Tuan Le Minh

2026 Silver Ethereum Uranium (Energy) Algorithm (AI) Rare Earth Bitcoin Gold Crypto: DePIN, DeSci, Tokenization (RWA), Stablecoins (DeFi), Privacy, Zero-Knowledge, Chain Abstraction, Interoperability, Prediction Markets, Perps, DeFAI

$TIG hit $1.56 tonight. @tigfoundation Before you ape in or dismiss it, do your homework. Here's what you'll find: The team: Cambridge PhD. Bank of England. ARM General Counsel. Oxford mathematicians. Not anonymous. Not hype. The problem: Google is quietly monopolizing the algorithms that build AI. The same way they monopolized search 25 years ago. No open competitor ever caught up. The solution: The first open market for algorithm discovery. Linux + Bitcoin combined. Researchers get paid to publish instead of hide. The tokenomics: Top 2 holders? A vesting contract and a protocol locker. 55% is infrastructure. 22K real holders. Healthy distribution, check yourself. The timing: Jensen Huang just said algorithm gains delivered 30-50x last generation. More than Moore's Law ever did. $TIG built the marketplace for exactly that. Years early. The market cap: $33M circulating. $77M FDV. Early, so at least do some research, so you are not sad in 2 years. This is the algorithm infrastructure layer for AI. Do the math. Do the research. Then do moves, which allow you to sleep nicely, means: do not gamble. Invest with awareness. $TIG

Over three years ago, we said AI will lead to 300 million layoffs in US and Europe. Some laughed. They aren't laughing now

🔵 "The only way to really get 10x or 100x leaps is to fundamentally change the algorithm and how it's computed every single year" The solution is $TIG btw 👍

🦔The 30-year Treasury yield hit 5.198% on Tuesday, the highest level since July 2007. The 10-year is at 4.687% and the 2-year is at 4.127%. The S&P closed down 0.67% for its third straight losing session. A Bank of America survey shows 62% of global fund managers now expect the 30-year to reach 6%, and Citi says 5.5% is the next target. The selloff is global, with UK 30-year gilts at 5.77%, Japan's 30-year hitting a record high, and the 30-year fixed mortgage at 6.36%. Bond yields move opposite to prices, so the move means investors are dumping bonds on inflation fears tied to Iran energy prices and rising US deficit concerns. My Take Here is what this actually means if you are not a bond trader. When the 30-year yield rises, the cost of borrowing money for everything you might want to do also rises. Mortgages, car loans, business loans, and credit card rates all take their cues from these Treasury yields. So when investors demand 5.2% to lend the US government money for 30 years, your local bank cannot offer you a 4% mortgage and still make any money. The bond market is the foundation everything else gets priced off of, and that foundation just moved. The Fed lost control of the long end of the curve, which is a polite way of saying Kevin Warsh got handed a job where the most important number in the economy is no longer something he can directly influence. He can cut short-term rates and the 30-year could still keep climbing, because investors are pricing in higher inflation and bigger deficits no matter what the Fed says. For your personal finances, mortgage rates are not coming down meaningfully and refinance plans should not assume otherwise. High-yield savings accounts paying 4% to 5% are now earning a real return above inflation for the first sustained period in two decades, which is a genuine opportunity for anyone holding cash. Long-duration assets like growth stocks and long bonds remain the most exposed to further yield increases, and the gap between what the bond market is pricing in and what the stock market is assuming is wide enough that one of them is wrong. Hedgie🤗

Big Tech is now spending billions on agentic algorithm discovery. Dr John predicted this years ago, and already designed the cure! 5 loops → $TIG market mechanism neutralises 4, Prometheus neutralises the 5th. This isn't a race anymore. It's a war: adoption vs lock-in.

You know what soaring Treasury yields will really help with? The $1.3 trillion in annual US interest expense. For context, the largest US government outlay is Social Security. It is $1.6 trillion.

Only 35 protocols cleared $2M in monthly revenue last month. Here are the top 25 by revenue: 1. @tether $476.6m 2. @circle $191.1m 3. @HyperliquidX $48.3m 4. @Pumpfun $33.2m 5. @Polymarket $20.2m 6. @Grayscale $19.6m 7. @SkyEcosystem $15.1m 8. @AxiomExchange $11.3m 9. @Paxos $10.3m 10. @aave $9.4m 11. @phantom $6.9m 12. @edgeX_exchange $6.4m 13. @titanbuilderxyz $6.4m 14. @Courtyard_io $5.7m 15. @LidoFinance $4.6m 16. @chainlink $4.5m 17. @JupiterExchange $4.0m 18. @gmgnai $3.9m 19. @ether_fi $3.8m 20. @AerodromeFi $3.7m 21. @PancakeSwap $3.4m 22. @Uniswap $3.1m 23. @MetaMask $2.7m 24. @phygitals $2.7m 25. @Securitize $2.7m The entire onchain economy runs on maybe 25 businesses.

