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Social Media Through the Years 1. Classmates. com - 1995 - Active 2. SixDegrees - 1997 - Closed - 2001 3. LiveJournal - 1999 - Active 4. Friendster - 2002 - Closed - 2015 5. Myspace - 2003 - Active 6. LinkedIn - 2003 - Active 7. Flickr -...

36,142 просмотров • 3 дней назад •via X (Twitter)

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Before the week ends, let's acknowledge one of the most INSANE week ever for open AI, with 25+ notable open-weight drops across every modality: 🧠 LLMs → NVIDIA Nemotron 3 Ultra: 550B hybrid Mamba-MoE, only 55B active, 1M context, MMLU 89.1. NVFP4 variant claims ~5x throughput on Blackwell. First openly-weighted 550B hybrid Mamba-Transformer, closing the gap with frontier closed models. → Google Gemma 4 12B: fully open dense any-to-any (text/image/audio/video), 256k context, encoder-free, 140+ languages, AIME 2026 at 77.5. Shipped with a 23-checkpoint QAT wave (mobile ONNX + MLX). Most deployable model of the week. → StepFun Step-3.7-Flash: 198B sparse MoE VLM, ~11B active, SWE-Bench PRO 56.3. Apache 2.0. → Liquid AI LFM2.5-8B-A1B: edge MoE, just 1.5B active, 128k ctx, MATH500 88.8, MLX-ready. Best on-device option this week. → JetBrains Mellum2-12B-A2.5B-Thinking: their first open MoE, near-Qwen3-14B coding at 2.5B active. Apache 2.0. 🎨 Image gen (the surprise of the week) → Ideogram 4: their FIRST-EVER open weights. 9.3B flow-matching DiT trained from scratch. #2 overall behind GPT Image 2, top open-weight model on Design Arena + LMArena. Strongest open checkpoint for text-rich images, full stop. It has taste. Still can't believe this is open weights. 🔊 Audio & Speech (a breakout week for open TTS, 4 labs shipped) → Boson Higgs Audio v3 4B: 102 languages, 21 emotions, singing/whispering/shouting, sub-second TTFA. → RedNote dots.tts: the only fully continuous (no codec) open TTS pipeline, Apache 2.0. → Google Magenta RealTime 2: real-time music gen, <200ms latency, text+audio+MIDI. multimodalart ported it to PyTorch within hours with live ZeroGPU demos. → NVIDIA Nemotron-3.5 ASR: 600M streaming, 17x more concurrent streams vs Parakeet RNNT 1.1B. 👁️ Vision & VLMs → PaddleOCR-VL-1.6: SOTA document parsing at 1B params, Apache 2.0. → Baidu NAVA: 6.3B joint audio-video gen, best-in-class A/V sync, Apache 2.0. 🎬 Video, 3D & World Models → NVIDIA Cosmos3-Super: 64B omnimodal world model coupling action trajectories with video+audio gen, for Physical AI. → JD JoyAI-Echo: up to 5-min multi-shot text-to-video on LTX-2.3. → ByteDance Bernini-R + VAST TripoSplat (single-image-to-3D Gaussian splats, MIT).

Victor M

542,146 просмотров • 3 месяцев назад

Michael Jackson vs. Madonna: The Battle for music relevancy. 1. Grammy Awards Michael Jackson — 13 Madonna — 7 2. Career Awards Michael Jackson — 1000+ Madonna — 350+ 3. Spotify Streams Michael Jackson — 25.2B Madonna — 11.9B 4. Monthly Spotify Revenue Michael Jackson — $6M+ Madonna — $1.0M 5. CSPC Units Michael Jackson — 362M Madonna — 258.6M 6. Pure Album Sales Michael Jackson — 290.1M Madonna — 214M 7. Physical Singles Sold Michael Jackson — 79.4M Madonna — 75.2M 8. Digital Singles Sold Michael Jackson — 80M Madonna — 42.1M 9. Most-Streamed Song on Spotify Michael Jackson — Billie Jean (3B) Madonna — Popular (1.3B) 10. RIAA Diamond Singles Michael Jackson — 2 Madonna — 0 11. RIAA Diamond Albums Michael Jackson — 3 Madonna — 1 12. RIAA-Certified Songs Michael Jackson — 32 Madonna — 30 13. RIAA-Certified Albums Michael Jackson — 16 Madonna — 20 14. Guinness World Records Michael Jackson — 40 Madonna — 20 15. Billboard Hot 100 No. 1 Hits Michael Jackson — 17 Madonna — 12 16. Billboard 200 No. 1 Albums Michael Jackson — 6 Madonna — 10 17. Weeks at No. 1 on the Billboard Hot 100 Michael Jackson — 37 Madonna — 32 18. Weeks at No. 1 on the Billboard 200 Michael Jackson — 51 Madonna — 21 19. Youtube subscribers Michael Jackson — 40M Madonna — 8M 20. Songs over 1 Billion views on Youtube Michael Jackson — 5 Madonna — 1 21. Followers on Spotify Michael Jackson — 50M Madonna — 9M 22. Songs over 1 Billion streams on Spotify Michael Jackson — 4 Madonna — 1 23. Days at No.1 on the Global Spotfy chart Michael Jackson — 18 Madonna — 0 24. Days at No.1 on the Global Digital Artist Ranking Michael Jackson — 44 and counting Madonna — 0 25. Albums on the Biggest selling albums in history list. Michael Jackson — 5 Madonna — 1 26. Years Active Michael Jackson — 1964–2009 Madonna — 1979–Present She may live longer but his legacy and global impact will be forever and will eventually out live us.

