Large Language Models (Paperback)

Trevor Cohen

ISBN 13: 9798993314013

Editore: Semanticvectors Publishing, 2025

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Paperback. Large Language Models (LLMs) are transforming science, technology, and business - faster than any innovation we've known. They generate text, write code, summarize knowledge, and even help scientists make new discoveries. But what are they really doing? Have we built something that can think? And what will happen as their energy needs and influence continue to grow? This book offers a clear, accessible explanation of how LLMs work and how they came to be. It traces the surprising lineage of language modeling - from statistical experiments in the 1940s and search engines of the 1960s, to the neural networks and GPUs that made today's AI revolution possible. Written for a broad audience of scientists, technologists, business leaders, and curious readers, it connects the dots between ideas, algorithms, and engineering breakthroughs - showing how a few simple components can scale to systems that understand and generate language at human-like levels. The authors, Dominic Widdows and Trevor Cohen, have worked in natural language processing since the early 2000s. Collaborators since 2009 on the SemanticVectors project - an open-source tool for building early word embeddings - they have published extensively in AI, biomedical informatics, and quantum computing, with experience at Google, Microsoft, and leading universities including Stanford, Oxford, Columbia, and the University of Washington. This book will give you the conceptual foundation to see beyond the hype and into the heart of how large language models work, and what this may mean for humanity.***The historical overview allows a birds eye perspective on the long journey to modern LLMs, while the gentle introduction to their building blocks and architecture demystifies their magical-looking qualities. The book is authoritative, accessible, and insightful. - Emmanuel Pothos, Professor of Psychology, City, University of LondonIf you are curious about what's under the hood of the Large Language Models behind the current AI Bots, you must read the Widdows and Cohen book on the topic. It clears away the mystery by providing the history of the techniques involved and the details of their workings in clear and accessible language. It's a great read! - Roger Schvaneveldt, Professor Emeritus of Cognitive Psychology, New Mexico State University and Arizona State University.This book strikes a perfect balance between depth and breadth in presenting an engaging account of large language models including their inner workings, history, as well as their applications and implications. Neural language modeling approaches are masterfully placed in a broader context drawing on parallels from history, science and arts. It is as enjoyable to read as it is educational and thought provoking. - Serguei Pakhomov, Professor of Health Informatics, University of Minnesota This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Codice articolo 9798993314013

Dati bibliografici

• Titolo: Large Language Models (Paperback)
• Editore: Semanticvectors Publishing
• Data di pubblicazione: 2025
• Lingua: Inglese
• ISBN 13: 9798993314013
• Rilegatura: Paperback
• Condizione: new

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Riassunto

Large Language Models (LLMs) are transforming science, technology, and business — faster than any innovation we’ve known. They generate text, write code, summarize knowledge, and even help scientists make new discoveries. But what are they really doing? Have we built something that can think? And what will happen as their energy needs and influence continue to grow?

This book offers a clear, accessible explanation of how LLMs work and how they came to be. It traces the surprising lineage of language modeling — from statistical experiments in the 1940s and search engines of the 1960s, to the neural networks and GPUs that made today’s AI revolution possible.

Written for a broad audience of scientists, technologists, business leaders, and curious readers, it connects the dots between ideas, algorithms, and engineering breakthroughs — showing how a few simple components can scale to systems that understand and generate language at human-like levels.

The authors, Dominic Widdows and Trevor Cohen, have worked in natural language processing since the early 2000s. Collaborators since 2009 on the SemanticVectors project — an open-source tool for building early word embeddings — they have published extensively in AI, biomedical informatics, and quantum computing, with experience at Google, Microsoft, and leading universities including Stanford, Oxford, Columbia, and the University of Washington.

This book will give you the conceptual foundation to see beyond the hype and into the heart of how large language models work, and what this may mean for humanity.

***

The historical overview allows a birds eye perspective on the long journey to modern LLMs, while the gentle introduction to their building blocks and architecture demystifies their magical-looking qualities. The book is authoritative, accessible, and insightful.

- Emmanuel Pothos, Professor of Psychology, City, University of London

If you are curious about what’s under the hood of the Large Language Models behind the current AI Bots, you must read the Widdows and Cohen book on the topic. It clears away the mystery by providing the history of the techniques involved and the details of their workings in clear and accessible language. It’s a great read!

- Roger Schvaneveldt, Professor Emeritus of Cognitive Psychology, New Mexico State University and Arizona State University.

This book strikes a perfect balance between depth and breadth in presenting an engaging account of large language models including their inner workings, history, as well as their applications and implications. Neural language modeling approaches are masterfully placed in a broader context drawing on parallels from history, science and arts. It is as enjoyable to read as it is educational and thought provoking.

- Serguei Pakhomov, Professor of Health Informatics, University of Minnesota