T-Rex

🚨🚨Tense moment on Piers Morgan Uncensored: "All you want is all the Palestinians gone... you don't care how many die in the process, do you?" Piers Morgan relentlessly grills Daniella Weiss the ‘Godmother’ of the Israeli settler movement over the deaths of thousands of Palestinian children and the vision for the land. Unfiltered. Uncomfortable. Must-watch. What do you think, straight talk or too far?

I promise this will be the best 20 min you spend today! Robotics: Endgame, the sequel to my last year's Sequoia AI Ascent talk, "Physical Turing Test". I laid out the roadmap for solving Physical AGI as a simple parallel to the LLM success story. Be a good scientist, copy homework ;) And stay till the end, more easter eggs and predictions for your polymarket! 00:30 DGX-1 origin story at OpenAI, I was there in 2016 signing with Jensen and Elon. Heading to the Computer History Museum! 01:42 The Great Parallel 03:31 Robotics, the Endgame 03:39 Why VLAs fall short 04:32 Video world models as the 2nd pretraining paradigm 06:09 World Action Models (WAM) 07:46 Strategies for robot data collection and the FSD equivalent to physical data flywheel for robot manipulation 11:06 EgoScale and the Dexterity Scaling Law we discovered recently 14:00 Physical RL: bridging the last mile 15:39 DreamDojo: an end-to-end neural physics engine for scaling RL in silico 17:00 Civilizational Technology Tree and my predictions for the near future. Spoiler: it's closer than you think. Thanks to my friends at Sequoia for inviting me back to AI Ascent this year! I had a blast! Last year's talk is attached in the thread if you missed it.

The 9/21EMA crossback continues to be one of my favorite areas for momentum returning to a leader. You just needed to recognize the character change and catch a piece of the trend. +50% on the underlying in 12 trading sessions, right off the 9/21EMA crossback. Chart: $MU.

@userofintellect @EzPzTrading epic move again 🙌🤝

EZPZ members will soon have access to two powerful new features: 1) AI-powered portfolio analysis Connect your portfolio directly, or upload positions via csv (fictional or real), or add them manually. EZPZ will function like a professional financial advisor, but powered by real market data, EZPZ analytics, options flow, positioning, and market structure. This will include equity swing score and investment score allowing members to take action. 2) Trade journaling Members will now be able to journal and track their trades directly within EZPZ. This will help traders review performance, identify strengths and weaknesses, and improve consistency over time. We are also building an AI layer into the journaling system to help members analyze behavior, recognize patterns, and improve decision-making with data-driven feedback. This will find the flaws in your trading and will expose them to you.