THE BAD GUY

14,837 просмотров • 2 месяцев назад

In week 2, Jackson Bennee’s Pick 6 increased Utah’s streak of consecutive seasons with a Pick 6 to 22! Scooby Davis Pick 6 las night at Baylor was the 50th Pick 6 in those 22 seasons! Here’s a look at all 50 of those Pick 6s, and the legends that have kept the streak alive ⬇️ List compiled by the official UTESPN Stat Nerd 🦣⭕🪶 x-Darius Chode 🦣⭕🪶. Please drop Chode a follow! ⬇️ @ Utah State 2004 Jonathan Fanene 76 yds V UNLV 2004 Steve Fifita 6 yds V Arizona 2005 Eric Weddle 24 yds @ Utah State 2006 Eric Shyne 21 yds, Stevenson Sylvester 45 yds @ San Diego State 2006 Eric Weddle 30 yds, Eric Weddle 30 yds V UNLV 2006 J. J. Williams 22 yds @ TCU 2007 Martail Burnett 55 yds @ Wyoming 2008 Sean Smith 25 yds @ San Diego State 2008 Deshawn Richard 89 yds, Deshawn Richard 38 yds @ UNLV 2009 Robert Johnson 64 yds V San Diego State 2009 Joe Dale 30 yds V Cal 2009 Stevenson Sylvester 27 yds @ New Mexico 2010 Matt Martinez 36 yds @ Pitt 2011 Derrick Shelby 21 yds V UCLA 2011 Conroy Black 67 yds V Northern Colorado 2012 Joe Kruger 24 yds V UCLA 2013 Keith McGill 19 yds V Wazzu 2014 Eric Rowe 11 yds @ UCLA 2014 Tevin Carter 27 yds @ Colorado 2014 Dominique Hatfield 20 yds V Michigan 2015 Justin Thomas 55 yds V BYU 2015 Tevin Carter 28 yds, Dominique Hatfield 46 yds V BYU 2016 Sunia Tauteoli 41 yds @ ASU 2016 Chase Hansen 34 yds @ Arizona 2017 Javelin Guidry 14 yds @ NIU 2018 Chase Hansen 40 yds @ Stanford 2018 Jaylon Johnson 100 yds V BYU 2018 Julian Blackmon 27 yds @ BYU 2019 Francis Bernard 58 yds, Julian Blackmon 39 yds @ Oregon State 2019 Devin Lloyd 64 yds @ Washington 2019 Jaylon Johnson 39 yds V Wazzu 2020 Clark Phillips III 36 yds V Wazzu 2021 Clark Phillips III 54 yds @ Stanford 2021 Devin Lloyd 2 yds V Oregon 2021 Devin Lloyd 34 yds V SUU 2022 R. J. Hubert 39 yds V Oregon State 2022 Clark Phillips III 38 yds @ UCLA 2022 Clark Phillips III 80 yds V Weber State 2023 Lander Barton 23 yds V UCLA 2023 Karene Reid 21 yds V Iowa State 2024 Lander Barton 87 yds @ UCF 2024 Zemaiah Vaughn 60 yds, Smith Snowden 13 yds V Cal Poly 2025 Jackson Bennee 46 yds @ Baylor Scooby Davis 65 yds

UTESPN

16,733 просмотров • 10 месяцев назад

Gemma 4 26B A4B MoE - 500+ t/s decode - Single RTX 4090 (24 GB VRAM) - Llama.cpp concurrency 24 - q8 kv cache How many API users can you simultaneously host on a single RTX 4090 (24 GB VRAM) before it crashes? Yesterday, I proved you can host 14 active users using unquantized memory. Today, I used 8 bit KV Cache Quantization to hack the VRAM footprint. I successfully scaled to 24 concurrent users without a single dropped connection. A 71% server capacity boost for free. By adding the -ctk q8_0 -ctv q8_0 flags to llama.cpp, you compress the KV cache context memory from 16 bit to 8 bit. This unlocks massive concurrency limits on Gemma 4 26B (MoE) on a single 24GB consumer GPU. Here is the exact telemetry from pushing 8 bit quantization to its absolute physical edge: # TEST 1: The 24 User Concurrency Max Server Config: 24 slots (np 24) | 4,096 context per slot | 98,304 Total Context Client Load: 24 simultaneous requests (2,000 token prompt per user) Unquantized KV cache for this load requires 28GB+ VRAM (Instant OOM). Quantized to Q8, it allocated safely at 23.35 GB. The C++ engine crunched the entire batch in 28.5 seconds. Decode Speed: 21 t/s (Per User) | 500 t/s (Agg) # TEST 2: The 48 User Queue Overload What happens to a compressed cache during a traffic spike? Server Config: 24 slots (np 24) | 4,096 context per slot | 98,304 Total Context Client Load: 48 simultaneous requests (2k token prompt per user) Zero queue drops. The scheduler flushed and hot swapped the 8 bit memory flawlessly on the fly, completing all 48 users in 66.0 seconds (a perfect 2.3x queue scaling multiplier). Decode Speed: 18 t/s (Per User) | 430 t/s (Agg) # TEST 3: The 8 User RAG Slam Server Config: 8 slots (np 8) | 60,000 context per slot | 480,000 Total Context Client Load: 8 simultaneous requests (30k token prompt per user) It allocated 23.83 GB VRAM and chewed through ~240,000 prefill tokens in 46 seconds under massive memory pressure. Prefill Speed: 6,200 t/s (Agg) Decode Speed: 22 t/s (Per User) | 175 t/s (Agg) # The Engineering Alpha (The Quantization Tradeoff): You gain a massive 71% increase in server capacity, but what do you lose? Compute latency. Because the cache is stored in 8 bit, the GPU's cores have to dequantize the memory back to 16 bit on the fly during every single prefill step. In my unquantized tests yesterday, single slot prefill was hitting ~1,500+ t/s. Today, under the heavy 48-user Q8 load, prefill dropped as low as ~750 t/s. You trade a few seconds of initial prefill latency to essentially double your API hosting capacity. For production high volume SaaS, this is the ultimate unit economics cheat code. Here is the exact command to run a 24 user Q8 continuous batching server on your own single 4090, single 3090 or any 24gb vram rig: ./build/bin/llama-server -m gemma-4-26B-A4B-it.gguf -c 98304 -np 24 -b 2048 -ub 2048 -ngl 99 -fa on -ctk q8_0 -ctv q8_0 --port 8080 (Note: -c 98304 allocates exactly 4,096 tokens of context per user across 24 slots). Hugging Face links to the Unsloth Gemma 4 26B QAT quants along with performance graphs available in the replies. Would you trade 3 seconds of Time To First Token latency to double your active user capacity?

