🇬🇧 England vs Norway 🇳🇴 – All Historical Football Matches 1937: Norway 0-6 England 1938: England 4-0 Norway 1949: Norway 1-4 England 1966: Norway 1-6 England 1980: England 4-0 Norway 1981: Norway 2-1 England 1992: England 1-1 Norway 1993: Norway 2-0 England 1994: England 0-0 Norway 1995: Norway 0-0 England 2012: Norway 0-1 England 2014: England 1-0 Norway England wins: 7 Draws: 3 Norway wins: 2

🇺🇸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.

🧩 Qwen3.8-Flash-Next: A 6B-Active Preview of the Qwen4 Architecture On the same night Zhipu's GLM-5.3-Flash took over the timeline, @Alibaba_Qwen open-sourced Qwen3.8-Flash-Next — explicitly positioned as a preview of the Qwen4 architecture. Zhihu contributor Kitt在进化 argues that for people who actually run models locally, this is the more practical release of the night. The local-deployment groups he is in are, in his words, on fire. His take: the model is called 3.8, but the architecture is really Qwen4 in preview — and it borrows the best ideas from across the field. 1️⃣ Smaller, cheaper, and realistic for local deployment Flash-Next has 125B total parameters with only 6B active — far smaller than the 300B-class GLM-5.3-Flash. The API is priced at ¥1 input, ¥3 output, and ¥0.1 per cached million tokens, roughly matching DeepSeek-V4-Flash's off-peak rates. His comparison, per 1M tokens in RMB — input / output / cache hit: 🔹 Qwen3.8-Flash-Next: 1.0 / 3.0 / 0.1 🔹 GLM-5.3-Flash: 0.4 / 1.4 / 0.115 (limited-time promo rate) 🔹 DeepSeek-V4-Flash (off-peak): 1.5 / 4.5 / 0.05 2️⃣ A Qwen4 preview wearing a Qwen3.8 name The author points out this is the same play Zhipu made: GLM-5.3-Flash's architecture is also completely different from GLM-5.3. Shipping the new architecture as open weights early is deliberate pathfinding. Inference frameworks like vLLM and SGLang, plus the quantization toolchain, all need lead time to adapt before Qwen4 proper arrives. 3️⃣ An architecture that borrows from everyone The author reads Flash-Next as a synthesis of the field's best recent ideas. 🔹 Attention: Qwen's in-house QSA, built to balance throughput and speed on long context. 🔹 Knowledge: it absorbs DeepSeek's Engram line of work, packing prior knowledge into 51B of N-gram side parameters — high knowledge density at minimal compute cost. 🔹 Training: the Muon optimizer, popularized by Kimi, scheduled together with AdamW. 4️⃣ Half the active parameters, still overtaking At 6B active, Flash-Next is nearly half the size of DeepSeek-V4-Flash — yet Qwen's reported benchmarks show it overtaking that model on multiple coding and agent leaderboards. The author says he is not worried about real-world experience: the recent Qwen3.8-27B already proved itself in daily use, and this sits on the same foundation. 🔗 Full Reading: #Qwen# #Alibaba# #Qwen4# #OpenWeights# #LLM# #AIInference# #MoE#

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#

Last wk S&P/Nas/Mag7 +1.0%/+1.6%/+4.7%. The forced asset sale by Situational Awareness helped drive a sharp rally on 7/30. On 7/29, I wrote, “From a technical standpoint, I believe forced liquidations and margin calls in both retail accounts and hedge funds that typically run with leverage over the past couple of weeks is leading to a technical bottom… In summary, my view is that we could have seen at least a short-term bottom today with a strong rally ahead of us in the sectors most caught in the latest speedbump.” On Thursday 7/30, the Morgan Stanley TMT (Tech Media and Telecom) Momentum Index rebounded a record 19% on Thursday and added another 1% on Friday. This followed a decline of 54% from 6/22-7/29. It is now down 44% from 6/22. This is why I focus on avoiding “speed bumps” as I warned about on my 6/20 post. It is hard to predict how bad they will be and down 50% requires a 100% gain to get back to even. I feel like the near-term low on the current speedbump was seen on 7/29. Looking at Mag7 results this earnings season, stock reaction to earnings results mostly came down to two factors: 1) did estimates go up for CQ3 if capex went up and 2) did you report results before or after the Situational Awareness (SA) forced sale. $MSFT results strengthened my recent view that co-Pilot could be a winner in enterprise AI longer-term. As I wrote in my earnings preview. “It operates natively within the Microsoft 365 ecosystem where enterprise work already happens.” There are ~450M M365 paid seats but only ~30M Co-Pilot. Microsoft guided above consensus for CQ3 while capex remained unchanged. Azure also saw growth improve sequentially from 39% to 43% y/y with guidance to 45% for CQ3. Helped by the SA forced sale, the stock saw the 5th highest one day percentage stock move in history at +16% on Thursday. $META unfortunately had both revs & operating income go down for Q3 while revising up capex & opex. They also did not announce any definitive plans around a public cloud offering or API for their foundational models to monetize this spend. The stock declined 8% in reaction on Thursday which likely would have been worse if not for the SA forced sale. $AMZN while guiding both revs & operating income below consensus for Q3 and increasing capex, had AWS rev growth accelerate from 28% in Q1 to 37% in Q2 which was the highest growth rate since Covid in Q4:2021. AWS normalized operating margins expanded 1% sequentially. The stock rallied 15% on Friday in reaction to earnings following a 4% rally on Thursday as investors continued to regross in the AI names. But this brings me to $GOOGL which remains my long-term winner in consumer AI with the complete AI stack. Google like Amazon guided capex higher while implied revs & operating income declined for Q3. But Google Cloud Platform performance crushed AWS performance. GCP saw revs accelerate from 63% in CQ1 to 82% in CQ2 while operating margins expanded 3% sequentially. But Google unfortunately reported a week prior to the SA forced sale and saw their stock decline 7% in reaction the next day. $AAPL was the anti-AI trade leading up to their results and their stock hit an all-time high intra-day on Wednesday. The stock as a result declined 1% on Thursday as investors regrossed AI names on the SA forced sale and fell 7% on Friday in reaction to revenue & gross margin guidance that was below consensus. Big picture, I think the severe drawdown in the AI favorites from 6/22-7/29 was good for the market. It reminded investors of the need to be vigilant and the perils of excessive leverage/risk taking. Long-term bond yields hitting new 20 year highs last week and the unresolved Iran war are factors I am monitoring. In summary, out of the mega-cap earnings the past two weeks and the forced SA sale, my favorites are $GOOGL, $AMZN and $MSFT. I increasingly view value as shifting from the model layer which is increasingly getting commoditized to the infrastructure layer which includes the public clouds. I think the short-term bottom in the current speed bump was on 7/29. Best of luck in the week ahead.

BREAKING: The US personal savings rate fell -0.1 percentage point in June, to 2.7%, the lowest since June 2022. This marks the 5th consecutive monthly decline, bringing the cumulative drop to -1.7 percentage points. This is also the 3rd-lowest monthly reading since April 2008, during the Financial Crisis. To put this into perspective, the personal savings rate averaged ~5.5% between 2014 and 2019. The only period in modern history with similarly low saving rates was 2005-2007, when the rate fluctuated between 1.4% and 3.3%. US households are struggling to save money.