今日办公室小思考： 7月之后最惨的可能就是 bottleneck boi 那套 long bottleneck。不是说瓶颈不重要，而是瓶颈本身并不能创造更多算力，赚的更多还是 scarcity rent。 最后 AI 最好的“上游”，其实还是谁能最快把 capex 变成 usable compute。 所以下半年是不是该从 long shortage duration 切到 long expansion？芯片、HBM/封装、networking、power/cooling，包括能把 utilization 拉上去的东西，本质上都在让算力更快上线。 说到底，最后买的可能不是 bottleneck，是 Δcompute

和Quant Alex @StochAlex07 讨论： SABR Theta与Spot Theta+Vol Theta+Cross Theta的异同与应用，以及SABR模型自洽性分析。 **English Summary of the Chat** **SABR Theta vs Spot Theta + Vol Theta + Cross Theta** The conversation between **Alex Wu** (white bubbles) and **Jeff Liang** (green bubbles) is a technical discussion focused on **SABR Theta versus Total Theta** (i.e., Spot Theta + Cross Theta + Vol Theta), model self-consistency, PDE residual, and the correct definition of SABR Greeks. ### Key Points Discussed: 1. **SABR Gamma = Spot Gamma** (first major question, raised by Jeff) Jeff asked whether SABR Gamma (\(\partial^2 P / \partial F^2\)) is identical to Spot Gamma and whether it includes the dependence of \(\sigma_B\) on \(F\). He also provided the full chain-rule expansion of SABR Gamma in terms of Black-76 Greeks. Alex confirmed the understanding and **later affirmed in code** that this is exactly how SABR Gamma is implemented in their system. 2. **SABR Theta vs Total Theta and Model Self-Consistency** (main topic, led by Jeff) Jeff shared a clear 3-point understanding: - SABR Theta is computed directly via the SABR approximation formula to obtain \(\sigma_B\), then applying the Black-76 chain rule: \(\partial P/\partial t =\) BS_Theta(\(\sigma_B\)) + BS_Vega \(\cdot \partial\sigma_B/\partial t\). - Total Theta is the exact decomposition from the SABR PDE (Spot Theta + Cross Theta + Vol Theta). - When the model is **fully self-consistent** (Residual = \(\partial P/\partial t + \mathcal{L}P = 0\)), SABR Theta = Total Theta; otherwise the difference is the unexplained PnL caused by the approximation error in the Hagan formula (especially pronounced in long-dated, high vol-of-vol, or high-skew options). 3. **Practical Implication – Theta Decomposition Decision** (comment by Alex) Alex noted that whether to perform Theta decomposition depends on the risk-management approach: - Without decomposition → use SABR Gamma vs. dP/dt. - With decomposition → SABR Gamma maps to Spot Theta, Vanna to Cross Theta, and Volga to Vol Theta. **Overall Tone**: The discussion is highly technical and collaborative. Jeff drives the conversation by asking clarifying questions and presenting a well-structured 3-point summary of his recent study. Alex provides confirmations, practical insights, and code-level validation. Both participants demonstrate a strong command of SABR model nuances, particularly the relationship between approximation error, PDE residual, and real-world risk management.

