feat: update prompt engineering docs and AI history demos
This commit is contained in:
sanbuphy
@@ -1,142 +1,78 @@
|
||||
<template>
|
||||
<div class="ai-evolution-demo">
|
||||
<!-- Timeline -->
|
||||
<div class="timeline-container">
|
||||
<div class="timeline-track"></div>
|
||||
<div class="header">
|
||||
<div class="title">AI 进化：规则 → 学习 → 生成</div>
|
||||
<div class="subtitle">
|
||||
点击切换阶段；不自动推进，避免“点一下就连续发生很多事”的误解。
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div class="tabs" role="tablist" aria-label="AI Evolution Stages">
|
||||
<button
|
||||
v-for="(stage, index) in stages"
|
||||
:key="index"
|
||||
class="timeline-node"
|
||||
:class="{
|
||||
active: currentStage === index,
|
||||
passed: currentStage > index
|
||||
}"
|
||||
:key="stage.key"
|
||||
class="tab"
|
||||
:class="{ active: currentStage === index }"
|
||||
role="tab"
|
||||
:aria-selected="currentStage === index"
|
||||
@click="currentStage = index"
|
||||
>
|
||||
<div class="node-dot">
|
||||
<div class="inner-dot"></div>
|
||||
</div>
|
||||
<div class="node-content">
|
||||
<span class="year-badge">{{ stage.year }}</span>
|
||||
<span class="node-label">{{ stage.label }}</span>
|
||||
</div>
|
||||
<div class="tab-year">{{ stage.year }}</div>
|
||||
<div class="tab-label">{{ stage.label }}</div>
|
||||
</button>
|
||||
</div>
|
||||
|
||||
<!-- Content -->
|
||||
<div class="content-wrapper">
|
||||
<transition name="fade-slide" mode="out-in">
|
||||
<div :key="currentStage" class="stage-content">
|
||||
<div class="header-section">
|
||||
<h3>
|
||||
<span class="stage-index"
|
||||
>{{ indexToRoman(currentStage + 1) }}.</span
|
||||
>
|
||||
{{ stages[currentStage].title }}
|
||||
</h3>
|
||||
<p>{{ stages[currentStage].desc }}</p>
|
||||
<div class="stage">
|
||||
<div class="stage-head">
|
||||
<div class="stage-title">{{ stages[currentStage].title }}</div>
|
||||
<div class="stage-desc">{{ stages[currentStage].desc }}</div>
|
||||
</div>
|
||||
|
||||
<div class="grid">
|
||||
<div class="card">
|
||||
<div class="card-title">核心思想</div>
|
||||
<ul class="list">
|
||||
<li v-for="(item, i) in stages[currentStage].core" :key="i">
|
||||
{{ item }}
|
||||
</li>
|
||||
</ul>
|
||||
</div>
|
||||
|
||||
<div class="card">
|
||||
<div class="card-title">代表应用</div>
|
||||
<div class="pill-row">
|
||||
<span
|
||||
v-for="(tag, i) in stages[currentStage].examples"
|
||||
:key="i"
|
||||
class="pill"
|
||||
>{{ tag }}</span
|
||||
>
|
||||
</div>
|
||||
<div class="note">{{ stages[currentStage].appDesc }}</div>
|
||||
</div>
|
||||
|
||||
<div class="visualization-grid">
|
||||
<!-- Concept/Logic View -->
|
||||
<div class="mac-window concept-window">
|
||||
<div class="window-bar">
|
||||
<div class="traffic-lights">
|
||||
<span class="light red"></span>
|
||||
<span class="light yellow"></span>
|
||||
<span class="light green"></span>
|
||||
</div>
|
||||
<div class="window-title">Core Logic</div>
|
||||
</div>
|
||||
<div class="concept-canvas">
|
||||
<!-- Stage 0: Symbolism -->
|
||||
<div v-if="currentStage === 0" class="vis-symbolism">
