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🚨 THIS IS WHY BITCOIN KEEPS CRASHING BELOW $67,000 If you still think Bitcoin trades like an asset whose price is determined purely by spot supply and demand, you need to read this carefully. Because that market no longer exists. What you’re watching right now is NOT normal price action. This isn’t just an AI stock sell-off. This isn’t just hotter inflation. And this definitely isn’t retail suddenly deciding to dump Bitcoin at the exact same time. Most people have no idea what is actually happening. And by the time it becomes obvious, the damage is usually already done. This didn’t start today. It has been building underneath Bitcoin for YEARS. And now it’s accelerating. Here’s the truth: Bitcoin still has a hard cap of 21 MILLION coins. But Wall Street can create almost unlimited financial EXPOSURE around those coins. That distinction changes everything. Because once derivatives dominate short-term price discovery... Bitcoin stops trading purely on who wants to own the actual coins. It starts trading on: 1) LEVERAGE. 2) HEDGING. 3) MARGIN. 4) LIQUIDATIONS. 5) FORCED SELLING. And that is exactly what is happening right now. It’s the same mechanism that repeatedly drives violent moves in: → Gold → Silver → Oil → Stocks Once derivatives become large enough, spot buyers are no longer the only force setting the price. And this is the part almost nobody understands: Bitcoin’s scarcity didn’t disappear. But scarcity alone no longer controls the SCREEN PRICE. Wall Street built an entire financial layer on top of Bitcoin: → Cash-settled futures → Perpetual contracts → Options → ETFs → Broker lending → Swaps → Wrapped BTC The 21 million cap controls the COINS. It does NOT cap the amount of leveraged exposure that can be created around them. And once that leverage starts unwinding... The market doesn’t care what the long-term thesis is. It SELLS. Look at what just happened: Over $1.9 BILLION in leveraged crypto positions wiped out in 24 hours. More than $1.1 BILLION liquidated in Bitcoin alone. Spot Bitcoin ETFs have already seen roughly $1.9 BILLION in outflows this month. Once leveraged selling overwhelms real buyers, price stops responding only to long-term demand. It starts responding to positions. Hedging. Margin calls. And cascading liquidations. Wall Street does not need to own millions of physical Bitcoin to push the market around. It only needs enough derivatives exposure and enough leverage sitting in the wrong place. The playbook is brutally simple: 1st: Build enormous leveraged exposur 2nd: Push price through obvious liquidity 3rd: Trigger stops and liquidations 4th: Forced selling pushes price even lower 5th: Buy back into the panic 6th: Repeat THIS is why Bitcoin can lose thousands of dollars while the number of coins on-chain barely changes. The coins didn’t suddenly disappear. The PRICE DISCOVERY mechanism changed. That’s what people are missing. Bitcoin is still scarce. But the financial claims built around Bitcoin are NOT. And when leverage controls the marginal trade... 21 million coins can behave like a market with FAR more supply than 21 million coins. That’s not the Bitcoin market retail thinks it is trading. That’s a WALL STREET PRICING SYSTEM built on top of Bitcoin. You can choose to ignore it. But don’t pretend nobody warned you. Bitcoin is now trading around $66,600, its lowest level since August and roughly 48% below the $126,200 high. If $65k breaks, the next level I’m watching is $62k. Reminder: I called the Bitcoin top at $126,000 and told you to start buying again around $60,000. The next call will matter even more. When I EXIT the markets completely, I’ll post it here publicly like I always do. Turn notifications on. If you’re not following yet, you’ll understand why that was a mistake later.

