New edition (5/2023) of the book “Artificial Intelligence Science and Society Part A” (Amazon/Kindle) treating ChatGPT, Large Language Models (LLMs) and Artificial General Intelligence (AGI)

June 22nd, 2023 Daniela Lopez de Luise

a new edition (May 2023) of “Artificial Intelligence Science and Society Part A: Introduction to AI Science and Information Technology“ (paperback and e-book versions only) is now available in Amazon/Kindle.

Thought the first edition (October 2023) of this 4-volume book was quite prophetic on various AI topics (e.g., on the development of Deep Arts, or the very slow adoption of Metaverse), I felt the need to add two sections in its Part A on Large Language Models (LLMs)  and Artificial General Intelligence (AGI) to clarify issues that sprang out of ChatGPT success, primarily on AI technophobia and on the long-term AI prospects. 

AI Science and Engineering is un upcoming scientific discipline that can fuse AI, brain and mind studies and social engineering in a new scientific discipline. It has huge impact on both our society and environment.    The new book “Artificial Intelligence Science and Society” consists of four volumes (parts) debating all technical and social grand challenges of AI Science and Engineering in an understandable and scientifically accurate manner. They are published in Amazon/Kindle.

The first volume “Artificial Intelligence Science and Society Part A: Introduction to AI Science and Information Technology“ https://www.amazon.com/dp/9609156460?ref_=pe_3052080_397514860 overviews the entire domain of AI Science/Engineering and Information Technology (IT). It presents various hot AI and IT disciplines, e.g., Deep Learning, Symbolic AI, Signals and Systems, Computer Vision, Robotics and Autonomy, Networks and Social Media, Security and Blockchain (partial list). It requires no mathematical/scientific background. Yet it is scientifically precise and clarifies many misunderstandings and wrong concepts that can be routinely found in the related literature.

Here is just an indicative list of few of the debated topics and grand AI challenges:

  • Are Large Language Models (LLMs)  a precursor of Artificial General Intelligence?
  • Why LLMs hallucinate?
  • Does Generative AI pose a serious threat to humanity?
  • Is AI Science and Technology a scientific discipline in its own right?
  • What is the difference between data, information, and knowledge?
  • How can we quantify knowledge?
  • What is the relation of Machine learning, AI and metadata, semantics and concepts?
  • Can Virtual Reality truly empower meta-societies or is it just a hype?
  • Can AI-powered human-centred computing surpass human intelligence?
  • Why swarm intelligence is so powerful?
  • How networks analytics and epidemiology explain the propagation of ideas in social media?
  • How can we protect digital documents from tampering?

Part A Table of contents (276 pages): Data, Signals, Systems, Mathematics, Data Acquisition, Processing and Analysis, Data Storage and Search, Computer Vision, Data Visualization, Computer Graphics and Animation, Virtual and Augmented Reality, Audio, Speech, and Text Analysis, Machine Learning. Pattern Recognition, Deep Learning, Information, Metadata, Semantics, Concepts, Symbolic Artificial Intelligence, Knowledge, Anthropocentric Computing, Robotics, Autonomy, Networks and the Internet, The World Wide Web, Social Media, Network analytics, Swarm Intelligence, Software, Computing, Communications, Security, Blockchain.

Part A provides the scientific background to understand the other three book parts:  AI Science, brain, mind, and humans (Part B), AI and its impact on society, including AI Ethics (Part C) and the impact of AI and Information Science on the environment (Part D).

The four book volumes debate and try to forecast the future of AI Science and Engineering, as well as the upcoming Mind and Social Science and Engineering.

 

About the author: This book is a result of a two-year effort by Prof. Ioannis. Pitas (IEEE fellow, IEEE Distinguished Lecturer, EURASIP fellow) and was influenced by his being principal investigator of 75+ R&D projects on Computer Vision, Machine Learning, Digital Media and chairing the International AI Doctoral Academy (AIDA). Prof. I. Pitas is Director of the  Artificial Intelligence and Information Analysis (AIIA) lab at the Aristotle University of Thessaloniki (AUTH), Greece. He was chair and initiator of the IEEE Autonomous Systems Initiative (ASI). He has (co-)authored 15 books, 45 book chapters and over 950 papers in the above topics. He has 34500+ citations to his work and h-index 87+. He is ranked 319 worldwide and first in Greece in the field of Computer Science (2022).

 

Enjoy!

Prof. Ioannis. Pitas

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