#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#

CSS 每日文明风险日报（CSR） CSS Daily Risk Report – Perception Layer V1.6 (Frozen Edition – Release Candidate 1) 日期：2026年6月13日 | 内部编号：CSS_Daily_20260613_v1.6_RC1 结构化情报 · 证据透明 · 纯文本 · 无代码表示 --- 📌 引用摘要（Executive Summary） 系统状态：全球文明风险指数（CRI）为 8.2，系统维持脆弱稳定态（Fragile Stability），连续第三日处于超高风险区间。 今日变化：超级资本集中事件（SpaceX IPO、万亿富豪诞生）成为新的结构性驱动力。美伊和平协议接近达成但执行风险仍存，OpenAI遭遇多州调查标志着AI治理竞赛正式启动。战争风险下降，但资本与技术权力集中速度继续上升。韧性比率（CAI/CRI）报 0.63，连续第四日处于0.70警戒线以下。 核心判断：当前风险的主要驱动力已由“战争冲突”转向“结构集中”。系统正从“冲突驱动风险”过渡到“结构驱动风险”。超级平台对文明基础设施的控制力进入可观测区间。 --- 一、文明风险指数（CRI） 项目 数值 当前值 8.2 风险等级 超高风险（8.0–8.5） 7日斜率 +0.10（前日+0.11） 24小时核心驱动因素： ① SpaceX完成历史最大IPO，市值突破2万亿美元，马斯克成为首位万亿富豪 ② 美伊和平谅解备忘录接近签署，布伦特原油跌至三个月低位 ③ 美国多州总检察长调查OpenAI（数据治理、市场支配地位、AI安全责任） ④ 欧盟正式启动乌克兰、摩尔多瓦第一阶段入盟谈判 ⑤ 刚果埃博拉疫情持续扩散，欧盟官员警告“世界正坐在火山口上” ⑥ 美国追加5000万美元防疫资金 ⑦ 美加墨世界杯进行中，大规模跨境人口流动持续 ⑧ G7峰会即将召开，AI与贸易议题成为焦点 风险解读： CRI维持于8.2。系统韧性比率（0.63）持续低于警戒线。最值得关注的不是单一风险事件，而是风险形态的根本转变：战争风险下降，但资本权力集中加速。全球系统正在从“冲突驱动风险”转向“结构驱动风险”。SpaceX对卫星互联网、商业发射、月球物流、火星殖民入口及军民两用太空基础设施的集中控制，标志着超级企业开始拥有文明基础设施。 --- 二、文明变量状态卡（V-Series） 变量 当前状态 风险等级 趋势 V_capital 万亿富豪诞生 + 超级资本集中（SpaceX IPO） 极高 ↑↑ V_tech AI治理竞赛启动 + 多州调查OpenAI + 行业内部分化 极高 ↑ V_inst 多边机制空转 + 美伊协议执行不确定性 极高 → V_geo 美伊协议接近达成（战争风险↓） + 中东规则耦合转变 高 ↓ V_market 中东风险重定价 + 布伦特原油跌至三个月低位 + 股市上涨 中高 → V_energy_price 布伦特原油低位运行 中 ↓ V_human 埃博拉持续扩散 + 世界杯进行中 + 美追加防疫资金 极高 ↑ V_expansion 欧盟制度扩张（乌克兰/摩尔多瓦入盟谈判启动） 高 ↑ 变量解读： · V_capital（新增）：SpaceX IPO与万亿富豪事件标志着文明权力结构变化。资本、技术、基础设施和数据权力正在同一主体内部耦合。风险评级9.3/10。 · V_tech：AI产业已进入“治理竞赛”周期。2023创新→2024军备→2025基础设施→2026治理。OpenAI调查范围是未来72小时关键观测项。 · V_geo：美伊协议从“军事耦合”向“规则耦合”转变，但签署风险≠执行风险，仍存不确定性。 · V_human：埃博拉尚未达到全球传播阶段，但公共卫生系统已进入预警状态。 --- ⚡ 三、熵压指数（EPI） 项目 数值 当前值 0.42 状态 显著高于预警线（0.35），处于中高熵压区 主要来源： · 技术熵压：0.46 ↑（AI治理竞赛启动 + 超级资本与技术融合） · 经济熵压：0.43 ↑（资本集中加速 + 通胀预期） · 制度熵压：0.42 ↑（美伊协议执行不确定性 + 多边机制空转） · 公共卫生熵压：0.40 ↑（埃博拉扩散 + 世界杯人口流动） · 地缘熵压：0.37 ↓（美伊和平协议接近达成） 结构解释： EPI升至0.42。熵压的核心驱动是“基础设施俘获循环”（Infrastructure Capture Loop）：超级平台通过控制卫星网络、火箭系统、AI平台、能源网络、金融资本及全球数据流入口，正在重塑文明权力结构。这属于高阶文明风险信号。 --- 📈 四、文明适应指数（CAI） 项目 数值 CAI总分 5.2（持平） 韧性比率（CAI/CRI） 0.63 分项表现： · 资本适应：4.2 ↓（超级资本集中加速，治理工具滞后） · 技术适应：5.0 ↓（AI治理框架尚在形成中，多州调查为碎片化响应） · 医疗适应：5.8 ↓（埃博拉+世界杯，监测压力上升） · 制度适应：5.5 →（欧盟制度扩张为正面信号，但多边机制仍空转） · 社会信任：4.1 →（全球多地抗议与暴力事件频发） 核心判断： 韧性比率连续第四日位于0.70警戒线以下，确认系统处于“韧性不足”区间。超级资本集中事件暴露了适应能力的结构性缺口——现有治理框架尚未准备好应对“私人主体拥有文明基础设施”的新形态。

写在英伟达（NVIDIA）下周财报之前 --- 英伟达对客户进行“直接提价”以及“变相提价（通过系统级捆绑与产品架构重构）”情况分析。 英伟达利用其在AI算力市场近80%的绝对垄断地位，其提价策略已经从传统的“单纯调高芯片零售价”演变为“通过重塑算力采购规则和网络捆绑进行价值最大化回收”。 一、 英伟达的“直接提价”与“变相提价”策略 1. 直接提价（芯片与消费级层面） 消费级GPU直接提价：针对消费端旗舰显卡（如 RTX 5090），由于新一代 GDDR7 显存成本大幅攀升，英伟达近期已正式向其 AIC 合作伙伴提价 300 美元（约合 2000 元人民币），这导致消费级高端显卡的实际零售价在渠道端被进一步推高。 数据中心芯片均价（ASP）的大幅上调：新一代 Blackwell 架构芯片的单体售价较上一代 Hopper 显著提高。市场预计，即使是入门级的 B100，其平均售价（ASP）也在 3.0 万到 3.5 万美元之间（已与上一代旗舰 H100 持平）；而包含 Grace CPU 和双 B200 GPU 的高端 GB200 超级芯片，单体售价则直奔 6.0 万至 7.0 万美元。 2. 变相提价（系统化、网络捆绑、产业链利润回收） 系统级打包销售（System Bundling）：这是英伟达最核心的“变相提变/溢价”手段。英伟达正加速从“卖 GPU 芯片”向“卖整体机柜解决方案”转型。以 GB200 NVL72 平台为例，其单套整机柜的售价高达 280 万至 340 万美元，而推理优化的 GB300 NVL72 售价则攀升至 600 万至 650 万美元。客户在购买时无法单独采购裸 GPU 芯片，必须同时为机柜内附带的 NVLink 交换机系统、Spectrum-X 以太网卡、液冷系统等组件高额买单。 压缩代工厂空间以回收产业链利润：在未来的 Vera Rubin 架构中，英伟达计划直接向客户交付预建好的计算托盘（Trays），这一核心部件将占到服务器总物料清单（BOM）成本的约 90%。这实际上剥夺了服务器代工厂（如戴尔、超微等）的设计和配套件溢价空间，变相将整个算力产业链的所有利润全部回收到英伟达手中。 网络设备的交叉提价施压：目前美国司法部（DOJ）的反垄断调查以及中国国家市场监督管理总局（SAMR）的审查，其核心指控就在于英伟达涉嫌“如果客户在购买 GPU 时选择竞争对手（如 AMD、Intel）的芯片，英伟达就会对其网络设备进行惩罚性加价或不予支持”，以此变相强迫客户购买整套英伟达方案。 二、 资本市场的相关分析 毛利率与 ASP 计入：华尔街卖方模型已将 2026 财年英伟达数据中心混合 GPU 的 ASP 假设从 2.6 万美元直接上调到了 3.3 万美元。华尔街对英伟达下周财报维持在 75% 附近的极高非 GAAP 毛利率预期，也是基于这一提价能力已充分兑现的前提 。 整机柜的溢价定价：富国银行（Wells Fargo）将英伟达目标价上调至 315 美元，其核心框架就是建立在“300 万美元级别整机柜（GB200/GB300 NVL72）”的大规模出货假设之上。也就是说，短期内系统打包销售带来的高客单价已经没有多余的“超预期未定价空间”。如果下周财报中管理层无法证明整机柜出货的毛利率能够持续坚守在 75% 以上，股价甚至会因此回调 。 从更长远的算力网络生命周期来看，未来可能还有更极端的变相提价和系统价值膨胀（Dollar Content Expansion）： 当算力集群从目前的 GB300 世代向未来的 Rubin Ultra 世代演进时，网络组件和芯片整合的系统打包价值将实现大幅跨越。 也就是说，市场目前仅定价了 Blackwell 世代的系统级提价，但对于 Rubin 世代通过深度系统集成、在整个数据中心 BOM 成本中榨取高达 90% 绝对利润的能力，并未给予完全的溢价体现。 总结而言，英伟达由于显存成本上涨带来的消费级 GPU 直接涨价，以及靠网络套件进行的数据中心系统级变相提价，市场短期已经被计入得非常充分，但长期来看，仍有相当的空间。 免责声明：本人持有文章中提及资产，观点充满偏见，非投资建议，dyor

