Refines visual styles and content layout

Improves the visual presentation and layout of the book by:

- Adjusting the slimcontent layout to match the standard floating layout on larger screens.
- Updating the color scheme for custom-numbered blocks to improve visual distinction and consistency, including updates to quiz questions, chapter connections, and code listings.
- Correcting minor typographical errors in the introduction.

book/assets/styles/style.scss

@@ -67,7 +67,12 @@ body .callout .callout-title-container {
   font-weight: bold !important;           /* Bold titles - override foldbox.css */
 }
 
-
+/* Override slimcontent layout to match regular floating layout */
+@media (min-width: 992px) {
+  body.floating.slimcontent .page-columns {
+    grid-template-columns: [screen-start] 1.5em [screen-start-inset] 5fr [page-start] minmax(25px, 50px) [page-start-inset] minmax(50px, 150px) [body-start-outset] minmax(25px, 50px) [body-start] 1.5em [body-content-start] minmax(500px, calc(800px - 3em)) [body-content-end] 1.5em [body-end] minmax(25px, 50px) [body-end-outset] minmax(50px, 150px) [page-end-inset] minmax(25px, 50px) [page-end] 5fr [screen-end-inset] 1.5em [screen-end] !important;
+  }
+}
 
 // Figure spacing improvements
 figure {

book/config/_quarto-html.yml

@@ -517,39 +517,39 @@ format:
 custom-numbered-blocks:
   groups:
     quiz-question:
-      colors: ["E6F4F7", "119EC7"]  # Updated to refined teal palette
+      colors: ["F0F0F8", "5B4B8A"]  # Darker purple for quiz questions
       collapse: true
     quiz-answer:
-      colors: ["E8F2EA", "4a7c59"]  # Updated to muted forest green
+      colors: ["E8F2EA", "4a7c59"]  # Forest green for quiz answers
       collapse: true
     resource-slides:
-      colors: ["E9F3E3", "55984D"]
+      colors: ["E0F2F1", "20B2AA"]  # Teal for resources
       collapse: true
       numbered: false
     resource-videos:
-      colors:  ["f9f5f0", "8b5e3c"]
+      colors: ["E0F2F1", "20B2AA"]  # Teal for resources
       collapse: true
       numbered: false
     resource-exercises:
-      colors: ["f7f0fa", "815AA4"]
+      colors: ["E0F2F1", "20B2AA"]  # Teal for resources
       collapse: true
       numbered: false
     chapter-connection:
-      colors: ["FDF2F7", "ED3237"]
+      colors: ["FDF2F7", "A51C30"]  # Harvard crimson for chapter connections
       boxstyle: foldbox.simple
       collapse: true
       numbered: false
     chapter-forward:
-      colors: ["FDF2F7", "ED3237"]
+      colors: ["FDF2F7", "A51C30"]  # Harvard crimson for chapter connections
       boxstyle: foldbox.simple
       collapse: true
       numbered: false
     chapter-recall:
-      colors: ["FFF4E6", "E67E22"]
+      colors: ["FFF4E6", "C06014"]  # Warm orange for chapter recall
       collapse: true
       numbered: false
     code-listing:
-      colors: ["E1F3F8", "119EC7"]
+      colors: ["F2F4F8", "D1D7E0"]  # Light blue-gray background, slate border for code listings
       collapse: false
       numbered: false
   classes:

book/contents/core/introduction/introduction.qmd

@@ -80,6 +80,7 @@ The relationship between AI and ML exemplifies the connection between theoretica
 
 The emergence of machine learning as a viable scientific discipline approach to artificial intelligence resulted from extensive research and fundamental paradigm shifts in the field. The progression of artificial intelligence encompasses both theoretical advances in understanding intelligence and practical developments in implementation methodologies. This development mirrors the evolution of other scientific and engineering disciplines—from mechanical engineering's advancement from basic force principles to contemporary robotics, to electrical engineering's progression from fundamental electromagnetic theory to modern power and communication networks. Analysis of this historical trajectory reveals both the technological innovations leading to current machine learning approaches and the emergence of deep reinforcement learning[^fn-rl] that inform contemporary AI system development.
 
+[^fn-rl]: **Deep Reinforcement Learning**: A machine learning approach that combines deep neural networks with reinforcement learning principles, allowing agents to learn optimal actions through trial and error interaction with an environment while receiving rewards or penalties.
 
 ## AI Evolution {#sec-introduction-ai-evolution-0dd8}
 
@@ -220,7 +221,7 @@ Alan Turing publishes \textbf{``Computing Machinery and Intelligence''} in the j
 \node[textt](1957)at(axis cs:1969,0.00022){\textcolor{red}{1957}\\
 \textbf{Cornell psychologist Frank Rosenblatt invents the perceptron}, a system that paves the way for
 modern neural networks
-(see “The Turbulent Past and Uncertain Future of Artificial Intelligence," p. 26).};
+(see "The Turbulent Past and Uncertain Future of Artificial Intelligence," p. 26).};
 \draw[Line] (axis cs:1957,0) -- ++(0mm,17mm)-|(1957.248);
 %
 \node[textt,text width=21mm](1966)at(axis cs:1972,0.00012){\textcolor{red}{1966}\\
@@ -234,19 +235,19 @@ Hans Moravec builds the \textbf{Stanford Cart}, one of the first autonomous vehi
 %
 \node[textt,text width=21mm](1981)at(axis cs:1990,0.00006){\textcolor{red}{1981}\\
 Japanese \textbf{Fifth-Generation Computer Systems} project begins. The infusion of
-research funding helps end first “AI winter."};
+research funding helps end first "AI winter."};
 \draw[Line] (axis cs:1981,0) -- ++(0mm,10mm)-|(1981);
 %
 \node[textt,text width=15mm](1997)at(axis cs:2001,0.00007){\textcolor{red}{1997}\\
-\textbf{IBM’s Deep Blue} beats world chess champion Garry Kasparov};
+\textbf{IBM's Deep Blue} beats world chess champion Garry Kasparov};
 \draw[Line] (axis cs:1997,0) -- ++(0mm,10mm)-|(1997);
 %
 \node[textt,text width=15mm](2011)at(axis cs:2014,0.00003){\textcolor{red}{2011}\\
-\textbf{IBM’s Watson} wins at Jeopardy!};
+\textbf{IBM's Watson} wins at Jeopardy!};
 \draw[Line] (axis cs:2011,0) -- (2011);
 %
 \node[textt,text width=19mm](2005)at(axis cs:2012,0.00009){\textcolor{red}{2005}\\
-\textbf{DARPA Grand Challenge} Stanford wins the agency’s second driverless-car
+\textbf{DARPA Grand Challenge} Stanford wins the agency's second driverless-car
 competition by driving 211 kilometers on an unhearsed trail};
 \draw[Line] (axis cs:2005,0) -- (2005);
 %
@@ -257,7 +258,7 @@ later causes an outcry when it begins spouting bigoted remarks};
 %
 \draw[Line,solid,-] (axis cs:1991,0.0002) --++(50:35mm)
 node[bluegraph,above,align=center,text width=30mm]{Percent of U.S.-published books
-in Google’s database that mention artificial intelligence};
+in Google's database that mention artificial intelligence};
 \end{axis}
 \end{tikzpicture}
 ```