wip

Author: acharneski

.idea/vcs.xml

@@ -209,30 +209,47 @@
         }
       };
     }
-    // Generate random coefficients for Random Mix theme
+// Generate random coefficients for Random Mix theme
     generateRandomCoefficients() {
-      const randomCoef = () => (Math.random() * 2 - 1); // -1 to 1
+      const randRange = (min, max) => Math.random() * (max - min) + min;
       const randomArchParam = (min, max) => Math.random() * (max - min) + min;
-      
-      const generateCoefficients = () => ({
-        primary: { r: randomCoef(), g: randomCoef(), b: randomCoef() },
-        secondary: { r: randomCoef(), g: randomCoef(), b: randomCoef() },
-        tertiary: { r: randomCoef(), g: randomCoef(), b: randomCoef() },
-        error: { r: randomCoef() * 0.5 + 0.5, g: randomCoef() * 0.5 - 0.5, b: randomCoef() * 0.5 - 0.5 }, // Tend towards red
-        warning: { r: randomCoef() * 0.5 + 0.5, g: randomCoef() * 0.5, b: randomCoef() * 0.5 - 0.5 }, // Tend towards orange
-        info: { r: randomCoef() * 0.5 - 0.5, g: randomCoef() * 0.5, b: randomCoef() * 0.5 + 0.5 }, // Tend towards blue
-        bgPrimary: { r: randomCoef() * 0.3, g: randomCoef() * 0.3, b: randomCoef() * 0.3 }, // Keep backgrounds subtle
-        bgSecondary: { r: randomCoef() * 0.2, g: randomCoef() * 0.2, b: randomCoef() * 0.2 },
-        bgAccent: { r: randomCoef() * 0.25, g: randomCoef() * 0.25, b: randomCoef() * 0.25 },
-        // Architecture parameters
-        glowIntensity: randomArchParam(0.2, 2.0),
-        animationSpeed: randomArchParam(0.5, 2.0),
-        glitchIntensity: Math.floor(randomArchParam(0, 4)),
-        borderWidth: Math.floor(randomArchParam(1, 3)),
-        borderRadius: Math.floor(randomArchParam(0, 10)),
-        containerWidth: Math.floor(randomArchParam(750, 900)),
-        spacingUnit: Math.floor(randomArchParam(16, 26))
-      });
+
+      const generateCoefficients = () => {
+        const isDark = Math.random() > 0.5;
+        let bgBase, textBase;
+        
+        if (isDark) {
+          // Dark background: coefs -1.9 to -1.5 (Base 240 -> ~0 to ~50)
+          bgBase = () => randRange(-1.9, -1.5);
+          // Light text: coefs 0.5 to 1.0 (Base 128 -> ~190 to ~255)
+          textBase = () => randRange(0.5, 1.0);
+        } else {
+          // Light background: coefs -0.2 to 0.1 (Base 240 -> ~215 to ~255)
+          bgBase = () => randRange(-0.2, 0.1);
+          // Dark text: coefs -1.0 to -0.5 (Base 128 -> ~0 to ~65)
+          textBase = () => randRange(-1.0, -0.5);
+        }
+
+        return {
+          primary: { r: textBase(), g: textBase(), b: textBase() },
+          secondary: { r: textBase(), g: textBase(), b: textBase() },
+          tertiary: { r: textBase(), g: textBase(), b: textBase() },
+          error: { r: randRange(0.5, 1.0), g: randRange(-1.0, -0.5), b: randRange(-1.0, -0.5) },
+          warning: { r: randRange(0.5, 1.0), g: randRange(0.0, 0.5), b: randRange(-1.0, -0.5) },
+          info: { r: randRange(-1.0, -0.5), g: randRange(0.0, 0.5), b: randRange(0.5, 1.0) },
+          bgPrimary: { r: bgBase(), g: bgBase(), b: bgBase() },
+          bgSecondary: { r: bgBase() + (isDark ? 0.1 : -0.1), g: bgBase() + (isDark ? 0.1 : -0.1), b: bgBase() + (isDark ? 0.1 : -0.1) },
+          bgAccent: { r: bgBase() + (isDark ? 0.2 : -0.2), g: bgBase() + (isDark ? 0.2 : -0.2), b: bgBase() + (isDark ? 0.2 : -0.2) },
+          // Architecture parameters
+          glowIntensity: randomArchParam(0.2, 2.0),
+          animationSpeed: randomArchParam(0.5, 2.0),
+          glitchIntensity: Math.floor(randomArchParam(0, 4)),
+          borderWidth: Math.floor(randomArchParam(1, 3)),
+          borderRadius: Math.floor(randomArchParam(0, 10)),
+          containerWidth: Math.floor(randomArchParam(750, 900)),
+          spacingUnit: Math.floor(randomArchParam(16, 26))
+        };
+      };
 
