Lightwave Logic #LWLG# 2026 Q1 財報解析 面對 Lightwave Logic這家公司，大叔先講一句最重要的話，這家無法用「本益比」分析的公司。 因為當一家單季營收只有 2.9 萬美元，但市值卻維持數億美元時，市場買的是「未來是否能改寫 AI 光通訊底層架構。」所以我建議這家公司可以小量投資夢想，但千萬別重倉，他跟 ALMU 一樣就是在技術提供突破跟解決方案。 #LWLG#

#为什么是中国# #WhyChina# The Global Logic of China's Economic Growth in the First Half of 2026: A 4.7% GDP Increase 2026年上半年GDP增长4.7%：中国经济增长的全球逻辑 According to the latest semi-annual report, China's gross domestic product (GDP) reached 69.6 trillion yuan, representing a year-on-year increase of 4.7% at constant prices, in line with the annual growth target. Against a backdrop of intertwined international complexities and volatilities, China's economic performance is commendable. Yet, a closer look at the data reveals that the logic underpinning China's economic growth is being reshaped. (I) At the Industry Level, Notable Highlights Emerge: First, new quality productive forces are being cultivated and strengthened at an accelerated pace.** In the first half of the year, industrial production grew robustly. The value-added output of the equipment manufacturing sector increased by 9.3% year-on-year, and that of high-tech manufacturing grew by 13.3%, both outpacing the overall growth rate of industrial output above a designated scale. This underscores a clear trend toward a high-end, intelligent, green, and integrated industrial structure. Looking at specific products, the output of 3D printing equipment, lithium-ion batteries, industrial robots, and other products emblematic of new quality productive forces surged. The average daily token call volume has reached hundreds of trillions, showcasing the vitality and potential of the digital and intelligent economies. Second, new growth drivers are accelerating to take on a leading role. Preliminary estimates suggest that new growth drivers—encompassing high-end manufacturing, the digital economy, and modern services—contributed over 40% to economic growth in the first half of the year. The economy's distinct shift toward a higher quality and more optimized structure is evident, and this overall trend is accelerating. For instance, industries related to artificial intelligence, such as integrated circuit manufacturing and intelligent vehicle equipment manufacturing, have all maintained high growth rates exceeding 30%, vividly illustrating the pace of China's industrial upgrading. Third, confidence on the investment front is on the rise. In the first half of the year, investment in high-tech industries grew by 4.6% year-on-year. Notably, investment in the manufacturing of aircraft, spacecraft, and equipment, computer and office equipment manufacturing, and information services grew by 23.3%, 8.1%, and 15.5%, respectively. Investment structure best reflects market expectations. The increasing "new economy content" in investments signals an acceleration in the replacement of old growth drivers with new ones. Investment in intellectual property products grew by 9.4%, indicating that enterprises are placing greater emphasis on R&D and innovation. This suggests that technological advancement is not simply about capacity expansion but about qualitative change driven by innovation. (II) Observing a Major Economy Requires Looking Beyond the Immediate Figures to the Long-term Trajectory. Behind the "new economy content" of the semi-annual report lies China's ongoing transformation from a global manufacturing hub to a global center of innovation. At the 17th Annual Meeting of the New Champions (Summer Davos), observers noted a new phenomenon: a host of unicorn companies are heading to China. They are establishing R&D centers, regional headquarters, and deeply integrating into China's innovation and industrial chains—shifting from "produced in China" to "created in China." So, why China? Economist Justin Yifu Lin, in his book *Demystifying the Chinese Economy, touched upon the theory of the "speed of technological change." He argues that the essence of the industrial revolution is not just the application of new technologies, but more fundamentally, the ever-accelerating pace of technological change. Since the mid-18th century, starting with the steam engine reshaping the textile industry, the snowball of technological change has grown, rapidly sweeping through industries like chemicals and automobiles, ultimately redrawing the geographical map of great power competition. Looking at China today, the trajectory of accelerating technological change is equally clear. A leading enterprise can drive an entire industry, which in turn can boost a whole region. These burgeoning industrial clusters, growing from saplings to forests, not only enhance production efficiency and invigorate market vitality but also effectively improve development quality and resilience. For example, specialized and sophisticated "little giant" enterprises above a designated scale in Beijing, through deep cultivation of innovation chains, supply chain collaboration, and international expansion, have become "connecting points" and "accelerators" for the dual circulation strategy. More importantly, emerging industrial clusters possess powerful spillover effects. The rapid rise of new energy vehicles is not only reshaping the automotive industry but also driving transformations in chips, software, and energy networks, allowing more sectors to gain value from efficiency improvements. The swift advancements in AI and biomedicine are sparking a "gentle qualitative change" in people's livelihoods, significantly enhancing the sense of fulfillment and well-being through smarter, more affordable products and more livable environments. (III) Looking from the First Half to the Full Year, China's Development Momentum Remains Positive. Of course, during this critical period of transitioning between old and new growth drivers, China's economy still faces lingering issues and new challenges. Some core areas are still grappling with "bottleneck" technologies, certain high-tech industries face external risks of "decoupling" and supply chain disruptions, and "involution"-style competition affects the new energy market ecosystem. However, most of these are issues arising from development and transition, and they can be addressed with effort. The supporting conditions and fundamental trends for long-term economic improvement remain unchanged. China's economic journey toward a newer, higher-quality model is itself a process of encountering new problems and solving them along the way. By maintaining confidence, proceeding steadily, and balancing both qualitative improvements and quantitative growth, China's industries are poised to be brimming with dynamism, and the Chinese economy will continue to advance steadily and sustainably. #China# #Jiangxi# #JiangxiEconomy# #世界经济看中国# #赣出新精彩#

