Oliver

Uzbekistan recently played at the World Cup for the first time in their history. And in this video an Uzbek fan is sitting in the stands. A 2022 World Cup quarterfinal broadcast plays next to her. Where Uzbekistan wasn't. The video was generated before Uzbekistan ever had fans at a World Cup. Nobody in the comments noticed. Pause at 0:03. A girl in a white UFA jersey, number 7. Uzbekistan flag on her cheek. Eating a burger. An "AI generated" label is on the video. TikTok flagged it itself. The algorithm still pushes it. Three real score overlays from the 2022 World Cup. Morocco-Portugal 1-0. Iran-England 0-2. Scotland-Switzerland 1-1. Real scores convince. Nobody fact-checks. This format still works. This format hasn't been exposed yet. Veo3 is still in beta. Real scores still convince. AI fans still slip through. In six months everyone will know that half of those fans are generated. Until then the video will rack up millions. Right now they're paying those who got there first.

@YourAlphaMom Remember when AI couldn't draw hands? 😀

New body-physics test for the best AI video tools: The newly released Grok Imagine 1.5, the king Seedance 2.0, Google’s “revolutionary super-duper” Gemini Omni Flash, and the old-timer Kling 3.0 Pro. This time I tested how each model handles realistic running motion, body movement, fabric physics, and natural secondary motion. And the result was much less obvious than I expected. Believe it or not, I can’t call Seedance the clear winner this time. Each model got several attempts. - Grok Imagine 1.5: The new version is finally available on the official Grok website, so I could properly test it. Honestly, I didn’t notice a massive improvement over the previous version. Still, the result was acceptable. It produced the most cartoonish image, and the woman runs as if she’s wearing heels, but the body physics were decent enough. It also understood the instructions quickly and followed them correctly. - Kling 3.0 Pro: The old man decided to test my patience. It repeatedly blocked a simple running scene as adult content, then misunderstood the instructions several times. The successful result has the most realistic lighting and frame rate, but the actual body physics look strange. It almost feels like loose foam padding is bouncing inside the leggings. There are also several visible artifacts and unnatural movements. - Gemini Omni Flash: As usual, it gave me that strange slow-motion, low-FPS look that Google models seem to love. But it didn’t censor anything, understood the instructions immediately, and produced a beautiful, realistic result. Surprisingly, this is the output I liked the most in this test. - Seedance 2.0: Seedance also blocked a couple of generations, just like Kling, but eventually produced a strong result. It delivered the most beautiful and visually appealing footage, but I honestly expected better physics. The video looks great, yet I can’t confidently call it the most physically accurate result. - My ranking: 1. Gemini Omni Flash — not perfect, but the best overall result for me 2. Seedance 2.0 — visually stunning, but I preferred Omni’s physics 3. Grok Imagine 1.5 — cartoonish look and strange running, but still acceptable 4. Kling 3.0 Pro — the longest wait, the strangest physics, and the most inconsistent result Do you agree with my ranking? #AIVideo

@ZentrixHQ seedance my favorite

📖THE SEEDANCE 2.0 PROMPT FORMAT THAT NOBODY IS USING BUT EVERYONE SHOULD Most people use Seedance 2.0 wrong. They type a normal prompt and wonder why the result looks generic. The difference between these two visuals isn't a better idea — it's a better prompt format. Normal prompt gives you a good result. JSON prompt gives you a cinematic one. Here's why it works: A normal prompt describes what you want. A JSON prompt tells Seedance exactly how to build the scene — camera movement, lighting angle, atmosphere, texture, depth, timing. You're not asking for a video. You're engineering one. The crystal dolphin jumping above an ancient courtyard with floating jellyfish — same concept, two completely different outputs. The JSON version has golden hour, dramatic clouds, volumetric light, and a sense of scale the normal prompt never reached. The glowing lotus fountain — same story. Normal prompt gives you a clean render. JSON gives you a full cinematic frame with layered depth, warm lantern light, and a composition that looks like it belongs in a feature film. The workflow that produces this: • Step 1 — Write your scene idea in plain language first •Step 2 — Ask Claude to convert it into a structured JSON prompt with fields for: subject, environment, camera, lighting, mood, motion, color grade • Step 3 — Paste the JSON into Seedance 2.0 • Step 4 — Take the best clip into Premiere Pro for final color correction and sound design The tools are free or cheap. The knowledge of how to prompt is what separates the results. This is the gap most creators never close. 📥 BACK TOMORROW. There will be new life hacks 🔖 The full guide is pinned below. Save it before you need it.

