663 lines
34 KiB
HTML
663 lines
34 KiB
HTML
|
||
<!DOCTYPE html>
|
||
<html lang="zh-CN">
|
||
<head>
|
||
<meta charset="utf-8" />
|
||
<meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
|
||
<title>神经网络突破与应用 - 行业洞察报告</title>
|
||
|
||
<!-- Google Fonts -->
|
||
<link href="https://fonts.googleapis.com/css?family=Inter:300,400,500,600,700,800" rel="stylesheet" />
|
||
|
||
<!-- Font Awesome Icons -->
|
||
<script src="https://kit.fontawesome.com/1d2b6c4f81.js" crossorigin="anonymous"></script>
|
||
|
||
<!-- Tailwind CSS -->
|
||
<link href="https://cdn.jsdelivr.net/npm/tailwindcss@2.2.19/dist/tailwind.min.css" rel="stylesheet">
|
||
|
||
<!-- DaisyUI -->
|
||
<link href="https://cdn.jsdelivr.net/npm/daisyui@5" rel="stylesheet" type="text/css" />
|
||
<link href="https://cdn.jsdelivr.net/npm/daisyui@5/themes.css" rel="stylesheet" type="text/css" />
|
||
|
||
<!-- Custom Styles -->
|
||
<style>
|
||
:root {
|
||
--primary-gradient: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
|
||
--secondary-gradient: linear-gradient(135deg, #f093fb 0%, #f5576c 100%);
|
||
--dark-gradient: linear-gradient(135deg, #434343 0%, #000000 100%);
|
||
}
|
||
|
||
body {
|
||
font-family: 'Inter', sans-serif;
|
||
background-color: #0f172a;
|
||
color: #e2e8f0;
|
||
overflow-x: hidden;
|
||
}
|
||
|
||
.gradient-text {
|
||
background: var(--primary-gradient);
|
||
-webkit-background-clip: text;
|
||
-webkit-text-fill-color: transparent;
|
||
background-clip: text;
|
||
}
|
||
|
||
.card-gradient {
|
||
background: rgba(30, 41, 59, 0.7);
|
||
backdrop-filter: blur(10px);
|
||
border: 1px solid rgba(255, 255, 255, 0.1);
|
||
}
|
||
|
||
.timeline-item::before {
|
||
content: '';
|
||
position: absolute;
|
||
left: -9px;
|
||
top: 0;
|
||
width: 18px;
|
||
height: 18px;
|
||
border-radius: 50%;
|
||
background: var(--primary-gradient);
|
||
z-index: 1;
|
||
}
|
||
|
||
.timeline-line {
|
||
position: absolute;
|
||
left: 0;
|
||
top: 0;
|
||
bottom: 0;
|
||
width: 2px;
|
||
background: rgba(102, 126, 234, 0.3);
|
||
}
|
||
|
||
.neural-bg {
|
||
position: fixed;
|
||
top: 0;
|
||
left: 0;
|
||
width: 100%;
|
||
height: 100%;
|
||
z-index: -1;
|
||
opacity: 0.4;
|
||
}
|
||
|
||
.table-container {
|
||
overflow-x: auto;
|
||
}
|
||
|
||
.highlight-box {
|
||
background: rgba(102, 126, 234, 0.15);
|
||
border-left: 4px solid #667eea;
|
||
}
|
||
|
||
@media (max-width: 768px) {
|
||
.card {
|
||
margin-bottom: 1rem;
|
||
}
|
||
}
|
||
</style>
|
||
</head>
|
||
<body class="min-h-screen">
|
||
<!-- Neural Network Background -->
|
||
<div id="neural-bg" class="neural-bg"></div>
|
||
|
||
<!-- Main Content -->
|
||
<div class="container mx-auto px-4 py-8 max-w-6xl">
|
||
<!-- Header -->
|
||
<div class="text-center mb-12">
|
||
<h1 class="text-4xl md:text-5xl font-bold mb-4 gradient-text">神经网络突破与应用</h1>
|
||
<p class="text-lg text-gray-300">从实验室突破到商业化临界点的深度分析</p>
|
||
</div>
|
||
|
||
<!-- Concept Events Timeline -->
|
||
<div class="card card-gradient rounded-xl p-6 mb-8">
|
||
<h2 class="text-2xl font-bold mb-6 text-white">概念事件时间轴</h2>
|
||
<div class="relative pl-8">
|
||
<div class="timeline-line"></div>
|
||
|
||
<div class="timeline-item relative pb-8">
|
||
<div class="ml-6">
|
||
<h3 class="text-lg font-semibold text-purple-300">2024年10月</h3>