최소 2030년까지 돌고도는 AI 병목정리 L0 ㅡ Permitting + 숙련 노동 돈·자원 다 있어도 인력·허가 없으면 무의미 $PWR, $MTZ, $STRL, EME L1a ㅡ 변압기·Switchgear 2~3년 리드타임, copper 의존 $GEV, $ETN, HUBB L1b ㅡ 구리·전기 메탈L1a의 원재료 + 모든 인프라 공통 인풋 $FCX, $SCCO, TECK L1c ㅡ Cooling (Liquid/Air) 전력 밀도 폭증 → 필수, 전력과 양의 피드백 $VRT, $MOD, $ETN, $FIX, $AAON, CLS L2a ㅡ Compute / AI Accelerators & Server CPU (GPU+CPU, 가장 근본적·순환 병목) $NVDA , $AMD, $INTC, $TSM, $AVGO, ARM L2b ㅡ HBM , Memory L2c와 결합돼야 의미, sold out 2026 $MU, $SNDK, $WDC, $LRCX, $RMBS, AMKR L2c ㅡ CoWoS 패키징 / 반도체 backend의 진짜 좁은 파이프 $TSM, $AMKR, ASX L2.5 ㅡ Neo Cloud/AI 인프라 $IREN, $NBIS, $CRWV, $CIFR, APLD L3 ㅡ On-site Power 발전 그리드 우회, 즉시성 측면 강력 $BE, $CEG, $VST, GEV L3.5 ㅡ SMR / 차세대 원전 2030년 이후 게임체인저, 지금은 기대감 $OKLO, $SMR, BWXT L4 ㅡ Photonics / Optical Interconnect Cluster scale-out 필수, 전력 절감 효과 $LITE, $COHR, $CRDO, $AAOI, $LWLG, $AEHR, MRVL L5 ㅡ 희토류·영구자석 지정학 리스크 + 로보틱스 본격화 시 폭발 $MP, $USAR, $CRMA, UUUU L6 ㅡ 로보틱스 / 우주 위 모든 것 풀려야 본격적인 스케일 $TSLA, $NVDA, $ISRG, $TER, $SERV, $RKBL, $ASTS, PL 병목이라는게 순차적으로 발생하는게 아니고 진짜 핵심은 병목들이 어떻게 상호작용하는가임 병목은 단순히 "더해지는" 게 아니라 서로 곱해지고, 일부는 음의 피드백, 일부는 양의 피드백을 만듦 1. 직선 의존성 (A가 막히면 B도 막힘) 🔸Permitting → 전력 발전소/송전선 건설 🔸숙련 노동 → 모든 건설 (DC, 변압기 공장, 발전소) 🔸변압기/Switchgear → 전력 전달 → DC 가동 🔸CoWoS → GPU 생산 (HBM, 3nm 웨이퍼 준비돼도 무용지물) 🔸구리 → 변압기, 케이블, 모터 (모든 전력 인프라의 원재료) 여기서 중요한 게 "가장 느린 노드가 전체 속도를 결정"한다는 점임. 지금은 그게 변압기(2~3년 리드타임)와 숙련 전기공임 2. 양의 피드백 루프 (서로를 악화시킴) 이게 흥미로운 부분인데 Loop 1: 전력 ⇄ 냉각 액침/액냉 도입 → 랙당 전력 밀도 ↑ (50kW → 120kW+) 그러면 → 단위면적당 더 많은 전력 필요 → 전력 병목 악화 즉, 냉각 기술 발전이 전력 문제를 풀어주는 게 아니라 더 키우게 됨 ◈VRT가 강한 이유가 이 dual-bind을 둘 다 잡기 때문 Loop 2: 숙련 노동 ⇄ 발전소 건설 전력 부족 → 발전소(가스, 원자력) 더 짓자 근데 발전소 건설에도 똑같은 전기공·용접공 필요 →DC와 발전소가 같은 인력 풀을 두고 경쟁 "데이터센터가 확장되는 동시에 유틸리티, 제조, 재생에너지, 그리드 인프라, 건설이 모두 같은 숙련 인력 풀을 두고 경쟁하고 있고, AI가 이 압력을 증폭" Loop 3: 구리 ⇄ 모든 것 DC 1개당 구리 3~5배 → 구리 가격 ↑ 변압기 가격 ↑ → DC 건설비 ↑ EV·재생에너지·로보틱스도 같은 구리 두고 경쟁 구리는 "공통 인풋"이라 영향력이 가장 광범위 3. 음의 피드백 루프 (자기조정) Loop 4: 가격 → Capex → 완화 (2~3년 시차) HBM/CoWoS sold-out → MU·SK Hynix·TSMC 대규모 capex 전력장비 백로그 → GEV·ETN 증설 단, 시차가 길어서 2027~2028년에야 효과 그 사이에 수요가 더 커지면 따라잡지 못함 Loop 5: Photonics → 전력 절감 광 인터커넥트가 구리 대비 전력 효율 ↑ 클러스터 scale-out에서 전력 부담 일부 경감 LITE·COHR가 실제로 이 효과로 수요 폭발 중 4. 우회 루트 Off-grid power = 그리드 우회 (가장 핫한 트렌드) BE(Fuel Cell), CEG(원전 PPA), VST(가스+원전), GEV(가스터빈) 이게 왜 지금 폭등하냐면 그리드 인터커넥션 5~7년 대기를 90일~2년으로 단축시킴 하지만 가스터빈 자체도 sold-out, 리드타임 3~5년으로 늘고 있음. 결국 또 다른 병목으로 이동 이런식으로 병목은 순차적으로 하나에만 영향을 미치는게 아니고 동시다발적이며 여러군데로 영향을 미침 이 흐름을 잘 숙지하고 있으면 앞으로 2030년까지는 계속 울궈먹을수 있음

