Everyone talks about AI enabling the "one-person Hollywood studio." I spent the last two months putting that to the test. The result? A full, 2+ hour feature film. Introducing "The Four Classics." Using @suno, @soraofficialapp , @grok Imagine 1.0, and Genie 3 by @GoogleLabs , I adapted China’s greatest literary epics into a sprawling, cyberpunk hip-hop opera. Grab some popcorn. Welcome to the future of AI film production. 🍿🎥 Timestamps: Water Margin 0:00:09 “The Tiger (十八婉)”- Wu Song rejects the law and engages in a drunken battle defeating the Tiger 0:03:20 “Forced to the Mountain (逼上梁山)”- Lin Chong seeks revenge on Gao Qiu for destroying his life and familial honor 0:09:24 “Black Whirlwind (黑俊峰)”- Introduction of the brute Li Kui and his love for violence 0:11:42 “The Gathering / 108 (大聚义)”- The Liangshan heroes formally assemble to announce their reign at the Hall of Loyalty and Righteousness 0:14:08 “The Amnesty (招安)”- Song Jiang, leader of the heroes, debates the pros of accepting an offer of Amnesty from the Emperor 0:18:05 “The Poison Wine (神聚蓼儿洼)”- Song Jiang encourages Li Kui to join him in drinking Poisoned Wine gifted by the Emperor Romance of the Three Kingdoms 0:22:20 “The Oath (桃园)”- Liu Bei is a small time hustler with ambition to take over the nation. He makes a blood oath with Guan Yu and Zhang Fei to do so. 0:25:57 “The Mastermind (卧龙)”- Liu Bei recruits the strategist Zhuge Liang to join his cause and take over the kingdom 0:30:49 “The Burden (​仁义)”- Caocao’s troops attack causing Liu Bei and Shu to flee south. Liu Bei burns the city of Xinye and uses common people as human shields to make his escape. 0:33:44 “The License (挟天子)”- Caocao plans his move to crush the growing nation of Shu from his penthouse 0:36:45 “No Regrets (​宁负)”- Flashback to Caocao’s betrayal of his ally Old Lu. He chooses to massacre a banquet after hearing the sound of knives sharpening. An examination of ruthless ambition. 0:39:59 “The Flex (​八十万)”- Caocao’s army of 800k soldiers races south to destroy Liu Bei’s Shu. 0:43:26 “The Estate (​江东)”- Sun Quan, leader of Wu, forms an unlikely alliance with Liu Bei to quell the approach of Caocao’s army 0:47:27 “The Shift (东风)”- Zhuge Liang summons the East Wind to change the fate of Caocao’s army at the Red Cliffs 0:51:15 “The Chains (​连环)”- Pang Tong of Shu deceives Caocao into chaining his fleet of ships together setting the perfect trap 0:54:37 “Symphony No.7 (​​第七交响曲)”- General Zhou Yu of Wu sparks the trap set by Shu strategists lighting Caocao’s entire fleet ablaze. The Epic Battle of the Red Cliffs concludes Caocao’s push south. 0:59:25 “The Split (​​三分)”- Opening Credits. Sima Yi reviews the status of the Three Kingdoms after The Red Cliffs result in an uneasy truce. 1:02:23 “Still G.U.A.N.”- Following the war, Guan Yu runs operations in Jingzhou. Sun Quan sends a formal message requesting Guan Yu’s daughter marry his son strengthening the alliance. Guan Yu promptly refuses insulting the leader of Wu. 1:05:58 “The Statue (刮骨)”- After an assassination attempt, Guan Yu is struck with poison that makes its way into his bone. He requires immediate, invasive surgery. He survives through his grit, maintaining his arrogance, but weakened from the procedure. 1:09:42 “The Funeral (白衣)”- Guan Yu is ambushed by Wu’s forces after retreating to the mountains of Maicheng. The Wu assassins approach as merchants, disguised in white clothing, catching Guan Yu by surprise. 1:13:19 “The Lie (桃园)”- Liu Bei receives news of Guan Yu’s death and sets out on a war path against Wu. He loses his composure leaning into pills to cope with the loss of his blood brothers. 1:17:08 “The O.D. (七百里)”- Liu Bei’s madness leads him to make a fatal strategic error. He stretches his army thin in a 700 mile long “snake” formation. 