@slash1sol Agencies charging $20k. Claude charging $20.

THIS GUY GENERATED A PREMIUM SITE FOR AN F1 DRIVER INSIDE CLAUDE WHILE AGENCIES CHARGE $20,000 FOR THE SAME THING On screen is not just a business card site, it's a custom interactive portal for a Formula 1 driver. Spinning 3D helmet models you can rotate, dynamic scroll with massive typography, a photo grid and even a built in 8 bit mini game at the end. The question floating over the demo, asking if Claude really built this, sounds like a death sentence for sports marketers and traditional web studios. Packaging a personal brand at this level usually takes a full team, an art director, a motion designer and a couple of senior frontend engineers. Here's where it gets uncomfortable for celebrities and their managers. A promo site like this through an agency runs at least $15,000 and drags through months of endless calls. With a $20 Claude subscription, any content creator can ship a working prototype over a weekend without touching manual code. Full breakdown of how this was built in article below. Save & Read it today ↓

@radar24hvn You are right

@fomoliver Early adopters always have the advantage.

Entering the AI fan-cam niche right now costs $300 a month in tool subscriptions. Veo3 is still in beta. This filters out 90% of those interested. In six months the barrier drops to zero, and everyone enters. But the first ones take the biggest share. Pause at 0:08. A Swedish fan, gold chain bag, blue stadium seats. The video has an "AI generated" label on it. The platform itself flagged the generation. The algorithm still pushes it. Right now there are a few hundred creators working in the AI fan-cam niche. A few hundred, damn. Most came in the last two months. Half will quit in the first week when they realize there's no reach right away. Those who stay will take most of the market. This market isn't closed. This market hasn't saturated. This niche still isn't for everyone. Veo3 still costs money. The algorithm is still looking for creators. In 6 months the entry barrier drops to zero. Everyone comes in, the niche jams up. Right now only a handful have entered.

@YourAlphaMom The real alpha is learning distribution.

New action test: Seedance 2.0 vs Gemini Omni Flash vs Kling 3.0 Pro vs Google Veo 3.1. This time, a Lara Croft-style heroine had to escape armed enemies, perform multiple stunts, and shoot back during one complex action sequence. Each model got 4–6 attempts. I brought Veo 3.1 back instead of Grok Imagine. The reason is simple: Veo handled this scene better, while new Grok 1.5 still isn’t available on the official Grok website, so I left it out. - Google Veo 3.1: Predictably finished last, but I wouldn’t call the result terrible. It clearly looks weaker and more outdated than the others, but for such a difficult scene, the result was still acceptable. - Gemini Omni Flash: Not perfect, but still pretty good. The stunts, physics, and overall execution worked well. My main issue is Google’s familiar low-FPS look. The footage constantly feels slightly slowed down, which makes it less cinematic than both Seedance and Kling. Still, I liked the result, and it was strong enough to take second place. - Kling 3.0 Pro: Better than I expected. Its biggest problem is character consistency. The heroine and other characters become distorted during fast movement, with plenty of unnatural poses and animation errors when you look closely. The overall result is still acceptable. Worse than Gemini Omni Flash, but definitely better than Veo 3.1. - Seedance 2.0 This was Seedance’s territory. Complex action remains its greatest strength, and it started producing excellent results within the first few attempts. The physics, movement, instruction following, and overall intensity were all impressive. This might be one of the best results I’ve ever received from Seedance. This test once again shows that Seedance remains the king of difficult action scenes. - My ranking: 1. Seedance 2.0 — clearly on another level 2. Gemini Omni Flash — strong, but held back by the slow-motion feel 3. Kling 3.0 Pro — better than expected 4. Google Veo 3.1 — predictably failed again What do you think of the new test? #AIVideo

@Rulia2505 Aesthetic paradoxes...

@fomoliver "AI as a generator of aesthetic paradoxes" is the best framing of this whole moment I've read 🔥

More people have seen this Ghana fan than a real Ghana match. She doesn't exist in any stadium in the world. Only in Veo3. Pause at 0:04. Dark skin + white hair + blue eyes in one frame. In nature this combination almost never occurs. In the algorithm it's just a prompt. In the TikTok feed, damn, every 30 seconds. A white Puma jersey, Ghana flag on the lips, red seats in the background. The quality is such that in the first seconds you don't realize it's a render. TikTok itself flagged it as "AI generated", sees that it's not real, still pushes it. AI has become a generator of aesthetic paradoxes. Color combinations incompatible in nature. Faces you'd never meet on the street. Compositions no operator would catch by accident. She doesn't exist. Her appearance doesn't occur in nature. This scene never happened. > Veo3 drew her in 30 seconds. > TikTok found the audience in an hour. In a year, ordinary faces in the feed will start to feel boring. AI has already found its new aesthetic, and it beats real ones on reach.

