ChatGPT and the Future of AI: The Deep Language Revolution (book cover)

In ChatGPT and the Future of AI, the sequel to The Deep Learning Revolution, Terrence Sejnowski offers a nuanced exploration of large language models (LLMs) like ChatGPT and what their future holds. How should we go about understanding LLMs? Do these language models truly understand what they are saying? Or is it possible that what appears to be intelligence in LLMs may be a mirror that merely reflects the intelligence of the interviewer? In this book, Sejnowski, a pioneer in computational approaches to understanding brain function, answers all our urgent questions about this astonishing new technology.

Sejnowski begins by describing the debates surrounding LLMs’ comprehension of language and exploring the notions of “thinking” and “intelligence.” He then takes a deep dive into the historical evolution of language models, focusing on the role of transformers, the correlation between computing power and model size, and the intricate mathematics shaping LLMs. Sejnowski also provides insight into the historical roots of LLMs and discusses the potential future of AI, focusing on next-generation LLMs inspired by nature and the importance of developing energy-efficient technologies.

Grounded in Sejnowski’s dual expertise in AI and neuroscience, ChatGPT and the Future of AI is the definitive guide to understanding the intersection of AI and human intelligence.

Terrence J. Sejnowski is Francis Crick Chair at The Salk Institute for Biological Studies and Distinguished Professor at the University of California at San Diego. He has published over 500 scientific papers and 12 books, including The Computational Brain with Patricia Churchland. He was instrumental in shaping the BRAIN Initiative that was announced by the White House in 2013, and he received the prestigious Gruber Prize in Neuroscience in 2022.

Sejnowski and Shermer discuss:

Large Language Models
ChatGPT, GPT-4, GPT-5 and beyond
What is AI and AGI?
The alignment problem
What set of values should AI be aligned with, and what legal and ethical status should it have?
What is thinking?
How brains evolved
Reverse engineering brains
How language evolved
Artificial intelligence and natural intelligence
Emotions, mind, and sentience
What is “mind”, “thinking”, and “consciousness”, and how do molecules and matter give rise to such nonmaterial processes?
The hard problem of consciousness
The self and other minds
How would we know if an AI system was sentient?
Can AI systems be conscious?
Does Watson know that it beat the great Ken Jennings in Jeopardy!?
Self-driving cars
What set of values should AI be aligned with, and what legal and ethical status should it
AI as an existential threat
Why there is no such thing as “the” singularity. There are lots of them and we’ve already experienced them and will continue to do so.

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