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From FAIR Principles to AI-Ready Science
Sept 18, 2026 By Kimberly Mann Bruch, Lynne Schreiber and Christine Kirkpatrick The scientific community continues to implement the FAIR principles, which aim to make data, software and models findable, accessible, interoperable and reusable. Where practices exist, most have not been widely adopted and they vary by discipline. Now, generative AI and large language models are introducing new challenges for how research data and infrastructure are prepared, documented and used.
5 days ago


Do Containers Improve the Reproducibility of Machine Learning Experiments?
Do containers improve the reproducibility of Machine Learning (ML) experiments? First, we need to define what it means to be...
Mar 15, 2024


AI Reproducibility Minute: Implementation Factors
“researcher and practitioner survey[s] shows that 83.8% of participants are unaware of or unsure about any implementation-level...
Dec 1, 2022


Reproducibility in AI, and What Computing Professionals Should Know for Supporting Researchers
This article was written by Kevin Coakley and Alexandra Andreiu. It was published on January 28, 2022 on the GO FAIR US website. The “r”...
Nov 17, 2022
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