@ChungDinh73379 The competition was never AI vs humans. It's attention vs everything else.

@fomoliver このガーナのファンよりも多くの人々が彼女を見た。自然でほとんど起こらないダークスキン+白髪+青い目の組み合わせ。AIは美的逆説のジェネレータになった。Veo3が30秒で描いた。 TikTokは1時間で観客を見つけた。果たして、AIがリーチでリアルなものを打ち負かすのか。 次は何が起こるでしょうか？

@Rulia2505 Grandma discovered the ultimate age hack.

A 60-year-old grandmother just became a 25-year-old model. In her sweater. In her kitchen. In one afternoon. Pause at 0:06 — that's the moment the algorithm stopped caring about age, makeup, or genetics. Anyone can be anyone now. The only filter left is who hits "post" first. Drop a name + I bet she'll do it next 👇

@ZentrixHQ The wedding industry is about to discover AI agencies

📖BUILDING AN AI WEDDING CONTENT STUDIO WITH SEEDANCE 2.0. AI Startup of the Day #8. Wedding vendors — photographers, venues, florists, planners — all need portfolio videos to attract clients. Most have great photos but zero video presence. Here's exactly how to start: • Step 1 — Find wedding venues and photographers on Instagram or wedding directories like Hitched and Bridebook. Look for beautiful photo portfolios with no video content. • Step 2 — Generate a cinematic wedding atmosphere video in Seedance 2.0:
"Elegant wedding reception, fairy lights, slow motion flower petals, golden hour, romantic cinematic grade" • Step 3 — Send the sample to the venue or photographer with an offer: "Full portfolio video pack — $900." Wedding vendors have clear seasonal budgets and plan months ahead. • Step 4 — Time your outreach for January–March when wedding vendors prepare their marketing for peak season. That's when budgets open up. The numbers: 
4 vendors × $900 = $3,600/month during peak outreach season
Off-season: offer highlight reels at $400 each to stay active year-round. Wedding vendors rely entirely on visual content to win clients. A strong video sample sells itself. 📥 Tomorrow's startup might be bigger than today's. Stay tuned. 🔖 The complete guide is waiting in the pinned post. You'll thank yourself later.

@rileywestreel Most people are waiting for certainty.

Dario Amodei (CEO, Anthropic): "The biggest surprise of the last three years isn't the technology, it's how few people realize how close we are to the end of the exponential." in a 9-minute interview, Dario Amodei breaks down why RL now scales exactly like pre-training did, and why that puts us closer to the finish line than almost anyone admits while everyone keeps arguing the same tired hot-button issues, he says the exponential is about to hit its ceiling, and almost no one has priced it in. Watch the talk, then read the article below.

@Flandermaxx Every regulation is just a startup idea wearing a suit.

A 26 year old in Shenzhen. He makes 4.1 million yen a month. Off Tokyo firms that banned AI. Every line he ships is AI. In January he watched a Japanese news segment. A Tokyo real estate firm had banned AI for first year engineers. He saw the arbitrage in four minutes. Three more firms followed in two weeks. The work still had to ship. It just had to ship without the smell. He registered on Lancers as Kentaro Yamada. He paid a Beijing studio 4,200 RMB for a one minute intro video. Soft, accented Japanese. A rented coworking desk in Daikanyama. He had never been to Tokyo. The pitch was one line. No generative AI. Written by hand. Reviewed three times. First contract on day nine. 38,000 yen. A backend module in Node. He fed the spec to Claude. A wrapper stripped the model's rhythm. It cut the long sentences. It renamed every variable. Cadence of a mid level Japanese coder. Delivered in 14 hours. The client wrote back. This is exactly the human work we paid for. Month five. 31 active contracts. 4.1 million yen booked in May. One client paid 612,000 yen for a CRM module. The agent finished it while he was at hotpot. pause at 0:46 of the intro. Behind his left shoulder. A paper wall calendar on a small shelf. The characters are simplified. Japan only uses traditional. The only honest object in the frame. The profile photo was generated. The voice was cloned from a podcaster he never met. The Daikanyama desk was empty. The Hong Kong account was the only other real thing. A Tokyo developer forum ran the audio through a clone detector. 1,800 replies in one night. Lancers suspended the account in 48 hours. He had already registered four more. His girlfriend in Shenzhen still thinks he writes mobile games. The firms banned AI to protect their engineers. He pulls 4 million yen a month to pretend he is one.