Alok

17,465 просмотров • 2 месяцев назад

Part Two: 20th Amendment of the CONSTITUTION: ( Some will say Obama took the Oath before Noon once, but that was because the Inauguration date fell on a Sunday. You can educate yourself here: ABC on Sunday / Obama: ( 6. The "Soldiers" shown at the Cannons... ZERO Commissioned Officer present. Violation of Army Regulations 600-25, 2–3 Cannon Salutes. Page 2: ( 7. Those “soldiers” shown for “Biden” were also non-regulation coats. 8. Those "soldiers" were moving around and did NOT perform any kind of marching ceremony, all waiting on their "cue." That’s NOT how the 3rd Infantry Regiment performs. Do yourself a favor and YouTube the Presidential Salute Battery. 9. The BEST of all… Remember, you heard the “Press Secretary”… refer to the Army, National Guard, and Arlington National Cemetery Rules and Regulations. The ONLY Cannons shown ALL day l ong for "Biden" on January 20, 2021, were 3 Cannons at Arlington National Cemetery. 3 Cannons at Arlington National Cemetery is NOT a 21-Gun Salute. It's a Military Honors FUNERAL. You heard the “Press Secretary”… the LOCATION is key. The number of cannons and location are key. Arlington National Cemetery website: "The 21-gun salute is not to be confused with the three-volley salute (or three-rifle volley) rendered at military honors funerals, which you might see or hear at Arlington National Cemetery." NOT to be confused with the three-volley salute. 3 Volley = 3 Cannons. Arlington 21 Gun Salute: Cannons: ( Again, the ONLY Cannons shown ALL day l ong for "Biden" were 3 Cannons at Arlington National Cemetery. = Funeral. The 21-Gun Salute is 4 Cannons, 21 Guns. 21 Guns = rounds / shots fired. The ONLY 4 Cannons shown all day long January 20, 2021, was at Joint Base Andrews with President Donald John Trump, in which the Media told you it was the 3rd Infantry Regiment, Presidential Salute Battery, aka ‘The Old Guard.’ January 20, 2021, at Joint Base Andrews with President Trump = The Inauguration. I don't think you want to discuss ARLINGTON... OR the National Guard. Let me go ahead and chap your asses about the National Guard. You’re all about the Military until a Veteran like myself puts your asses in your place with Military Laws, Orders, Regulations, and Customs, then as 99.9% of liberals, you run to your holes or your spew off a bunch of 💩 that doesn’t matter. You CANNOT support the Military without supporting our Laws, Orders, Regulations, and Customs. Even though those of us who served for the CORRECT reasons already knew this, but as the United States Supreme Court clarified in the Military Justice Act of 2016, passed in the NDAA of 2017, Military Laws are separate from Federal. Everyone of us who raised our right hand and took the Oath to serve in the Armed Forces, swore in under: Title 10 Section §502. From this point forward, you cannot like one portion of Title 10 without the rest of it. There’s a VERY good reason why there’s a DASH between 45–47 on President Trump’s ball cap. He didn’t live 78 years to forget the difference between a comma, &, and a - . The DASH = 👉🏻 Military Occupation 👉🏻 Government in Exile 👉🏻 Continuity of Operations You sure you want talk National Guard? The ONLY person who can Federalize the National Guard to Active-Duty is THE President. The ONLY President who’s recently Federalized the National Guard to Active-Duty. 👉🏻 45–47 President Trump signed 11 Executive Orders with 11 National Emergencies, and even though PEADs are draft classified, there’s enough evidence, Legislatively and Visual Enforcement, to make the statement, PEADs were signed. Visual Enforcement: 2016 Campaign Trail: President Trump, “I have 200 Generals backing me and more to come.”

Derek Johnson

17,695 просмотров • 2 лет назад

I still don't understand why everyone isn't doing this yet. Elon Musk reposted this guide, and using this exact agent setup, I made $9,300 just last week Eight Grok agents on the desk, costing $200 a month, service a trading floor that typically costs a crypto fund $500,000 a year in analyst salaries A 5 AM morning call. I don't participate in it How the agents are distributed: SEARCH: gathers real-time alpha, developer repositories on GitHub, and unindexed Telegram signals before CT finds them RISK: checks contract functions, minting rights, and LP locks, flagging honeypots before entry SNIPER: places high-speed orders on-chain at the exact millisecond the risk clearance passes WHALE: tracks smart money wallets and flags insider accumulation in real time. RUG: monitors developer wallet activity 24/7 and dumps the entire position if they touch the LP EXIT: dynamically trails stops, scaling out as liquidity accumulates SHILL: tracks social volume, impulse speed, and key influencer calls HEAD OF DESK: never trades, routes data, checks transmissions, and brings me the single decision that requires a human While I was sleeping, the system scanned 164 tokens, selected 21 qualifying setups, and executed 8 trades. The result: net profit of $9,300 (already after fees) Each agent has its own virtual browser, terminal, and local cloud memory. The trading floor remains active even when my laptop is closed Setup is easier than it seems: 1. Download Grok Bot and create your Head of Desk 2. Give the remaining 7 agents task descriptions as if you were instructing new employees 3. Run the workflow once on your screen while they observe 4. Connect Telegram and wallet webhooks No VPS, no code, no waiting for developers Crypto trading used to mean 16 hours in front of a screen, paid alpha groups, and constant fatigue. Mine took one evening to set up Save this before your next trade. Save the guide

Bober_smart

364,700 просмотров • 26 дней назад

Western Railway is undertaking a major safety-driven encroachment removal operation at Garib Nagar, Bandra (East), today i.e 19th May 2026, after due legal process extending over several years. The following facts may kindly be noted: 1. The matter is not sudden or arbitrary. Proceedings under the Public Premises Act were initiated before 2017 and eviction orders were passed on 27.11.2017. 2. The issue has undergone extensive judicial scrutiny over nearly nine years, including proceedings before the Hon’ble Bombay High Court and Hon’ble Supreme Court. 3. The latest orders of the Hon’ble Bombay High Court dated 29.04.2026, subsequently upheld in further proceedings as well as before the Hon’ble Supreme Court, have permitted removal of unauthorized encroachments, while protecting identified eligible structures. 4. Western Railway is fully complying with judicial directions. Structures identified for protection through the joint survey process are not being disturbed. 5. The action is being undertaken primarily in the railway safety zone adjacent to active railway tracks, where unauthorized habitation poses serious risks to human life and train operations. 6. This railway area stretch is operationally critical for augmentation of rail capacity in Mumbai. Removal of encroachments is essential for railway safety, operational flexibility and future infrastructure expansion, including additional train services. 7. The proposed works are linked to enhancement of carrying capacity on one of the busiest rail corridors in the country and will facilitate introduction of additional long-distance train services for passengers across India. 8. Railway land cannot remain perpetually encroached, be it anywhere, and more so in safety-sensitive operational areas. At the same time, Railway administration is acting strictly within the framework of law and court directions. 9. The operation is being carried out jointly with civil administration, police authorities and railway security agencies to ensure maintenance of law and order and humane execution of the drive.

