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This one is tricky! - single static mesh per light - disabled depth test - ray-traced cone - ray marched scattering (5 samples + blue noise) - projected light texture - screen normals used for simulating fake refraction xD #UnrealEngine #techart #vfx

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Krystian Komisarek

8,958 subscribers

62,389 görüntüleme • 2 yıl önce •via X (Twitter)

#UnrealEngine#techart#vfx
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David Carrez profil fotoğrafı
David Carrez2 yıl önce

Is a similar method possible for direct sunlight diffusion? Would bring a lot of realism when the water is in the shadow. Maybe some kind of screen space sss might work, or particles 🤔

Krystian Komisarek profil fotoğrafı
Krystian Komisarek2 yıl önce

It might work. However, in the case of sunlight, I would try to implement the effect "right way" in the water shader :)

Money Glitch profil fotoğrafı
Money Glitch2 yıl önce

Beautiful. You could calculate the IOR for each points of the cone's mantle (16 would be enough), then distort the mantle's underwater part with it. It would be truly efficient, yet the light cone would dance underwater like a real one. 😏

Carlos J. profil fotoğrafı
Carlos J.2 yıl önce

I need this!! I’m making an underwater short film, and this would help a lot. Where to get it?

io🏄🏽‍♂️ profil fotoğrafı
io🏄🏽‍♂️2 yıl önce

Amazing

Jonathan profil fotoğrafı
Jonathan2 yıl önce

I think they used your plugin in the new hellblade 2

Andreas Xirtus 📐 profil fotoğrafı
Andreas Xirtus 📐2 yıl önce

Is there a tutorial on tubular waves? Dude?

EauCalme profil fotoğrafı
EauCalme2 yıl önce

ur insane

Khen profil fotoğrafı
Khen2 yıl önce

Very interesting solution!!

Pedro Martins profil fotoğrafı
Pedro Martins2 yıl önce

nice work 🙂

Benzer Videolar

Meshes can be made light sources in ray tracing. This is only a test, colors are baked in that Cathedral pane. Thanks for エイブ - Abraham Link for remaking pane mesh and discord use DrNova for the texture edit. I will add texture sampling support for emissive only sources.
0:20

Meshes can be made light sources in ray tracing. This is only a test, colors are baked in that Cathedral pane. Thanks for エイブ - Abraham Link for remaking pane mesh and discord use DrNova for the texture edit. I will add texture sampling support for emissive only sources.

Dark Souls Lighting Engine

22,377 görüntüleme • 9 ay önce

Great question! 🤔 How do you simulate *multiple* layers of glass/refraction in video games? In the last breakdown, I discussed how to create a glass shader in Unity URP. In essence, we were taking the render of the scene from the camera without any transparent objects. This is available in URP as the global _CameraOpaqueTexture. This is good enough for most use-cases, and more or less the classic way of doing it. 🔍 What is _CameraOpaqueTexture? As the name implies, there are no transparent objects rendered into this texture, so it's not possible by default to have something like a transparent-type ocean material/shader rendered through a refractive glass shader (which samples and distorts this texture to render on its surface, as if it's transparent). ⚠️ Why it’s tricky: It's much easier to sort without much further setup if you don't have refraction, and only a transparent material, because in that case you're not simulating the transparency yourself via sampling the rendered scene texture. But for refraction, it's required-- unless you want to go down the ray/path tracing route. You could simulate accurate, real dispersion... and that's about as expensive as it sounds, and it requires a rework of your entire rendering. --> 🚫 It's not a viable suggestion to offer. 📚 There are well-known terms regarding transparency sorting you can search up, but as you've specifically asked for refractive boxes, I'll discuss briefly about that. 🧱 Simulating layers of refraction: For this kind of rendering, you need some way to render the backfaces before rendering the front. And the backfaces that are rendered may contain whatever data you'd like for additional processing in the layer front-facing mesh render. 🧪 Examples: You could render the back face as a glass shader of its own, as an intermediate step after _CameraOpaqueTexture. Then you sample this texture instead and you end up with multi-layered refraction, "just like that". You can also render the back normals only, via a fully opaque shader, and use that to manually account for that during the front render. You could even bake in data needed for thickness in realtime. 🛠️ Without making it complicated for yourself, the most straightforward method is via render textures, and you can easily set some fractional resolution. Cameras in Unity have an open slot for target textures to render to. You can use custom render textures to process _SelfTexture2D. ⏱️ It's great to do low-resolution processing for more complex tasks, like blurring and caustics. You can get massive performance boosts, considering the square law and number of pixels/fragments that need calculations (quadratic scaling). 🚧 I've not fully exploited the possibilities myself, but research/development with PRISM is ongoing!
0:56