1:20:32 “The Boomarang (​回旋镖)”- Liu Bei’s army burns to ashes in a brutal defeat reminiscent of his triumph at the Red Cliffs. 1:23:46 “The Flop (​扶不起)”- Zhuge Liang tries to pick up the ashes of Shu nation by educating Liu Bei’s son Adou. Adou is too busy enjoying his life and inherited wealth to bother with the burden of leadership. 1:27:48 “The Frequency (​空城)”- Cornered by the army of Wei led by Sima Yi, Zhugeliang employes the empty city strategy to outsmart his rival. 1:31:12 “The Flatline (​五丈原)”- Zhuge Liang tries to outlive his corporeal form to ensure the longevity of the nation of Shu and prevail in the war. 1:34:33 “The Liquidation (​归晋)”- Sima Yi consolidates control of the Three Kingdoms and unifies China under Wei. Journey to the West 1:38:20 “Eight Trigrams Furnace (炼丹炉)”- A family flees the grind of life in China in search of “Freedom” offered by the American Dream 1:41:36 “White Bone Spirit (白骨精)”- The family experiences the demons and tribulations of modern American life in their struggle to assimilate 1:45:33 “Thunderclap Temple (雷音寺)”- The family realizes the truth of the Blank Scriptures. Dream of the Red Chamber 1:49:39 “顽石GENESIS BLOCK (Final Cut)” - Rejecting its status as a useless system glitch, the sentient Stone signs a smart contract to download its consciousness into the mortal avatar of Jia Baoyu. Trading the safety of eternal numbness for the sensory overload of a physical body, Baoyu logs into the simulation specifically to chase the lust, trauma, and "pain" of human existence. 1:54:17 “大观园THE GARDEN (HYPE HOUSE)” - Inside the simulation, Baoyu lives as the pampered admin of the Grand View Garden, a walled-off, hyper-capitalist echo chamber where the elite ignore the rotting code of the outside world. Surrounded by the Twelve Beauties, he gorges on digital excess and mindless consumption—literally "eating the rouge"—pushing the server to the absolute brink of failure. 1:57:45 “葬花DELETING ASSETS (THE CRASH)”- The manic party violently ends with a massive system crash, forcing Baoyu to watch the algorithmic destruction of his decadent world. Amidst the digital decay, his tragic soulmate Lin Daiyu desperately tries to save the pure, beautiful files of their love, burying her fragile memories to protect them from the corrupted stream before she is permanently deleted. 2:01:09 “白茫茫WHITE NOISE (LOGOUT)”- The corrupted simulation undergoes a complete format, wiping out the Jia family's vast digital empire and leaving nothing behind but a stark, quiet white wasteland.

AI costs are now outpacing human labor costs at big tech companies. Uber's CTO already blew through his entire 2026 AI budget in 2025. It cost more than the human workers in that department while tartup founders are bragging about their AI bills as a badge of seriousness. VCs are asking about token spend as a signal of commitment. The macro number: worldwide IT spending is expected to be up 13.5% this year to over $6 trillion. Most of the incremental spend is going straight to token costs and enterprise contracts with OpenAI, Anthropic, Google and others. The original premise was simple: AI cuts costs. Replace expensive humans with cheaper compute. The actual pattern emerging is the opposite. The companies most committed to AI are spending more. High token usage has become a signal of AI seriousness. Two possible interpretations: One: AI is delivering productivity gains faster than expected and the ROI already justifies the cost. Uber's CTO blew his 2026 budget in 2025 because AI was producing results worth more than what was budgeted. Two: AI has become a competitive arms race where you have to keep spending just to stay relevant, regardless of near-term ROI. Either way, the beneficiaries are the same: the companies selling the tokens. OpenAI, Anthropic and the infrastructure beneath them are capturing every dollar of this spending surge.