|
||||
<div class="logic-gate">
|
||||
<div class="input-group">
|
||||
<span class="input-val">A: True</span>
|
||||
<span class="input-val">B: False</span>
|
||||
</div>
|
||||
<div class="gate-box">AND Rule</div>
|
||||
<div class="output-val">Output: False</div>
|
||||
</div>
|
||||
<div class="math-note">If A and B then C</div>
|
||||
</div>
|
||||
|
||||
<!-- Stage 1: Expert Systems -->
|
||||
<div v-if="currentStage === 1" class="vis-expert">
|
||||
<div class="decision-tree">
|
||||
<div class="tree-node root">Is it raining?</div>
|
||||
<div class="branches">
|
||||
<div class="branch">
|
||||
<span class="condition">Yes</span>
|
||||
<div class="tree-node leaf">Take Umbrella</div>
|
||||
</div>
|
||||
<div class="branch">
|
||||
<span class="condition">No</span>
|
||||
<div class="tree-node leaf">Go Out</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
<div class="kb-note">Knowledge Base + Inference Engine</div>
|
||||
</div>
|
||||
|
||||
<!-- Stage 2: Deep Learning -->
|
||||
<div v-if="currentStage === 2" class="vis-dl">
|
||||
<div class="neural-net">
|
||||
<div class="layer input">
|
||||
<div class="neuron" v-for="n in 3" :key="`i-${n}`"></div>
|
||||
</div>
|
||||
<div class="layer hidden">
|
||||
<div class="neuron" v-for="n in 4" :key="`h-${n}`"></div>
|
||||
</div>
|
||||
<div class="layer output">
|
||||
<div class="neuron" v-for="n in 2" :key="`o-${n}`"></div>
|
||||
</div>
|
||||
<!-- Connections drawn via CSS/SVG ideally, simplified here -->
|
||||
<svg class="connections">
|
||||
<line x1="10" y1="20" x2="60" y2="10" />
|
||||
<line x1="10" y1="20" x2="60" y2="30" />
|
||||
<!-- Abstract lines -->
|
||||
</svg>
|
||||
</div>
|
||||
<div class="dl-note">Feature Extraction (Black Box)</div>
|
||||
</div>
|
||||
|
||||
<!-- Stage 3: GenAI -->
|
||||
<div v-if="currentStage === 3" class="vis-genai">
|
||||
<div class="transformer-block">
|
||||
<div class="block-layer attn">Self-Attention</div>
|
||||
<div class="block-layer ff">Feed Forward</div>
|
||||
<div class="block-layer norm">Norm & Add</div>
|
||||
</div>
|
||||
<div class="chat-sim">
|
||||
<div class="msg user">"Draw a cat"</div>
|
||||
<div class="msg ai">Generates 🐱...</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
<div class="card full">
|
||||
<div class="card-title">优势 / 局限</div>
|
||||
<div class="two-col">
|
||||
<div class="col">
|
||||
<div class="col-title">优势</div>
|
||||
<ul class="list">
|
||||
<li v-for="(item, i) in stages[currentStage].pros" :key="i">
|
||||
{{ item }}
|
||||
</li>
|
||||
</ul>
|
||||
</div>
|
||||
|
||||
<!-- Application/Impact View -->
|
||||
<div class="mac-window app-window">
|
||||
<div class="window-bar">
|
||||
<div class="window-title">Real-world Impact</div>
|
||||
</div>
|
||||
<div class="app-canvas">
|
||||
<div class="impact-card">
|
||||
<div class="impact-icon">{{ stages[currentStage].icon }}</div>
|
||||
<div class="impact-title">
|
||||
{{ stages[currentStage].appTitle }}
|
||||
</div>
|
||||
<div class="impact-desc">
|
||||
{{ stages[currentStage].appDesc }}
