July 10, 2026
Year of AI 2026 · Updated July 2026
SAUDI COMPUTE
The Kingdom's Compute Buildout, Tracked.
Sovereign AI Infrastructure · Capital Flows · Geopolitical Intelligence

Report · Page 187

report.pdf

Page 187 · 716 words

On the Opportunities and Risks of Foundation Models
187
data, pathology images, and clinical outcomes. IEEE Transactions on Biomedical Engineering 58, 12 (2011), 3469–3474.
Diane M Korngiebel and Sean D Mooney. 2021. Considering the possibilities and pitfalls of Generative Pre-trained
Transformer 3 (GPT-3) in healthcare delivery. NPJ Digital Medicine 4, 1 (2021), 1–3.
Christine Korsgaard. 2009. Self-constitution : agency, identity, and integrity. Oxford University Press, Oxford New York.
SE Kreps and DL Kriner. 2020. Model uncertainty, political contestation, and public trust in science: Evidence from the
COVID-19 pandemic. Science advances 6, 43 (2020), eabd4563.
Sarah Kreps, R. Miles McCain, and Miles Brundage. 2020. All the News That’s Fit to Fabricate: AI-Generated Text as a Tool
of Media Misinformation. Journal of Experimental Political Science (2020), 1–14. https://doi.org/10.1017/XPS.2020.37
Kundan Krishna, Sopan Khosla, Jeffrey P Bigham, and Zachary C Lipton. 2020. Generating soap notes from doctor-patient
conversations. arXiv preprint arXiv:2005.01795 (2020).
Kalpesh Krishna, Gaurav Singh Tomar, Ankur P Parikh, Nicolas Papernot, and Mohit Iyyer. 2019. Thieves on sesame street!
model extraction of bert-based apis. arXiv preprint arXiv:1910.12366 (2019).
Ranjay Krishna, Yuke Zhu, Oliver Groth, Justin Johnson, Kenji Hata, Joshua Kravitz, Stephanie Chen, Yannis Kalantidi,
Li-Jia Li, David A. Shamma, Michael S. Bernstein, and Fei-Fei Li. 2017. Visual genome: Connecting language and vision
using crowdsourced dense image annotations. International Journal of Computer Vision 123 (2017), 32–73.
Alex Krizhevsky, Geoffrey Hinton, et al. 2009. Learning multiple layers of features from tiny images. (2009).
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton. 2012. Imagenet classification with deep convolutional neural
networks. Advances in neural information processing systems 25 (2012), 1097–1105.
Harlan M Krumholz, Sharon F Terry, and Joanne Waldstreicher. 2016. Data acquisition, curation, and use for a continuously
learning health system. Jama 316, 16 (2016), 1669–1670.
Rohith Kuditipudi, Xiang Wang, Holden Lee, Yi Zhang, Zhiyuan Li, Wei Hu, Sanjeev Arora, and Rong Ge. 2019. Explaining
landscape connectivity of low-cost solutions for multilayer nets. arXiv preprint arXiv:1906.06247 (2019).
Taku Kudo and John Richardson. 2018. SentencePiece: A simple and language independent subword tokenizer and
detokenizer for Neural Text Processing. In EMNLP.
Ananya Kumar, Tengyu Ma, and Percy Liang. 2020a. Understanding Self-Training for Gradual Domain Adaptation. In
International Conference on Machine Learning (ICML).
Ananya Kumar, Aditi Raghunathan, Robbie Matthew Jones, Tengyu Ma, and Percy Liang. 2022. Fine-Tuning Distorts
Pretrained Features and Underperforms Out-of-Distribution. In International Conference on Learning Representations
(ICLR).
Aviral Kumar, Aurick Zhou, George Tucker, and Sergey Levine. 2020b. Conservative Q-Learning for Offline Reinforcement
Learning. (2020). https://arxiv.org/abs/2006.04779
Keita Kurita, Nidhi Vyas, Ayush Pareek, Alan W Black, and Yulia Tsvetkov. 2019. Measuring bias in contextualized word
representations. arXiv preprint arXiv:1906.07337 (2019).
Alexandre Lacoste, Alexandra Luccioni, Victor Schmidt, and Thomas Dandres. 2019. Quantifying the carbon emissions of
machine learning. arXiv preprint arXiv:1910.09700 (2019).
Iro Laina, Christian Rupprecht, Vasileios Belagiannis, Federico Tombari, and Nassir Navab. 20
→ report.pdf page 187