The $TIG thesis is that algorithms are the most undervalued and most monopoly-prone layer of the AI stack, and TIG is building the open-source alternative to what Google DeepMind / Anthropic / Open AI could otherwise own outright - innovators submit optimised algos - benchmarkets test algos vs. test cases - TIG manages license rights to these algos Critical to this endeavour is Philip David Who spent a decade at ARM, who licensed their chip design to companies like Apple, Qualcomm, Samsung etc But let's be clear: their commercial model is not yet empirically proven Licensing revenue is the long-term engine, but the network is still in its build phase and trades as such 1. TIG has assembled fascinating token architecture 2. Run by a Class A team 3. Tackling one of the defining problems of our time Available in the public markets

A MUST-read interview with a Siemens employee explaining just how high demand is for energy equipment right now because of AI: 1. The whole situation is shocking even for people who have been in the business for 40 years. They are getting orders that are double the size of what their entire factory can produce in a year. 2. Demand is so high in the last 5-8 months that they don't need to convince or send any analysis (such as CO2 emissions, etc.) to clients because they just want the equipment, because there's so much backlog that they just want to catch the order. 3. Decisions are being made very quickly by clients; the backlog for some of the energy equipment companies is 5-6 years. For transformers, the situation is even more difficult. 4. He mentions that right now, data center builders do not care about sustainability; they just want power at any expense, reliable power. They say they will think about sustainability later. 5. The orders have gone from previous 20-30 MW orders to now 200-500 MW units. Customers have previously wanted to get equipment from different OEMs, but now they prefer an integrated standardized solution. 6. An interesting dynamic is that even though the data center requires 100 MW, the builders are buying N+1 units of gas turbines (so more than just for 100 MW) as backups, as well as having more energy capacity, as they believe they will continue to grow that data center. 7. He does believe there is some double booking going on on transformers and switchgears because of extra-long lead times. 8. Everyone is trying to reduce PUE, and water use effectiveness, but even after improving, they just use the same power to run more compute. 9. The problem is also liquid cooling, as it is expensive, and water availability in many regions is a problem. 10. Margins on equipment in the sector have gone from 4-6%, where they were 2-3 years ago, to 20-23% and in some cases even 40%. The data center builders know the margins are high, but they are fine with it because they just want to get it. found on @AlphaSenseInc

The entire global reset explained in 4 minutes. The system of global trade balances goes through a reset roughly every 2 decades. (1929, 1960, 1980, 2008 and 2026) This is what Iran, trade war and shipping blockades are all about. Either these meetings with China become a Bretton Woods 2.0 or the system violently resets through a deflationary bust. Both plans are being deployed simultaneously, which is why they've created the largest bubble since 1929. Either China plays ball and we get a gradual deflation or it is imposed to intentionally break the system.

$SIVE This is one of the most interesting reads on why the recent phenomenon of “Swedes sell, Americans buy” keeps happening. Great read.