⛽️ The West hasn't felt the full force of the oil shock yet, but the ripple effects are already visible 📉 This chart reveals a critical insight: The oil shock isn't initially felt in prices. It's first felt in the barrels that never reach their destination. 🚢 The Blue Line: Global Oil on Water This represents oil currently being transported by tankers between producers and consumers. When this line suddenly plunges, it indicates a serious disruption to the physical oil supply chain. Simply put, the oil that should be on the water is gone. This is always where the trouble begins for the physical oil market. 🛢 The Red Line: Commercial Crude Oil Inventories in Europe and the Americas Interestingly, this line hasn’t dropped significantly yet. This shows that Western nations are currently relying on existing reserves, alternative routes, and emergency management to delay the main impact. Think of it like a dam where the inlet water has been cut off, but the city doesn't go thirsty immediately because the reservoir is still full. 🧠 The Hidden Danger Many believe a full-blown crisis only occurs when Western gas stations go empty. But the oil market doesn’t work that way. The barrels that aren't on the water today won't be in the storage tanks tomorrow. This delay is what makes the crisis so dangerous. The market may appear normal for a time, but underlying pressure is building. ⚡️ The Domino Effect If the red line (inventories) also begins to fall dramatically, the situation will escalate from a geopolitical concern to a real, tangible shortage. This won’t just impact oil prices. It will cascade through: ⛽️ Gasoline and Diesel Prices 🚛 Transportation Costs 🌾 Food Inflation 🏭 Production Costs 🏦 Central Bank Decisions on Interest Rates The shock is on its way. The data shows it. It's only a matter of time...

@userofintellect weekly 🤩

Futures traders: You need Futures Movers and Shakers. Talk to me. - X subscribers have a link to the indicator under Highlights. - EZPZ members, check Discord under Futures. 🚨Not using this is not an option. Better than CVD.

@SecScottBessent pathetic words. You do not deserve your chair.

While the surviving IRGC Leaders are trapped like drowning rats in a sewage pipe, Iran’s creaking oil industry is starting to shut in production thanks to the U.S. BLOCKADE. Pumping will soon collapse. GASOLINE SHORTAGES IN IRAN NEXT!

@userofintellect oil&gas supply shock> less energy&derivates > less production capacity > smaller markets > lower GDP 🩸

🚨 Personal Take - Macro Trend I am establishing a long-term short position in the market. I do not see a clear path out of the ongoing supply disruptions driven by tariffs and the prolonged Iran conflict, including higher oil prices and shifting shipping routes. On top of that, the disinflationary impact of AI could pressure employment and weaken consumer demand. Economic protectionism and nationalism have often preceded economic downturns and war. The collapse of the Washington Consensus, with nothing clear to replace it, may mark the beginning of a shift from an interconnected world to a more isolated, neo-mercantilist economic system. At this point, the Fed feels less relevant. Its actions may simply reinforce existing trends rather than change them. The “soft landing” will not have a happy ending. In fact, it carries huge risks, especially with a potential AI bubble and unresolved geopolitical tensions. This is my opinion, not investment advice. What is your view?