Rajendra B. Aklekar

18,070 просмотров • 4 месяцев назад

I still can't wrap my head around why not everyone is using this approach yet. Elon Musk reposted this guide, and using this exact agent setup, I managed to make $7,250 just last week Eight Grok agents on the desktop cost $200 a month, but they replace a full trading floor, the maintenance of which typically costs a crypto fund $550,000 a year in analyst salaries A 5:30AM morning call. I don't participate in it How the agents are distributed: SEARCH: gathers real-time alpha, developer repositories on GitHub, and unindexed Telegram signals before CT finds them RISK: checks contract functions, minting rights, and LP locks, flagging honeypots before entry SNIPER: places high-speed orders on-chain at the exact millisecond the risk clearance passes WHALE: tracks smart money wallets and flags insider accumulation in real time RUG: monitors developer wallet activity 24/7 and dumps the entire position if they touch the LP EXIT: dynamically trails stops, scaling out as liquidity accumulates SHILL: tracks social volume, impulse speed, and key influencer calls HEAD OF DESK: never trades, routes data, checks transmissions, and brings me the single decision that requires a human. While I was sleeping, the system scanned 143 tokens, selected 15 qualifying setups, and executed 8 trades. The result: net profit of $7,250 (already after fees). Each agent has its own virtual browser, terminal, and local cloud memory, and the trading floor remains active even when my laptop is closed Setup is easier than it seems: 1. Download Grok Bot and create your Head of Desk 2. Give the remaining 7 agents task descriptions as if you were instructing new employees 3. Run the workflow once on your screen while they observe 4. Connect Telegram and wallet webhooks No VPS, no code, no waiting for developers. Crypto trading used to mean 16 hours in front of a screen, paid alpha groups, and constant fatigue. Mine took one evening to set up Save this guide before your next trade

Bober_smart

55,240 просмотров • 24 дней назад

Valorant streamer alt tabbed for 4 seconds during stream three nights ago. 400 viewers watching. His browser tabs were visible. Chat exploded. BRO IS THAT POLYMARKET?? He tabbed back immediately. Laughed it off. Nah, you're seeing things. Too late. Someone clipped it. Posted to Twitter. One tab clearly said: Polymarket - gabagool22 20 minutes later, someone found the wallet. gabagool22. $790,310 profit. 24,575 predictions. Joined October 2025. → Wallet: His Twitch bio: Broke college student. Living off donations. Help me eat His biggest donation ever: $12. His biggest Polymarket win: $4,696. Stream went from 400 to 2,100 viewers in 15 minutes. Chat went insane. BRO IS BEGGING FOR PIZZA MONEY WITH $790K This man said help me eat sitting on three quarters of a million He kept playing. Tried to ignore it. Chat kept spamming the wallet link. The numbers broke everyone: 24,575 trades in 4 months. That's 200+ trades per day. Every single day. All BTC 15 minute windows. Buy between 2-55 cents. Collect $1. Repeat 200 times daily. $790,310 profit ÷ 24,575 trades = $32 average per trade. $32 sounds tiny until you do it 200 times a day. Last week he tweeted: Can't afford new headphones. Drop recs under $30. His wallet the same week: - Feb 1: $6,000 win +360% ROI - Feb 6: $4,218 win +901% ROI - Feb 7: $4,144 win +696% ROI Total: $14,362 in 6 days. He was crying about $30 headphones while making $14K that week. He finally addressed it: That's not my wallet. Someone's trolling. I'm broke, I need donations for rent. Chat: The blockchain is public bro. We can see every trade. He ended stream. Deleted the VOD. Changed bio to Taking a break. Too late. The clip had 47,000 views. 596,700 people have viewed that wallet since the leak. Reddit post from his Discord mod: I've been modding for him for 8 months unpaid. Just found out he's sitting on $790K. I'm done. The Discord went private. Twitter went private. Twitch went dark. His last message: It's a testing wallet from work. Not real money. Someone checked his LinkedIn. He's unemployed. Listed as Content Creator since 2023. The wallet is still active. Currently holding $28,000 in positions. Placed 15 trades today. Someone tried to hide $790K behind a broke gamer persona while streaming for $5 subs. Got exposed by one 4 second alt tab. Twitch donations: $12 max. Polymarket profit: $790,310. The blockchain doesn't care about your persona.

Marlow

42,125 просмотров • 7 месяцев назад

Elon Musk pays one wallet $115K. He doesn't even know about it. Every time he opens Twitter and starts typing someone on the other end earns money. Quietly. Methodically. Tweet by tweet. I stumbled upon this wallet by accident. Was scrolling through the Polymarket leaderboard. Looking for interesting strategies. Most tops are politics crypto mix of everything. And then I saw Prexpect → Opened the profile. Looked at positions. Closed it. Opened again. Thought it was a bug. Every position is the same market. Will Elon Musk post X tweets this week? Not ten different bets. No hedge on politics. One market. Over and over. For months. Scrolled through closed trades history. Won. Won. Won. Won. Scrolled further. Won. Won. Won. This is not trading. This is harvesting. Started breaking down how this works. Every Monday Polymarket opens fresh markets on Elon's tweets. Buckets of 20: 400-419 tweets 420-439 440-459 and so on. At the moment of opening chaos. Nobody knows where to set prices. Zero liquidity. Spreads like a canyon. Prexpect is already there. Pours in limit orders on YES at 1-2 cents across several buckets simultaneously. Becomes the order book before the order book exists. Looking at his active positions right now: 10000 shares 400-419 tweets entry 1¢ now 22¢ 10000 shares 420-439 tweets entry 1¢ now 18¢ 10000 shares 380-399 tweets entry 1¢ now 17¢ x17-x22 in a few days. The week isn't even over. But that's only half of it. Elon is a chaotic poster. 50 tweets in the morning then silence. Night raid at 3am then sleep. The market reacts slowly. People at work. People sleeping. People don't count tweets manually every hour. Prexpect counts. Imagine: you're watching football on TV. Score is 0-0. But someone at the stadium already saw the goal. For him it's 1-0. He places a bet while your picture catches up to reality. Prexpect is at the stadium. Always. Elon starts speeding up at 2am? Prexpect sees the pacing. Recalculates probabilities. Adjusts positions. By morning the market wakes up and prices have already moved. Closed positions tell the whole story: $3280 → $14871 March $11450 → $22979 November $27123 → $44597 December $41117 → $60388 January The fattest gain 353%. On tweets. Just on counting how many times a person hit Post. Scrolling further. Looking for at least one other bet. Maybe crypto. Maybe elections. Something for variety. Nothing. Only Elon. Week after week. Month after month. No diversification. No just in case. One edge sharpened to automation. While all of Twitter argues about WHAT Elon wrote one trader quietly collects money for HOW MUCH he wrote. $115314 and growing. Right now while you're reading this post Elon is possibly typing another tweet. And someone already bet on it.