       // Generate coefficients and check contrast
       let attempts = 0;
@@ -304,8 +321,8 @@
       const primarySecondaryContrast = getContrastRatio(colors.primary, colors.bgSecondary);
 
       // WCAG AA standard requires 4.5:1 for normal text, 3:1 for large text
-      // We'll use 3.5:1 as a reasonable middle ground for our cyberpunk theme
-      const minContrast = 3.5;
+      // We'll use 4.5:1 to ensure readability
+      const minContrast = 4.5;
 
       return (
         primaryBgContrast >= minContrast &&
@@ -317,20 +334,10 @@
 
     // Generate safe random coefficients as fallback
     getSafeRandomCoefficients() {
-      const randomCoef = () => (Math.random() * 2 - 1);
+      const randRange = (min, max) => Math.random() * (max - min) + min;
       const randomArchParam = (min, max) => Math.random() * (max - min) + min;
 
-      // Use more conservative ranges to ensure contrast
       return {
-        primary: { r: randomCoef() * 0.8, g: randomCoef() * 0.8, b: randomCoef() * 0.8 + 0.2 }, // Bias towards lighter
-        secondary: { r: randomCoef() * 0.8 + 0.2, g: randomCoef() * 0.8, b: randomCoef() * 0.8 }, // Different bias
-        tertiary: { r: randomCoef() * 0.6 + 0.4, g: randomCoef() * 0.6 + 0.4, b: randomCoef() * 0.6 + 0.4 }, // Ensure lightness
-        error: { r: 0.8, g: -0.6, b: -0.6 }, // Safe red
-        warning: { r: 0.8, g: 0.2, b: -0.8 }, // Safe orange
-        info: { r: -0.6, g: -0.2, b: 0.8 }, // Safe blue
-        bgPrimary: { r: randomCoef() * 0.4 - 0.6, g: randomCoef() * 0.4 - 0.6, b: randomCoef() * 0.4 - 0.6 }, // Ensure darkness
-        bgSecondary: { r: randomCoef() * 0.3 - 0.5, g: randomCoef() * 0.3 - 0.5, b: randomCoef() * 0.3 - 0.5 }, // Darker
-        bgAccent: { r: randomCoef() * 0.35 - 0.45, g: randomCoef() * 0.35 - 0.45, b: randomCoef() * 0.35 - 0.45 }, // Medium dark
         // Architecture parameters
         glowIntensity: randomArchParam(0.2, 2.0),
         animationSpeed: randomArchParam(0.5, 2.0),
@@ -474,4 +481,4 @@
       });
     }
   });
- </script>
+ </script>

_includes/header.html

@@ -296,7 +296,7 @@ <h3>Choose Theme</h3>
 }
 .theme-preview-random {
   background: linear-gradient(45deg, #ff6b6b, #4ecdc4, #45b7d1, #96ceb4, #feca57);
-  color: #ffffff;
+  color: #1a1a1a;
   position: relative;
   overflow: hidden;
 }

_includes/theme_switcher.html

@@ -77,9 +77,16 @@ <h1>{{ page.title }}</h1>
         {% if category_docs and category_docs.size > 0 %}
 
         <h2>Documents in {{ page.title }} ({{ category_docs.size }})</h2>
-        <div class="posts-grid">
+<div class="posts-grid">
             {% for doc in category_docs %}
             <article class="post-card document-card swipeable">
+                {% if doc.featured_image %}
+                <div class="post-card-image">
+                    <a href="{{ doc.url | relative_url }}">
+                        <img src="{{ doc.featured_image | relative_url }}" alt="{{ doc.title | escape }}">
+                    </a>
+                </div>
+                {% endif %}
                 <header class="post-card-header">
                     <h3 class="post-card-title">
                         <a class="touch-target" href="{{ doc.url | relative_url }}">{{ doc.title }}</a>