Great question! 🤔 How do you simulate *multiple* layers of glass/refraction in video games? In the last breakdown, I discussed how to create a glass shader in Unity URP. In essence, we were taking the render of the scene from the camera without any transparent objects. This is available in URP as the global _CameraOpaqueTexture. This is good enough for most use-cases, and more or less the classic way of doing it. 🔍 What is _CameraOpaqueTexture? As the name implies, there are no transparent objects rendered into this texture, so it's not possible by default to have something like a transparent-type ocean material/shader rendered through a refractive glass shader (which samples and distorts this texture to render on its surface, as if it's transparent). ⚠️ Why it’s tricky: It's much easier to sort without much further setup if you don't have refraction, and only a transparent material, because in that case you're not simulating the transparency yourself via sampling the rendered scene texture. But for refraction, it's required-- unless you want to go down the ray/path tracing route. You could simulate accurate, real dispersion... and that's about as expensive as it sounds, and it requires a rework of your entire rendering. --> 🚫 It's not a viable suggestion to offer. 📚 There are well-known terms regarding transparency sorting you can search up, but as you've specifically asked for refractive boxes, I'll discuss briefly about that. 🧱 Simulating layers of refraction: For this kind of rendering, you need some way to render the backfaces before rendering the front. And the backfaces that are rendered may contain whatever data you'd like for additional processing in the layer front-facing mesh render. 🧪 Examples: You could render the back face as a glass shader of its own, as an intermediate step after _CameraOpaqueTexture. Then you sample this texture instead and you end up with multi-layered refraction, "just like that". You can also render the back normals only, via a fully opaque shader, and use that to manually account for that during the front render. You could even bake in data needed for thickness in realtime. 🛠️ Without making it complicated for yourself, the most straightforward method is via render textures, and you can easily set some fractional resolution. Cameras in Unity have an open slot for target textures to render to. You can use custom render textures to process _SelfTexture2D. ⏱️ It's great to do low-resolution processing for more complex tasks, like blurring and caustics. You can get massive performance boosts, considering the square law and number of pixels/fragments that need calculations (quadratic scaling). 🚧 I've not fully exploited the possibilities myself, but research/development with PRISM is ongoing!

Mirza Beig

61,581 görüntüleme • 1 yıl önce

⚡ RECIPE TO PROTECT YOURSELF IF YOU WORK IN AN OFFICE 1️⃣ 🌞Morning Sunlight = Non-negotiable If your job starts after sunrise, spend 10–15 minutes outside looking at the sky. Doesn’t matter if it’s raining, snowing, or cloudy; infrared light still passes through and starts your circadian clock through the eyes. No sunglasses, no screens. Let natural UV + IR set your biological rhythm. 😬 but If you start before sunrise, buy a near-infrared lamp and turn it on while getting ready. It’s the next-best option. 2️⃣ 🔵Blue-Blocking Glasses = A Must Wear amber lenses under office LEDs. After 4 p.m., switch to red lenses if still under artificial light. 3️⃣🥋Natural Clothing for Protection Choose natural fabrics like wool, cotton, or linen. They don’t hold static charge like synthetics and let your body breathe. Indoors, pick dark colors (black, navy, charcoal) to block excessive artificial light. Remember: Hair, hand, and neck. EMF-blocking fabrics are even better if you can afford them. 4️⃣🆘Add Infrared Support Keep a near-infrared therapy light on your desk or near your computer. If you can’t afford it, use small red bulbs, halogen, or incandescent lamps instead to replace missing infrared from LEDs. 5️⃣💻Screen Filters & Settings On your computer, activate Night Shift, f.lux, or Iris; set color temperature around 1800–2000 K (red/orange tone) if can go bellow better.. if you can bring your own, buy one of those pc with Build-in-blue-light-filters.(if you can afford) If you can not buy a blue-light filter film for your monitor. Reduce brightness slightly; increase contrast for comfort. 6️⃣🪑Reposition Your Desk Sit near a window and open it if possible. Avoid sitting directly under fluorescent or LED ceiling lights. If coworkers ask why you opened the window, say it’s to “circulate the stagnant air.” 😉 Remember: even if the window is far from you, cracking it open still helps. The Lid Experiment shows that infrared light passes through even the smallest gaps, meaning that open window benefits everyone in the office; including you. ☀️ 7️⃣🚬Light Breaks…Your “Fake Smoke” Trick Every 90 minutes, go outside for 3–5 minutes of natural light. Hold a real cigarette, and fake it... you’re feeding your mitochondria, not nicotine. 8️⃣🌳Ground at Lunch Step outside and find the biggest tree near your office. Touch it with bare hands or feet for one minute; trees discharge harmful stray currents from the ground. Even one minute of grounding stabilizes your body’s electrical charge. 9️⃣💦Hydrate Intelligently Drink mineral or spring water, not distilled. Add a pinch of sea salt and a few drops of local lemon juice to improve structure and conductivity. (Check my page for the big crystal water pitcher setup to structure your water naturally.) 🔟💡Reduce Reflections & Glare Use matte screen protectors and avoid glossy surfaces; glare amplifies blue frequencies. 🚫Keep Tech Off the Body Never rest a laptop on your lap. Keep phones and routers off or away when not in use. 🌅Sunset Reset After work, go outside for sunset light exposure. It tells your brain that the day is ending and resets your circadian rhythm. ⚫️🏴‍☠️Dark Office Cleanup If you are alone and must stay late, use red light only. If note, cover you body head to toe… Avoid bright screens and overhead LEDs after dark…., 🍱 🧬 Feed the Mitochondrial Antenna Seafood = DHA rebuilds light-conducting membranes. Magnesium & sulfur-rich foods (eggs, onions, garlic) = support redox cycling….
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14,918 görüntüleme • 11 ay önce

