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🚨‼️Sharing a few frames from our backyard security camera taken very early this morning. This anomaly persisted for several minutes and showed smooth movement, shape changes, and pulsing brightness. There was no rain, no visible insects, and no obvious light source. We’re not claiming this is anything extraordinary, but...

204,381 görüntüleme • 8 ay önce •via X (Twitter)

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"But where's the flash?" Watch this CNN demonstration of 6g of PETN being ignited by open flame. What happens? The PETN burns with a visible flame for several seconds. Then it detonates. The detonation happens so fast there is no visible flash — the camera goes straight from fire to debris field. And here's the key: the fire that WAS there is blown OUT by the blast wave. This is not a shaped charge. This is unconfined PETN in open air. No flash. No fireball. The blast wave actually extinguishes the existing flame. Why? Three reasons: PETN's reaction zone is measured in microns and completes in nanoseconds (Anderson et al., Propellants Explosives Pyrotechnics, 2022). At gram scale, the entire detonation event is over in single-digit microseconds. A 30fps camera captures 33,000 μs per frame. The event occupies <0.03% of one frame. The visible "flash" people expect from explosions comes from compression-heating of surrounding air — not the explosive itself. At gram scale there simply isn't enough gas volume being heated to produce visible light that registers on a standard camera. In a shaped charge, it's even less visible because the energy is directed INTO the target as a hydrodynamic metal jet (Munroe effect), not radiated outward as heat and light. The Hezbollah pager attacks (Sept 2024) used 3-6g PETN per device. Watch the CCTV footage — no fireballs. Just a pop and casualties. Sandia National Labs detonates ~32mg PETN and researchers stand next to the chamber in safety glasses. No flash. No fire. "No flash = no explosive" is a Hollywood education, not a physics one. Joe Rogan shaw

Jon Bray

25,456 görüntüleme • 5 ay önce

Rainy morning, unexpected rescue. Sometimes kindness finds you. Created with Seedance 2.5. Prompt: Create a 15-second ultra-realistic cinematic emotional video set on a rainy morning. Maintain the same young woman and the same small kitten consistently throughout every scene. Natural acting, realistic physics, detailed rain, cinematic lighting, smooth camera movement, shallow depth of field, realistic facial expressions, and seamless scene transitions. Scene 1 — Breakfast on a Rainy Morning (0–3s) Inside a cozy modern home during early morning. A young woman with long straight dark hair is sitting at a dining table, peacefully eating breakfast. Warm natural morning light enters through the large window. Her breakfast, a cup of tea/coffee, and simple tableware are visible. Outside the window, the sky is dark and rain is beginning to fall. The atmosphere feels calm and cozy. Camera: Medium cinematic shot, slowly pushing toward the woman. Scene 2 — She Notices the Rain (3–5s) The woman suddenly hears the sound of heavy rain. She pauses while eating and looks toward the window. The camera moves closer to her face as she notices the rain falling heavily outside. Raindrops cover the glass, with a realistic rainy neighborhood visible in the background. Camera: Close-up on her face, then rack focus from her face to the rain-covered window. Scene 3 — The Kitten Is Trapped (5–7s) Cut to outside. A tiny fluffy kitten is stranded in a corner beside a wall and some plants. The kitten is completely soaked by the rain, shivering and looking frightened. Water is flowing across the ground and rain is falling heavily around it. The kitten tries to move but is trapped in the narrow sheltered corner. Camera: Low-angle close-up of the wet kitten, with cinematic rain droplets and realistic fur detail. Scene 4 — The Rescue (7–10s) The woman quickly grabs an umbrella and runs outside. She kneels beside the frightened kitten, carefully reaches toward it, and gently picks it up. She protects the kitten from the rain with the umbrella and wraps it in a soft cloth or her jacket. Camera: Dynamic handheld cinematic movement following her outside, then a close-up as she gently lifts the kitten. Scene 5 — Bringing the Kitten Home (10–13s) She carries the kitten back inside her warm home. The scene transitions from the cold blue rainy exterior to a warm, cozy interior. She places the kitten gently on a soft towel and carefully dries its wet fur. The kitten begins to relax and feel safe. Camera: Smooth tracking shot following her through the doorway, followed by a warm close-up of the woman drying the kitten. Scene 6 — Happy Ending (13–15s) The kitten is now warm, dry, and safe. The woman gently holds it against her chest and smiles with relief. The kitten looks comfortable and calm in her arms. Warm morning light fills the room while rain continues softly outside the window. Camera: Emotional close-up, slow cinematic push-in, ending on the woman and kitten together. Visual Style Ultra-realistic cinematic photography, emotional storytelling, realistic human movement, realistic kitten behavior, detailed wet fur, natural skin texture, physically accurate rain and water reflections, soft morning light, realistic interior lighting, shallow depth of field, subtle film grain, high dynamic range, smooth camera transitions, premium cinematic color grading. Audio Soft realistic rain ambience, gentle breakfast sounds, distant thunder, footsteps on wet ground, umbrella opening, subtle emotional background music, soft kitten meows, and warm peaceful music during the final scene. Negative Prompt No cartoon style, no animation, no distorted faces, no changing character appearance, no extra fingers, no deformed hands, no duplicate kitten, no duplicate people, no unnatural movements, no floating objects, no unrealistic rain, no exaggerated expressions, no sudden camera jumps, no text, no subtitles, no watermark, no logos.