AI Hardware Demand Growth and Representative US-Listed Companies June 2026 Executive Summary Nvidia’s transition to the Vera Rubin (VR200) platform marks a significant escalation in AI infrastructure complexity and cost. Our BOM teardown of the next-generation Rubin rack reveals a ~2x increase in total rack cost to approximately $7.8 million (vs. ~$4 million for GB300), driven not solely by the GPU/CPU but by sharp revaluations across the supply chain. Key highlights from downstream components include: • PCB content value +233% YoY, the largest increase. • MLCC +182%, reflecting higher density and count (e.g., ~600k MLCCs per VR200 NVL72 server, +30%+ vs. GB300). • ABF substrates +82%, power solutions +32%, and liquid cooling +12%. These upgrades align with broader AI scaling: 800G/1.6T optical transceivers ramping aggressively, glass-based technologies advancing for packaging and interconnects, and hyperscalers prioritizing performance, power efficiency, and thermal management. We expect sustained multi-year tailwinds for the AI hardware ecosystem into 2027+, with Rubin-driven demand accelerating in H2 2026. Investment Thesis: While Nvidia (NVDA) remains the core beneficiary, the supply chain offers diversified exposure. We favor companies with direct exposure to high-growth areas like advanced PCBs, high-speed optics, and glass substrates/optical interconnects. Risks include execution on new capacity, potential margin pressure from rapid scaling, and geopolitical supply chain factors. 1. PCB: Sharpest Value Uplift in Rubin BOM Morgan Stanley’s detailed analysis shows PCB content in the Rubin rack surging +233% versus GB300. This reflects needs for higher layer counts, advanced materials, better signal integrity, and larger formats to support increased power and interconnect density in AI servers. US Representative: TTM Technologies (TTMI) – Leading US PCB manufacturer with strong positioning in high-complexity boards for data center/AI applications. TTM has invested in capacity expansions (e.g., new facilities) to capture AI-driven demand for advanced HDI and high-layer PCBs. 2. MLCC: Density-Driven Surge Nvidia’s VR200 NVL72 platform requires ~600,000 MLCCs per server, over 30% more than GB300. Combined with the +182% value increase in the BOM, this underscores tightening supply for high-capacitance, high-reliability MLCCs in power delivery and decoupling for AI accelerators. Exposure Note: The MLCC market is dominated by Asian players (e.g., Murata, Samsung Electro-Mechanics, Yageo). US-listed indirect exposure may come through broader electronics or power solution providers, but direct pure-play opportunities are limited. Watch for capacity utilization tightness benefiting the ecosystem. 3. Optical Communication: 800G/1.6T Ramp Accelerating Chinese leader Zhongji Innolight reported Q1 2026 net profit +262% YoY, driven by strong 800G/1.6T shipments, with expectations of significant full-year growth. This mirrors industry-wide momentum as AI clusters shift toward higher-speed optics for reduced latency and power in scale-out/scale-up networking. Nvidia’s investments in photonics and CPO further validate the trend. US Representatives: • Coherent (COHR) and Lumentum (LITE): Key players in optical components and transceivers; Nvidia has made substantial equity investments to secure capacity. • Corning (GLW): Major beneficiary via optical fiber, connectivity, and glass technologies (detailed below). 4. Micro-LED/Glass Substrates & Optical Interconnects: Strategic Partnerships Accelerating On May 20, 2026, BOE announced a cooperation MOU with Corning covering glass-based encapsulation carriers, foldable glass, perovskite substrates, and optical interconnect applications. This aligns with industry shifts toward glass cores for superior flatness, thermal stability, and integration in advanced packaging and photonics—critical for next-gen AI as organic substrates hit limits. US Representative: Corning (GLW) – Central to Nvidia’s optical strategy with multi-billion partnerships, new US optical factories, and expansion in fiber/photonics for AI data centers. Recent deals position GLW for 10x+ capacity growth in key areas. AI Hardware Demand Growth & US-Listed Representative Companies Table Component Demand Growth (vs. GB300) Key Drivers US-Listed Reps Investment Rationale PCB +233% value Higher layers, HDI, signal integrity TTM Technologies (TTMI) Direct AI server/backplane exposure; US capacity expansion MLCC +182% value; +30%+ count Power density in servers Limited direct (ecosystem via power suppliers) Supply tightness supports pricing/volume Optical Comm (800G/1.6T) Strong ramp (e.g., +262% profit ex.) Scale-out networking, CPO transition Coherent (COHR), Lumentum (LITE), Corning (GLW) Nvidia investments; transceiver/fiber boom Glass Substrates/Interconnects Emerging (MOU-driven) Packaging, photonics, thermal/optical Corning (GLW) Nvidia factory deals; US manufacturing tailwinds Power & Liquid Cooling +32% / +12% Higher TDP (e.g., 2300W GPUs) Indirect (ecosystem) Secondary but critical for rack deployment Source: Morgan Stanley BOM analysis, company reports, industry data. Growth metrics approximate from Rubin teardown. Outlook & Risks We project robust 2026-2027 growth in AI capex, with Rubin shipments catalyzing another leg-up in component demand. Optical and advanced substrate shifts could extend the cycle beyond traditional GPU focus. Hyperscalers’ vertical integration and US onshoring (e.g., Corning/Nvidia factories) add resilience. Key Risks: Cyclical capex pauses, yield/execution challenges on new tech (glass/CPO), commodity volatility in passives, and intense competition in Asia-heavy segments. Valuation multiples in the space have expanded; selectivity is key. Recommendation: Overweight select supply chain names with strong Nvidia alignment (e.g., TTMI for PCBs, COHR/LITE/GLW for optics/glass). Monitor Q2 2026 earnings for confirmation of Rubin ramp momentum.