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Where the original painter would load their brush with white or yellow to hit a bright highlight, the paint should visibly sit above the surface. In dark shadow areas, the paint should appear thinner, letting canvas weave show through slightly. Color palette. Restrict the entire scene to a historical oil palette. Titanium white, naples yellow, yellow ochre, raw sienna, burnt sienna, burnt umber, raw umber, ivory black, vermillion used sparingly, and a muted blue-grey. No modern saturated colors. All color mixing should feel subtractive and warm. Edge treatment. No hard edges anywhere in the scene. Object silhouettes must soften and blur slightly as if the painter's brush feathered where one form meets another. Implement this as a screen-space edge-detection pass that blurs based on depth discontinuity and overlays brushstroke texture at boundaries. Canvas texture. The entire final image must have a linen canvas weave overlay rendered with its own normal map that interacts with the scene lighting. As you orbit, the canvas tooth should glint differently. This sells the illusion more than anything else. Varnish layer. Apply a post-processing pass that simulates aged oil varnish. A warm amber tint that is slightly uneven, thicker in corners and thinner in center. A subtle gloss reflection that shifts as you move the camera. Very fine craquelure, hairline crack patterns, visible only when you zoom in close. The Scene. A Dutch Golden Age Study. Model everything procedurally with no external assets. A small intimate room with rough plastered walls in thick paint, warm grey-ochre. A single tall window on the left wall. Leaded glass with thick mullions letting in one dominant shaft of warm light. The window glass should have slight imperfections like bubbles and waviness visible in the paint treatment. A heavy dark wood table positioned center-left. On the table place a brass candlestick with a half-melted candle where the wax drips are modeled and painted with naples yellow impasto highlights. A pewter plate with a half-peeled lemon, the peel curling off the edge of the plate, the exposed fruit flesh a jewel of thick yellow paint catching light. A partially unfolded letter with a broken red wax seal. A small glass of dark wine catching a single highlight. A dark velvet cloth draped from the table edge falling in heavy folds to the floor. The velvet should have that characteristic oil painting treatment where shadows go almost black and the fabric catches light in soft broken highlights. The floor is wide dark wooden planks painted with long horizontal brushstrokes. Against the back wall, barely visible in shadow, a tall wooden cabinet with a few old leather-bound books leaning against each other. A single beam of light from the window cuts diagonally across the scene illuminating floating dust motes painted as soft tiny dots of naples yellow, not CG particles. The rest of the room falls into rich warm shadow. Lighting One dominant directional light from the left simulating window light. Warm, strong, with soft VSM shadows. A very subtle fill from the right in cool blue-grey at perhaps 5% intensity. No ambient light. The shadows should be genuinely dark and warm. This is Vermeer lighting. The contrast between the luminous light-struck areas and the deep velvety shadows is what makes the painting breathe. Post-Processing Chain Render pass. Painterly edge softening pass. Canvas texture overlay pass. Varnish and aging pass. Heavy vignette like a dark gallery frame encroaching. Very subtle bloom only on the brightest impasto highlights. Film grain that mimics canvas tooth texture rather than photographic noise. Interaction OrbitControls with very slow damping at 0.02 and limited orbit range so you can look around the painting but not flip it upside down. Slow zoom. The feeling should be like leaning closer to a painting in a museum and discovering more detail. The Standard When someone opens this file and takes a screenshot, people should genuinely argue whether it is a photograph of a real oil painting or a digital render.
0:36