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
<div class="col">
|
||||
<div class="col-title">局限</div>
|
||||
<ul class="list">
|
||||
<li v-for="(item, i) in stages[currentStage].cons" :key="i">
|
||||
{{ item }}
|
||||
</li>
|
||||
</ul>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</transition>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</template>
|
||||
@@ -146,475 +82,226 @@ import { ref } from 'vue'
|
||||
|
||||
const currentStage = ref(0)
|
||||
|
||||
const indexToRoman = (num) => {
|
||||
const map = { 1: 'I', 2: 'II', 3: 'III', 4: 'IV' }
|
||||
return map[num] || num
|
||||
}
|
||||
|
||||
const stages = [
|
||||
{
|
||||
year: '1950s-1970s',
|
||||
label: 'Symbolism',
|
||||
title: 'The Dawn: Logic & Rules',
|
||||
desc: 'AI started as "Symbolic AI". Scientists believed intelligence could be described by formal logic and rules. If we can write down all the rules of the world, a computer can be intelligent.',
|
||||
icon: '♟️',
|
||||
appTitle: 'Chess & Logic',
|
||||
key: 'symbolic',
|
||||
year: '1950s–1980s',
|
||||
label: '符号主义',
|
||||
title: '规则与逻辑推理（专家系统）',
|
||||
desc: '相信“智能 = 规则 + 推理”。把专家经验写成 If/Then 规则与知识库。',
|
||||
core: [
|
||||
'知识用“符号/规则”表达：If 条件 Then 结论',
|
||||
'推理引擎按规则匹配、触发、推导',
|
||||
'可解释：能指出用了哪条规则'
|
||||
],
|
||||
pros: ['可解释性强', '在边界明确的垂直领域有效'],
|
||||
cons: [
|
||||
'规则写不完（组合爆炸）',
|
||||
'脆弱：世界稍变就失效',
|
||||
'难处理不确定性与常识'
|
||||
],
|
||||
examples: ['专家系统', 'MYCIN', '逻辑推理'],
|
||||
appDesc:
|
||||
'Programs could solve logic puzzles and play simple chess, but failed at "common sense" or recognizing a cat in a photo.'
|
||||
},
|
||||
{
|
||||
year: '1980s-1990s',
|
||||
label: 'Expert Systems',
|
||||
title: 'Knowledge Engineering',
|
||||
desc: 'The era of "Expert Systems". We tried to hard-code human expertise (e.g., medical diagnosis rules) into databases. Useful for specific domains, but brittle and hard to maintain.',
|
||||
icon: '🏥',
|
||||
appTitle: 'MYCIN / Deep Blue',
|
||||
appDesc:
|
||||
'Systems that could diagnose blood infections or beat Garry Kasparov at chess (Deep Blue, 1997), but still lacked true learning capability.'
|
||||
'适合“规则明确”的任务（如部分诊断流程、合规校验），但遇到现实世界的灰度与噪声会迅速失效。'
|
||||
},
|
||||
{
|
||||
key: 'dl',
|
||||
year: '2010s',
|
||||
label: 'Deep Learning',
|
||||
title: 'Connectionism & Big Data',
|
||||
desc: 'The breakthrough of Neural Networks. Inspired by the human brain, computers learned patterns from massive data instead of being told rules. AlexNet (2012) changed everything.',
|
||||
icon: '🧠',
|
||||
appTitle: 'AlphaGo & FaceID',
|
||||
label: '深度学习',
|
||||
title: '从数据中学习（连接主义）',
|
||||
desc: '相信“智能 = 表示学习 + 统计优化”。用神经网络从大量数据里自动学特征与决策边界。',
|
||||
core: [
|
||||
'用参数（权重）表示知识；通过优化让参数拟合数据',
|
||||
'特征提取从“手写规则”变成“自动学习”',
|
||||
'数据、算力、算法（GPU + 大数据 + 网络结构）共同推动'
|
||||
],
|
||||
pros: ['强大的模式识别能力', '同一范式覆盖多任务（视觉/语音/推荐等）'],
|
||||
cons: ['数据需求大', '可解释性较弱', '对分布外/对抗样本敏感'],
|
||||
examples: ['AlexNet', 'ImageNet', 'AlphaGo'],
|
||||
appDesc:
|
||||
'AI learned to see (ImageNet), hear (Siri), and play Go (AlphaGo). It surpassed humans in specific perceptual tasks.'
