CHOOSE YOUR FIGHTER Warren Buffett vs Stanley Druckenmiller Buffett stepped down as Charman of Berkshire Hathaway $BRK.B today. Druckenmiller has never had a losing year in more than 30 years. Here are their full portfolios as of Q2 2026. BERKSHIRE HATHAWAY - Apple $AAPL: 22% - American Express $AXP: 17% - Google $GOOGL: about 12.6% across both share classes - Coca-Cola $KO: 11% - Bank of America $BAC: 9.2% - Chevron $CVX: 4.7% - Occidental $OXY: 4.3% - Chubb $CB: 3.9% - Moody's $MCO: 3.7% - Kraft Heinz $KHC: 2.6% - DaVita $DVA: 2.1% - Delta $DAL: 1.8% - SiriusXM $SIRI: 1.2% - VeriSign $VRSN: 0.8% - Kroger $KR: 0.7% - Liberty Live $LLYVA: about 0.6% across both share classes - Ally $ALLY: 0.4% - Lennar $LEN: 0.4% - New York Times $NYT: 0.4% - Capital One $COF: 0.2% - Louisiana-Pacific $LPX: 0.1% - Nucor $NUE: 0.1% - Macy's $M: 0.1% - NVR $NVR - Jefferies $JEF - D.R. Horton $DHI DUQUESNE FAMILY OFFICE - Natera $NTRA: 17% - Insmed $INSM: about 5.7% in shares and calls - Taiwan Semi $TSM: 5.4% - Brazil ETF $EWZ: about 5.1% in shares and calls - Amazon $AMZN: about 4.6% in shares and calls - STMicro $STM: 4.5% - S&P 500 Equal Weight $RSP: about 3.7% in calls and shares - Fox $FOXA: about 2.8% across both share classes - YPF $REPYY: 2.7% - CDW $CDW: about 2.7% in shares and calls - BBB Foods $TBBB: 2.3% - Google $GOOGL: 2.3% - Seagate blockstack:native: 2.3% - United Airlines $UAL: 2.1% - Sea $SE: 2.0% - NewAmsterdam Pharma $NAMS: 2.0% - Russell 2000 ETF $IWM: 1.9% in calls - Sandisk $SNDK: 1.5% - Revolution Medicines $RVMD: 1.4% - S&P 500 ETF: 1.3% in calls - Bitdeer: 1.2% - CRH: 1.1% - Delta: 1.1% - Tesla $TSLA: 1.0% in calls - Fluor: 1.0% - D.R. Horton: 0.9% - Coupang: 0.9% - AMD: 0.8% - Palo Alto Networks: 0.8% - Cleveland-Cliffs: 0.8% - Hut 8: 0.7% - Caris Life Sciences: 0.6% - Argentina ETF: 0.6% - Woodward: 0.5% - Meta: 0.5% in calls - Nuvation Bio: 0.5% - Protagonist Therapeutics: 0.5% - Roku: 0.5% - Cavco: 0.5% - ADMA Biologics: 0.4% - Hyperliquid Strategies: 0.4% - Rambus: 0.4% - Rhythm Pharmaceuticals: 0.4% - Champion Homes: 0.4% - Daktronics: 0.4% - PureCycle: 0.4% - Southern Copper: 0.4% - Linde: 0.4% - Entegris: 0.4% - Teva: 0.4% - Unity: 0.4% - Aeva: 0.4% - Riot Platforms: 0.4% - Qnity Electronics: 0.4% - Equinix: 0.4% - Lam Research: 0.4% - Definium Therapeutics: 0.3% - Belite Bio: 0.3% - 10x Genomics: 0.3% - Wabtec: 0.3% - Eli Lilly: 0.3% - Xenon Pharmaceuticals: 0.3% - Olema Pharmaceuticals: 0.2% - Repligen: 0.2% - Rocket Companies: 0.2% - Baidu: 0.2% - Arm: 0.2% - Carvana: 0.2% - Reddit: 0.2% - Alcoa: 0.2% - Thermo Fisher: 0.2% - Danaher: 0.2% - F5: 0.2% - Vista Energy: 0.2% - Skeena Resources: 0.2% - JBS: 0.1% - Monte Rosa Therapeutics: 0.1% - Relay Therapeutics: 0.1% - DBV Technologies: 0.1% - CCC Intelligent Solutions: 0.1% - UWM Holdings: 0.1% - Navitas Semiconductor: 0.1% - Solstice Advanced Materials: 0.1% - FTAI Aviation: 0.1% - Beam Therapeutics: 0.1% - Aurora Innovation: 0.1% - IREN: 0.1% - Grupo Financiero Galicia: 0.1% - Wave Life Sciences: under 0.1% Both own Google, Delta and D.R. Horton. Neither owns Nvidia $NVDA.

