Issue #219

October 12, 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. The Handbook of Rationality [direct.mit.edu]
2. Tiny Language Models Come of Age [quantamagazine.org]
3. We can predict solar eclipses to the second. Here’s how. [popsci.com]
4. Why the world needs computational social science [petterhol.me]
5. Artificial General Intelligence Is Already Here [noemamag.com]
6. Decomposing Language Models Into Understandable Components [anthropic.com]
7. Role Of Algorithms [matklad.github.io]

• AI and science: what 1,600 researchers think (R. Van Noorden, J. M. Perkel)
• Hyper-cores promote localization and efficient seeding in higher-order processes (M. Mancastroppa, I. Iacopini, G. Petri, A. Barrat)
• Effective Dynamics of Generative Adversarial Networks (S. Durr, Y. Mroueh, Y. Tu, S. Wang)
• Exposing influence campaigns in the age of LLMs: a behavioral-based AI approach to detecting state-sponsored trolls (F. Ezzeddine, O. Ayoub, S. Giordano, G. Nogara, I. Sbeity, E. Ferrara, L. Luceri)
• The structure of segregation in co-authorship networks and its impact on scientific production (A. M. Jaramillo, H. T. P. Williams, N. Perra, R. Menezes)
• Genius Cliques: Mapping out the Nobel Network (M. Janosov)
• The influence of coordinated behavior on toxicity (E. Loru, M. Cinelli, M. Tesconi, W. Quattrociocchi)

Attention Is All You Need

October 12, 2023

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