|
||||
'擅长“感知类”任务（图像、语音、推荐）；但对“为何这么判”解释不够直观，且对数据分布较敏感。'
|
||||
},
|
||||
{
|
||||
key: 'genai',
|
||||
year: '2020s+',
|
||||
label: 'Generative AI',
|
||||
title: 'Generative Intelligence (LLMs)',
|
||||
desc: 'The Transformer architecture allowed AI to understand context and generate new content. AI moved from "classifying" (is this a cat?) to "creating" (draw a cat).',
|
||||
icon: '✨',
|
||||
appTitle: 'ChatGPT & Midjourney',
|
||||
label: '生成式 AI',
|
||||
title: '从“分类”到“生成”（大模型）',
|
||||
desc: '用 Transformer 建模上下文关系，学习“下一 token”分布，从而能生成文本/代码/图像等新内容。',
|
||||
core: [
|
||||
'统一接口：给提示词（prompt）→ 生成输出',
|
||||
'能力来源：规模化预训练 + 指令微调/对齐',
|
||||
'把很多任务“变成一个生成问题”'
|
||||
],
|
||||
pros: ['通用性强（多任务）', '交互友好（自然语言接口）'],
|
||||
cons: [
|
||||
'可能幻觉',
|
||||
'安全与权限边界复杂',
|
||||
'需要系统化评测与约束（格式/工具/检索）'
|
||||
],
|
||||
examples: ['ChatGPT', 'GPT-4', 'Midjourney'],
|
||||
appDesc:
|
||||
'AI that can write code, poetry, paint images, and reason across multiple domains. A step towards AGI (General Intelligence).'
|
||||
'更像“通用助手”：能写、能改、能解释、能生成；但要通过提示词、上下文与工具链把它约束到可验收、可控。'
|
||||
}
|
||||
]
|
||||
</script>
|
||||
|
||||
<style scoped>
|
||||
.ai-evolution-demo {
|
||||
border-radius: 8px;
|
||||
background: var(--vp-c-bg-soft);
|
||||
border: 1px solid var(--vp-c-divider);
|
||||
overflow: hidden;
|
||||
margin: 1rem 0;
|
||||
}
|
||||
|
||||
/* Reusing Timeline Styles from FrontendEvolutionDemo for consistency */
|
||||
.timeline-container {
|
||||
padding: 2rem 1rem 1rem;
|
||||
background: var(--vp-c-bg-soft);
|
||||
display: flex;
|
||||
justify-content: space-between;
|
||||
position: relative;
|
||||
border-bottom: 1px solid var(--vp-c-divider);
|
||||
border-radius: 8px;
|
||||
padding: 1.5rem;
|
||||
margin: 1rem 0;
|
||||
color: var(--vp-c-text-1);
|
||||
}
|
||||
|
||||
.timeline-track {
|
||||
position: absolute;
|
||||
top: 2.5rem;
|
||||
left: 3rem;
|
||||
right: 3rem;
|
||||
height: 2px;
|
||||
background: var(--vp-c-divider);
|
||||
z-index: 0;
|
||||
.header {
|
||||
margin-bottom: 1rem;
|
||||
}
|
||||
|
||||
.timeline-node {
|
||||
position: relative;
|
||||
z-index: 1;
|
||||
background: transparent;
|
||||
border: none;
|
||||
display: flex;
|
||||
flex-direction: column;
|
||||
align-items: center;
|
||||
cursor: pointer;
|
||||
padding: 0;
|
||||
width: 25%;
|
||||
transition: all 0.3s ease;
|
||||
opacity: 0.6;
|
||||
.title {
|
||||
font-weight: 800;
|
||||
color: var(--vp-c-text-1);
|
||||
}
|
||||
|
||||
.timeline-node:hover {
|
||||
opacity: 0.9;
|
||||
}
|
||||
.timeline-node.active,
|
||||
.timeline-node.passed {
|
||||
opacity: 1;
|
||||
.subtitle {
|
||||
margin-top: 0.25rem;
|
||||
color: var(--vp-c-text-2);
|
||||
font-size: 0.9rem;
|