Algorithms Are All You Need! $TIG

It's interesting to scan through MIIT's list of 67 pilot projects for high-tech industrialization to get a sense of what tech China thinks is important: High-End Functional and Intelligent Materials 1. Ultra-high energy-density dielectric materials and devices — Tsinghua University 2. Data-driven design and manufacturing of copper alloys for integrated-circuit lead frames — University of Science and Technology Beijing 3. High-sensitivity entropy-regulated amorphous-alloy stress-impedance strain gauge for seismic resistance and disaster prevention in buildings — Nanjing University of Science and Technology 4. Noble-metal reduction technology for selective hydrogenation — Zhejiang University 5. Complete preparation technology for liquid-cooling thermal-management materials — Juhua Group 6. Single-phase immersion liquid-cooling solution for data centers — Juhua Group 7. 450 km/h high-speed train traction motor integrating new electromagnetic materials — National High-Speed Train Qingdao Technology Innovation Center 8. Aviation fuel coalescence-separation device — South China University of Technology 9. Inorganic two-dimensional material membranes for efficient hydrogen separation — South China University of Technology Advanced Structural and Composite Materials 10. Preparation technology for sound-absorbing honeycomb and composite materials — China Aviation Manufacturing Technology Research Institute 11. Wear-resistant, fatigue-resistant, corrosion-resistant rails and frogs for the Sichuan–Tibet Railway — China Academy of Railway Sciences Corporation 12. Long-term performance-retention technologies for structural concrete in complex environments on the Sichuan–Tibet Railway — China Academy of Railway Sciences Corporation 13. High-performance shotcrete technology for complex environments on the Sichuan–Tibet Railway — China Academy of Railway Sciences Corporation 14. Crack-resistance improvement technologies for structural concrete in complex environments on the Sichuan–Tibet Railway — China Academy of Railway Sciences Corporation 15. Powder-making technology and applications for recycling coarse high-temperature alloy powder — AECC Beijing Institute of Aeronautical Materials 16. Large-tonnage carbon-fiber composite cables — University of Science and Technology Beijing 17. Multi-layer gradient cold-spray repair and nano-hard reinforcement composite plating for continuous-casting molds — Ansteel Group Beijing Research Institute 18. Key technologies and application development for ultra-high-stiffness magnesium-matrix composites — Harbin Institute of Technology New Displays and Strategic Electronic Materials 19. Sub-6GHz GaN radio-frequency devices — CETC 13th Research Institute 20. High-frequency, high-power laser modulator technology — Fujian Institute of Research on the Structure of Matter, Chinese Academy of Sciences Rare-Earth New Materials 21. Preparation technology for high-temperature-resistant cobalt-based permanent magnet materials — China Jiliang University 22. Heavy-rare-earth-free high-coercivity sintered NdFeB technology — Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences High-Performance Manufacturing Technologies and Major Equipment 23. 6-inch semi-insulating SiC crystal-growth furnace and 6/8-inch compatible SiC epitaxial furnace — NAURA 24. New MOCVD equipment for Micro-LED — Advanced Micro-Fabrication Equipment Inc. China 25. Precision forming technology for large aerospace thin-walled aluminum-alloy integrated cylindrical sections — Shanghai Aerospace Precision Machinery Institute 26. High-temperature-resistant, corrosion-resistant transmission-system bearings — Luoyang Bearing Group 27. High-performance seals for aviation hydraulic systems — Guangzhou Mechanical Engineering Research Institute 28. Key manufacturing technology for ultra-large seamless titanium cathode rollers — Xi’an Taijin New Energy Technology Intelligent Sensors 29. Advanced sensors, core components, and manufacturing processes for spacecraft control systems — Beijing Institute of Control Engineering 30. Flexible intracranial implantable multimodal sensing and modulation system for multiparameter brain monitoring — Aerospace Information Research Institute, Chinese Academy of Sciences 31. Self-powered sensor technologies for human health monitoring — Beijing Institute of Nanoenergy and Nanosystems 32. High-sensitivity MEMS magnetic sensing components and sensors — State Grid Smart Grid Research Institute 33. Miniature high-performance accelerometers — Beijing Aerospace Xinghua Technology 34. Rocket sensors — Long March Rocket Technology 35. New broadband ng-resolution triaxial accelerometer — Tianjin SIASUN Robot & Automation 36. Automotive-grade high-precision integrated navigation sensors — Hebei Meitai Electronic Technology 37. Series of sensors for deep-sea environmental observation and resource exploration — Shenyang Institute of Automation, Chinese Academy of Sciences 38. Multi-parameter differential-pressure flowmeter — Shenyang Zhongke Bowei Technology 39. Quantitative sensing-interface model and analytical instrument technology based on resonant cantilever beams — Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences 40. High-performance X-ray sensors — iRay Technology 41. Electromagnetic sensors — Xinlian Superconductor Shanghai 42. Thin-film getter structure with a micro-heater and its manufacturing method — Shanghai New Micro Technology R&D Center 43. High-performance acoustic sensing elements and sensors — Wuxi Weigan Semiconductor 44. New high-performance MEMS gas sensors — Suzhou Huiwen Nanotechnology 45. MEMS sensor mass-manufacturing platform — XINLIAN Integrated Circuit Manufacturing 46. Development and application of diamond quantum magnetic sensors — University of Science and Technology of China 47. In-situ continuous temperature sensors and measurement systems for molten steel — Maanshan Iron & Steel 48. High-performance laser gas-sensing components — Shandong Science & Technology Innovation Group 49. Key technologies and applications for biosensor sensitive elements — Shandong Kanghua Biomedical Technology 50. Wireless passive temperature sensors based on polymer-derived ceramic metamaterials — Zhengzhou University 51. High-precision printing technology and equipment for ultrafine fiber surfaces — Huazhong University of Science and Technology 52. Complete sensor set for high-speed rail vehicle health-monitoring systems — CRRC Zhuzhou Institute 53. Industrializable mass-producible automotive-grade solid-state LiDAR for autonomous driving — RoboSense 54. Sensing-computing integrated room-temperature infrared imaging detection technology — Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences 55. Nanometer-precision displacement-measurement grating sensors — Xi’an Jiaotong University 56. Distributed thin-film sensors for highway infrastructure — AVIC Electromechanical Measurement Instrument Xi’an Industrial Software 57. Core components of an industrial internet operating system for discrete industries — Beijing Institute of Technology 58. Data-driven closed-loop performance analysis, regulation, and optimization technology and software for manufacturing processes — University of Science and Technology Beijing 59. Intelligent analysis and decision-making system for full-process industrial data in discrete manufacturing — Beihang University 60. Distributed time-series data management system Apache IoTDB — Tsinghua University 61. MEC-based edge control and real-time simulation theories and methods — Shenyang Institute of Automation, Chinese Academy of Sciences 62. Cloud-based service-oriented MES and intelligent management-control platform system — Beijing Xiaomi Mobile Software 63. Domestic isogeometric-analysis software ADIGA — Dalian University of Technology 64. Distributed factory industrial interconnection platform — Shanghai Aircraft Manufacturing 65. Industrial interconnection platform for personalized customization industries — Guangzhou MINO Equipment 66. End-edge-cloud interconnection integration technology and system for OT/IT convergence — Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences 67. Industrial interconnection platform for large-scale manufacturing industries — Gree Electric Appliances of Zhuhai