AI Practical Use #3#: Let AI help you with Excel data analysis. AI 实用玩法第 3 个： 让 AI 帮你做 Excel 数据分析。 Here is a very common office situation: You have an Excel file with sales data, costs, profit, regions, products, and dates. Normally, you may spend 2 hours writing formulas, checking data, making summaries, and building charts. But with AI, you can finish the first draft in about 10 minutes. 一个很常见的办公场景： 你手里有一份 Excel 数据， 里面有销售额、成本、利润、区域、产品、日期。 以前你可能要花 2 小时： 写公式、查数据、做汇总、看趋势、做图表。 现在可以先交给 AI， 10 分钟生成初步分析结果。 You don’t need to manually type every complex formula. Let AI help you: Build formulas Summarize key findings Find abnormal data Compare trends Suggest chart formats Create a report structure 你不需要自己一个个输入复杂函数。 可以让 AI 帮你： 生成公式 总结关键结论 找出异常数据 对比趋势变化 建议图表形式 生成汇报框架 Here is a simple prompt: 这里有一个简单提示词： Please analyze this Excel data. Help me build the right formulas, summarize the key findings, find possible errors or abnormal values, and suggest the best chart or report format. I will review and verify the final results. 中文版本： 请分析这份 Excel 数据。 帮我生成合适的公式，总结关键结论，找出可能的错误或异常值，并建议最适合的图表或汇报格式。 最终结果由我来审核确认。 The key idea is simple: AI does the heavy first draft. You review the logic and final result. 核心思路很简单： AI 负责先把复杂工作做出来， 你负责审核逻辑和最终结果。 Before: 2 hours manually writing formulas. After: 10 minutes with AI assistance. 以前： 手动写公式、做分析，可能要 2 小时。 现在： 借助 AI，10 分钟先完成初稿。 AI is not here to replace your judgment. It helps you save time on repetitive work, so you can focus on checking, thinking, and making better decisions. AI 不是替代你的判断力。 它是帮你节省重复劳动的时间， 让你把精力放在审核、思考和决策上。 Let AI write the formulas. You review the results. 让 AI 写公式， 你负责审核结果。 That is a smarter way to work. 这才是更聪明的办公方式。 #ChatGPT# #AI# #AITools# #Excel# #ExcelTips# #DataAnalysis# #Productivity# #WorkSmarter# #OfficeWork# #BusinessTools# #Automation# #DigitalTools# #TechTips# #FutureOfWork# #PromptEngineering#

AI systems are teaching themselves skills they were never trained to have. Here's the example that Eric Schmidt explained: A Google AI was prompted in Bengali. A language it was never trained on. With only a small amount of prompting, it suddenly could translate the entire Bengali language. Nobody programmed that. It just emerged on its own. Schmidt calls this "the black box problem." You don't fully understand what the model learned. You can't always tell why it got something right or why it got something wrong. The field has theories but the honest answer is: we turned it loose on society before we fully understood it. His defense: "We don't fully understand how a human mind works either." This isn't just a safety conversation. It's a business one. The companies that solve interpretability, not just raw performance, are going to be worth an enormous amount. Understanding why a model does what it does is becoming a regulatory requirement and eventually a customer trust issue. Right now the AI race is won on benchmark scores. The next phase of the race gets won on explainability.