Issue #233

February 2, 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. Hugging Face and Google partner for open AI collaboration [huggingface.co]
2. Machine Learning Engineering Open Book [github.com/stas00]
3. The Big Little Guide to Message Queues [sudhir.io]
4. Lessons from history’s greatest R&D labs [answer.ai]
5. 🦅 Eagle 7B : Soaring past Transformers with 1 Trillion Tokens Across 100+ Languages (RWKV-v5) [blog.rwkv.com]
6. New Theory Suggests Chatbots Can Understand Text [quantamagazine.org]
7. Build a Large Language Model (From Scratch) [github.com/rasbt]

• Temporal rich club phenomenon and its formation mechanisms (M.-Y. Li, Y.-T. Zhang, W.-X. Zhou)
• Routes of importation and spatial dynamics of SARS-CoV-2 variants during localised interventions in Chile (B. Gutierrez, J. L.-H. Tsui, G. Pullano, M. Mazzoli, K. Gangavarapu, R. P. D. Inward, S. Bajaj, R. E. Pena, S. Busch-Moreno, M. A. Suchard, O. G. Pybus, A. Dunner, R. Puentes, S. Ayala, J. Fernandez, R. Araos, L. Ferres, V. Colizza, M. U.G. Kraemer)
• Do You Need a Zero Knowledge Proof? (J. Ernstberger, S. Chaliasos, L. Zhou, P. Jovanovic, A. Gervais)
• An embedding-based distance for temporal graphs (L. Dall'Amico, A. Barrat, C. Cattuto)
• Fast degree-preserving rewiring of complex networks (S. Mannion, P. MacCarron, A. Saxena, F. W. Takes)
• LoMA: Lossless Compressed Memory Attention (Y. Wang, Z. Xiao)
• Tweets to Citations: Unveiling the Impact of Social Media Influencers on AI Research Visibility (I. X. Weissburg, M. Arora, L. Pan, W. Y. Wang)

Large Language Models in Five Formulas

February 2, 2024

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