Japan dumping ~$30B of U.S. Treasuries in Q1 is one more confirmation of the reserve-selling theory. Energy-import dependent nations are being forced into a liquidity squeeze: Oil rises → dollars are needed for purchases → local currency comes under pressure → reserves are sold to defend liquidity and slow currency depreciation. This is also why gold is seeing selling pressure in the short term. But because during dollar-liquidity stress, everything liquid gets sold first, Treasuries, gold, FX reserves. The irony is this: The same stress that pressures gold temporarily is also building the foundation for its next major upside. Once the liquidity stress eases, and once oil trade slowly diversifies away from the petrodollar system, gold becomes the biggest beneficiary. Reserve selling is the stress signal. Gold is the endgame asset.

@fhtabd Excellent! $TIG

Still don't understand why $TIG is the next big deal after $BTC & $ETH Bezos: $16B Recursive: $650M seed. $4.65B valuation Isomorphic: $600M Sakana AI: $379M DeepMind: $1.53B All of this, to build something like the part in the red circle TIG is the whole diagram. And is works

24 stocks have returned 100x or more over the last 15 years across the US and Europe. The top of the list isn't Netflix or Nvidia. It's XPEL, a Texas company that makes protective films for cars. +118,100%. Second place: Patrick Industries. Mobile homes and RV parts. +65,325%. Most of the list looks like that. Boring industries. Companies most people have never heard of. Founders quietly compounding without making the news. 100-baggers rarely look like 100-baggers when you find them. They look like dull little companies that happen to do their work very well, for a very long time.

how to master stablecoins: - ask why stablecoins exist: crypto's problem of volatile price - use the majors first: USDC, USDT, DAI - send, swap, bridge, offramp - ask yourself how each one stays at $1, wonder - learn the three main types: fiat-backed (USDC, USDT), crypto-backed (DAI, LUSD), algorithmic (and why most failed) - study attestations vs audits, read Circle's monthly reserve reports, Tether's quarterly ones - learn what "depeg" means and look at historical depegs (UST, USDR, circle's SVB writeup, etc) - understand peg mechanisms: PSMs, redemption arbitrage, AMM curves designed for stables (curve, uni v3 tight ranges) - farm stables on curve, ethena, pendle, aave, morpho, sky - compare risk adjusted yields - research newer designs: ethena (USDe, delta neutral), sky/maker (USDS, DSR), frax, crvUSD, GHO - understand RWA-backed stables and treasury bill yield (ondo, mountain, sky) - learn redemption mechanics - who can actually redeem at $1, at what size, AND at what fees - study stablecoin flows onchain: dune, defillama, @stablewatchHQ - stablecoins as payment rails. onramps, offramps, FX spreads, AML/KYC, total costs (it's not 0.01$, rather 2-3$). fxcintelligence and moonpay have good primers - explore non-USD stables: EURC, BRLA, XSGD, JPYC. and what corridors they unlock - who makes money on stablecoins: issuers earn float, apps fight for distribution, chains barely capture transfer fees. read @jonah_b series at blockchain capital - understand regulatory risk: GENIUS act, MiCA: why issuers can freeze addresses, how, in what cases - ask smart people or LLMs hard questions about reserve composition, redemption rights etc if you have questions or need reading recommendations, ask me :)

