USD 2,064,847,419 More than $2 billion The estimated total amount forcibly paid under unlawful coordination arrangements involving Israeli, Egyptian, and international entities to bring commercial goods into the Gaza Strip since the onset of the genocide

$10,000 invested 3 days ago: $MRNA: $25,499 $HYPE: $12,149 $MSTR: $12,142 $ETH: $12,064 $BTC: $11,344 $SOFI: $10,067 $SPY: $9,850 $GME: $9,743 $QQQ: $9,712 $ACHR: $9,707 $NVDA: $9,653 $ASTS: $9,403 $RKLB: $9,135 $RGTI: $9,126 $AMD: $9,004 $RDDT: $8,563 $CRWV: $8,451

🚨 BITCOIN HAS DUMPED TO $63K FOR A REASON The market isn't moving randomly. → 1,064 days of bull market. → 364 days of bear market. History will repeat, and Bitcoin will bottom out at ~$50,000 this cycle. Reminder: I publicly called the $17K Bitcoin bottom in 2022 and the $126K top in 2025. The next market call will be posted here first. Follow and turn notifications on. Don't become exit liquidity.

Tesla is still dominating. In the first half of 2026, they secured over 52% of the U.S. EV market. 1. Tesla: 52.3% — 242,100 units sold 2. Chevrolet: 6.1% — 28,267 3. Hyundai: 5.8% — 26,936 4. Cadillac: 4.7% — 21,855 5. Rivian : 4.7% — 21,770 6. Toyota: 4.7% — 21,767 7. Ford: 3.6% — 16,606 8. Kia: 2.7% — 12,627 9. BMW: 2.4% — 10,790 10. Subaru: 2.2% — 10,064 11. Honda: 1.8% — 8,407 12. Lexus: 1.7% — 7,814 13. GMC: 1.4% — 6,645 14. Lucid: 1.1% — 5,208 15. Volvo: 0.9% — 3,964 16. VW: 0.8% — 3,768 17. Mercedes: 0.6% — 3,010 18. Porsche: 0.6% — 2,967 19. Other Brands: 0.6% — 2,596 20. Nissan: 0.4% — 1,774 21. Audi: 0.4% — 1,697 22. Genesis: 0.1% — 560 23. Dodge: 0.1% — 534 24. Jeep: 0.1% — 418 25. Mini: 0.1% — 307 26. Acura: 0.0% — 108 (Data Via Cox Automotive Q2 2026 EV sales)

🚨HOW TO TURN YOUR HOUSE INTO A LEVERAGED SHORT ON THE UNITED STATES GOVERNMENT🚨 The United States is now almost $40 trillion in debt. They are going to print so much money. You know they are. The problem is terminal. So WHAT are YOU going to DO about it? Mortgage the house. Buy STRK. Let fiat debasement attack the debt. Collect dividends while Bitcoin attacks the asset side. Then convert the STRK into MSTR. Let’s actually run the math. Assume you have $300,000 of home equity you can borrow against. Take out a $300,000 second mortgage at 7%. For simplicity, assume interest-only financing. Annual interest expense: $300,000 × 7% = $21,000 Now look at STRK. Current STRK price: $66.92 Fixed annual dividend: $8.00/share Effective yield: 11.95% Put the entire $300,000 into STRK: $300,000 / $66.92 = 4,483 STRK Those 4,483 shares generate: 4,483 × $8 = $35,864/year Your house costs you $21,000/year in interest STRK pays you $35,864/year Difference: +$14,864 PER YEAR You have borrowed dollars at 7% and purchased a dollar-denominated preferred yielding almost 12%. Before Bitcoin does literally anything, the spread is approximately +4.95%. Your mortgage is sitting there quietly getting older in nominal dollars while STRK throws off cash. Now we get to the funny part. My projection takes Bitcoin from: $63,394 → $1,000,000 over 8 years And the assumptions are hilariously conservative for Strategy: 1. ZERO additional Bitcoin purchases. 2. Strategy stays at 842,138 BTC for the entire projection. 3. I also assume ZERO mNAV expansion. MSTR simply remains at approximately 1.064× CEBE mNAV it is at today. Common shares increase from roughly 387.6M → 410.9M as the model absorbs the financing burden. Even with all of that: At $1,000,000 Bitcoin, the model produces: MSTR = $2,134.45 Read that again. Strategy never buys another Bitcoin. The multiple never expands. Bitcoin simply reaches $1 million. MSTR still reaches ~$2,134. Now convert the STRK. At the 0.1 MSTR share per STRK conversion ratio: 4,483 STRK → 448.3 MSTR shares At the projected MSTR price of $2,134.45: 448.3 × $2,134.45 = $956,868 Your original $300,000 STRK position has effectively become $956,868 OF MSTR. But you also spent 8 years collecting the spread. Annual excess STRK income is +$14,864. 8 yearsof that is +$118,910. So now the scoreboard looks like this: Converted MSTR: $956,868 Net dividend carry: +$118,910 Total financial assets: $1,075,778 Pay back the original mortgage principal: -$300,000 You are left with: $775,778 And you still own the fucking house. That is the part that makes this structure so deranged. You took $300,000 of dormant home equity and transformed it into a leveraged monetary trade. Your liability was fixed in dollars. Your income stream came from STRK. Your upside came from MSTR. MSTR's underlying treasury was Bitcoin. And your ultimate counterparty on the other side of the trade was an American monetary system carrying almost $40 trillion of federal debt. If dollars lose purchasing power over the next eight years, the real burden of that $300,000 liability shrinks. If Bitcoin monetizes upward, Strategy's Bitcoin treasury explodes in dollar value. If MSTR follows the balance-sheet math, your STRK conversion option becomes increasingly valuable. Meanwhile: The bank wants dollars. STRK produces dollars. Bitcoin reprices the collateral above it. You are essentially standing between two giant machines. One machine manufactures dollars. The other machine has a permanently scarce supply of 21 million units. And you borrowed from the first machine to gain exposure to the second. That is why I call this: TURNING YOUR HOUSE INTO A LEVERAGED SHORT ON THE UNITED STATES GOVERNMENT. They debase. You owe fixed dollars. STRK pays the carry. Bitcoin does the violence. MSTR provides the convexity. Then you convert. Absolutely psychotic financial engineering. God bless America.