@Awakend_Citizen LEFT 👨⚽ RIGHT 👨📸⚽⚽

おっぱいガン見してるところを全世界に中継されたオッサンの今後が気になる

@kilo_cpa retail gets the recipe. desks own the kitchen.

55gb of l2 order book data. cointegration formulas. ornstein-uhlenbeck calibration. the article is real and the math is correct. the edge it describes belongs to people you cannot beat at it → the math tells you when a 200ms gap opens between polymarket and kalshi → closing that gap requires colocated servers, direct feeds, tuned routers, six-figure capital ready to cross instantly → none of that infrastructure is in the github repo a desk running these models earns the spread because it arrives first a retail trader running these models reads the same imbalance, submits the order, and takes the worse side of the spread what actually transfers to retail: → the dataset is useful research material, not a trade pipeline → knowing what desks look at lets you stop trying to compete on the same surface → the only retail-survivable lane is the markets where desks do not deploy capital the formulas are the floor of a quant desk's operation, not its edge we wrote the retail version of this last week. eight wallet archetypes, twelve metrics, a watchlist for finding traders in markets the desks haven't touched yet → read this article to see what desks do → read ours to see what retail can do → the formulas are not the moat. latency is.

@ZentrixHQ the craziest part is that $600 will look expensive in a year.

Day 4 of building an AI explainer video studio with Seedance 2.0 SaaS startups need explainer videos for landing pages, investor decks, and onboarding flows. Most pay $1,500–4,000 to agencies with 3-week turnarounds. The counter-offer: $600, delivered in 48 hours. - Script with Claude. - Visuals with Seedance 2.0. - Voice with ElevenLabs. - Final edit in CapCut. Total production time per video: 4–5 hours. Find clients on Product Hunt, Indie Hackers, and LinkedIn. Message founders the week they launch — that's when they need everything at once. Six projects a month is $3,600. The bottleneck is outreach, not production. Now you understand that you can create absolutely anything: clips, commercials, films, content for social networks. I will continue to work in the format - startups from 0. Do you like this content? 🔖The article with the full guide is pinned below, bookmark it for later use.

@Rulia2505 infinite content glitch unlocked.

He turns into followers. Someone asks in the comments: "can you do Tyson?" He answer with ine video. Face-swap. AI. 30 second of work. Pause at 0:07. Not a filter. Not a custome. A completely different human built on top of his face. Every video — a new follower. Every follower — a new comment. Every comment — a new view. He isn't chasing a trend. He became a machine that turns comments into content.

A girl on TikTok pulled 72,400 likes off a single World Cup match. This content didn't exist three months ago. Now TikTok pushes it harder than goals from the players. AI fan-cam World Cup has become a separate category in the algorithm, and it's growing faster than anything else tied to the tournament. Pause the video at 0:11. The CapCut template "Football AI Trend" by "Painkiller" has been used 2,464 times. The post by "Elyas": 72,400 likes, 15,700 reposts, 11K bookmarks. You can only imagine how many sponsorship offers landed in her DMs. She didn't buy a World Cup ticket. She didn't film a video. > CapCut placed her on the stands. > TikTok found the audience itself. The algorithm already figured out this category is growing. The World Cup window stays open for four weeks, then the peak goes away with the tournament and gets replaced by new ones. Something to think about.

@ZentrixHQ getting fired is becoming the best growth hack.

📖 He is 43 years old and was fired from his job, so he created an AI girl to make his employer jealous. He earned $7,000 and 10,000 followers in the first month. Ji-hoon worked at a factory that manufactured mobile phones for a famous brand and the manager came to him and told him to leave the sales department and the most he could do was package phones. Ji-hoon said that he had devoted 10 years to the company and he would not package phones because his calling was marketing and sales. After these words, he was fired and the man remained unemployed. Then he came across an advertisement with a free guide to creating an AI agent that could manage social networks. And earlier he had seen how his employees often subscribed to similar social networks and he decided to try it. His first video with an AI girl, which he created as a joke, quickly went viral. His former employees started signing up for it, and his director even donated to promote and develop the project, without even knowing that it was actually Ji-hoon's project 🔖Attached below is an article with his method of creating an AI agent