@stamatoudism @stamatoudlsm_ @chartfanatics @Wordsofrizdom natural educator , full clarity.

linktw.in/MariosCF I gave a mini masterclass on the Parabolic Shorts setup in an episode that just dropped on @chartfanatics & @Wordsofrizdom . If you wanna have an A-Z way of how to trade things like $SMCI, $MSTR, $SLV, etc, I recommend watching the full episode, it's full of nuggets This strategy is a setup that I've used since my early trading days, and it's great both for quick injections of capital into the equity as well as, even more importantly timing your partials if you're already on the long side! Hope you enjoy!

"Only 7 stocks are carrying the market. That's unhealthy. We're due for a correction." Half of FinTwit has posted some version of this in the last two weeks. 22 years. 5,696 trading days. $SPY vs $RSP (equal-weight S&P 500). We measured the 20-day rolling spread between cap-weighted and equal-weighted returns, the concentration signal. When SPY outperforms RSP, mega-caps are leading. When RSP outperforms SPY, the broad market is leading. When mega-caps lead (top 10% concentration), $SPY 20-day forward returns are +1.53% with a 69% win rate. When the broad market leads (bottom 10%), it's +0.53% with a 64% win rate. The difference is +1.00% with a p-value of 0.002. Bootstrap confidence interval excludes zero. Narrow leadership isn't bearish. It's nearly triple the forward return of "healthy breadth." $QQQ loves concentration even more. Top 5% concentration, QQQ 20-day forward: +3.22%, 79% win rate. When mega-caps lead, they keep leading. The drawdown data flips the narrative entirely. Probability of a >5% drawdown in the next 20 days when mega-caps lead (top 10%): 27%. When the broad market leads (bottom 10%): 33%. The "healthy breadth" regime has HIGHER drawdown risk. When equal-weight starts beating cap-weight, it often means mega-caps are rolling over and they drag the index down next. Sustained concentration doesn't weaken the signal. After 21-40 consecutive days of mega-cap leadership, 20-day forward returns are +1.23% with a 74% win rate. Duration makes it stronger, not weaker. Is concentration a crash predictor? Only 3 of 7 major drawdowns (>10%) since 2003 started from a concentrated reading. The other 4 started from normal or broad-led regimes. Concentration alone doesn't predict crashes. What predicts trouble is when concentration BREAKS meaning when mega-caps stop leading and the spread rolls over. Current reading: the SPY vs RSP 20-day spread is +3.39%, the 97.6th percentile. This is extreme concentration. FinTwit is calling it a warning sign. The data says it's the strongest forward return regime in the dataset. The actionable framework: When SPY is outperforming RSP (concentration rising): stay long, favor $QQQ and mega-cap exposure. The momentum is self-reinforcing. 69% win rate at 20 days. When the spread is above the 90th percentile: lean into it. The top 10% regime has the best forward returns and the lowest short-term drawdown risk in the dataset. The warning sign to watch for: when the spread REVERSES meaning when RSP starts outperforming SPY after a period of extreme concentration. That's when mega-cap leadership breaks, and historically that transition carries the highest drawdown risk. We'll flag it when it happens. The danger signal isn't narrow leadership. It's when narrow leadership stops. $SPY $QQQ $RSP $NVDA $MSFT $AAPL $GOOGL $META $AMZN