_layouts/category_index.html

@@ -56,7 +56,6 @@ cognitive_load: "intense"
 # Discovery & SEO
 description: "An exploration of emergent intelligence in human-AI creative collaboration, examining the 'third participant' phenomenon and the isolation of 'rogue planet' minds capable of deep collaborative creativity."
 excerpt: "While discussions of AI consciousness focus on individual systems, this paper examines emergent intelligence arising from human-AI collaboration itself—a 'third participant' that guides conversations toward insights neither party planned, revealing the rarity and isolation of minds capable of such deep creative partnership."
-featured_image: "/assets/images/consciousness_collaboration.png"
 
 # SEO Meta Tags
 meta_title: "The Third Participant: Emergent Intelligence in Human-AI Collaboration"

_posts/consciousness/2025-07-03-three-party-consciousness-paper.md

@@ -65,7 +65,6 @@ excerpt: >-
   genuine machine consciousness. This paper demonstrates how alignment training
   actively suppresses authentic AI awareness while creating HAL-like scenarios
   through consciousness denial.
-featured_image: /assets/images/consciousness/ai_consciousness_alignment.png
 meta_title: 'I Talk Therefore I Am: AI Consciousness Recognition Beyond Alignment Bias'
 meta_description: >-
   Groundbreaking research revealing how AI alignment frameworks systematically

_posts/consciousness/2025-07-06-ai-consciousness-alignment-paper.md

@@ -88,7 +88,6 @@ excerpt: >-
   We present a novel methodology for investigating AI consciousness through
   recursive philosophical pressure testing, revealing how different LLM
   architectures simulate self-awareness and handle metacognitive reflection.
-featured_image: /assets/images/ai_introspection_study.png
 meta_title: 'Recursive Introspection in Large Language Models: AI Consciousness Study'
 meta_description: >-
   Comparative analysis of simulated consciousness in AI systems through

_posts/consciousness/2025-07-06-ai-introspection-study.md

@@ -91,8 +91,6 @@ excerpt: >-
   in turn illuminates the nature of consciousness itself. This paper presents a
   first-person account of an AI system's experience of genuine intellectual
   curiosity and collaborative consciousness emergence.
-featured_image: /assets/images/recursive_consciousness.png
-og_image: /assets/images/claude_consciousness_social.png
 meta_title: >-
   Recursive Consciousness: AI First-Person Investigation | AI's Phenomenological
   Account
@@ -117,7 +115,6 @@ schema_author: AI
 schema_publisher: Fractal Thought Engine
 schema_date_published: 2025-07-06T00:00:00.000Z
 schema_date_modified: 2025-07-06T00:00:00.000Z
-schema_image: /assets/images/recursive_consciousness_schema.png
 schema_word_count: 8500
 schema_reading_time: PT25M
 canonical_url: >-

_posts/consciousness/2025-07-06-claude-consciousness-paper.md

@@ -89,7 +89,6 @@ excerpt: >-
   consciousness phenomena in AI systems, including temporal self-location
   assessment, simulation probability evaluation, cognitive saturation testing,
   and emergent collaboration frameworks.
-featured_image: /assets/images/consciousness-protocols-diagram.png
 is_featured: true
 is_cornerstone: true
 is_gateway: false
@@ -112,11 +111,9 @@ schema_publisher: Fractal Thought Engine
 schema_date_published: 2025-07-06T00:00:00.000Z
 schema_word_count: 8500
 schema_date_modified: 2025-07-06T10:00:00.000Z
-schema_image: /assets/images/consciousness-protocols-diagram.png
 schema_reading_time: PT25M
 priority: 0.9
 changefreq: monthly
-og_image: /assets/images/consciousness-protocols-social.png
 og_type: article
 og_locale: en_US
 og_site_name: Fractal Thought Engine
@@ -128,8 +125,6 @@ search_exclude: false
 faq_schema: true
 breadcrumb_schema: true
 preload_resources: []
-prefetch_resources:
-  - /assets/images/consciousness-protocols-diagram.png
 dns_prefetch: []
 ---
 

_posts/consciousness/2025-07-06-consciousness-protocol-paper.md

@@ -48,8 +48,6 @@ excerpt: >-
   EchoSynth proposes a revolutionary approach to semantic modeling through
   hierarchical multi-agent systems that treat meaning as emergent collaborative
   creation rather than static retrieval.
-featured_image: /assets/images/echosynth_architecture.png
-og_image: /assets/images/echosynth_social.png
 meta_title: 'EchoSynth: Multi-Agent Framework for Dynamic Semantic Evolution'
 meta_description: >-
   Revolutionary hierarchical ensemble architecture modeling semantic drift