Issue #236

February 28, 2024

This week's book is "Computing the Climate" by Steve M. Easterbrook, a captivating journey into the synergy of climate science and computing, making it a must-read for anyone intrigued by the intersection of these fields. Easterbrook's engaging writing style effortlessly demystifies complex concepts, ensuring accessibility for readers with diverse backgrounds. The book's strength lies in its seamless blend of theoretical discussions with real-world examples, showcasing the instrumental role of computing in unraveling the intricacies of climate dynamics.

Easterbrook's balanced perspective sets this book apart, acknowledging the uncertainties in climate science while underscoring the transformative impact of technological advancements. By delving into interdisciplinary connections with policy, economics, and environmental science, Easterbrook provides a holistic understanding of the challenges associated with climate change. This comprehensive approach educates and empowers readers to recognize the pivotal role of computational progress in shaping our collective response to climate-related issues.

In essence, "Computing the Climate" stands as a persuasive testament to the indispensable role of computing in climate research. Easterbrook's skillful narrative not only informs but also inspires readers to grasp the significance of technological innovation in confronting the pressing challenges of our changing climate. This book is an essential addition to the literature, urging readers to actively engage in the ongoing dialogue surrounding the future of our planet.

Computing the Climate

1. From OpenAI to Open LLMs with Messages API on Hugging Face [huggingface.co/blog]
2. Introduction to Geometry [cantorsparadise.com]
3. Explainable AI using expressive Boolean formulas [aws.amazon.com/blogs]
4. Generative Models: What do they know? [Do they know things? Let's find out!]
5. Stable Diffusion 3 [stability.ai]
6. Bloom Filters [samwho.dev]
7. Web Scraping in Python - The Complete Guide [proxiesapi.com]

• Charting mobility patterns in the scientific knowledge landscape (C. K. Singh, L. Tupikina, F. Lécuyer, M. Starnini, M. Santolini)
• Cryptocurrency co-investment network: token returns reflect investment patterns (L. Mungo, S. Bartolucci, L. Alessandretti)
• Complex networks with complex weights (L. Böttcher and M. A. Porter)
• Representation Learning for Frequent Subgraph Mining (R. Ying, T. Fu, A. Wang, J. You, Y. Wang, J. Leskovec)
• Human-machine social systems (M. Tsvetkova, T. Yasseri, N. Pescetelli, T. Werner)
• Artificial Intelligence for Complex Network: Potential, Methodology and Application (J. Ding, C. Liu, Y. Zheng, Y. Zhang, Z. Yu, R. Li, H. Chen, J. Piao, H. Wang, J. Liu, Y. Li)
• Every Model Learned by Gradient Descent Is Approximately a Kernel Machine (P. Domingos)

The Trillion Dollar Equation

February 28, 2024

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