Issue #262
November 6, 2024
Welcome to the November 6th edition of the Data Science Briefing!
The most recent post on the Epidemiology series, Epidemiology 303: Metapopulation Models, explores how to connect multiple populations through a travel matrix. In the graph subsection, you’ll find all you need to know about k-core Decomposition, while in the Visualization section, you can explore The Effects of Vaccination through a WSJ visualization.
In our regularly scheduled content, we ponder why the deep learning boom caught almost everyone by surprise, What Shapes Matrix Multiplications Like, and explore Ensemble Learning for Anomaly Detection.
On the academic front, we learn networked spreading models from noisy and incomplete data, dive into how Large Language Model Influence on Diagnostic Reasoning and explore A Public Dataset Tracking Social Media Discourse about the 2024 U.S. Presidential Election on Twitter/X.
This week’s book recommendation is “Life as No One Knows It: The Physics of Life’s Emergence” by S. I. Walker. You can find all the previous book recommendations on our website. In this week’s video, we have a tutorial on Claude AI – Build Text Summarizers, Image Describers, and More with the Anthropic API.
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Semper discentes,
The D4S Team
This weeks book is "Life as No One Knows It: The Physics of Life's Emergence" by S. I. Walker. In this book, Walker offers a groundbreaking reimagining of life’s nature, challenging traditional definitions and exploring the origins of living systems from a fresh perspective. At the heart of the book lies Assembly Theory, which proposes that all matter can be viewed as information, with life representing a highly complex assembly of causal information. This paradigm-shifting framework not only redefines life universally but also paves the way for identifying non-terrestrial life forms.
In an interdisciplinary approach that blends insights from Physics and Philosophy, the book explores key distinctions between knowledge, information, and consciousness. It encourages readers to move beyond anthropocentric perspectives, prompting us to consider the existence of life forms vastly different from anything encountered on Earth.
- 1. Why the deep learning boom caught almost everyone by surprise [understandingai.org]
- 2. What Shapes Do Matrix Multiplications Like? [thonking.ai]
- 3. You-Get: command-line utility to download media contents [github.com/soimort]
- 4. Embeddings are underrated [technicalwriting.dev]
- 5. How I write code using Cursor: A review [arguingwithalgorithms.com]
- 6. Creating a Knowledge Graph for ICD Codes using LLMs [ai.gopubby.com]
- 7. Ensemble Learning for Anomaly Detection [towardsdatascience.com]
- • Network community detection via neural embeddings (S. Kojaku, F. Radicchi, Y.-Y. Ahn,S. Fortunato)
- • Learning of networked spreading models from noisy and incomplete data (M. Wilinski, A. Y. Lokhov)
- • Using Mathematics to Make Money (J. Simons)
- • Large Language Model Influence on Diagnostic Reasoning (E. Goh, R. Gallo, J. Hom, E. Strong, Y. Weng, H. Kerman, J. A. Cool, Z. Kanjee, A. S. Parsons, N. Ahuja, E. Horvitz, D. Yang, A. Milstein, A. P. J. Olson, A. Rodman, H. Chen)
- • A Public Dataset Tracking Social Media Discourse about the 2024 U.S. Presidential Election on Twitter/X (A. Balasubramanian, V. Zou, H. Narayana, C. You, L. Luceri, E. Ferrara)
- • Information diffusion assumptions can distort our understanding of social network dynamics (M. R. DeVerna, F. Pierri, R. Aiyappa, D. Pacheco, J. Bryden, F. Menczer)
- • Language Models Learn to Mislead Humans via RLHF (J. Wen, R. Zhong, A. Khan, E. Perez, J. Steinhardt, M. Huang, S. R. Bowman, H. He, S. Feng)
Learn Claude AI – Build Text Summarizers, Image Describers, and More with the Anthropic API
All our videos are also available in our
YouTube playlist.
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