My first test with the new Gemini Deep Think 3 🔥🔥🔥 Build a complete Three.js scene in a single HTML file that renders a fully 3D interior room indistinguishable from a classical oil painting hanging in a museum. The Painterly Rendering System Write custom GLSL shaders that replace all standard rendering with oil paint simulation. Every pixel must feel painted by hand. The system needs these layers working together. Brushstroke normals. Generate a procedural brushstroke normal map using layered directional noise at varying scales. Large bold strokes for walls and floors following the plane direction. Small delicate strokes for fine details like metal and glass. Circular strokes for rounded objects. The brushstrokes must catch sidelight and cast tiny shadows into their grooves exactly like real impasto paint on canvas. Paint thickness. Use parallax occlusion mapping to give highlights genuine physical thickness. Where the original painter would load their brush with white or yellow to hit a bright highlight, the paint should visibly sit above the surface. In dark shadow areas, the paint should appear thinner, letting canvas weave show through slightly. Color palette. Restrict the entire scene to a historical oil palette. Titanium white, naples yellow, yellow ochre, raw sienna, burnt sienna, burnt umber, raw umber, ivory black, vermillion used sparingly, and a muted blue-grey. No modern saturated colors. All color mixing should feel subtractive and warm. Edge treatment. No hard edges anywhere in the scene. Object silhouettes must soften and blur slightly as if the painter's brush feathered where one form meets another. Implement this as a screen-space edge-detection pass that blurs based on depth discontinuity and overlays brushstroke texture at boundaries. Canvas texture. The entire final image must have a linen canvas weave overlay rendered with its own normal map that interacts with the scene lighting. As you orbit, the canvas tooth should glint differently. This sells the illusion more than anything else. Varnish layer. Apply a post-processing pass that simulates aged oil varnish. A warm amber tint that is slightly uneven, thicker in corners and thinner in center. A subtle gloss reflection that shifts as you move the camera. Very fine craquelure, hairline crack patterns, visible only when you zoom in close. The Scene. A Dutch Golden Age Study. Model everything procedurally with no external assets. A small intimate room with rough plastered walls in thick paint, warm grey-ochre. A single tall window on the left wall. Leaded glass with thick mullions letting in one dominant shaft of warm light. The window glass should have slight imperfections like bubbles and waviness visible in the paint treatment. A heavy dark wood table positioned center-left. On the table place a brass candlestick with a half-melted candle where the wax drips are modeled and painted with naples yellow impasto highlights. A pewter plate with a half-peeled lemon, the peel curling off the edge of the plate, the exposed fruit flesh a jewel of thick yellow paint catching light. A partially unfolded letter with a broken red wax seal. A small glass of dark wine catching a single highlight. A dark velvet cloth draped from the table edge falling in heavy folds to the floor. The velvet should have that characteristic oil painting treatment where shadows go almost black and the fabric catches light in soft broken highlights. The floor is wide dark wooden planks painted with long horizontal brushstrokes. Against the back wall, barely visible in shadow, a tall wooden cabinet with a few old leather-bound books leaning against each other. A single beam of light from the window cuts diagonally across the scene illuminating floating dust motes painted as soft tiny dots of naples yellow, not CG particles. The rest of the room falls into rich warm shadow. Lighting One dominant directional light from the left simulating window light. Warm, strong, with soft VSM shadows. A very subtle fill from the right in cool blue-grey at perhaps 5% intensity. No ambient light. The shadows should be genuinely dark and warm. This is Vermeer lighting. The contrast between the luminous light-struck areas and the deep velvety shadows is what makes the painting breathe. Post-Processing Chain Render pass. Painterly edge softening pass. Canvas texture overlay pass. Varnish and aging pass. Heavy vignette like a dark gallery frame encroaching. Very subtle bloom only on the brightest impasto highlights. Film grain that mimics canvas tooth texture rather than photographic noise. Interaction OrbitControls with very slow damping at 0.02 and limited orbit range so you can look around the painting but not flip it upside down. Slow zoom. The feeling should be like leaning closer to a painting in a museum and discovering more detail. The Standard When someone opens this file and takes a screenshot, people should genuinely argue whether it is a photograph of a real oil painting or a digital render.