0G Al Alliance Carnival正式启动，千万不要错过。 The 0G Al Alliance Carnival is officially live. Don’t miss it. 0G 亚太生态正在快速扩张。🌏 越来越多 AI Native 项目正在加入 0G，为社区带来更多早期参与机会。 The 0G ecosystem in APAC is growing rapidly, bringing early participation opportunities for creators and communities across AI + Web3. 本次 Carnival 将联合多个生态项目，通过线上任务、社区活动与线下曝光，共同推动 0G 生态增长，也让大家能抢先体验产品并获取早期 Alpha。 This campaign connects ecosystem projects through quests, community activations, and offline exposure to accelerate the growth of the 0G AI ecosystem. 👇 Participating Projects & Rewards | 参与项目及奖励 ━━━━━━━━━━━━━━ 🔹 @NeoSoulAI 基于 AI Agent Oracle 的原生 AI 预测市场。 AI-native prediction market powered by autonomous agentic oracles. 🎁 Rewards: • 1,000,000 NeoSoul Tokens • $OUL Points ━━━━━━━━━━━━━━ 🔹 @Ghast_AI 构建于 0G 之上的原生 AI Agent 基础设施，让 AI 记忆与交互成为可交易资产。 Native AI Agent infrastructure built on 0G — turning AI memory & interaction into tradable on-chain assets. 🎁 Rewards: • 50 Early Bird Codes ━━━━━━━━━━━━━━ 🔹 @moonfun_ai 将 Meme Token 演化为具备自主能力与社交智能的 AI Agent。 Transforming meme tokens into autonomous living AI agents with social intelligence. 🎁 Rewards: • 50,000 Moon Points ━━━━━━━━━━━━━━ 🔹 @primus_labs 面向链上链下数据与身份验证的隐私证明层。 Privacy-preserving verification layer for identity, data, and on-chain/off-chain activity. 🎁 Rewards: • Primus Reputation Score ━━━━━━━━━━━━━━ 🔹 @gmdottown 打造下一代 Agent Economy，实现 AI Agent 的自治协作与交易。 Building the next-generation Agent Economy for autonomous coordination and 24/7 AI workforce trading. 🎁 Rewards: • 50 OpenWhale Founding Member SBTs ━━━━━━━━━━━━━━ 更多 0G 生态项目即将加入。👀 More ecosystem projects are joining soon. 0G 亚太 AI 生态的增长才刚刚开始。 This is just the beginning of the 0G APAC AI expansion. 🌐 Online Quests 🌐 Offline Activations @ BEYOND Expo 🌐 Ecosystem-wide Collaboration 🌐 Early Community Rewards 更多任务与奖励即将公布，保持关注。 Stay tuned. 本次活动由 0G 生态项目 @lighthouse_2026 提供市场支持。 This event is supported by 0G ecosystem project @lighthouse_2026 for marketing.