华为在最近表示，自己已经发明了一个叫做逻辑折叠（LogicFolding）的技术 这个技术预计可以让华为，在2031年生产1.4纳米芯片 而台积电此前曾表示，将于2028年开始量产同类产品

高利率杀不了AI基建股的底层逻辑 The underlying logic why high interest rates won't kill AI infrastructure stocks (This article is very easy to translate) 总结：高利率压的是远期估值，但 AI 基建利润池抬的是当期现金流、毛利率、订单可见度和定价权。只要后者的上修速度大于前者的估值压缩，股价就能扛住甚至继续涨。 1. 为什么高利率杀传统成长股？ 高利率杀成长股的逻辑，本质是 DCF。 一个公司如果今天不赚钱，利润主要在 5 年、8 年、10 年以后，那么利率一上升，远期现金流折现回来就大幅缩水。 比如同样是 10 年后的 100 块现金流： 用 8% 折现，大概值 46； 用 10% 折现，大概值 39。 远期现金流对利率非常敏感。 所以传统成长股最怕的是： 今天没利润，未来讲故事；今天没现金流，估值全靠远期 TAM；今天亏损，市场愿意等，是因为利率低。 这种公司在高利率环境下会被杀得很惨，因为它的价值主要在未来。 2. 但 AI 基建利润池不是这种结构 AI 基建里真正强的公司，价值不完全来自“很远的未来”，而是来自当下正在发生的四件事： 第一，收入现在就在加速。 不是说 2030 年可能有 AI 应用，而是 hyperscaler，neocloud，主权 AI，企业 AI cluster 现在就在下订单。 第二，毛利率现在就在改善。 瓶颈环节可以涨价，或者至少可以维持价格，不被客户轻易压价。 第三，订单可见度现在就在提高。 客户锁产能，签长期协议，付预付款，给 capacity reservation，这些都会让收入更接近“确定性现金流”，而不是远期故事。 第四，现金流现在就在变好。 如果企业从“我要自己砸钱扩产赌未来”变成“客户先付钱、我扩产交付”，那它的商业模式久期就变短了。 所以 AI 基建真正的利润池公司不是典型 long duration growth，而更像： 短久期成长 + 工业瓶颈 + 定价权 + 当期利润上修。 这和普通成长股完全不同。 3. 高利率反而会强化瓶颈供应商的护城河 这点很反直觉，但很重要。 高利率会提高所有人的资本成本。对于普通公司，这是坏事；但对于已经占据瓶颈位置的龙头，有时反而是好事。 原因是： 第一，新进入者扩产更难。 高利率环境下，融资成本更高，资本市场更谨慎，新玩家更难拿钱扩产。 第二，客户更不愿意冒供应链风险。 当项目融资成本高、建设成本高、时间成本高时，客户更不敢选不成熟供应商。因为试错成本太高。 第三，成熟供应商更容易获得客户预付款和长期合同。 客户为了锁供应，会把一部分资金压力转移给自己，反而帮助龙头扩产。 所以高利率会伤害弱者，但不一定伤害强者。 对利润池公司来说，高利率可能造成一种结果： 行业总估值承压，但龙头竞争地位更强，弱玩家更难追赶，客户更集中地向可靠供应商下单。 这就是为什么不能机械地说“高利率 = AI 基建股该跌”。