BREAKING: SpaceXSI completes MiniHard construction in just ~5 months, with Gun Range targeting a ~4-month build. According to SemiAnalysis, SpaceXSI is roughly halving construction timelines while most comparable projects face 8–12 month builds. • MiniHard: Construction finished in approximately 5 months. • Gun Range: The new site just south of the Tennessee–Mississippi state line is targeting approximately 4 months of construction. • Colossus 1: Its first retrofit delivered 150 MW of capacity in 122 days. • Colossus 2: A subsequent retrofit delivered 210 MW in just 91 days. • Project SPAM: Work started October 5, with the first capacity targeted for December. • Massive expansion: SemiAnalysis projects the Memphis–Mississippi campus will grow from 0.4 GW of IT capacity in January to 2.4 GW by the end of 2026. That would be a sixfold increase in one year. • Five major projects: The expansion spans Macrohard, MiniHard, Macroharder, Project SPAM and Gun Range. • Tesla powering the scale: SemiAnalysis reports 1,377 Tesla Megapacks across Colossus 2, providing nearly 6 GWh of battery storage. The construction timelines and capacity forecasts are SemiAnalysis estimates, with future milestones still targets. Elon Musk’s teams are bringing extraordinary speed and scale to the infrastructure powering AI.

Ever seen cherries labelled "J," "JJ" or "JJJ" in a Chinese supermarket? Here's what it means. In China, imported sweet cherries are called "che li zi," a transliteration of the English word "cherries." They're sold by size grade, and the number of J's tells you the diameter. Based on common labels on Chinese e-commerce platforms:
 J: about 26 to 28 mm
JJ: about 28 to 30 mm
JJJ: about 30 to 32 mm
4J: about 32 to 34 mm Each extra J adds roughly 2 mm, and can add quite a bit to the price. Right now is Chilean cherry season in China. Chile's summer is China's winter, so the first air shipments arrive in late October, with peak supply in December and January, just in time for New Year and Lunar New Year gifting. China is Chile's biggest cherry customer by far: according to 21st Century Business Herald, China has bought more than 90% of Chile's cherry exports for seven years in a row. Does anywhere near you grade fruit by size like this? 
#cherries# #Chile# #agriculture# In-depth reports at

In December 2015, during my first year at Stanford GSB, I chose to intern at a top hedge fund. Researching advanced driver assistance systems (ADAS) and autonomous driving, I saw a new growth opportunity for GPUs beyond gaming. The only stock I pitched during my internship was NVDA—then worth roughly $18 billion, trading around $0.80 a share, split-adjusted. The fund took a large position (and still hold today), and I bought some too. I didn’t hold it all the way to its peak, but I’m grateful of the returns from the investment. @JensenHuang has created tremendous value for shareholders. Pushing him out is a mistake. After 33 years building NVIDIA, his leadership is still central to its future. NVIDIA and the broader AI developer community still need his leadership and spirit of innovation. (Back then no AI to help on stock research, have to learn those terminologies in this old fashion…😂) Look at the impact Jensen has created to the world, unbelievable. Still can’t believe what just happened. We need a prediction market on this: when will Jensen be back?

Everyone believes CUDA is NVIDIA's moat, the reason we've maintained our dominance in the AI era. I've never believed that. NVIDIA has only one true moat: its people. And the most important of them is Jensen Huang. I've worked on CUDA compilers, libraries, and DSLs for eight years, from Volta to Rubin. I think I've earned the right to share my perspective on what NVIDIA's moat really is. I hope you'll bear with me. 1. What is CUDA? Many people think CUDA is just a programming language and its compiler, and that NVIDIA's moat comes from the massive amount of software written in CUDA, making it impossible for developers to leave NVIDIA GPUs. This is completely wrong. It's an incredibly naive understanding of CUDA. To me, CUDA is everything NVIDIA does. CUDA isn't just a language, software, or hardware architecture. It's a product defined by a unique customer experience. When you find GPU programming too difficult, CUDA gives you an easier way. When your GPU code isn't fast enough, NVIDIA engineers respond and help you solve it. When a handful of GPUs can no longer push your technology forward, NVIDIA has already scaled its computing platform from desktops to massive data centers. When you need more data centers than anyone else can supply, NVIDIA has already secured wafer and HBM capacity years in advance to meet your demand. That experience is CUDA. It's made possible by the relentless, day-to-day work of everyone at NVIDIA. And the person who brings all these people together, who gives them a shared vision and purpose, is Jensen Huang. 2. What made CUDA possible? Patience. Perseverance. An unwavering commitment to a vision. Around 2006, NVIDIA bet that the future would demand far more computing power, and began transforming GPUs from graphics processors into a platform for general-purpose computing. Initially, it was a commercial disaster. The added costs hurt margins, the market wasn't ready, and the strategy faced enormous skepticism and pressure, including questions from the board. But Jensen persisted. For roughly a decade, NVIDIA kept investing in CUDA, building its hardware, software, and developer ecosystem long before the commercial payoff became clear. Eventually, deep learning arrived. And NVIDIA was ready. Today, this sounds like an inspiring story. But for those who lived through it, it meant a decade of perseverance, doubt, and being misunderstood. Looking back at the history of technology, how many people could have done the same? This is what I've always loved most about NVIDIA. And now, Jensen has been pushed out. This won't kill NVIDIA. The company can still create tremendous commercial value. But it has killed NVIDIA's soul. And how far can a body go without its soul? If this is how Jensen Huang is treated today, how will those of us who built CUDA be treated tomorrow? I love NVIDIA deeply, but I have to say it: NVIDIA is dead.

