A) Looks really good, will be checking it out in depth as I get time! Thanks for sharing.<p>B) The endorsements are interesting before you even get to the book; I know all textbooks are marketed, but this seems like quite the concerted effort. For example, take Judea Pearl's quote (an under-appreciated giant):<p><pre><code> This revised and extended edition of Artificial Intelligence: Foundations of Computational Agents should become the standard text of AI education.
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Talk about throwing down the gauntlet - especially since Russell looks up to him as a personal inspiration!<p>(Quick context for those rusty on academic AI: Russell & Norvig's 1995 (4th ed in 2020) <i>AI: A Modern Approach</i> ("AIAMA") is the de facto book for AI survey courses, supposedly used in 1500 universities via 9 languages as of 2023.[1])<p>I might be reading drama into the situation that isn't necessary, but it sure looks like they're trying to establish a connectionist/"scruffy", ML-based, Python-first replacement for AIAMA's symbolic/"neat", logic-based, Lisp-first approach. The 1st ed hit desks in 2010, and the endorsements are overwhelmingly from scruffy scientists & engineers. Obviously, this mirrors the industry's overall trend[2]... at this point, most laypeople think AI <i>is</i> ML. Nice to see a more nuanced--yet still scruffy-forward--approach gaining momentum; even Gary Marcus is on board, a noted Neat!<p>C) ...Ok, after writing an already-long comment (sorry) I did a quantitative comparison of the two books, which I figured y'all might find interesting! I'll link a screenshot[3] and the Google Sheet itself[4] below, but here's some highlights b/w "<i>AMA</i>" (the reigning champion) and "<i>FCA</i>" (the scrappy challenger):<p>1. My thesis was definitely correct; by my subjective estimation, <i>AMA</i> is ~6:3 neat:scruffy (57%:32%), vs. a ~3:5 ratio for <i>FCA</i> (34%:50%).<p>2. My second thesis is also seemingly correct: <i>FCA</i> dedicates the last few pages of every section to "Social Impact", aka ethics. Both books discuss the topic in more depth in the conclusion, representing ~4% of each.<p>3. <i>FCA</i> seems to have some significant pedagogical advantages, namely length (797 pages vs. <i>AMA</i>'s 1023 pages) and the inclusion of in-text exercises at the end of every section.<p>4. Both publish source code in multiple languages, but <i>AMA</i> had to be ported to Python from Lisp, whereas <i>FCA</i> is natively in Python (which, obviously, dominates AI atm). The <i>FCA</i> authors actually wrote their own "psuedo-code" Python library, which is both concerning and potentially helpful.<p>5. Finally, <i>FCA</i> includes sections explicitly focused on data structures, rather than just weaving them into discussions of algorithms & behavioral patterns. I for one think this is a really great idea, and where I see most short-term advances in unified (symbolic + stochastic) AI research coming from! Lots of gold to be mined in 75 years of thought.<p>Apologies, as always, for the long comment -- my only solace is that you can quickly minimize it. I should start a blog where I can muse to my heart's content...<p><i>TL;DR:</i> This new book is shorter, more ML-centric, and arguably uses more modern pedagogical techniques; in general, it seems to be a slightly more engineer-focused answer to Russell & Norvig's more academic-focused standard text.<p>[1] <i>AIAMA</i>: <a href="https://en.wikipedia.org/wiki/Artificial_Intelligence:_A_Modern_Approach" rel="nofollow">https://en.wikipedia.org/wiki/Artificial_Intelligence:_A_Mod...</a><p>[2] NGRAM: <a href="https://books.google.com/ngrams/graph?content=%28Machine+Learning%2FAI%29%2C%28Expert+Systems%2FAI%29&year_start=1950&year_end=2022&corpus=en&smoothing=3" rel="nofollow">https://books.google.com/ngrams/graph?content=%28Machine+Lea...</a><p>[3] Screenshot: <a href="https://imgur.com/a/x8QMbno" rel="nofollow">https://imgur.com/a/x8QMbno</a><p>[4] Google Sheet: <a href="https://docs.google.com/spreadsheets/d/1Gw9lxWhhTxjjTstyAKliwdy75VHXLtCDxCPFJhe5pPQ/edit?usp=sharing" rel="nofollow">https://docs.google.com/spreadsheets/d/1Gw9lxWhhTxjjTstyAKli...</a>