Blaze

389,496 просмотров • 8 месяцев назад

How to make money on the weather using Polymarket I've been noticing more and more traders quietly printing on Polymarket's weather markets lately - and the category is exploding for a reason. Weather has always been super predictable for meteorologists (and us normals) right up to the day of. The whole point? You can earn easy, near-certain yield just knowing it'll rain in London tomorrow. I'm sharing a finished tutorial with you. Here is a small list of traders 1. gopfan2 ( - The absolute leader in weather. Earned over $2M in net profit by focusing on temperature and precipitation. Strategy - buy Yes below 15 cents, No above 45 cents, with risks of less than $1 per position. It dominates the NYC and London markets where the weather is predictable 2. enzocostapt81 ( is a weather-exclusive trader whose profile shows a complete wipeout in resolved positions-no active/open trades, current positions value $0.00, and all listed markets (resolved) at -100% P/L. The trader focused solely on daily/precise temperature predictions in major cities like New York City and London. 3. 0x594edb9112f526fa6a80b8f858a6379c8a2c1c11 ( 100% of active positions are weather/temperature markets across cities like Dallas, London, Seattle, Atlanta, NYC, and Toronto—focused on precise daily highs/thresholds/ranges. 4. meropi ( - Earned ~$30k on micro bets ($1-3) with multipliers up to 500x. Automated bets on temperature rise for 0.01 cents. Focus on speed to capture momentum in daily markets. One of the most stable in weather 5. 1pixel ( – $18.5k profit from $2.3k deposit, weather only (NYC and London) 6. erb80 ( Dominant focus-two massive Atlanta temperature range bets for Dec 17, with enormous share volume at ultra-low entries (0.1¢) turning into huge unrealized gains (+49,550% on the main one) 7. Hans323 ( - Earned $1.1M on one temperature trade in London. Started with $741 in January 2025 and increased to $87k net profit for the year 8. securebet ( - Turned $7 into $640 (+9244%) on a series of temperature bets in NYC and Seattle. 3077 predictions, top 0.04% by metrics. Focus on small bets ($3-20) with high growth on low quotes. High win rate thanks to NOAA data 9. automatedAItradingbot ( Micro/low-cost bets (0.4¢–15¢) on specific outcomes, especially weather thresholds in Seoul/London and fighter matchups.Explosive wins (300%+ on select weather 1,000–5,000% average ROI across successful weather specialists based on this traders Tools and Automation > ( - Built specifically for Polymarket weather traders. Offers real-time multi-model forecasts (GFS, ECMWF, etc.), temperature range dashboards, climate pattern guides per city/station, and settlement station details. Includes educational guides on seasonal biases and forecasting challenges—highly recommended for NYC/London/Atlanta markets. > ( — Free guide/resource hub for weather betting on Polymarket. Covers market overviews, settlement rules >Tropical Tidbits ( - US GFS and ECMWF Europe models for temperature, precipitation, hurricane forecasts. Updates every 6 hours. Ideal for comparing models if 3+ agree, the probability is high >Climate Reanalyzer ( - real-time maps of air/ocean temperature, precipitation anomalies. With historical context for calculating probabilities >Windy ( - interactive maps of wind, temperature, rain, snow. 10+ models, for local events NOAA Climate Data Online ( - 100+ years of historical location data NOAA Weather Prediction ? >Center ( - short forecasts for precipitation, anomalies. Climate Prediction Center ( - long-term ENSO, droughts >Open-Meteo ( - Completely free open-source weather API with no key required. Provides GFS, ECMWF-derived, and ensemble forecasts for temperature, precipitation, and more at hourly/sub-hourly resolution globally. Excellent for scripting quick checks on NYC/London highs or comparing multiple models. Direct API calls make it ideal for automation or batch probability calculations. >OpenWeatherMap ( = Free tier gives current conditions, 5-day/3-hour forecasts, and 16-day daily forecasts. Good for real-time verification and basic historical pulls (limited free). Use for cross-checking Polymarket ranges before resolution. >Visual Crossing Weather ( - Free tier includes historical data (50+ years), current conditions, hourly/sub-hourly forecasts, and alerts. Strong for querying specific cities >WeatherAPI. com ( - Free plan covers real-time, hourly, daily forecasts (up to 14 days), historical data (from 2010), and bulk requests. Reliable for urban stations and includes marine/pollen extras if needed. Quick Tips for Using These in Trading >>>Cross-verify 3+ models (e.g., GFS + ECMWF via Open-Meteo + Windy) → if 80%+ agree on a range/threshold, probability is often very high for "Yes" bets under 10-15¢. >>>Focus on major stations (e.g., Central Park for NYC, Heathrow for London) - check settlement rules on Polymarket pages. >>>ADD TO BOOKMARKS so you don't lose alpha information

