible experiments on the largest-scale open AI systems. NDIF will advance our nation's understanding of the capabilities of large-scale AI systems, as well as their limitations, robustness, safety issues, and impacts on human society.
NDIF is supported by a grant from the U.S. National Science Foundation. It is developed by a team at Northeastern University in Boston, Massachusetts. Computing capacity comes from Delta at NCSA, University of Illinois Urbana-Champaign. The NDIF community is developed in partnership with PIT-UN, a consortium of 63 universities and colleges.
Our Team
NDIF is developed by a team at Northeastern University's Khoury School of Computer Sciences.
Our Partners
External Advisory Board
The ESAB 2025 advises NDIF on strategic direction, community needs, and impact across disciplines.
Get in Touch
Interested in using NDIF, collaborating, or learning more? Reach out through any of the channels below.