时不时有人会问我油价的事情。原油不是我的专长，但是我可以拿我的本行化肥举个例子。做多Supply Shock其实是三个不同阶段。 今年从一月末就有要对伊朗动手的信号了。这个时候如果去做原油/化肥，属于提前埋伏，做预期。真的打了就涨，打不了就不涨，属于个人倾向和分析能力的事情，就不多说了。这个是做事件，左侧交易。 但是除了本质的做多事件以外，还分“做多风险溢价”、“做多价格中枢”和“做多边际影响”三种。 做多风险溢价比较好举例子。比如说现在，伊朗封锁海峡，美国也封锁海峡，船就是出不来，没有油就是没有油，海峡是死的。但是每次有利好利空消息出来依旧有涨跌，尽管就算海峡真的开发了，供给恢复也需要几个月；或者说海峡继续关闭对于原油运输量不存在新的减少，但是还是会跌。这种时候的价格变动属于纯粹的风险溢价变化，不属于基本面。所以这种时候要想明白，买卖的是波动。麻烦之处在于风险溢价一旦定价完成之后，如果没有更坏的消息，恐慌是要回吐的。快进快出。 做多价格中枢，是指价格中枢必然上移。要有耐心。有人这次看化肥涨了，就想着去做多食品企业或者农产品企业，不是这么回事。食品价格上涨容易压缩食品企业利润，反而跌。另一头，农民也不是傻的。春耕时间段的化肥是不是提前准备好了、化肥价格上涨是否应对增量需求，农民是不是少种一点玉米多种一点大豆。市场会自行进行调节，在短期内缩减一部分需求，转移一部分渠道，寻找一些替代品，比如从别的国家买原油、使用别的能源或者运输路径，或者减少生产支出。就算是以中期来看，价格上涨依旧不是线性的。如果有信念，那就时间换空间，等待新的价格均衡。 最后一条是做多边际，去吃那个被作为新供应商的产业或者国家。但这个东西的前提是要经过了供需再平衡之后，价格开始钝化了，才去有做的意义。不然就一直等。 这四个阶段策略基本是按照时间分的。事件发生前，事件刚发生，事件发酵，事件结束。预期，恐慌，重构。搞清楚自己做的是哪一段。

I'm going to be brutally honest here I pay almost no attention to news headlines they almost never feature in my market analysis- and if they DO, my outcomes are almost always worse (short thread)

This is how you read the market makers’ hand. 😍 Does that mean #SPX $7000 and $SPY $700 by Friday? No. But the magnetic pull, with no significant negative GEX below those levels, clearly suggests a gamma push is more likely. More importantly the GEX levels formed intraday! (the gradual increase in size) That said, time and again we have seen an invisible hand distort options data or those levels act as call wall. So I never trade with conviction. I follow the market regime. If the market regime is 15-20%+ bullish, then I go long big knowing the gamma presure will intensify. If the market regime is bearish, I trade bearish but smaller and more cautiously, with tight stop losses. That’s it. Learn to time the market’s breath and follow the rhythm... dance with it. If you are tense, you are not riding it, you are drowning. #VIX Checkout the GEX Depth plot: ezpztrading.com/option-chart/o…

@aryanXmahajan board

I replaced my $400K/year strategy team with an AI Executive Board... 7 frontier models. 5 countries. $0.30 per verdict. 34 seconds per decision. → No more shipping copy that one AI rubber-stamped → No more pricing decisions made with zero pushback → No more proposals that felt right but lost the deal → No more positioning gaps you only discover after the client says no Just paste your draft → 7 models argue independently → 1 synthesis verdict delivered. Here's how it works: → Claude (Anthropic) — strategic narrative + positioning → GPT (OpenAI) — structure + persuasion gaps → Gemini (Google) — logic flow + audience framing → DeepSeek — contrarian pressure-testing → Qwen (Alibaba) — market angle + commercial framing → Kimi (Moonshot AI) — risk flags + blind spots → MiniMax — final synthesis + verdict No cross-talk. No model sees the other's answer. One chairman model reads all 7 and delivers the final call. Built for decisions that cost you money if you get them wrong. Runs in your terminal. One command. $0.30. Results from real deployments: → $400K strategy function replaced completely → 34-second average verdict per decision → 7 independent opinions vs 1 AI hallucination → Catches the 1 line that quietly kills your sale Want the complete system? Like + comment "BOARD" + repost, and I'll DM it to you. (must be following)

This isn't Berlin. This isn't Soho. This isn't New York. It's somewhere far more interesting and friendly....it's Tehran. The level of misinformation about the country is staggering. This is what the US is bombing. For Israel.