Aleiah

77,547 просмотров • 8 месяцев назад

How to make money on the weather using Polymarket I've been noticing more and more traders quietly printing on Polymarket's weather markets lately - and the category is exploding for a reason. Weather has always been super predictable for meteorologists (and us normals) right up to the day of. The whole point? You can earn easy, near-certain yield just knowing it'll rain in London tomorrow. I'm sharing a finished tutorial with you. Here is a small list of traders 1. gopfan2 ( - The absolute leader in weather. Earned over $2M in net profit by focusing on temperature and precipitation. Strategy - buy Yes below 15 cents, No above 45 cents, with risks of less than $1 per position. It dominates the NYC and London markets where the weather is predictable 2. enzocostapt81 ( is a weather-exclusive trader whose profile shows a complete wipeout in resolved positions-no active/open trades, current positions value $0.00, and all listed markets (resolved) at -100% P/L. The trader focused solely on daily/precise temperature predictions in major cities like New York City and London. 3. 0x594edb9112f526fa6a80b8f858a6379c8a2c1c11 ( 100% of active positions are weather/temperature markets across cities like Dallas, London, Seattle, Atlanta, NYC, and Toronto-focused on precise daily highs/thresholds/ranges. 4. meropi ( - Earned ~$30k on micro bets ($1-3) with multipliers up to 500x. Automated bets on temperature rise for 0.01 cents. Focus on speed to capture momentum in daily markets. One of the most stable in weather 5. 1pixel ( - $18.5k profit from $2.3k deposit, weather only (NYC and London) 6. erb80 ( Dominant focus-two massive Atlanta temperature range bets for Dec 17, with enormous share volume at ultra-low entries (0.1¢) turning into huge unrealized gains (+49,550% on the main one) 7. Hans323 ( - Earned $1.1M on one temperature trade in London. Started with $741 in January 2025 and increased to $87k net profit for the year 8. securebet ( - Turned $7 into $640 (+9244%) on a series of temperature bets in NYC and Seattle. 3077 predictions, top 0.04% by metrics. Focus on small bets ($3-20) with high growth on low quotes. High win rate thanks to NOAA data 9. automatedAItradingbot ( Micro/low-cost bets (0.4¢–15¢) on specific outcomes, especially weather thresholds in Seoul/London and fighter matchups.Explosive wins (300%+ on select weather 1,000–5,000% average ROI across successful weather specialists based on this traders Tools and Automation > - Built specifically for Polymarket weather traders. Offers real-time multi-model forecasts (GFS, ECMWF, etc.), temperature range dashboards, climate pattern guides per city/station, and settlement station details. Includes educational guides on seasonal biases and forecasting challenges—highly recommended for NYC/London/Atlanta markets. > - Free guide/resource hub for weather betting on Polymarket. Covers market overviews, settlement rules > - US GFS and ECMWF Europe models for temperature, precipitation, hurricane forecasts. Updates every 6 hours. Ideal for comparing models if 3+ agree, the probability is high > - real-time maps of air/ocean temperature, precipitation anomalies. With historical context for calculating probabilities > - interactive maps of wind, temperature, rain, snow. 10+ models, for local events NOAA Climate Data Online - 100+ years of historical location data NOAA Weather Prediction > - short forecasts for precipitation, anomalies. Climate Prediction Center - long-term ENSO, droughts > - Completely free open-source weather API with no key required. Provides GFS, ECMWF-derived, and ensemble forecasts for temperature, precipitation, and more at hourly/sub-hourly resolution globally. Excellent for scripting quick checks on NYC/London highs or comparing multiple models. Direct API calls make it ideal for automation or batch probability calculations. > - Free tier gives current conditions, 5-day/3-hour forecasts, and 16-day daily forecasts. Good for real-time verification and basic historical pulls (limited free). Use for cross-checking Polymarket ranges before resolution. > - Free tier includes historical data (50+ years), current conditions, hourly/sub-hourly forecasts, and alerts. Strong for querying specific cities > - Free plan covers real-time, hourly, daily forecasts (up to 14 days), historical data (from 2010), and bulk requests. Reliable for urban stations and includes marine/pollen extras if needed. Quick Tips for Using These in Trading >>>Cross-verify 3+ models (e.g., GFS + ECMWF via Open-Meteo + Windy) → if 80%+ agree on a range/threshold, probability is often very high for "Yes" bets under 10-15¢. >>>Focus on major stations (e.g., Central Park for NYC, Heathrow for London) - check settlement rules on Polymarket pages. >>>ADD TO BOOKMARKS so you don't lose alpha information

Valentin

17,150 просмотров • 4 месяцев назад

This Chinese guy built a Second Brain in Obsidian and every morning gets 3 trading ideas that brought him $180,000 in 6 months. Inside he runs a pipeline of 6 workflows on N8N that automatically pulls every read article, listened podcast, and voice note into a shared Obsidian vault, and a neural network analyst every morning at 6:00 finds connections between the fresh and the old and puts the 3 strongest trading ideas for the day into the inbox. No analytics desk, no Bloomberg terminal, no Telegram chats with traders. Just a Mac Mini by the wall, an iPhone in the pocket, and 1 local Obsidian vault. And traditional quant funds keep entire teams of 8 people on salary for the same flow of insights, while his expenses are only subscriptions to Readwise, Whisper API, and N8N hosting. 6 pipelines process about 200 sources a day and close the monthly API bill at about $120. The Mac Mini itself stores the entire vault and keeps the neural network analyst running 24/7, and from the iPhone the owner drops any idea he hears on the go into a Telegram bot, and it lands in the vault inbox in just 30 seconds. The starting instruction that sits in the VAULT.md file at the root of his vault looks like this: "you are the AI analyst of a solo trader. you read his vault every morning at 6:00, find connections between fresh and old notes, and deliver 3 trading ideas he can verify in the hour before the market opens. pipelines: // Reader (pulls every article and highlight from Readwise, Twitter bookmarks, and Kindle into /notes) // Listener (transcribes podcasts through Airr and voice notes through Whisper, puts them in /notes) // Catcher (accepts any message from the Telegram bot and writes it to /inbox with a timestamp) // Connector (every night reads across the entire vault and updates the connection graph between 4,000 notes) // Briefer (at 6:00 AM writes a brief: 3 trading ideas for today plus the emerging thesis of the week, puts it in /inbox) // Mobile (lives in the iPhone, answers any question about the vault by voice, and confirms alerts while the owner is on the go). you wake the owner with a push notification only when a fresh note contradicts his active thesis or when 1 of the 3 morning ideas has a confidence score above 90%." This instruction immediately sets the role for the system and the limits of its autonomy. It knows it is supposed to connect new with old on its own. It knows it is supposed to prepare 3 trading ideas every morning on its own. It knows it connects the live trader only when a thesis is contradicted or an ultra-confident idea appears. → Reader pulls about 80 articles and highlights a day from Readwise, Twitter, and Kindle → Listener transcribes 4 to 6 podcasts a week through Airr and Whisper → Catcher intercepts all voice and text ideas through the Telegram bot, averaging 15 to 20 a day → Connector updates the connection graph between 4,000 notes every night, adding 25 to 30 new edges → Briefer puts a fresh brief with 3 trading ideas and the emerging thesis into the inbox at exactly 6:00 → Mobile answers any question about the vault by voice and confirms alerts right from the iPhone And only when a new note contradicts his active thesis or 1 of the ideas breaks 90% confidence does the orchestrator raise the owner with a push notification. And when the trader at that moment is driving to the gym or eating breakfast, the Mobile agent in his iPhone answers any quick question about the vault by voice: what he wrote about this ticker last week, which 3 sources support the idea of long NVDA, and what counter-thesis already sits in his notes. The trader makes the decision and sends the order before New York opens. The fresh brief from last Monday looks like this: "reader: 78 materials added over the weekend, 11 of them about semiconductors, 4 about energy, 3 about biotech. passing to connector." "connector: 27 new connections found between fresh materials and the vault, the strongest one is that the Goldman report from Wednesday matches the NVDA thesis you wrote 3 weeks ago." "briefer: 3 trading ideas for today: long NVDA (confidence 0.84), short Tesla at the close of the quarterly report (0.71), watch URI (0.62). emerging thesis of the week: the market is underpricing capex on data centers." "alert: your fresh note about long-term risk in semis contradicts the NVDA thesis. sending for review." In his work setup there is no cloud server, no team of analysts, and not even a Bloomberg subscription. At home sits a Mac Mini with a local Obsidian vault, on top run 6 N8N pipelines and a neural network analyst, and the same vault mirrors to a secure terminal on the iPhone. Out of everything I have seen this year, this is the cleanest solo trading setup on a second brain: $120 a month on the API, about $30,000 a month into the account, and between them 6 pipelines, 4,000 connected notes, and 1 iPhone in the pocket.

