Issue #217

September 22, 2023

This week’s Data Science Book, "What Is ChatGPT Doing ... and Why Does It Work?" by Stephen Wolfram. Wolfram, a prominent figure in mathematics and computation, offers a compelling exploration of ChatGPT's success and the broader implications of artificial intelligence while delving into the inner workings of ChatGPT and its historical context.

The book stands out for its accessibility, making complex concepts understandable to non-computer scientists and non-mathematicians alike. Wolfram provides a high-level overview of ChatGPT's components, such as embeddings and transformers, without getting bogged down in technical details.

While acknowledging ChatGPT's successes, Wolfram candidly addresses its limitations, especially in real-world computational tasks. He critically examines ChatGPT's reliance on neural network weightings and raises intriguing questions about intelligence, drawing parallels with biological evolution.

In conclusion, "What Is ChatGPT doing ... and Why Does It Work?" is a thought-provoking read that demystifies AI for a wide audience. Wolfram's expertise and candid exploration make it a must-read for those interested in AI's frontiers and the complexities of intelligence.

What Is ChatGPT Doing ... and Why Does It Work?

1. Guide to Searching and Annotating Text on Maps [machines-reading-maps.github.io]
2. Smart people first in line for COVID-19 vaccines, study suggests [cidrap.umn.edu]
3. Dirty Secrets of BookCorpus, a Key Dataset in Machine Learning [towardsdatascience.com]
4. DALL·E 3 [openai.com]
5. Is the end of AIDS in sight? [economist.com]
6. We've Been Misreading a Major Law of Physics For The Past 300 Years [sciencealert.com]
7. Compiling ML models to C for fun [bernsteinbear.com]

• Toward Effective Link Prediction Based on Local Information in Organizational Social Networks (P. Szyman, D. Barbucha)
• Dirac signal processing of higher-order topological signals (L. Calmon, M. T. Schaub, G. Bianconi)
• Intermediate levels of scientific knowledge are associated with overconfidence and negative attitudes towards science (S. Lackner, F. Francisco, C. Mendonça, A. Mata, J. Gonçalves-Sá)
• Cross-national analyses require additional controls to account for the non-independence of nations (S. Claessens, T. Kyritsis, Q. D. Atkinson)
• The social stratification of internal migration and daily mobility during the COVID-19 pandemic (E. Elejalde, L. Ferres, V. Navarro, L. Bravo, E. Zagheni)
• Network Science in Social Media Analysis: Analyzing Information Diffusion and Viral Trends (K. U. Mir, I. Kilani)
• Link Prediction Based on the Relational Path Inference of Triangular Structures (X. Li, Q. Han, L. Li, Y. Wang)

Social Network Analysis - From Graph Theory to Applications

September 22, 2023

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