|
||
<p class="text-gray-300">某公司通过神经网络+数据要素技术实现订单规模从千万级到数亿级跨越</p>
|
||
</div>
|
||
</div>
|
||
|
||
<div class="timeline-item relative pb-8">
|
||
<div class="ml-6">
|
||
<h3 class="text-lg font-semibold text-purple-300">2024年12月</h3>
|
||
<p class="text-gray-300">新型光芯片可执行深度神经网络关键计算，MIT团队发布全集成光芯片（<0.5纳秒完成分类任务）</p>
|
||
</div>
|
||
</div>
|
||
|
||
<div class="timeline-item relative pb-8">
|
||
<div class="ml-6">
|
||
<h3 class="text-lg font-semibold text-purple-300">2025年2月</h3>
|
||
<p class="text-gray-300">Figure机器人宣布30天内用<strong>单神经网络端到端</strong>完成复杂任务，引爆机器人赛道</p>
|
||
</div>
|
||
</div>
|
||
|
||
<div class="timeline-item relative pb-8">
|
||
<div class="ml-6">
|
||
<h3 class="text-lg font-semibold text-purple-300">2025年3月</h3>
|
||
<p class="text-gray-300">上海国投与智元战略合作，推动具身智能（人形机器人）规模化应用</p>
|
||
</div>
|
||
</div>
|
||
|
||
<div class="timeline-item relative">
|
||
<div class="ml-6">
|
||
<h3 class="text-lg font-semibold text-purple-300">2025年4月</h3>
|
||
<p class="text-gray-300">宾夕法尼亚大学实现<strong>光训练神经网络</strong>可编程芯片（《自然·光子学》），能耗降低90%</p>
|
||
</div>
|
||
</div>
|
||
</div>
|
||
|
||
<div class="mt-6 p-4 highlight-box rounded-lg">
|
||
<p class="text-white"><strong>核心催化：</strong>技术突破（光芯片、端到端神经网络）与产业落地（机器人、AI终端）形成共振</p>
|
||
</div>
|
||
</div>
|
||
|
||
<!-- Core View Summary -->
|
||
<div class="card card-gradient rounded-xl p-6 mb-8">
|
||
<h2 class="text-2xl font-bold mb-4 text-white">核心观点摘要</h2>
|
||
<div class="bg-gradient-to-r from-purple-900/30 to-indigo-900/30 p-6 rounded-lg border border-purple-500/30">
|
||
<p class="text-lg text-gray-200 leading-relaxed">
|
||
神网络技术正从<strong>实验室突破</strong>转向<strong>商业化临界点</strong>，核心驱动力是<strong>光计算+端侧AI</strong>的能效革命。未来6个月，机器人与智能终端将是验证技术成熟度的主战场，<strong>2025年或成"神经网络硬件元年"</strong>。
|
||
</p>
|
||
</div>
|
||
</div>
|
||
|
||
<!-- Core Logic and Market Analysis -->
|
||
<div class="card card-gradient rounded-xl p-6 mb-8">
|
||
<h2 class="text-2xl font-bold mb-6 text-white">概念核心逻辑与市场认知分析</h2>
|
||
|
||
<div class="grid md:grid-cols-3 gap-6 mb-6">
|
||
<div class="bg-blue-900/20 p-5 rounded-lg border border-blue-500/30">
|
||
<h3 class="text-xl font-semibold mb-3 text-blue-300">核心驱动力</h3>
|
||
<ul class="space-y-2 text-gray-300">
|
||
<li><i class="fas fa-microchip text-blue-400 mr-2"></i><strong>技术突破：</strong>光芯片将计算延迟降至纳秒级，能效比GPU提升100倍</li>
|
||
<li><i class="fas fa-chart-line text-blue-400 mr-2"></i><strong>需求爆发：</strong>Figure机器人需10万台/4年交付</li>
|
||
<li><i class="fas fa-landmark text-blue-400 mr-2"></i><strong>政策加持：</strong>国务院"人工智能+"行动明确支持具身智能</li>
|
||
</ul>
|
||
</div>
|
||
|
||
<div class="bg-purple-900/20 p-5 rounded-lg border border-purple-500/30">
|
||
<h3 class="text-xl font-semibold mb-3 text-purple-300">市场热度与情绪</h3>
|
||
<ul class="space-y-2 text-gray-300">
|
||
<li><i class="fas fa-fire text-purple-400 mr-2"></i><strong>新闻热度：</strong>2025年2月关键词搜索量环比+300%</li>
|
||
<li><i class="fas fa-file-alt text-purple-400 mr-2"></i><strong>研报密集度：</strong>2024Q4以来相关研报15篇</li>
|
||
<li><i class="fas fa-balance-scale text-purple-400 mr-2"></i><strong>情绪分歧：</strong>技术派乐观，产业派谨慎</li>
|
||
</ul>
|
||
</div>
|
||
|
||
<div class="bg-pink-900/20 p-5 rounded-lg border border-pink-500/30">
|
||
<h3 class="text-xl font-semibold mb-3 text-pink-300">预期差</h3>
|
||
<ul class="space-y-2 text-gray-300">