Blaze

930,842 просмотров • 4 месяцев назад

10 TRUMP POSITIONS NOBODY IS TALKING ABOUT. MOST OF THEM CONTRADICT HIS OWN POLICIES!!! Everyone covers the Nvidia and Boeing. Nobody reads past them. We went through the filings properly. First, for scale. Joe Biden made 13 stock trades in his entire presidency. Trump's 2025 annual disclosure lists 21,235 transactions. That is nearly as many as the entire rest of the Executive Branch filed in the same period, across 8 separate accounts. His own first term, in 2017, had 86. Now here are the ones nobody covers. 1️⃣ Invitation Homes He signed an executive order to stop large institutional investors from competing with regular families for single family homes. His accounts bought $250,000 to $500,000 of Invitation Homes, one of the largest institutional owners of single family rental homes in America. The stock sold off when those announcements landed. He owns the exact thing the policy targets. 2️⃣ Coupang 18 separate trades in a South Korean e-commerce company between October 2025 and May 2026. Filings suggest he may still hold up to around $130,000. All of it during active trade friction with Korea and a data breach investigation by Korean regulators. 3️⃣ Toyota A Japanese automaker, in a portfolio belonging to the president tariffing foreign vehicles and demanding domestic production. 4️⃣ Procter & Gamble Enormous global supply chain, heavily exposed to imported materials and packaging. Tariffs raise their input costs directly. He owns it anyway. 5️⃣ Carvana Bought $250,000 to $500,000 on January 6, 2026. Online used car retailer. Tariffs on imported parts and vehicles push costs up across the entire auto market. 6️⃣ Axon Enterprise This is the timeline that should get more attention than it does. February 10, the accounts buy $1 million to $5 million of Axon. February 24, fourteen days later, ICE posts a solicitation for a five year, $220 million Taser contract. Roughly 17,800 units. The solicitation never names Axon. The technical specs match their Taser 10 almost exactly, and Axon holds around 90% of the US Taser market. 7️⃣ GEO Group and CoreCivic The two largest private prison operators in the country, both directly exposed to detention capacity. Held while running the largest immigration enforcement expansion in modern history. 8️⃣ Blue Owl Capital A business development company yielding 10 to 12%, lending to middle market businesses. Then he signed an executive order easing the rules so 401k money can flow into private equity and private credit. Sign the order. Collect the dividend. 9️⃣ PulteGroup Multiple purchases through late 2025 in one of America's largest homebuilders. Bill Pulte, grandson of the founder, was nominated to run the Federal Housing Finance Agency, which oversees Fannie Mae and Freddie Mac. Family name on the company. Family name on the regulator. 🔟 Palantir Everyone knows he praised it publicly. Fewer people know that in the same quarter, his accounts bought $200,000 to $680,000 of it and sold between $1 million and $5 million. He was a net seller of the stock he was promoting. So what is the pattern? ➡️ Some holdings benefit enormously from his policies. Prisons, private credit, defense, homebuilders. ➡️ Some are actively damaged by them. Toyota, P&G, Carvana, Coupang. ➡️ And at least one, Invitation Homes, is the specific business his own executive order was written to restrict. That last category is the interesting one, because it argues against the simple version of this story. If someone were deliberately trading policy, they would not be long the companies their own tariffs hurt. The White House position has never changed. The accounts are managed independently by third party institutions with sole authority over investment decisions. Maybe. But 21,235 transactions in one year across 8 accounts, in dozens of companies regulated by the government he runs, is not a normal situation for anyone to be in. Regardless of who is pressing the buttons.

Donald Trump Stock Tracker

145,232 просмотров • 1 месяц назад

【Seedance2.0 4Kカリスマ - メンズダンステンプレ】 Dreamina( Dreamina AI )に4K来てたので使ってみました! 15秒で1890クレジットでした😏 #DreaminaAI #DreaminaCPP メンズを踊らせたいメンツいるよなー?🔊😎 と、いうわけでイケメンを踊らせたい民の皆さま… こちらがメンズ用のマルチカットダンスプロンプトでございます。 (ちょっと人外のエグいパワームーブしてますが、2回4K使う度胸はなかったですw ) キャラクターシート1枚参照させて15秒ドンっです! 👇 Prompt: Use the exact same character from the reference image. Preserve facial identity, hairstyle, outfit, colors, body proportions, silhouette, and overall design with absolute consistency in every frame. No redesigns. No facial drift. No outfit changes. 9:16 vertical format. The character performs an elite-level hip-hop dance performance with irresistible charisma, confidence, musicality, and effortless swagger. Dance style: premium commercial hip-hop, urban choreography, deep groove, musicality-driven movement, powerful chest isolations, sharp shoulder hits, controlled body waves, dynamic footwork, clean transitions, strong rhythm control, elite professional dancer quality. The performance feels natural, relaxed, stylish, and highly skilled. Never stiff. Never robotic. Continuous micro-groove throughout the performance. Natural breathing. Natural weight shifts. Authentic rhythm. Confident presence. The character commands attention from the very first frame. VIDEO STRUCTURE CUT 1 (0.0s–0.8s) Cowboy shot. The character is already moving when the video begins. Subtle groove active. At the first musical accent: sharp chest isolation, immediate shoulder hit, quick neck snap. The movement feels unexpected, precise, and highly skilled. Strong confidence. No posing. No stopping. CUT 2 (0.8s–3.5s) Full-body shot. The dancer explodes into groove-driven choreography. Strong bounce. Powerful rhythm. Clean footwork. Dynamic weight transfer. Large movement quality. Camera smoothly follows movement. CUT 3 (3.5s–5.5s) Low-angle hero shot. Large body roll. Strong directional movement. Powerful silhouette. Natural clothing movement. The dancer dominates the frame. CUT 4 (5.5s–7.5s) Medium cowboy shot. Focus on groove quality. Chest isolations. Shoulder grooves. Body waves. Clean musicality. Camera subtly tracks movement. Every accent feels satisfying. CUT 5 (7.5s–11.0s) Full-body performance section. Most impressive choreography. Traveling steps. Direction changes. Complex groove combinations. Elite dancer energy. Maximum visual impact. CUT 6 (11.0s–13.0s) Slow-motion sequence. Controlled body roll. Fluid body wave. Beautiful movement quality. Premium dance-film aesthetic. Elegant momentum. CUT 7 (13.0s–15.0s) Cowboy shot. The dancer advances toward the camera while continuing choreography. Confident swagger. Natural groove. Camera slowly pushes forward. Final musical accent. Strong finishing pose. Iconic ending frame. CAMERA STYLE Viral social-media dance cinematography. Fast pacing. Strong visual hooks. Character always remains dominant in frame. Alternating cowboy shots and full-body shots. Smooth tracking shots. Dynamic push-ins. Low-angle hero shots. No face close-ups. No unnecessary camera spinning. No empty establishing shots. No slow introduction. No static posing. VISUAL STYLE Luxury fashion campaign. High-end dance film. Premium music video production. Global superstar energy. Cinematic contrast. Rich blacks. Warm skin tones. Deep shadows. Subtle film grain. Beautiful skin rendering. Ultra photorealistic. 4K. Extremely detailed skin texture. Detailed fabric materials. Natural cloth simulation. Natural motion blur. Realistic inertia. Realistic weight transfer. Authentic professional dancer movement. 24fps. The final result should feel like a viral dance clip from a world-class performer, combining elite dance skill, irresistible charisma, cinematic quality, and maximum social media engagement.

