Issue #218

September 27, 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. Advanced NLP with SpaCy [course.spacy.io]
2. Psychedelics Open Your Brain. You Might Not Like What Falls In. [theatlantic.com]
3. Unleashing the Power of Language Models: A Hacker’s Manifesto [blog.musemind.net]
4. Teaching to machines: What is learning in machine learning entails? [memosisland.blogspot.com]
5. The Paradox That Broke Set Theory [cantorsparadise.com]
6. Causality for Machine Learning [ff13.fastforwardlabs.com]
7. The Emergence of Data Science in Web3 [blog.spectral.finance]

• Link prediction in complex network using information flow (F. Aziz, L. T. Slater, L. Bravo-Merodio, A. Acharjee, G. V. Gkoutos)
• Selective and deceptive citation in the construction of dueling consensuses (A. Beers , S. Nguyen, K. Starbird, J. D. West, E. S. Spiro)
• From alternative conceptions of honesty to alternative facts in communications by US politicians (J. Lasser, S. T. Aroyehun, F. Carrella, A. Simchon, D. Garcia, S. Lewandowsky)
• The limits of human mobility traces to predict the spread of COVID-19: A transfer entropy approach (F. Delussu, M. Tizzoni, L. Gauvin)
• Toward Effective Link Prediction Based on Local Information in Organizational Social Networks (P. Szyman, D. Barbucha)
• Infection patterns in simple and complex contagion processes on networks (D. A. Contreras, G. Cencetti, A. Barrat)
• Temporal networks provide a unifying understanding of the evolution of cooperation (A. Li, Y. Meng, L. Zhou, N. Masuda, L. Wang)

A Hackers' Guide to Language Models

September 27, 2023

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