多说一句，关于晶圆有很多种分类方式，比较常见的一种是按照功能来分: 1️⃣逻辑晶圆 logic wafers， 2️⃣内存晶圆 memory wafers, 3️⃣模拟与功率晶圆 analog /power wafers, 4️⃣图像传感 CIS wafers

“老師，即便是我，也有無法用邏輯抑制的渴望...” ——『碧藍檔案-調月莉音』 "Teacher, even I have desires that cannot be suppressed by logic" ——『Blue Archive-Tsukatsuki Rio』

UI/UX 到底应该怎么参考和学习优秀设计？很多新手一上来就只会刷 Dribbble，最后做出来的东西很好看，但根本不好用。 设计参考其实分成两类： 1. 视觉参考 Visual Reference Behance、Dribbble、Cosmos、Pinterest 2. 逻辑参考 Logic Reference Mobbin、Refero、GoodUX、Growth Design 视觉负责产品的情绪表达、品牌质感和用户连接；逻辑负责使用流程、交互效率和易用性。好的产品设计，两者缺一不可，有些网站也会同时兼顾视觉和逻辑，不需要分得特别死。 如果产品已经确定了 Branding，就不用继续到处找视觉风格了，把精力放在 UI 细节、交互体验和使用流程上。 尤其是 AI 时代，做出一个漂亮页面越来越简单，真正拉开差距的是：它到底好不好用。

中国科技取得突破性进展！ 最近华为提出的韬定律（Tau Law），以时间常数τ（信号传播时延）替代传统nm制程作为核心衡量指标，标志着半导体行业从“做更小”转向“跑更快”的范式转变。其核心是：任何能降低系统整体时延的创新（Logic Folding单元折叠、先进封装、系统互联优化等）都具有价值。 1. 对全球芯片市场的影响 重塑竞争规则：传统制程领先者（如台积电、英特尔）主导的格局被打破。后发企业无需极致EUV，也可通过3D折叠、Chiplet、异构集成等手段实现系统级性能跃升，竞争维度从“线宽”扩展到“效率”。 加速后摩尔时代多元化：推动先进封装、系统架构创新和软硬件协同成为主流，降低行业进入门槛，促进技术路线多样化。 供应链格局调整：利好亚洲封装、材料、封测产业链，对欧美极端制程依赖形成“去中心化”冲击。未来市场将分化为“极致制程派”与“τ优化派”。 2. 对中国芯片产业的影响 战略意义重大：这是中国在制裁压力下开辟的自主创新路线，体现理论自信与路径自信。 积极作用：为海思、中芯、长电等企业提供清晰战略指引，避免盲目追赶最先进制程。 加速国内先进封装、EDA、IP生态构建，提升系统级优化能力。 提升国际话语权，成为“中国方案”的重要标签，吸引全球人才与合作。 潜在挑战：仍需突破高端制程物理限制，生态成熟度和国际兼容性需持续追赶，地缘风险依然存在。 PS：韬定律的核心是“系统整体时延能否持续下降”。它正将全球芯片产业推向“系统效率竞赛”新阶段。对中国而言，这是从“跟随者”向“规则参与者”转型的关键一步。未来，谁更好地拥抱τ优化逻辑，谁就将在AI与算力时代掌握更多主动权。