Zeto

76,492 просмотров • 3 месяцев назад

The countdown to chaos begins. GPT Image 2 + Seedance 2.0 on Thank You AI prompt Use [Image 1](image_1)only as the layout, shot-order, camera, staging, screen direction, pacing, and spatial continuity reference. Treat every storyboard panel as an individual shot. Ignore storyboard drawing style, simplified anatomy, panel text, headers, borders, annotations, scribbles, malformed props, duplicate silhouettes, stray marks, icons, and effect sketches. Use @[Image 3](image_3) only for Character 1's final appearance, face, body proportions, long wavy blonde hair, black long coat, gloves, wardrobe materials, and overall likeness. Use @[Image 2](image_2)only for Character 2's final appearance, face, body proportions, short hair, dark hoodie, wrist device, multi-barrel handgun, wardrobe materials, and overall likeness. Create a photorealistic 15-second cinematic Hollywood action trailer with seamless continuity, maintaining exactly two lead characters throughout every shot. CHARACTER LOCK • C1: Female whip duelist only. Uses only a glowing crimson energy whip attached to her hand. • C2: Male gunner only. Uses only a blue wrist holographic device and a futuristic multi-barrel handgun. • Never merge identities. • Never duplicate either character. • Never introduce additional heroes. • Background pedestrians, guests, taxis and vehicles remain simplified environmental extras only. VISUAL STYLE Ultra photorealistic. Bright daytime. Gritty cyberpunk realism. Wet reflective New York streets. Orange construction barriers. Yellow taxis. Steam rising from manholes. Glass skyscrapers reflecting sunlight. Modern luxury glass building with a red carpet entrance. Purple architectural accent lighting. Hollywood blockbuster cinematography. Natural motion blur. Volumetric smoke. Practical explosions. Lens flares. Realistic debris. High-speed tracking. Large-scale cinematic lighting. 4K feature-film realism. Maintain consistent geography from the street battle into the red-carpet location. SHOT SEQUENCE SHOT 1 Street-level camera positioned behind C1 on wet reflective asphalt. Steam rises from a nearby manhole. C1 plants her feet and swings the crimson energy whip low across the pavement, generating a bright red whip trail that lashes sideways while the city reflects in the wet road. SHOT 2 Wide tracking shot. C1 launches into the air over an exploding yellow taxi. Fire and debris erupt behind her as the crimson whip forms a long glowing arc through the bright daytime skyline. SHOT 3 Extreme floor-level insert. Close on C1's boot striking wet pavement while the whip tip cracks the asphalt, sending sparks, shattered concrete and glowing fragments outward. SHOT 4 Low tracking shot beside C2 sprinting directly toward camera through drifting smoke. His glowing blue wrist device illuminates one raised arm while debris flies behind him. SHOT 5 Close-medium shot. C2 extends his arm forward. A bright cyan holographic grid rapidly projects from the wrist device, expanding outward while taxis and skyscrapers remain visible in the background. SHOT 6 Extreme close-up. C2 draws a futuristic multi-barrel handgun. The weapon fires its first brilliant blue energy shot, producing an intense muzzle flash with cinematic lens flare. SHOT 7 Bird's-eye overhead shot. Street geometry clearly visible below. C1's crimson whip trail and C2's blue muzzle fire cross dramatically through opposite corners of the frame while both characters remain small at opposite edges. SHOT 8 Slow-motion tilted action shot. C2 vaults over an exploding taxi as blue muzzle flashes continue beneath him. Fireballs, smoke and debris scatter realistically through the air. SHOT 9 Hard cinematic location transition. Wide establishing shot outside a luxurious modern glass building. Bright daylight continues. A pristine red carpet stretches toward the entrance. Elegant guests stand watching. C1 and C2 occupy opposite ends of the carpet. No weapons active. No energy effects visible. SHOT 10 Close two-shot. C1 and C2 stand only an arm's length apart on the carpet. Absolute stillness. Silent confrontation. Controlled breathing. Intense eye contact. Purple architectural lighting reflects softly on the glass facade. SHOT 11 Medium shot. C2 slowly raises one hand and pulls his hood over his head while already turning three-quarters away from C1 toward the entrance. C1 remains perfectly still behind him. SHOT 12 Maintain identical framing and geography from Shot 11. C2 calmly walks toward the building entrance as guests subtly turn to watch. C1 stays motionless at the edge of frame, silently observing his departure. Hold on the unresolved tension before fading to black. CAMERA STYLE Aggressive cinematic tracking. Steadicam. Drone overhead. Ground-level perspectives. Extreme close-ups. Wide establishing shots. Smooth transitions. Natural handheld energy during action. Controlled locked-off framing during the red-carpet sequence. ACTION STYLE Fast. Powerful. Readable silhouettes. Fluid stunt choreography. Heavy environmental interaction. Convincing physics. No exaggerated anime motion. Grounded Hollywood realism. COLOR PALETTE Bright daylight. Warm sunlight. Wet asphalt reflections. Crimson energy whip. Brilliant blue muzzle flashes. Cyan holographic projections. Orange construction barriers. Yellow taxis. Black wardrobe. Red carpet. Purple entrance lighting. Natural skin tones. AUDIO Large cinematic orchestral hybrid score. Driving trailer percussion. Deep sub-bass impacts. Powerful whip cracks. Explosive booms. Metal and glass debris. Blue energy weapon blasts. Holographic interface tones. Crowd ambience fading into near silence at the red carpet. The final moments become quiet, tense and emotionally restrained before ending with a dramatic cinematic trailer hit.

Sharon Riley

43,583 просмотров • 2 месяцев назад