Another legendary Li Ka-Shing exit. He sold his China equities in 2015. People laughed and said he was missing out bigly on the China boom. The Shanghai Composite peaked at 5000+ that year. Today, 11 years later, it sits at 4000+. Still below where he sold. No wonder they call him the Superman. My question is, his latest 2026 exit - is he short UK/EU, short telco, or just short global economy?

1989'da dünyanın en değerli 10 şirketinin 8'i Japondu. Bugün ABD'nin bir şirketi Japonya'nın en değerli 10 şirketinin toplamından büyük. NVIDIA'nın değeri 5 trilyon doları geçti. Sadece NVIDIA, Japonya'nın en değerli 10 şirketinin toplamından büyük. 35 yıl önce tablo tam tersineydi. Dünyanın en değerli 10 şirketinin 8'i Japondu. NTT tek başına ABD'nin en değerli 10 şirketinin toplamından daha büyüktü. O dönem herkes aynı şeyi söylüyordu. "Böyle giderse Japonya 21. yüzyılı teknoloji ve finans alanında yönetecek." Öyle olmadı. 35 yıl sonra Japonya 5. büyük ekonomi olma yolunda. NTT top 100'e zar zor giriyor. Peki Japonya bu noktaya nasıl düştü? Dikkatli okuyun. O dönem bugünkü Çin'in yerinde Japonya vardı. 1979'da Amerikalı sosyolog Ezra Vogel bir kitap yayınladı. Kitabın adı "Japan as Number One." Amerikan iş dünyasının zorunlu okuması oldu. Mesaj netti: Japonya zirvede, ABD geride kalıyor. 1980'de Japonya, ABD'yi geride bırakarak dünyanın en büyük otomobil üreticisi oldu. Toyota, Honda, Nissan Amerikan pazarını ele geçiriyordu. Daha az yakıyor, daha az arızalanıyor, daha ucuza geliyordu. Detroit çöküşteydi. Chrysler 1979'da iflasın eşiğine geldi, hükümet kurtarma paketiyle ayakta kaldı. Reagan yönetimi Japonya'ya ihracat kısıtlamasını kabul ettirdi. Japonya geri adım atmadı. Fabrikalarını ABD topraklarına taşıdı. Honda 1982'de Ohio'da, Nissan 1983'te Tennessee'de üretime başladı. Yine de ABD toparlanamadı. Amerikan halkının evindeki neredeyse her ekran Japon markasıydı. Eski Amerikan devleri tek tek silindi. RCA, Zenith, Magnavox pazardan çekildi. Yerlerini Sony, Panasonic, JVC, Sharp, Toshiba aldı. 1986'da Japonya küresel yarı iletken pazarının %50'sini ele geçirmişti. ABD %37'ye düşmüştü. DRAM bellek üretiminde Toshiba, NEC, Hitachi dünyayı yönetiyordu. Silikon Vadisi'nin pek çok şirketi bu işten çekilmek zorunda kaldı. 1989'da dünyanın en büyük 10 bankasının 9'u Japondu. Dai-Ichi Kangyo, Sumitomo, Fuji, Mitsubishi, Industrial Bank of Japan. Hepsi Wall Street devlerini geride bırakmıştı. Bu tablo ABD için bir tehditti. Japonya teknolojide önde. Üretimde önde. Finansta önde. ABD'nin yarım yüzyıllık hegemonyasına meydan okuyordu. Reagan yönetimi bir karar verdi: Japonya'nın hızını kesmek gerekiyordu. Yöntem belliydi. Japon ürünlerini pahalandırmak. Bunu yapmanın yolu döviz kurundan geçiyordu. Tarih 5 Eylül 1985. Plaza Anlaşması Beş ülkenin maliye bakanları aynı masada. ABD, Japonya, Almanya, Fransa, İngiltere. Reagan yönetiminin teklifi tek cümleydi. "Doları zayıflatın. Yen güçlensin. Yoksa Japonya'ya %50 gümrük vergisi koyarız." Japonya kabul etti. Bu kararla geleceğini imzaladı. Yen rallisi başladı 5 merkez bankası aynı anda dolar sattı. 