BREAKING: Huang and his wife Lori jointly own about 800 million Nvidia, $NVDA, shares worth roughly $135 billion through a complex web of trusts and LLCs, according to SEC filings. Jensen Huang directly owns about 70 million shares valued at about $12 billion.

Her name is Kimberly Powell. She is 48 this year and joined Nvidia in 2008. > November 8, 2026. Jensen Huang sends a letter to every Nvidia employee. > “I was unfaithful to my wife. My actions hurt her and our children. There is no excuse for what I did. I am deeply sorry.” > The affair was with Alice Huang, a Chinese businesswoman suspected by US intelligence of being a spy. > The board opens an investigation. > The FBI is involved. > Nvidia’s stock falls. > Then, three days later, the story gets worse. > November 11, 2026. The New York Times publishes a second report. > Jensen Huang had another affair. > A second woman. > A subordinate. > Someone who reports directly to him. > Her name is Kimberly Powell. > Vice president of healthcare at Nvidia. > Joined the company in 2008. > Promoted to senior director in 2016. > Vice president by the end of 2017. > Eighteen years at Nvidia. > One of Huang’s roughly sixty direct reports. > She is 48. He is 63. > Both are married. > March 2026. Nvidia’s GTC conference in San Jose. > Powell presents on AI and healthcare. > Her slides use animated images of Huang. > Then executives gather at a nearby hotel. > Huang and Powell are seen together. > Affectionate. Intimate. > A witness records it on their phone. > Huang’s security team spots the witness. > Escorts them away. > Asks them to sign a confidentiality agreement. > The video still exists. > Five former Nvidia employees confirm the relationship was discussed inside the company. > Nvidia’s code of conduct has a rule. > Personal relationships can create conflicts of interest. > The company says it promptly investigates reports of misconduct. > The CEO wrote the letter that begins the code. > He is now the subject of the investigation. > November 12, 2026. The board prepares to meet. > The Wall Street Journal reports the board could determine his future as soon as that day. > The board is preparing to oust the CEO who built the most valuable chip company on Earth. > Nvidia’s stock sinks more than 7% after hours. > Huang, Powell, and Nvidia have all declined to comment. > None of the allegations have been confirmed by any of them. > The first affair cost him his reputation. > The second affair may cost him his company. > He admitted one. He has said nothing about the other. > The board is meeting. > The investigation is expanding. > The man who kept his promise to Lori Mills is running out of promises to keep. He built the most powerful company in the history of computing. He admitted to one affair. Then a second woman’s name surfaced. The board is deciding whether he still runs the company he founded. His name is Jensen Huang. He is 63 years old. And for the first time in his life, the next move is not his to make.