OECD Forecasts US 2026 Growth Of 2.2% (Vs 2.0% In June), 2.1% In 2027 (Vs 1.8%) - World 2026 Growth Of 2.9% (Vs 2.8% In June), 3.0% In 2027 (Vs 3.1%) - China 2026 Growth Of 4.5% (Unchanged), 4.2% In 2027 (Vs 4.3%) - Euro Area 2026 Growth Of 1.0% (Vs 0.8% In June), 1.0% In 2027 (Vs 1.2%) - Japan 2026 Growth Of 0.8% (Vs 0.6% In June), 0.7% In 2027 (Vs 0.8%) - UK 2026 Growth Of 1.1% (Vs 0.9% In June), 1.0% In 2027 (Vs 1.1%)

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World Currencies vs. the U.S. Dollar One-Year Change As of June 30, 2026: 🇨🇴 Colombian peso: +19.2% 🇮🇱 Israeli shekel: +13.2% 🇭🇺 Hungarian forint: +8.9% 🇿🇦 South African rand: +8.1% 🇲🇽 Mexican peso: +7.7% 🇨🇳 Chinese yuan: +5.6% 🇦🇺 Australian dollar: +5.2% 🇧🇷 Brazilian real: +5.2% 🇲🇾 Malaysian ringgit: +3.1% 🇳🇴 Norwegian krone: +1.8% 🇨🇱 Chilean peso: +1.0% 🇪🇬 Egyptian pound: +0.8% 🇭🇰 Hong Kong dollar: +0.1% 🇦🇪 UAE dirham: 0.0% 🇶🇦 Qatari riyal: 0.0% 🇸🇦 Saudi riyal: -0.2% 🇷🇺 Russian ruble: -0.4% 🇨🇿 Czech koruna: -1.1% 🇸🇬 Singapore dollar: -1.7% 🇨🇭 Swiss franc: -1.8% 🇹🇭 Thai baht: -2.3% 🇸🇪 Swedish krona: -2.4% 🇪🇺 Euro: -3.0% 🇩🇰 Danish krone: -3.1% 🇬🇧 Pound sterling: -3.4% 🇨🇦 Canadian dollar: -4.1% 🇵🇱 Polish złoty: -4.2% 🇳🇿 New Zealand dollar: -6.8% 🇹🇼 Taiwan dollar: -8.2% 🇵🇭 Philippine peso: -8.2% 🇮🇩 Indonesian rupiah: -9.3% 🇮🇳 Indian rupee: -9.4% 🇯🇵 Japanese yen: -11.3% 🇰🇷 South Korean won: -12.6% 🇹🇷 Turkish lira: -14.6% 🇦🇷 Argentine peso: -18.9% Source: Deutsche Bank, Bloomberg Finance LP.

🇺🇸US DATA RUNS HOT: INFLATION STICKY, DEMAND FIRM INFLATION • Headline PCE MoM: +0.2% vs +0.1% est.; prior -0.1% • Headline PCE YoY: +3.7% vs +3.6% est.; prior +3.7% • Core PCE MoM: +0.2% vs +0.2% est.; prior +0.1% • Core PCE YoY: +3.3% vs +3.3% est.; prior +3.3% GDP • Q2 GDP annualized: +1.5% vs +1.5% est.; prior +1.5% • Personal consumption: +3.4% vs +3.2% est.; prior +3.2% • GDP Price Index: +6.4% vs +6.2% est.; prior +6.2% • Core PCE QoQ: +3.6% vs +3.4% est.; prior +3.4% INCOME & SPENDING • Personal income MoM: +0.4% vs +0.2% est.; prior +0.2% • Personal spending MoM: +0.2% vs +0.1% est.; prior +0.3% • Real personal spending MoM: 0.0% vs 0.0% est.; prior +0.4% DURABLE GOODS • Durable goods orders MoM: +1.1% vs +0.5% est.; prior +0.5% • Durables ex-transportation: +0.4% vs +0.6% est.; prior +0.7% • Core capital goods orders: +0.2% vs +0.7% est.; prior revised to +1.7% • Core capital goods shipments: +1.4% vs +1.0% est.; prior revised to +2.4% BOTTOM LINE: Inflation remains sticky while consumer demand and headline durable goods beat expectations. GDP growth was in line, but stronger price pressures could keep the Fed cautious on rates.