||||
}
|
||||
|
||||
.node-dot {
|
||||
width: 16px;
|
||||
height: 16px;
|
||||
border-radius: 50%;
|
||||
.tabs {
|
||||
display: grid;
|
||||
grid-template-columns: repeat(3, 1fr);
|
||||
gap: 0.5rem;
|
||||
margin: 0.75rem 0 1rem;
|
||||
}
|
||||
|
||||
.tab {
|
||||
text-align: left;
|
||||
border: 1px solid var(--vp-c-divider);
|
||||
background: var(--vp-c-bg);
|
||||
border: 2px solid var(--vp-c-text-3);
|
||||
margin-bottom: 0.8rem;
|
||||
display: flex;
|
||||
align-items: center;
|
||||
justify-content: center;
|
||||
transition: all 0.3s;
|
||||
color: var(--vp-c-text-1);
|
||||
border-radius: 8px;
|
||||
padding: 0.6rem 0.75rem;
|
||||
cursor: pointer;
|
||||
transition:
|
||||
border-color 0.2s ease,
|
||||
box-shadow 0.2s ease;
|
||||
}
|
||||
|
||||
.inner-dot {
|
||||
width: 0;
|
||||
height: 0;
|
||||
border-radius: 50%;
|
||||
background: var(--vp-c-brand);
|
||||
transition: all 0.3s;
|
||||
.tab:hover {
|
||||
border-color: rgba(var(--vp-c-brand-rgb), 0.55);
|
||||
}
|
||||
|
||||
.timeline-node.active .node-dot {
|
||||
.tab.active {
|
||||
border-color: var(--vp-c-brand);
|
||||
transform: scale(1.3);
|
||||
box-shadow: 0 0 0 4px var(--vp-c-bg-soft);
|
||||
}
|
||||
.timeline-node.active .inner-dot {
|
||||
width: 8px;
|
||||
height: 8px;
|
||||
}
|
||||
.timeline-node.passed .node-dot {
|
||||
border-color: var(--vp-c-brand);
|
||||
background: var(--vp-c-brand);
|
||||
box-shadow: 0 0 0 3px rgba(var(--vp-c-brand-rgb), 0.12);
|
||||
}
|
||||
|
||||
.node-content {
|
||||
text-align: center;
|
||||
display: flex;
|
||||
flex-direction: column;
|
||||
align-items: center;
|
||||
gap: 0.2rem;
|
||||
}
|
||||
|
||||
.year-badge {
|
||||
.tab-year {
|
||||
font-size: 0.75rem;
|
||||
color: var(--vp-c-text-2);
|
||||
font-family: var(--vp-font-family-mono);
|
||||
background: var(--vp-c-bg-alt);
|
||||
padding: 2px 6px;
|
||||
border-radius: 4px;
|
||||
color: var(--vp-c-text-2);
|
||||
}
|
||||
|
||||
.node-label {
|
||||
font-size: 0.85rem;
|
||||
font-weight: 600;
|
||||
.tab-label {
|
||||
margin-top: 0.15rem;
|
||||
font-weight: 800;
|
||||
}
|
||||
|
||||
.stage-head {
|
||||
margin-bottom: 0.75rem;
|
||||
}
|
||||
|
||||
.stage-title {
|
||||
font-weight: 900;
|
||||
color: var(--vp-c-text-1);
|
||||
}
|
||||
|
||||
/* Content Area */
|
||||
.content-wrapper {
|
||||
padding: 2rem;
|
||||
min-height: 400px;
|
||||
}
|
||||
|
||||
.header-section {
|
||||
text-align: center;
|
||||
margin-bottom: 2rem;
|
||||
max-width: 600px;
|
||||
margin: 0 auto 2rem;
|
||||
}
|
||||
|
||||
.header-section h3 {
|
||||
font-size: 1.5rem;
|
||||
margin-bottom: 0.5rem;
|
||||
color: var(--vp-c-text-1);
|
||||
}
|
||||
|
||||
.stage-index {
|
||||