|
||
<li><i class="fas fa-exclamation-triangle text-pink-400 mr-2"></i><strong>被忽略的关键：</strong>光芯片的商业化瓶颈</li>
|
||
<li><i class="fas fa-brain text-pink-400 mr-2"></i><strong>认知偏差：</strong>低估NPU在AI手机/PC的渗透率（2027年预计43%）</li>
|
||
</ul>
|
||
</div>
|
||
</div>
|
||
</div>
|
||
|
||
<!-- Catalysts and Future Path -->
|
||
<div class="card card-gradient rounded-xl p-6 mb-8">
|
||
<h2 class="text-2xl font-bold mb-6 text-white">关键催化剂与未来发展路径</h2>
|
||
|
||
<div class="grid md:grid-cols-2 gap-6">
|
||
<div>
|
||
<h3 class="text-xl font-semibold mb-4 text-green-300">近期催化剂（3-6个月）</h3>
|
||
<div class="space-y-3">
|
||
<div class="flex items-start">
|
||
<div class="bg-green-500 rounded-full w-6 h-6 flex items-center justify-center mt-1 mr-3 flex-shrink-0">
|
||
<span class="text-xs font-bold">1</span>
|
||
</div>
|
||
<p class="text-gray-300"><strong>Figure机器人量产验证：</strong>2025年Q2交付第二批客户，验证单神经网络端到端能力</p>
|
||
</div>
|
||
<div class="flex items-start">
|
||
<div class="bg-green-500 rounded-full w-6 h-6 flex items-center justify-center mt-1 mr-3 flex-shrink-0">
|
||
<span class="text-xs font-bold">2</span>
|
||
</div>
|
||
<p class="text-gray-300"><strong>光芯片代工进展：</strong>国内厂商是否宣布光芯片流片成功</p>
|
||
</div>
|
||
<div class="flex items-start">
|
||
<div class="bg-green-500 rounded-full w-6 h-6 flex items-center justify-center mt-1 mr-3 flex-shrink-0">
|
||
<span class="text-xs font-bold">3</span>
|
||
</div>
|
||
<p class="text-gray-300"><strong>华为/高通NPU新品：</strong>2025年6月或发布AI终端芯片，催化NPU需求</p>
|
||
</div>
|
||
</div>
|
||
</div>
|
||
|
||
<div>
|
||
<h3 class="text-xl font-semibold mb-4 text-yellow-300">长期路径（2025-2027）</h3>
|
||
<div class="space-y-3">
|
||
<div class="flex items-start">
|
||
<div class="bg-yellow-500 rounded-full w-6 h-6 flex items-center justify-center mt-1 mr-3 flex-shrink-0">
|
||
<span class="text-xs font-bold">1</span>
|
||
</div>
|
||
<p class="text-gray-300"><strong>阶段1（2025）：</strong>光芯片实验室→小规模试产</p>
|
||
</div>
|
||
<div class="flex items-start">
|
||
<div class="bg-yellow-500 rounded-full w-6 h-6 flex items-center justify-center mt-1 mr-3 flex-shrink-0">
|
||
<span class="text-xs font-bold">2</span>
|
||
</div>
|
||
<p class="text-gray-300"><strong>阶段2（2026）：</strong>NPU渗透率突破30%，光芯片进入数据中心</p>
|
||
</div>
|
||
<div class="flex items-start">
|
||
<div class="bg-yellow-500 rounded-full w-6 h-6 flex items-center justify-center mt-1 mr-3 flex-shrink-0">
|
||
<span class="text-xs font-bold">3</span>
|
||
</div>
|
||
<p class="text-gray-300"><strong>阶段3（2027）：</strong>具身智能规模化，光芯片成为主流算力</p>
|
||
</div>
|
||
</div>
|
||
</div>
|
||
</div>
|
||
</div>
|
||
|
||
<!-- Industry Chain and Core Companies -->
|
||
<div class="card card-gradient rounded-xl p-6 mb-8">
|
||
<h2 class="text-2xl font-bold mb-6 text-white">产业链与核心公司深度剖析</h2>
|
||
|
||
<div class="mb-6">
|
||
<h3 class="text-xl font-semibold mb-3 text-cyan-300">产业链图谱</h3>
|
||
<div class="flex flex-wrap gap-2">
|
||
<span class="bg-cyan-900/30 text-cyan-200 px-3 py-1 rounded-full text-sm">上游：光芯片、NPU IP、量子随机数</span>
|
||
<span class="bg-cyan-900/30 text-cyan-200 px-3 py-1 rounded-full text-sm">中游：机器人本体、AI终端</span>
|
||
<span class="bg-cyan-900/30 text-cyan-200 px-3 py-1 rounded-full text-sm">下游：自动驾驶、服务机器人、AI手机</span>
|
||
</div>
|
||
</div>
|
||
|
||
<div>
|
||