@TheFlintFace @IterIntellectus 100GW in space is roughly equal to 800GW on Earth. Moreover, solar on Earth must be paired with massive batteries to continue powering compute at night and supplemented with combustion or nuclear power during winter. These are not the same at all.

Huge AI announcements from OpenAI, Anthropic, Meta, and Google in the past 48 hours. Here's everything going on in AI right now: 1. The authors of AI 2027 just moved their timelines up. They now expect AI on par with the best human AI researchers to arrive in 2027, after METR estimated Anthropic is improving about 2x as fast thanks to AI. Daniel Kokotajlo gives it a 50-50 chance by May 2027 and says he's "scared, sad, and angry." 2. Anthropic opened the investor pitch for its IPO, with shares likely trading as soon as Thursday next week. An updated filing also says it has now crossed its own safety line for AI-driven progress. 3. OpenAI launched Businesses in ChatGPT, a beta hub where brands can set up AI agents for shoppers, claim a verified profile, and track how often ChatGPT mentions them. Paid ads can point users to those agents too. This is like the start of SEO for chatbots. 4. Anthropic rolled out Claude Sheets and Whiteboards in beta, made Claude Data generally available, and announced Claude Meetings, an assistant that sits in on your video calls. Add those to Slides, Design, and Docs. Seems like Claude is slowly rebuilding the entire office suite. 5. Anthropic also released Claude Fable 5.2 and Mythos 5.2 yesterday, with Fable debuting at #1# on Artificial Analysis' Intelligence Index, 5 points ahead of Google's Gemini 4 Carbon. It's also 20% cheaper and up to 30% faster than 5.1. Google lost the top spot before Carbon even shipped (!) 6. Meta released Muse Ember, its smallest model, built for high-volume agent work. It ties Claude Haiku 5.5 on the Intelligence Index at roughly one-third of the cost per task ($0.14 vs. $0.41 on an average test). Meta shipped its first Muse model in April and now has an answer for every tier OpenAI and Anthropic sell. 7. Google announced 2 new AI chips coming next year: the TPU 8tx, which keeps data encrypted even while a model is working on it, and the 8i Max, which joins 2 chips into one for agents that need to hold an entire codebase in view. Google already has nearly 100 TPU customers (including Anthropic and Apple) and every available chip is spoken for. 8. Nvidia's top lawyer reportedly emailed agents in August 2025 while they were investigating whether Singapore's Megaspeed smuggled its chips to China. The Commerce Department then halted the case and handed it to the Justice Department. Not a great week for Nvidia. 9. Adobe signed a multi-year deal with Disney to build custom AI models trained on Disney's characters and visual styles, with work already underway for theme parks, film, and ESPN. Pretty interesting to see one of the most protective IP owners in entertainment is now training its own AI models. 10. OpenAI acquired Odessia, a months-old AI trip-planning startup from Sonder founder Francis Davidson, who is joining OpenAI to work on travel. Between this and #3#, ChatGPT is coming for shopping and travel. 11. France unveiled the Paris Call for AI Safety and Security, with OpenAI, Anthropic, and Mistral committing to build emergency off switches into their most advanced models. Interesting timing given #1# on this list. Daily reminder that this is the worst AI will ever be.

🧠Forum, Meta’s new standalone Groups app, was built by a small team that brought an AI agent into the development cycle as a participant — planning, building, testing, and verifying. Building Forum we moved from human-in-the-loop — engineer drives, AI assists inside each step — to human-on-the-loop, where the agent runs the iteration (plan, implement, build, test, correct, repeat) and the engineer sets the goal, watches the run, and owns the outcome. The key decision: success wasn’t measured in code volume. It was measured in changes that build, pass tests, and survive review. ✅ Reached core feature parity with Facebook Groups in eight weeks 📈 An autonomous stress-testing loop caught a memory issue during development, roughly halving memory use and page faults 🔗 Read how our engineers went AI-native to build Forum: #AI# #SoftwareEngineering# #DeveloperTools# #MobileEngineering# #Engineering#