color: var(--vp-c-text-3);
|
||||
-webkit-text-fill-color: var(--vp-c-text-3);
|
||||
margin-right: 0.5rem;
|
||||
font-weight: normal;
|
||||
}
|
||||
.header-section p {
|
||||
font-size: 1rem;
|
||||
.stage-desc {
|
||||
margin-top: 0.25rem;
|
||||
color: var(--vp-c-text-2);
|
||||
font-size: 0.95rem;
|
||||
line-height: 1.6;
|
||||
}
|
||||
|
||||
/* Visualization */
|
||||
.visualization-grid {
|
||||
.grid {
|
||||
display: grid;
|
||||
grid-template-columns: 1fr 1fr;
|
||||
gap: 2rem;
|
||||
align-items: stretch;
|
||||
gap: 0.75rem;
|
||||
}
|
||||
|
||||
@media (max-width: 768px) {
|
||||
.visualization-grid {
|
||||
@media (max-width: 720px) {
|
||||
.tabs {
|
||||
grid-template-columns: 1fr;
|
||||
}
|
||||
|
||||
.grid {
|
||||
grid-template-columns: 1fr;
|
||||
}
|
||||
}
|
||||
|
||||
.mac-window {
|
||||
border-radius: 12px;
|
||||
border: 1px solid var(--vp-c-divider);
|
||||
overflow: hidden;
|
||||
display: flex;
|
||||
flex-direction: column;
|
||||
background: var(--vp-c-bg);
|
||||
}
|
||||
|
||||
.concept-window {
|
||||
background: var(--vp-c-bg);
|
||||
}
|
||||
.app-window {
|
||||
background: var(--vp-c-bg);
|
||||
}
|
||||
|
||||
.window-bar {
|
||||
padding: 0.8rem 1rem;
|
||||
background: var(--vp-c-bg-soft);
|
||||
border-bottom: 1px solid var(--vp-c-divider);
|
||||
display: flex;
|
||||
align-items: center;
|
||||
position: relative;
|
||||
}
|
||||
|
||||
.traffic-lights {
|
||||
display: flex;
|
||||
gap: 6px;
|
||||
}
|
||||
.light {
|
||||
width: 10px;
|
||||
height: 10px;
|
||||
border-radius: 50%;
|
||||
}
|
||||
.light.red {
|
||||
background: var(--vp-c-red-1, #ef4444);
|
||||
}
|
||||
.light.yellow {
|
||||
background: var(--vp-c-yellow-1, #f59e0b);
|
||||
}
|
||||
.light.green {
|
||||
background: var(--vp-c-green-1, #22c55e);
|
||||
}
|
||||
|
||||
.window-title {
|
||||
position: absolute;
|
||||
left: 0;
|
||||
right: 0;
|
||||
text-align: center;
|
||||
font-size: 0.8rem;
|
||||
color: var(--vp-c-text-2);
|
||||
font-weight: 600;
|
||||
}
|
||||
|
||||
.concept-canvas,
|
||||
.app-canvas {
|
||||
padding: 2rem;
|
||||
flex: 1;
|
||||
display: flex;
|
||||
align-items: center;
|
||||
justify-content: center;
|
||||
min-height: 250px;
|
||||
}
|
||||
|
||||
/* Visualizations */
|
||||
/* Symbolism */
|
||||
.logic-gate {
|
||||
border: 2px solid var(--vp-c-divider);
|
||||
padding: 1rem;
|
||||
border-radius: 8px;
|
||||
text-align: center;
|
||||
background: var(--vp-c-bg);
|
||||
}
|
||||
.input-group {
|
||||
display: flex;
|
||||
gap: 1rem;
|
||||
justify-content: center;
|
||||
margin-bottom: 0.5rem;
|
||||
font-family: var(--vp-font-family-mono);
|
||||
}
|
||||
.gate-box {
|
||||
background: var(--vp-c-brand);