liana

15,932 görüntüleme • 21 gün önce

Chatgpt+ Sedance 2.0 Mini On OpenArt Seedance 2.0, 15 seconds, 16:9. Main subject from Image — lock her identity completely. Keep her face, skin tone, body shape, outfit, hairstyle, and every unique feature perfectly identical throughout the entire video. She is wearing a faded grey sleeveless crop top, loose high-waisted light blue jeans, black canvas sneakers, a black cord necklace, and has black wavy hair tied in a messy side-swept ponytail with bangs. Korean woman with an authentic early-2000s vibe. The entire video takes place in a quiet Korean residential neighborhood with narrow concrete alleys, low-rise houses featuring small terraces, a front yard with a clothesline, potted plants, parked bicycles and motorcycles, large trees, and overhead utility cables everywhere. There are no shops, vendors, or commercial elements—only a natural, everyday residential environment. The camera treatment is the defining element. The footage must feel as if a friend casually picked up a DV camcorder and started recording without any planning or setup. Use heavy handheld shake, constant reframing, the subject naturally drifting toward the edges of the frame, autofocus hunting, visible lens breathing, and exposure pumping. The image should appear faded, low-contrast, slightly washed out, with authentic early-2000s digital noise and compression artifacts. No stabilization, no cinematic movement, and no modern color grading. This camcorder aesthetic is absolutely non-negotiable. She begins sitting on a concrete sidewalk while fixing her ponytail with both arms raised, smiling naturally as the wind gently catches her hair while the camera struggles to maintain focus. The camera then follows her into a narrow alley where she crouches down and feeds a friendly stray cat that walks right up to her. Next, she is in her front yard hanging laundry on a clothesline as the morning breeze softly moves the clothes, while the camera continues swaying and searching for focus. Midway through, she sits quietly on the front terrace holding a coffee cup, calmly looking toward the street as the camera drifts loosely from the side. Then, in a close shot from her right side, she raises her arm, warmly waves to someone off-camera, and says, "Annyeong," with the camera catching the moment a beat late. The final shot follows her in a slow tracking walk down the street with the coffee cup still in hand. She notices the camera, turns slightly, gives a soft, genuine smile, and the recording abruptly cuts to black mid-motion as if the camcorder was simply switched off. Audio must remain entirely natural. Include only morning birds, a gentle breeze, distant motorcycle sounds, faint neighborhood chatter, the stray cat, coffee cup handling, footsteps on concrete, and rustling leaves. No music, no sound design, and no added audio effects.

Mahnoor Fatima

12,541 görüntüleme • 2 ay önce

HTML Artifacts are a big part of how I work with agents now. Artifacts can be more than just static files. When combined with agents, they can take action or help you take action. This unlocks all kinds of interesting ways to work with agents. This is clearly the future. Check out this writing and scheduler artifact I built in a few minutes. It uses a bit of HTML and JS. All the data is in markdown (Obsidian vaults), so the agent can access and modify it at any time. No DB needed. No sophisticated functionalities. The agent decides all that for me based on the skills, context, and memory it has access to. The best part about this simple stack is that all the important information stays with me. This has allowed me to build a recursive self-improving system and automations that can better tap into coding agents like Codex or Claude Code. I could have paid or built an entire app for scheduling posts, and there are so many of them out there. But I don't need to. I've realized a simple artifact does the job. And the simplicity of it is actually an advantage. Very little maintenance for very high returns on personalization, time, and efficiency. The other benefit of this is that I can add features as I please. That level of personalization feels magical, and we should all be pursuing more of it. All of this just keeps compounding. Of course, this example is just about writing. But I have similar artifacts for research, design, experimentation, evaluation, and so much more. And no, I didn't actually publish the post example I shared in the clip. It was just for demonstration purposes. I actually spend more time than this when writing together with agents. Lastly, having built my own agent orchestrator tool has made me realize that simplifying the tool stack is a superpower. If you are curious about how all this works, I will do a live session next week:

elvis

18,374 görüntüleme • 4 ay önce