<h3 class="text-xl font-semibold mb-3 text-cyan-300">核心玩家对比</h3>
|
||
<div class="overflow-x-auto">
|
||
<table class="min-w-full bg-gray-800/50 rounded-lg overflow-hidden">
|
||
<thead class="bg-gray-700/50">
|
||
<tr>
|
||
<th class="px-4 py-3 text-left text-sm font-medium text-gray-300">公司</th>
|
||
<th class="px-4 py-3 text-left text-sm font-medium text-gray-300">技术路线</th>
|
||
<th class="px-4 py-3 text-left text-sm font-medium text-gray-300">进展验证</th>
|
||
<th class="px-4 py-3 text-left text-sm font-medium text-gray-300">风险点</th>
|
||
</tr>
|
||
</thead>
|
||
<tbody class="divide-y divide-gray-700">
|
||
<tr>
|
||
<td class="px-4 py-3 text-sm font-medium text-white">华为</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">昇腾NPU+达芬奇架构</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">已量产Atlas 900集群</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">美国制裁限制先进制程</td>
|
||
</tr>
|
||
<tr>
|
||
<td class="px-4 py-3 text-sm font-medium text-white">高通</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">骁龙X Elite（45TOPs）</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">支持130亿参数端侧大模型</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">依赖台积电3nm产能</td>
|
||
</tr>
|
||
<tr>
|
||
<td class="px-4 py-3 text-sm font-medium text-white">泰尔股份</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">CNN/RNN故障诊断模型</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">已应用于风电齿轮箱（千万级订单）</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">技术通用性待验证</td>
|
||
</tr>
|
||
<tr>
|
||
<td class="px-4 py-3 text-sm font-medium text-white">德福科技</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">高频铜箔+神经网络优化</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">HVOP4铜箔36GHz性能超三井2.5%</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">良率爬坡不及预期</td>
|
||
</tr>
|
||
</tbody>
|
||
</table>
|
||
</div>
|
||
</div>
|
||
</div>
|
||
|
||
<!-- Risks and Challenges -->
|
||
<div class="card card-gradient rounded-xl p-6 mb-8">
|
||
<h2 class="text-2xl font-bold mb-6 text-white">潜在风险与挑战</h2>
|
||
|
||
<div class="grid md:grid-cols-3 gap-6">
|
||
<div class="bg-red-900/20 p-5 rounded-lg border border-red-500/30">
|
||
<h3 class="text-xl font-semibold mb-3 text-red-300">技术风险</h3>
|
||
<ul class="space-y-2 text-gray-300">
|
||
<li><i class="fas fa-microchip text-red-400 mr-2"></i>光芯片量产瓶颈：需硅光+CMOS混合工艺</li>
|
||
<li><i class="fas fa-robot text-red-400 mr-2"></i>神经网络泛化能力：复杂场景下成功率未公开</li>
|
||
</ul>
|
||
</div>
|
||
|
||
<div class="bg-orange-900/20 p-5 rounded-lg border border-orange-500/30">
|
||
<h3 class="text-xl font-semibold mb-3 text-orange-300">商业化风险</h3>
|
||
<ul class="space-y-2 text-gray-300">
|
||
<li><i class="fas fa-dollar-sign text-orange-400 mr-2"></i>成本倒挂：光芯片成本需从$1000降至$10</li>
|
||
<li><i class="fas fa-mobile-alt text-orange-400 mr-2"></i>场景局限：NPU应用受限于APP生态</li>
|
||
</ul>
|
||
</div>
|
||
|
||
<div class="bg-yellow-900/20 p-5 rounded-lg border border-yellow-500/30">
|
||
<h3 class="text-xl font-semibold mb-3 text-yellow-300">政策与竞争</h3>
|
||
<ul class="space-y-2 text-gray-300">
|
||
<li><i class="fas fa-gavel text-yellow-400 mr-2"></i>美国技术管制：光芯片核心设备可能被禁运</li>
|
||
<li><i class="fas fa-users text-yellow-400 mr-2"></i>行业内卷：国内20+厂商涌入NPU赛道</li>
|
||
</ul>
|
||
</div>
|
||
</div>
|
||
</div>
|
||
|
||
