|
FreeComputerBooks.com
Links to Free Computer, Mathematics, Technical eBooks all over the World
|
|
- Title: Understanding Science with Large Language Models?
- Author(s) Arno Simons, Adrian Wüthrich, Michael Zichert, Gerd Graßhoff
- Publisher: transcript publishing (2026); eBook (Creative Commons Licensed)
- License(s): Creative Commons License (CC)
- Paperback: 522 pages
- eBook: PDF
- Language: English
- ISBN-10: 3837679942
- ISBN-13: 978-3837679946
- Share This:
|
How are Large Language Models (LLMs) changing research in the history, philosophy, and sociology of science (HPSS)? Computer science develops powerful tools like LLMs, and HPSS explores the depth of their uses, limits, and broader consequences.
About the Authors- N/A
Similar Books:
-
Large Language Models in Cybersecurity: Threats and Mitigation
This open access book provides cybersecurity practitioners with the knowledge needed to understand the risks of the increased availability of powerful Large Language Models (LLM) and how they can be mitigated.
-
Quick Start Guide to Large Language Models: Early Release
The Practical, Step-by-Step Guide to Using Large Language Models (LLMs) at Scale in Projects and Products. Clears away those obstacles and provides a guide to working with, integrating, and deploying LLMs to solve practical problems.
-
Foundations of Large Language Models (Tong Xiao, et al.)
This is a book about Large Language Models (LLM). It primarily focuses on foundational concepts rather than comprehensive coverage of all cutting-edge technologies: pre-training, generative models, prompting techniques, and alignment methods.
-
Understanding Large Language Models (Jenny Kunz)
This practical book offers clear, example-rich explanations of how Large Language Models (LLM) work, how you can interact with them, and how to integrate LLMs into your own applications.
-
How to Scale Your Model: A Systems View of LLMs on TPUs
This book takes a very practical, systems-oriented approach to explain the performance side of LLMs like how Tensor Processing Units (TPUs) (and GPUs) work under the hood, how these devices communicate, and how LLMs actually run on real hardware.
-
Generative AI for Beginners (Akshay Kulkarni, et al.)
This book provides a deep dive into the world of generative AI, covering everything from the basics of neural networks to the intricacies of large language models like ChatGPT and Google Bard.
-
Generative AI Applications: Planning, Design and Implementation
This book is your indispensable guide through Generative AI. Launch your Generative AI application from idea to implementation. Understand the various options and trade-offs in using LLMs for applications.
-
RAG Optimization: Accurate and Efficient LLM Applications
Optimize your Retrieval-augmented generation (RAG) application for speed and accuracy by examining the whole system and each individual component. Learn about the latest techniques in advanced RAG architectures.
-
Generative AI in C++: Coding Transformers and LLMs
Do you know C++ but not AI? Do you dream of writing your own AI engine in C++? From beginner to advanced, this book covers the internals of AI engines in C++, with real source code examples and research paper citations.