@propialis skills

Your media buyer does these manually every week. Each one is now a free Claude Code skill 👇 that runs on a CSV export in under 2 minutes 1/ Creative fatigue scanner Tags every ad healthy, warning, or critical based on CTR, frequency, CPC trends. 2/ Wasted spend finder Zero-conversion ads grouped by theme with exact dollar amounts. 3/ CPA spike diagnosis Isolates the cause. Ranks by dollar impact. Fixes the biggest leak first. 4/ Audience overlap detector Maps all ad sets against each other. Flags self-competition. 5/ A/B test analyzer Statistical significance + sample size. Stops you calling winners too early. 6/ Budget reallocation modeler Models CPA at different spend levels using your actual data. 7/ Weekly performance report Exec summary, creative rankings, audience breakdown, action list. Ready to send. 8/ Ad copy generator Brief in, 20+ variations out. Placement specs baked in. 9/ Competitor ad library analyzer Their active ads → grouped by theme → top hooks identified. 10/ Lookalike audience refresher Flags degraded lookalikes. Recommends new seeds and what to retire. All free. All open source: → irinabuht12-oss/marketing-skills → AgriciDaniel/claude-ads → coreyhaines31/marketingskills → mathiaschu/meta-ads-analyzer No API keys. No account access. Just CSV + Claude Pro ($20/mo). The analysis is automated. Your media buyer just presses the buttons. Comment "Skills" and I'll send you the full pack. (must be connected)

@ihtesham2005 why 4?

A professor of engineering who failed math all through school built one of the most popular online courses in history by figuring out exactly why her brain had been working against her the whole time. Her name is Barbara Oakley, and she did not teach herself how to learn until she was in her mid-twenties, after leaving the military with a head full of Russian and almost no useful science knowledge. What she discovered about her own brain eventually became a Coursera course that over 4 million people have taken, and the core insight she teaches has been sitting in neuroscience research for decades waiting for someone to explain it in plain language. Here is the framework that changed how I think about every hard thing I am trying to learn. Your working memory is an octopus sitting in your prefrontal cortex with exactly four arms. Those four arms reach out and grab pieces of information, hold them in place, and manipulate them while you are actively thinking through a problem. Four is the limit. When you try to hold more than four things in conscious awareness at once, the arms start dropping things and everything becomes a scramble which is exactly what you experience as confusion when learning something genuinely difficult. This is not a flaw. It is a design feature. And the entire game of becoming expert at anything is learning how to game this constraint. The mechanism is something neuroscientists call chunking, and it is the most underexplained concept in all of learning. When you practice something enough times that it becomes automatic a guitar chord, a grammatical structure, a mathematical procedure, a debugging pattern in code your brain compresses it into a single neural package stored in long-term memory. That compressed package now fits in just one of your four working memory slots instead of filling all of them. Which means once you have built enough chunks, your octopus can reach down into long-term memory, pull up an entire complex procedure in a single grab, and still have three arms free to work with new information on top of it. This is what expertise actually is. Not raw intelligence. Not natural talent. A library of compressed patterns that can be retrieved quickly and stacked together to solve problems that would overwhelm a beginner whose working memory is still occupied with fundamentals. The finding that Oakley emphasizes most forcefully is the one that sounds backward until you understand the mechanism. People with smaller working memory capacity those who can only hold two or three items at once rather than four are often forced to develop stronger chunking habits earlier and more aggressively than people with larger working memories, because they have no choice. Their constraint becomes their training. Over time, that aggressive chunking practice can produce more robust expertise than a larger working memory that never had to be disciplined in the same way. The most powerful practical implication is this: when you feel completely overwhelmed trying to learn something, that feeling is almost always your four-slot octopus running out of arms. The solution is not to concentrate harder. The solution is to stop, isolate one small piece of the problem, practice it until it compresses into a single chunk, and only then pick up the next piece. You cannot learn everything at once because your brain was never designed to hold everything at once. It was designed to build libraries of compressed knowledge and retrieve them on demand. Every expert you have ever admired is not smarter than you. They just have a bigger library.

@LeronAssist MALWARE!