<!-- Conclusion and Investment Insights -->
|
||
<div class="card card-gradient rounded-xl p-6 mb-8">
|
||
<h2 class="text-2xl font-bold mb-6 text-white">综合结论与投资启示</h2>
|
||
|
||
<div class="mb-6">
|
||
<h3 class="text-xl font-semibold mb-3 text-green-300">阶段判断</h3>
|
||
<p class="text-gray-300 bg-green-900/20 p-4 rounded-lg">神经网络概念处于<strong>"技术验证→商业化拐点"</strong>过渡期，<strong>光芯片和NPU</strong>是两大主线，机器人是短期情绪催化。</p>
|
||
</div>
|
||
|
||
<div class="mb-6">
|
||
<h3 class="text-xl font-semibold mb-3 text-blue-300">投资方向</h3>
|
||
<div class="space-y-3">
|
||
<div class="flex items-start">
|
||
<div class="bg-blue-500 rounded-full w-8 h-8 flex items-center justify-center mt-1 mr-3 flex-shrink-0">
|
||
<i class="fas fa-star text-white text-sm"></i>
|
||
</div>
|
||
<div>
|
||
<p class="font-semibold text-blue-300">最确定</p>
|
||
<p class="text-gray-300"><strong>NPU产业链</strong>（华为昇腾、高通供应链）——渗透率提升逻辑清晰</p>
|
||
</div>
|
||
</div>
|
||
<div class="flex items-start">
|
||
<div class="bg-purple-500 rounded-full w-8 h-8 flex items-center justify-center mt-1 mr-3 flex-shrink-0">
|
||
<i class="fas fa-rocket text-white text-sm"></i>
|
||
</div>
|
||
<div>
|
||
<p class="font-semibold text-purple-300">弹性最大</p>
|
||
<p class="text-gray-300"><strong>光芯片设备</strong>（若中芯国际宣布流片）——技术突破带来估值跃升</p>
|
||
</div>
|
||
</div>
|
||
<div class="flex items-start">
|
||
<div class="bg-pink-500 rounded-full w-8 h-8 flex items-center justify-center mt-1 mr-3 flex-shrink-0">
|
||
<i class="fas fa-lightbulb text-white text-sm"></i>
|
||
</div>
|
||
<div>
|
||
<p class="font-semibold text-pink-300">预期差</p>
|
||
<p class="text-gray-300"><strong>高频铜箔</strong>（德福科技）——机器人放量+国产替代双击</p>
|
||
</div>
|
||
</div>
|
||
</div>
|
||
</div>
|
||
|
||
<div>
|
||
<h3 class="text-xl font-semibold mb-3 text-yellow-300">跟踪指标</h3>
|
||
<div class="flex flex-wrap gap-3">
|
||
<span class="bg-yellow-900/30 text-yellow-200 px-3 py-1 rounded-full text-sm">光芯片：中芯国际12寸硅光产线进度</span>
|
||
<span class="bg-yellow-900/30 text-yellow-200 px-3 py-1 rounded-full text-sm">NPU：高通骁龙8 Gen4的NPU算力</span>
|
||
<span class="bg-yellow-900/30 text-yellow-200 px-3 py-1 rounded-full text-sm">机器人：Figure Q2交付量</span>
|
||
</div>
|
||
</div>
|
||
</div>
|
||
|
||
<!-- Related Stocks -->
|
||
<div class="card card-gradient rounded-xl p-6">
|
||
<h2 class="text-2xl font-bold mb-6 text-white">关联股票</h2>
|
||
|
||
<div class="mb-6">
|
||
<h3 class="text-xl font-semibold mb-4 text-indigo-300">机器人-神经网络(241210)</h3>
|
||
<div class="table-container">
|
||
<table class="min-w-full bg-gray-800/50 rounded-lg overflow-hidden">
|
||
<thead class="bg-gray-700/50">
|
||
<tr>
|
||
<th class="px-4 py-3 text-left text-sm font-medium text-gray-300">股票名称</th>
|
||
<th class="px-4 py-3 text-left text-sm font-medium text-gray-300">项目/产品</th>
|
||
<th class="px-4 py-3 text-left text-sm font-medium text-gray-300">技术/应用</th>
|
||
<th class="px-4 py-3 text-left text-sm font-medium text-gray-300">关联原因</th>
|
||
</tr>
|
||
</thead>
|
||
<tbody class="divide-y divide-gray-700">
|
||
<tr>
|
||
<td class="px-4 py-3 text-sm font-medium text-white">泰尔股份</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">滚动轴承和齿轮箱的故障预警模型和故障诊断模型</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">卷积神经网络和循环神经网络</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">公司利用卷积神经网络和循环神经网络构建故障预警模型和故障诊断模型</td>