MiniMax H3 Fashion Lookbook | Anime Character Reveal + Editorial MV Prompt🔥 Made this high-saturation anime PV with 13 fast visual beats in 15 seconds. A few years ago, this would’ve been days of AE work. Now? Prompt → generate → refine. Prompt 👇 Create a **15s, 16:9, 24fps anime character reveal trailer** with **13 fast visual beats**. Style: **Japanese anime opening × premium AAA motion graphics × fashion campaign**. The video should feel **explosive, sexy, stylish, bold and high-impact**, with **80% motion graphics and 20% character action**. ## CHARACTER LOCK — HIGHEST PRIORITY AO is a **young adult East Asian anime woman** with a sexy, confident Japanese anime aesthetic. She has: * small refined face * sharp expressive crimson eyes * glossy lips * confident, teasing gaze * slim feminine curvy figure * long elegant legs * stylish, cool, alluring presence Keep her identical throughout: * chin-length vivid red bob with messy bangs * crimson-red eyes * black choker * fitted red cropped top * short white cropped jacket, worn open * black mini skirt or fitted shorts * red belt detail * black thigh strap * white-and-red platform sneakers * subtle silver accessories Preserve the same face, body proportions, hairstyle, outfit, materials and colors in every shot. **Never redesign AO. Never change her face or outfit. If a shot becomes too complex, simplify the action first.** ## VISUAL STYLE Palette: **vivid red, crimson, white, black, silver**. Use: giant kinetic typography, red circles, diagonal slashes, manga speed lines, split screens, halftone dots, barcode strips, UI ticks, freeze frames, RGB flashes, impact shakes, poster layouts and graphic wipes. Every beat should feel: **fast, sharp, sexy, explosive, graphic and iconic**. Keep typography bold and readable. Editing: hard cuts, aggressive snap zooms, whip pans, speed ramps, freeze frames, impact shakes and foreground wipes. ## 13 VISUAL BEATS **01 | 0.0–1.0s** White field. Massive red circle slams into frame. Black bars slash across. UI ticks flicker. Giant **A**, then **O**, hit with heavy impact shake. **02 | 1.0–2.0s** The O becomes a circular frame showing an extreme close-up of AO’s crimson eye and glossy lips. She gives a teasing side glance. RGB flash. Circle bursts into red-and-white fragments. **03 | 2.0–3.1s** Black background, huge white **AO**. AO enters fast, turns sharply and power-slides beneath the typography. Red speed streaks trail behind her. Whip-pan out. **04 | 3.1–4.0s** Three red/white/black vertical panels. AO appears in three poses: hip turn, hair touch, over-shoulder stare. Huge vertical **FULL SPEED** moves behind her. **05 | 4.0–5.1s** AO jumps through a rotating typography ring reading **NO BRAKES / ALL EYES ON ME**. One clean mid-air spin. Snap zoom into her confident face. **06 | 5.1–6.0s** White editorial frame. Huge black **HOT** with a red slash. AO crosses the frame with a runway-like step, one hand at her waist. Typography compresses and rebounds. **07 | 6.0–7.0s** Bright red field with black diagonal stripe. AO performs one smooth fast turn. Three ghosted freeze positions trace the movement. Giant outlined **TURN** rotates behind her. **08 | 7.0–8.0s** Words hit one per beat: **HOT / FAST / WILD / RED** AO changes pose with each word: direct stare, hair toss, hip shift, confident forward lean. **09 | 8.0–9.0s** Black frame with manga perspective lines and a graphic grid. AO steps forward and freezes in a strong hero pose. Red circular target graphics lock around her. **10 | 9.0–10.1s** AO moves toward camera through three red-and-white graphic panels. Each panel shatters as she passes. Large **A O** fragments appear behind her. Finish with a hair or leg foreground wipe. **11 | 10.1–11.1s** Rapid poster montage: four frames of the same AO — close-up stare, walking, side pose, hands at waist. Add **01–04**, barcodes, halftone dots and sharp Japanese poster graphics. **12 | 11.1–13.0s** Hero moment on a clean white background. AO lands in a powerful fashion pose: one leg forward, one hand at her waist, chin lifted, direct eye contact. Huge red shockwave rings explode behind her. Typography fragments and speed lines burst outward. Hold an iconic confident freeze. **13 | 13.0–15.0s** Final identity card. Huge black **AO** on a bright white field. AO stands relaxed and alluring in front of the letters. Red circles, halftone, technical arcs and sharp speed accents surround her. Final red pulse flashes through the frame and ends on a hard stinger. ## ANIME STYLE Premium modern Japanese anime rendering: * clean cel shading * sharp linework * polished highlights * cinematic close-ups * dynamic perspective * fashion-editorial full-body framing * smooth hair and fabric motion AO must look like a **stylish adult anime heroine**, not chibi and not childish. ## AUDIO Hard-hitting **electro / future bass / anime-opening style music**. Use: heavy drums, bass hits, risers, glitch fills, synth stabs, typography slams, whooshes and shutter impacts. Build continuously. Peak at Beat 12. End with a sharp electronic stinger. ## PRIORITIES 1. AO identity consistency 2. sexy adult anime character design 3. red-black-white outfit consistency 4. maximum visual impact 5. readable typography 6. premium anime rendering 7. fast beat-synced editing Avoid: childlike proportions, chibi style, blue clothing, face changes, outfit changes, extra characters, unreadable typography, weak motion, dull compositions or generic schoolgirl styling. Final result: **explosive, sexy, red-hot, premium, graphic-driven and visually unforgettable.** Try MiniMax H3 on Ima Studio 👉 #MiniMaxH3# #MotionDesign# #Anime# #AIVideo# #ImaStudio#