|
||||
color: var(--vp-c-bg);
|
||||
padding: 4px 10px;
|
||||
margin: 0.5rem 0;
|
||||
border-radius: 4px;
|
||||
}
|
||||
.math-note {
|
||||
margin-top: 1rem;
|
||||
font-family: var(--vp-font-family-mono);
|
||||
color: var(--vp-c-text-2);
|
||||
font-size: 0.8rem;
|
||||
}
|
||||
|
||||
/* Expert Systems */
|
||||
.decision-tree {
|
||||
display: flex;
|
||||
flex-direction: column;
|
||||
align-items: center;
|
||||
gap: 1rem;
|
||||
}
|
||||
.tree-node {
|
||||
border: 1px solid var(--vp-c-divider);
|
||||
padding: 6px 12px;
|
||||
border-radius: 20px;
|
||||
background: var(--vp-c-bg);
|
||||
font-size: 0.8rem;
|
||||
color: var(--vp-c-text-1);
|
||||
}
|
||||
.tree-node.root {
|
||||
border-color: var(--vp-c-brand);
|
||||
color: var(--vp-c-brand);
|
||||
font-weight: bold;
|
||||
}
|
||||
.branches {
|
||||
display: flex;
|
||||
gap: 2rem;
|
||||
}
|
||||
.branch {
|
||||
display: flex;
|
||||
flex-direction: column;
|
||||
align-items: center;
|
||||
gap: 0.5rem;
|
||||
}
|
||||
.condition {
|
||||
font-size: 0.7rem;
|
||||
color: var(--vp-c-text-2);
|
||||
background: var(--vp-c-bg-alt);
|
||||
padding: 2px 6px;
|
||||
border-radius: 4px;
|
||||
}
|
||||
.kb-note {
|
||||
margin-top: 1rem;
|
||||
font-size: 0.8rem;
|
||||
color: var(--vp-c-text-2);
|
||||
font-style: italic;
|
||||
}
|
||||
|
||||
/* Deep Learning */
|
||||
.neural-net {
|
||||
display: flex;
|
||||
gap: 2rem;
|
||||
align-items: center;
|
||||
position: relative;
|
||||
}
|
||||
.layer {
|
||||
display: flex;
|
||||
flex-direction: column;
|
||||
gap: 0.5rem;
|
||||
}
|
||||
.neuron {
|
||||
width: 12px;
|
||||
height: 12px;
|
||||
border-radius: 50%;
|
||||
background: var(--vp-c-bg-alt);
|
||||
border: 1px solid var(--vp-c-divider);
|
||||
}
|
||||
.layer.input .neuron {
|
||||
background: rgba(var(--vp-c-brand-rgb), 0.25);
|
||||
}
|
||||
.layer.hidden .neuron {
|
||||
background: rgba(var(--vp-c-brand-rgb), 0.18);
|
||||
}
|
||||
.layer.output .neuron {
|
||||
background: rgba(var(--vp-c-brand-rgb), 0.12);
|
||||
}
|
||||
.connections {
|
||||
position: absolute;
|
||||
top: 0;
|
||||
left: 0;
|
||||
width: 100%;
|
||||
height: 100%;
|
||||
pointer-events: none;
|
||||
opacity: 0.2;
|
||||
}
|
||||
.connections line {
|
||||
stroke: var(--vp-c-text-2);
|
||||
stroke-width: 1;
|
||||
}
|
||||
.dl-note {
|
||||
margin-top: 2rem;
|
||||
font-size: 0.8rem;
|
||||
color: var(--vp-c-text-2);
|
||||
}
|
||||
|
||||
/* GenAI */
|
||||
.vis-genai {
|
||||
display: flex;
|
||||
flex-direction: column;
|
||||
gap: 1rem;
|
||||
align-items: center;
|
||||
width: 100%;
|
||||
}
|
||||
.transformer-block {
|
||||
border: 2px solid var(--vp-c-brand);
|
||||
border-radius: 8px;
|
||||