|
||
</tr>
|
||
<tr>
|
||
<td class="px-4 py-3 text-sm font-medium text-white">深水海纳</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">精确控制系统模型</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">BP（反向传播）神经网络</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">公司建立以生物化学为基础、以BP神经网络为手段的精确控制系统模型</td>
|
||
</tr>
|
||
<tr>
|
||
<td class="px-4 py-3 text-sm font-medium text-white">宏达新材</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">量子随机数发生器</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">神经网络计算</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">公司产品量子随机数发生器用于神经网络计算</td>
|
||
</tr>
|
||
<tr>
|
||
<td class="px-4 py-3 text-sm font-medium text-white">金自天正</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">少量订单项目</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">人工神经网络算法</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">少量订单项目涉及人工神经网络算法</td>
|
||
</tr>
|
||
<tr>
|
||
<td class="px-4 py-3 text-sm font-medium text-white">思泰克</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">客户意图识别技术</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">长短时记忆神经网络</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">客户意图识别技术采用长短时记忆神经网络</td>
|
||
</tr>
|
||
<tr>
|
||
<td class="px-4 py-3 text-sm font-medium text-white">智信精密</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">工业缺陷检测平台</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">神经网络模型</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">工业缺陷检测平台集成了神经网络模型</td>
|
||
</tr>
|
||
<tr>
|
||
<td class="px-4 py-3 text-sm font-medium text-white">恒锋信息</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">视频内容解析系统</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">神经网络</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">基于神经网络构建视频内容解析系统</td>
|
||
</tr>
|
||
<tr>
|
||
<td class="px-4 py-3 text-sm font-medium text-white">声迅股份</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">安防应用</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">可变性卷积神经网络</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">公司聚焦可变性卷积神经网络的应用</td>
|
||
</tr>
|
||
<tr>
|
||
<td class="px-4 py-3 text-sm font-medium text-white">恒华科技</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">电力设计应用</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">神经网络创新应用</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">实现了神经网络在电力设计的创新应用</td>
|
||
</tr>
|
||
<tr>
|
||
<td class="px-4 py-3 text-sm font-medium text-white">汇纳科技</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">客流分析系统</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">人工神经网络模型</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">客流分析系统基于人工神经网络模型</td>
|
||
</tr>
|
||
<tr>
|
||
<td class="px-4 py-3 text-sm font-medium text-white">神思电子</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">神思云脑</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">大规模神经网络与行业知识库</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">神思云脑构建大规模神经网络与行业知识库</td>
|
||
</tr>
|
||
<tr>
|
||
<td class="px-4 py-3 text-sm font-medium text-white">恒银科技</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">金融科技领域</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">神经网络技术积累</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">神经网络技术有一定积累</td>
|
||
</tr>
|
||
<tr>
|
||