3 yıl içinde yen değerinin iki katına çıktı. Japon ürünleri dünya piyasasında pahalandı. Tüketici Toyota yerine Volkswagen'i tercih etti. Walkman yerine başka markaya yöneldi. 1985'te 175 milyar dolar olan Japon ihracatı, 1988'de 100 milyar dolara düştü. Ekonominin büyüme motoru durdu. Japon Merkez Bankası paniğe kapıldı Faiz düşürmeye başladı. %5'ten %2.5'a. Sonra %0.5'a. Trilyonlarca yen piyasaya akıttı. Niyet basitti: ucuz parayla ekonomiyi yeniden canlandırmak. Ama bu para fabrikalara gitmedi. Yeni teknolojiye gitmedi. Borsaya gitti. Gayrimenkule gitti. Bir balon doğdu Nikkei 13.000'den 38.916'ya çıktı. 4 yılda üç katına. Tokyo'da bir metrekare gayrimenkul 1.5 milyon dolara satılıyordu. Japonya'nın toplam gayrimenkul değeri ABD'nin 4 katına ulaştı. Japon şirketleri Amerika'nın simgelerini satın almaya başladı. Mitsubishi Rockefeller Center'ı 850 milyon dolara, Sony Columbia Pictures'ı 3.4 milyar dolara aldı. Amerikan medyası tek bir şey yazıyordu. "Japonya Amerika'yı satın alıyor." Sonra balon çöktü Nikkei 38.916'dan inişe geçti. 30 binin altına. 20 binin altına. 10 binin altına. Tek bir piyasa düşüşü değildi. Bir geleceğin sönüşüydü. Asıl yıkım fiyat çöküşü değil, sonrasıydı. Japon bankaları batık şirketlerine kredi vermeye devam etti. Mantık şuydu: kapatırsak büyük bir işsizlik dalgası gelir, sosyal kriz çıkar. İflas etmesi gerekenler ayakta kaldı. Verim düştü. Yeni şirketlere para akmadı. Bunlara "zombi şirketler" denildi. Japonya'nın doğum oranı düştü. 2 çocuğun altına indi. Sonra 1.5'a. Sonra 1.3'e. Genç nüfus eridi. Çalışma yaşındaki insan sayısı geriledi. Yaşlı bir toplum daha az risk alır. Daha az tüketir. Daha az girişim yapar. Üretim Japonya'da maliyetli hale geldi. Toyota Tayland'a gitti. Honda Çin'e gitti. Sony Malezya'ya gitti. Panasonic Vietnam'a gitti. "Made in Japan" damgası eridi. Yerine "Made in China" geldi. Japonya'nın 80 yıllık üretim kimliği, 20 yılda dağıldı. Üretim Japonya'dan çıkarken faiz sıfırda kalmıştı. Yen dünyanın en ucuz parası oldu. Yabancı yatırımcı bu boşluğu hemen doldurdu. Tokyo'da sıfır faizle borçlanıyor, dolara çeviriyor, Amerikan hisselerinde çalıştırıyordu. Aradaki farkı cebine atıyordu. Benzin pompasını düşünün. Japonya parayı pompaladı, dünyanın geri kalanı bu yakıtla büyüdü. Tokyo'daki yatırımcı ülkesinde sıfır faiz gördü. Wall Street'teki yatırımcı Japonya'nın parasıyla zenginleşti. 35 yıl sonra Japonya nerede 1989'da dünyanın 2. büyük ekonomisiydi. 2024'te 4'üncü. Analistler 2026 için 5'inci olacağını söylüyor. NTT bir zamanlar dünyanın en büyük şirketiydi. Bugün top 100'e zar zor giriyor. Bir ülke yarım yüzyılda zirveden orta sıralara çekildi. Ne bir savaşla. Ne bir darbeyle. Ne bir doğal afetle. Sadece bir imzayla. Henry Kissinger ne demişti "Amerika'nın düşmanı olmak tehlikeli olabilir. Ama dostu olmak ölümcüldür." Bu söz Japonya için yazılmış gibidir.