DOW JONES UP 338.87 POINTS, OR 0.64 PERCENT, AT 53,400.82 AFTER MARKET OPEN S&P 500 UP 34.25 POINTS, OR 0.45 PERCENT, AT 7,700.85 AFTER MARKET OPEN NASDAQ UP 118.74 POINTS, OR 0.45 PERCENT, AT 26,336.57 AFTER MARKET OPEN

Since spot Bitcoin ETFs launched: ETFs absorbed $51.3B Strategy alone deployed $58.0B Stablecoin supply expanded $171.4B But their weekly correlations with Bitcoin returns were: ETFs: 0.64 Stablecoins: 0.31 Strategy: 0.03 Capital size ≠ price impact. Bitcoin has the same supply curve, but it no longer has the same buyer. Even more interesting is that ETF flows’ correlation with the following week’s Bitcoin return collapses from 0.64 to 0.08. ETF flows are extremely useful for identifying the buyer moving price right now, but they are nearly useless as a standalone prediction of what happens next. And every major impulse is currently weakening: ETF flows, 30D: −$107M Stablecoin supply: −$5.6B Strategy purchases: −$216M Binance BTC open interest: −0.4% We have four liquidity channels retreating simultaneously:

NEW SKILL: This team take humanoid parkour to the next level! This project involves @zhenkirito123, @Yuanhang__Zhang, @pabbeel, @carlo_sferrazza, @GuanyaShi, and others. Called Perceptive Humanoid Parkour (PHP), it lets a Unitree G1 humanoid (29 DoF, 1.3 m) run long-horizon, vision-based parkour and decide on its own whether to step over, climb onto, vault, or roll off obstacles, using only onboard depth sensing (a 30 Hz camera) plus a discrete 2D velocity command from the operator. It builds the motions by motion matching, a nearest-neighbor search in a 27-dimensional feature space (imported from the video-game industry) that stitches retargeted atomic human clips into long-horizon kinematic trajectories through a shared Locomotion to Skill to Locomotion manifold. It then trains per-motion RL tracking experts (with a privileged height scan) and distills them into one depth-based multi-skill student via DAgger combined with RL. It replaces hand-scripted skill sequencing and operator-triggered skill selection. The onboard depth-only student holds 0.95 to 1.00 success across obstacle heights in simulation, while a naive end-to-end depth policy collapses from 0.95 to 0.07/0.08 at 58 and 76 cm. The upside comes from distilling privileged-height-scan experts and from motion-matching composition, not from training onboard from scratch. The operator sends only a coarse 2D velocity (W/A/D keys), and the robot itself picks which skill to run from the depth image. The training data contains only single-obstacle traversals, so the ability to chain skills across a multi-obstacle course is generalization the policy was never explicitly taught. Transitions are constructed in kinematics, not rediscovered by learning. Every skill enters and exits through a shared locomotion manifold, so no hand-captured skill-to-skill transition clip is needed. Motion matching densifies a sparse library into smooth long-horizon trajectories before any RL. The entire parkour library is only about 66 seconds of mocap, and each skill is just a few seconds. Ablating approach-distance variety ("Extreme Distances") drops the 76 and 94 cm climbs to 0.62 and 0.64, and "Half Density" drops the 76 cm climb to 0.32. Motion matching's job is to manufacture stride-phase and approach variety out of seconds of data. It clears a 1.25 m wall (96 percent of its 1.3 m height) in 3.63 s, and a cat-vault peaks at 3.41 m/s clearing a 0.4 m by 0.5 m obstacle in 0.8 s. A single 30 Hz depth stream drives both traversal and runtime re-planning, shown by displacing obstacles about 0.5 m mid-run.