padding: 0.5rem;
|
||||
width: 120px;
|
||||
text-align: center;
|
||||
background: rgba(var(--vp-c-brand-rgb), 0.08);
|
||||
}
|
||||
.block-layer {
|
||||
.card {
|
||||
border: 1px solid var(--vp-c-divider);
|
||||
background: var(--vp-c-bg);
|
||||
margin: 4px 0;
|
||||
padding: 4px;
|
||||
font-size: 0.7rem;
|
||||
border-radius: 4px;
|
||||
}
|
||||
.chat-sim {
|
||||
width: 100%;
|
||||
border: 1px solid var(--vp-c-divider);
|
||||
border-radius: 8px;
|
||||
padding: 1rem;
|
||||
background: var(--vp-c-bg);
|
||||
font-size: 0.8rem;
|
||||
}
|
||||
.msg {
|
||||
padding: 6px 10px;
|
||||
border-radius: 12px;
|
||||
margin-bottom: 0.5rem;
|
||||
max-width: 80%;
|
||||
|
||||
.card.full {
|
||||
grid-column: 1 / -1;
|
||||
}
|
||||
.msg.user {
|
||||
background: rgba(var(--vp-c-brand-rgb), 0.1);
|
||||
margin-left: auto;
|
||||
|
||||
.card-title {
|
||||
font-weight: 900;
|
||||
color: var(--vp-c-text-1);
|
||||
margin-bottom: 0.5rem;
|
||||
}
|
||||
.msg.ai {
|
||||
background: var(--vp-c-bg-soft);
|
||||
margin-right: auto;
|
||||
|
||||
.list {
|
||||
margin: 0;
|
||||
padding-left: 1.15rem;
|
||||
color: var(--vp-c-text-1);
|
||||
}
|
||||
|
||||
/* Impact Card */
|
||||
.impact-card {
|
||||
text-align: center;
|
||||
}
|
||||
.impact-icon {
|
||||
font-size: 4rem;
|
||||
margin-bottom: 1rem;
|
||||
}
|
||||
.impact-title {
|
||||
font-size: 1.2rem;
|
||||
font-weight: bold;
|
||||
.pill-row {
|
||||
display: flex;
|
||||
flex-wrap: wrap;
|
||||
gap: 0.5rem;
|
||||
margin-bottom: 0.5rem;
|
||||
color: var(--vp-c-text-1);
|
||||
}
|
||||
.impact-desc {
|
||||
font-size: 0.9rem;
|
||||
|
||||
.pill {
|
||||
border: 1px solid var(--vp-c-divider);
|
||||
background: var(--vp-c-bg-alt);
|
||||
color: var(--vp-c-text-2);
|
||||
line-height: 1.5;
|
||||
padding: 0.2rem 0.6rem;
|
||||
border-radius: 999px;
|
||||
font-size: 0.8rem;
|
||||
font-weight: 700;
|
||||
}
|
||||
|
||||
/* Transitions */
|
||||
.fade-slide-enter-active,
|
||||
.fade-slide-leave-active {
|
||||
transition: all 0.4s ease;
|
||||
.note {
|
||||
color: var(--vp-c-text-2);
|
||||
line-height: 1.6;
|
||||
}
|
||||
.fade-slide-enter-from {
|
||||
opacity: 0;
|
||||
transform: translateY(20px);
|
||||
|
||||
.two-col {
|
||||
display: grid;
|
||||
grid-template-columns: 1fr 1fr;
|
||||
gap: 0.75rem;
|
||||
}
|
||||
.fade-slide-leave-to {
|
||||
opacity: 0;
|
||||
transform: translateY(-20px);
|
||||
|
||||
@media (max-width: 720px) {
|
||||
.two-col {
|
||||
grid-template-columns: 1fr;
|
||||
}
|
||||
}
|
||||
|
||||
.col-title {
|
||||
font-weight: 900;
|
||||
color: var(--vp-c-text-1);
|
||||
margin-bottom: 0.35rem;
|
||||
}
|
||||
</style>
|
||||
|
||||
Reference in New Issue
Block a user