Artificial Intelligence A Guide For Thinking Humans

It's important to note that this book was written / published in 2019/20, this pre-dates the more recent explosion in the last couple years with the use of transformer architecture models such as LLMs (ChatGPT, Claude, Gemini). So you won't find anything about those in this book. The book however is great for developing an understanding of the historical development of AI and the breakthroughs that came right up to the point before the more recent explosion. Much of the knowledge remains relevant and is built on in newer AI architectures. The book was accessible and explained concepts very well with plenty of figures (an audiobook likely will be challenging to follow in parts) and I took a lot away from this book.

Thank you Prof Melanie Mitchell for the labor of love and commitment required to create your latest book, Artificial Intelligence A guide for Thinking Humans." The book is divided into four parts, with the first part serving as an introduction with appropriate historical background, and an update on current important concepts, developments and supporting terminology. Following the introduction, one core aspect of the book are the three main parts-- each with multiple chapters-- where Melanie explains the fundamentals, workings and applications of of of neural networks and image processing (Part II, Looking and Seeing), of reinforcement learning and game playing (Part III, Learning to Play), and of language processing (Part IV: Artificial Intelligence Meet Natural Language). If you are a manager or policy maker who desires a technically accurate and precise description of the foundations and key enabling mechanisms of these AI capabilities-- in order to strengthen your own understanding--- and your own "mental models" of what this technology is and how it really works--- the descriptions in this book are amongst the very best descriptions I have every come across (and I do a lot of reading in this area for both technical specialist and for broader audiences). The second core aspect of this book is the final part (Part V: The Barrier of Meaning) where Melanie beautifully develops the frameworks, concepts, illustrations and examples you need to deeply understand what it really means for humans to understand "meaning" and context, and to make intelligent inferences, predictions, abstractions and analogies based on this ability versus what very brittle and very limited ability of state-of-the-art AI systems to do so. Just these four chapters in Part V ( On Understanding; Knowledge, Abstraction, and Analogy in Artificial Intelligence; and Questions, Answers, and Speculations) justifies the effort to purchase and carefully read this book. I think Prof Melanie Mitchell has done modern society a great service by creating this book. She makes it possible for a broad range of people-- from a broad range of backgrounds--- to seriously understand the marvels of AI capabilities and accomplishments, how these capabilities and accomplishments are actually realized through computational methods, the limits of these abilities, why these limits exist, and how these machine-based computational methods that we refer to as Artificial Intelligence compare to human capabilities for understanding and intelligence. For those of you who look for this type of material to read, it is also important to know about the recently published book, "Rebooting AI" by Gary Marcus and Ernest Davis. I have read both of these books cover-to-cover, carefully. My advice-- get both of these books and read both of them. They do have overlapping concerns, and do cover some of the same types of concepts. But they go about it in very different ways. Both books are technically accurate, and have a lot of great examples. Both books will give you much deeper insight into the capabilities and limitations of state-of-the-art AI (both now, and in the foreseeable future). But they go about it in different ways, and with different styles. So I will refrain from prioritizing one book over the other, as each has its own approach, emphasis, and style. If you enjoy this type of topic, and want to learn more from people who write well, AND who have very deep understanding of these topics--- then go get both of these books, absorb them, understand them, and go on a campaign to make sure all of your friends and professional colleagues understand the key messages of both of these books.

Dies ist ein sehr verständliches und ausgewogenes Buch über künstliche Intelligenz. Melanie Mitchell erklärt in einfachen Worten, was KI ist, wie sie sich historisch entwickelt hat und wo ihre tatsächlichen Grenzen liegen. Besonders gut hat mir gefallen, dass sie weder übertreibt noch Angst schürt, sondern einen ruhigen und realistischen Ton beibehält, der hilft, das Thema besser zu verstehen. Der einzige Nachteil ist, dass das Buch bereits 2019 erschienen ist und deshalb die neuesten Entwicklungen bis 2025, wie große Sprachmodelle oder die breite Nutzung von KI im Alltag, nicht abdeckt. Die grundlegenden Ideen bleiben jedoch vollkommen aktuell und geben das theoretische Fundament, um die heutigen Fortschritte nachvollziehen zu können. Insgesamt halte ich es für eine hervorragende Einführung für alle, die künstliche Intelligenz ohne Übertreibungen verstehen möchten, und ich kann es uneingeschränkt empfehlen.

Liked the way AI evolution is explained without going too much into technical details and at the same time providing easy conceptual insights. Book is very engaging and would definitely recommend to someone who wants to explore AI or just starting AI journey.

Consegui ler o livro de capa a capa, a linguagem é bastante acessível para quem tem o domínio da língua inglesa. Muito interessante, muito material para reflexão. Se há uma linha que divide os otimistas dos pessimistas, em relação à Inteligência Artificial, a autora deste livro transita com naturalidade dos dois lados da linha. E ela sabe o que diz.