<td class="px-4 py-3 text-sm font-medium text-white">固高科技</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">机器人应用软件体系</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">自主研发</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">基于自主研发构建面向机器人应用的软件体系</td>
|
||
</tr>
|
||
<tr>
|
||
<td class="px-4 py-3 text-sm font-medium text-white">兴民智通</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">基于LSTM神经网络的专利</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">LSTM神经网络</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">拥有基于LSTM神经网络的专利</td>
|
||
</tr>
|
||
<tr>
|
||
<td class="px-4 py-3 text-sm font-medium text-white">奥比中光</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">3D视觉感知技术研发</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">人形机器人应用</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">专注3D视觉感知技术，积累神经网络芯片及算法，未来可应用于人形机器人等终端</td>
|
||
</tr>
|
||
<tr>
|
||
<td class="px-4 py-3 text-sm font-medium text-white">申昊科技</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">多层分类型模型</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">限制性玻尔兹曼机与SVM连接</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">将多个限制性玻尔兹曼机与SVM连接构建多层分类型，应用于图像识别任务</td>
|
||
</tr>
|
||
</tbody>
|
||
</table>
|
||
</div>
|
||
</div>
|
||
|
||
<div>
|
||
<h3 class="text-xl font-semibold mb-4 text-indigo-300">神经网络(241009)</h3>
|
||
<div class="table-container">
|
||
<table class="min-w-full bg-gray-800/50 rounded-lg overflow-hidden">
|
||
<thead class="bg-gray-700/50">
|
||
<tr>
|
||
<th class="px-4 py-3 text-left text-sm font-medium text-gray-300">股票名称</th>
|
||
<th class="px-4 py-3 text-left text-sm font-medium text-gray-300">项目/技术</th>
|
||
<th class="px-4 py-3 text-left text-sm font-medium text-gray-300">关联原因</th>
|
||
</tr>
|
||
</thead>
|
||
<tbody class="divide-y divide-gray-700">
|
||
<tr>
|
||
<td class="px-4 py-3 text-sm font-medium text-white">思泰克</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">客户意图识别技术采用长短时记忆神经网络</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">在客户意图识别技术中应用了神经网络技术</td>
|
||
</tr>
|
||
<tr>
|
||
<td class="px-4 py-3 text-sm font-medium text-white">智信精密</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">工业缺陷检测平台集成了神经网络模型</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">工业检测领域应用神经网络技术</td>
|
||
</tr>
|
||
<tr>
|
||
<td class="px-4 py-3 text-sm font-medium text-white">恒锋信息</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">基于神经网络构建视频内容解析系统</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">视频内容解析系统采用神经网络技术</td>
|
||
</tr>
|
||
<tr>
|
||
<td class="px-4 py-3 text-sm font-medium text-white">深水海纳</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">自主研发包含神经网络的精确控制系统模型</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">在控制系统中集成神经网络技术</td>
|
||
</tr>
|
||
<tr>
|
||
<td class="px-4 py-3 text-sm font-medium text-white">声迅股份</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">公司聚焦可变性卷积神经网络的应用</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">专注于可变性卷积神经网络技术应用</td>
|
||
</tr>
|
||
<tr>
|
||
<td class="px-4 py-3 text-sm font-medium text-white">申昊科技</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">运用BP神经网络模型</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">采用BP神经网络模型进行技术研发</td>
|
||
</tr>
|
||
<tr>
|
||