Grok Voice Transcribe 2.0 is the new king 👑 • Artificial Analysis: #1# for accuracy among 32 streaming models, beating GPT Live, Gemini 3.5, Scribe v2, Muse, Nova-3, Azure and more On SpaceXAI’s real-world tests, lower error rate is better: • Telephony: 7.1% — #1# • Conversations: 3.3% — #1# • Short phrases across 19 languages: 6.8% — #1# It beat Gemini 3.5, ElevenLabs Scribe v2, Deepgram Nova-3, Whisper Large v3 and others across major tests. Twice as accurate as Grok Voice Transcribe 1.0 at the same price. An incredible leap by SpaceXAI. 🚀

CPI Details: CPI rose 0.6% MoM after rising 0.4% MoM in August; it rose 3.7% YoY The index for gasoline rose 9.1% in September, accounting for over half of the monthly all items increase. The energy index increased 5.2% over the month following a 2.1% increase in August. Electricity CPI rose 0.2% over the month. In contrast, the natural gas index decreased 0.3% in September. The shelter index rose 0.4% in September after rising 0.3% in August. The index for food was unchanged in September, as the index for food away from home increased 0.2% and the index for food at home fell 0.1%. It increased 2.5% over the last year.Three of the six major grocery store food group indexes decreased in September, while the other three indexes increased. The meats, poultry, fish, and eggs index decreased 0.5%over the month, as the beef index fell 1.0%. The index for other food at home decreased 0.2 percent in September. The dairy and related products index decreased 0.9% over the month, as the milk index declined 2.0%. The energy index increased 20.4% YoY due in large part to the index for gasoline rising 34.2% over the same period. The natural gas index increased 5.0% YoY and the electricity index rose 4.4% YoY. Core CPI rose 0.3% in September, same as August. Indexes that increased over the month include recreation, used cars and trucks, education, airline fares, medical care, and apparel. Conversely, the index for communication was among the small number of major indexes that decreased in September. Shelter CPI increased 0.4% MoM, after rising 0.3% in August.Index for owners’ equivalent rent rose 0.3% in September, and the index for rent increased 0.2%. Lodging away from home index rose 2.0% in September after rising 2.4% the previous month. Index for recreation increased 0.5% over the month after being unchanged in August. Used cars and trucks index rose 0.7% in September, and the education index increased 0.6%. New vehicles index, the personal care index, and the motor vehicle insurance index also increased over the month. Index for airline fares increased 1.2% in September, and the index for apparel rose 0.3%. The medical care index increased 0.1% in September after falling 0.2% in August. The index for hospital services rose 0.7% over the month. Prescription drugs index declined 1.2% in September. Index for physicians’ services was unchanged over the month. Communication CPI declined 0.2% in September after rising 2.3% in August. Index for household furnishings and operations was unchanged over the month.

Part 4 of my TensorFold 1.0 test: long prompts. Does @ashxhart's new native engine hold up at 128k tokens? Same GB10 box (Lenovo PGX), Nemotron 3.5 Lightning, real book text from Project Gutenberg, old Python engine 0.6.6 vs 1.0.1, median of 3 different book passages per length: decode at 8k: 118.7 → 138.0 tok/s decode at 32k: 110.5 → 124.0 tok/s decode at 64k: 97.5 → 111.8 tok/s decode at 128k: 85.9 → 96.2 tok/s So 1.0.1 decodes 12–16% faster at every length (short prompts in part 1: 1–9%). Prefill is a tie: 0.6.6 is up to 2% faster (a 128k prompt takes 31.8 s vs 32.3 s to the first token). And all 12 answers to these long prompts are bit-identical between the two engines, from 8k to 128k. One limit: with 4 long prompts (32k each) at once, both engines read them one after another. The 4th request waits about 22–24 s for its first token on either engine, and all 4 finish in about 24 s.