Intern-Artificial Intelligence Benchmarking

Journal Article · Tue Jan 20 00:00:00 EST 2026 · No journal information

OSTI ID:3014039

Krishnan, Anjay ^[1]

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1. Fermilab

Benchmarks provide a standardized method for evaluating different AI models, enabling reproducibility and comparison between models, and facilitating scientific progress. As AI models continue to develop rapidly, incorporating new datasets, capabilities, and architectures becomes more complicated. Therefore, the current static benchmarks become increasingly irrelevant. The MLCommons team argues that to make AI benchmarks more relevant, it involves making the benchmarks themselves more dynamic, as well as technical innovations that make it easier for scientists and researchers at all levels to use and contribute to the benchmarks. The current progress in technical innovation is a software that allows for a detailed view of a collection of AI benchmarks to be output in various formats that are easily readable and accessible.

• Research Organization: Fermi National Accelerator Laboratory (FNAL), Batavia, IL (United States)
• Sponsoring Organization: US Department of Energy
• DOE Contract Number: 89243024CSC000002
• OSTI ID: 3014039
• Report Number(s): FERMILAB-PUB-25-0495-STUDENT; oai:inspirehep.net:3109111
• Journal Information: No journal information, Journal Name: No journal information
• Country of Publication: United States
• Language: English