<td class="px-4 py-3 text-sm font-medium text-white">泰尔股份</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">利用神经网络构建诊断模型</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">在设备诊断领域应用神经网络技术</td>
|
||
</tr>
|
||
<tr>
|
||
<td class="px-4 py-3 text-sm font-medium text-white">恒华科技</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">实现了在神经网络在电力设计的创新应用</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">将神经网络技术应用于电力设计领域</td>
|
||
</tr>
|
||
<tr>
|
||
<td class="px-4 py-3 text-sm font-medium text-white">金自天正</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">少量订单项目涉及人工神经网络算法</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">部分订单使用人工神经网络算法</td>
|
||
</tr>
|
||
<tr>
|
||
<td class="px-4 py-3 text-sm font-medium text-white">汇纳科技</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">客流分析系统基于人工神经网络模型</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">客流分析系统采用神经网络模型</td>
|
||
</tr>
|
||
<tr>
|
||
<td class="px-4 py-3 text-sm font-medium text-white">神思电子</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">神思云脑构建大规模神经网络与行业知识库</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">云脑平台集成大规模神经网络技术</td>
|
||
</tr>
|
||
<tr>
|
||
<td class="px-4 py-3 text-sm font-medium text-white">恒银科技</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">神经网络技术有一定积累</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">在神经网络技术领域有技术储备</td>
|
||
</tr>
|
||
<tr>
|
||
<td class="px-4 py-3 text-sm font-medium text-white">宏达新材</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">量子随机数发生器可用于神经网络计算</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">量子技术与神经网络计算结合</td>
|
||
</tr>
|
||
<tr>
|
||
<td class="px-4 py-3 text-sm font-medium text-white">固高科技</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">工业机器人大系统采用神经网络技术</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">工业机器人领域应用神经网络技术</td>
|
||
</tr>
|
||
<tr>
|
||
<td class="px-4 py-3 text-sm font-medium text-white">兴民智通</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">拥有基于LSTM神经网络的专利</td>
|
||
<td class="px-4 py-3 text-sm text-gray-300">持有LSTM神经网络相关专利技术</td>
|
||
</tr>
|
||
</tbody>
|
||
</table>
|
||
</div>
|
||
</div>
|
||
</div>
|
||
|
||
<!-- Risk Warning -->
|
||
<div class="mt-8 text-center text-sm text-gray-400">
|
||
<p>风险提示：若光芯片量产延迟或机器人订单不及预期，概念可能回调至主题炒作阶段。</p>
|
||
</div>
|
||
</div>
|
||
|
||
<!-- Scripts -->
|
||
<script src="https://cdn.jsdelivr.net/npm/tsparticles@3/tsparticles.bundle.min.js"></script>
|
||
<script>
|
||
// Initialize neural network background
|
||
document.addEventListener('DOMContentLoaded', function() {
|
||
if (typeof tsParticles !== 'undefined') {
|
||
tsParticles.load("neural-bg", {
|
||
fpsLimit: 60,
|
||
particles: {
|
||
color: {
|
||
value: "#667eea"
|
||
},
|
||
links: {
|
||
color: "#667eea",
|
||
distance: 150,
|
||
enable: true,
|
||
opacity: 0.5,
|
||
width: 1
|
||
},
|
||
move: {
|
||
direction: "none",
|
||
enable: true,
|
||
outModes: {
|
||
default: "bounce"
|
||
},
|
||
random: false,
|
||
speed: 1,
|
||
straight: false
|
||
},
|
||
number: {
|
||
density: {
|
||
enable: true,
|
||
area: 800
|
||
},
|
||
value: 80
|
||
},
|
||
opacity: {
|
||
value: 0.5
|
||
},
|
||
shape: {
|
||
type: "circle"
|
||
},
|
||
size: {
|
||
value: { min: 1, max: 5 }
|
||
}
|
||
},
|
||
detectRetina: true
|
||
});
|
||
}
|
||
});
|
||
</script>
|
||
</body>
|
||
</html>
|
||
``` |