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Status: Unchecked ×Keyword: foundation models ×Clear all

5 claims from 4 papers

1. Social Sciences › Ethics and Social Impacts of AI

   On the Opportunities and Risks of Foundation Models

   Bommasani, Hudson, Adeli et al. · arXiv (Cornell University) · 2021

   A report setting out the opportunities and risks of foundation models, AI models trained on broad data at scale and adaptable to many tasks, covering their capabilities, technical principles, applications and societal impact.

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   1. UncheckedBuilding many AI systems on one shared foundation model gives strong leverage, but any flaws in that model pass on to every system adapted from it.“Homogenization provides powerful leverage but demands caution, as the defects of the foundation model are inherited by all the adapted models downstream.”
   2. UncheckedThe paper says foundation models use standard techniques, but their scale brings new emergent abilities and their wide usefulness encourages homogenization.“Though foundation models are based on standard deep learning and transfer learning, their scale results in new emergent capabilities,and their effectiveness across so many tasks incentivizes homogenization.”

2. Medicine › Artificial Intelligence in Healthcare and Education

   Foundation models for generalist medical artificial intelligence

   Moor, Banerjee, Abad et al. · Nature · 2023

   The paper proposes generalist medical AI, flexible models built through self-supervision on large datasets, and sets out possible applications, needed capabilities and training data, and effects on regulation and data collection.

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   1. UncheckedThe authors propose that generalist medical AI models will be able to perform many different tasks with little or no task-specific labelled data.“GMAI models will be capable of carrying out a diverse set of tasks using very little or no task-specific labelled data.”

3. Earth and Planetary Sciences › Meteorological Phenomena and Simulations

   ClimaX: A foundation model for weather and climate

   Nguyen, Brandstetter, Kapoor, Gupta and Grover · arXiv (Cornell University) · 2023

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   1. Unchecked“The pre-trained ClimaX can then be fine-tuned to address a breadth of climate and weather tasks, including those that involve atmospheric variables and spatio-temporal scales unseen during pretraining.”

4. Computer Science › Artificial Intelligence Applications

   On the foundations of Earth foundation models

   Zhu, Xiong, Wang et al. · Communications Earth & Environment · 2026

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   1. Unchecked“Crafting the ideal Earth foundation model, we define eleven features which would allow such a foundation model to be beneficial for any geoscientific downstream application in an environmental- and human-centric manner.”