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What people think Methylene Blue is: - Fish tank cleaner What Methylene Blue actually is based on 100+ years of use in humans & 18,000+ scientific studies: 1. NEUROPROTECTIVE - Ongoing clinical trial for Alzheimer's - Antidepressant (humans: 15mg) - Promising anti-bipolar effects - Mild anti-schizophrenia properties - Anti-Parkinson’s properties - Anti-Huntington’s properties - Anti-anxiety properties - Improves stroke recovery - Improves TBI recovery 2. BRAIN MITOCHONDRIAL ENHANCER Almost all of the neuroprotective benefits listed above are a result of MB's ability to: - Reduce nitric oxide (too much is bad) - Reduce oxidative stress (antioxidant) - Donate electrons in mitochondria - Increase the number of mitochondria - Recycle old/damaged mitochondria As a result of this, Methylene Blue can: - Reduces neuroinflammation - Increase neurogenesis (BDNF) - Restore GDNF in Parkinson’s - Reduce amyloid & tau - Fortify blood-brain barrier - Improve cerebral blood flow Methylene Blue can also inhibit MAO-A enzymes and to a lesser extent MAO-B enzymes This boosts levels of dopamine, norepinephrine, & serotonin 3. COGNITIVE ENHANCER But Methylene Blue isn’t just a neuroprotective agent It’s also an cognitive-enhancer In human studies, MB has been shown to: - Improve attention span - Improve short-term memory - Enhance fear extinction (Anxiety/PTSD) I definitely feel sharper on 5-15mg of MB 4. ANTI-MICROBIAL & IMMUNOMODULATORY MB isn’t just a nootropic It’s actually one of the world’s best anti-microbial agents I personally used 30mg/day 2 weeks ago to annihilate the flu Went from down bad to back on my feet in about 24 hours - Improves COVID-19 treatment - Pulled C19 patients off respirators - Inhibits SARS-CoV-2 replication - Inhibits H1N1 replication - Cures malaria in ~48 hours - Kills parasites & fungal infections - May have anti-cancer properties - Reduces chemotherapy side effects Plus when it’s combined with light, MB: - Inactivates herpes virus - Inactivates zika virus - Reduces Hepatitis A & C levels - Reduces ebola infectivity - Reduces HIV-1 to undetectable levels 5. SKIN ENHANCEMENT - Very underrated skincare tool - Superior to Vit C + Retinol - Use MB tallow balm for skin - Will link my full guide below 6. MY PERSONAL EXPERIENCE - I’ve been taking MB for ~6 months - Best results combining with light - Feels very nourishing in a sense - Noticeable acute energy boost - Brain fog dissipates immediately - Heightened senses (vivid colors) - I use Meraki Blue Tongues - 10% off code = NOOTROPICGUY - USP-grade & heavy metal free - 5 mg orally per day 5x per week - 2-4 week break every 8 weeks 7. SAFETY Methylene Blue is extremely safe when used correctly In fact, it’s been used safely in humans for 100+ years: - First synthetic medicinal drug - Dozens of human clinical trials - Attractive safety profile - FDA-approved (methemoglobinemia) - Reverses cyanide poisoning - Reverses carbon monoxide poisoning With that said, there 3 key caveats: - Microdose to avoid pro-oxidant effect - Never combine with SSRI/SNRI drugs - Don’t use with G6PD deficiency - G6PD deficiency = hemolytic anemia 8. DISCLAIMER - This is not medical advice - Consult a physician prior to using - Methylene Blue will stain if spilled - Will temporarily stain tongue & pee blue - Only use USP-grade w/o heavy metals

NootBro

543,518 görüntüleme • 2 yıl önce

this guy built an ai-girl pipeline using real-time face filters, and d2c brands now pay him $2,000 per ugc video he got tired of watching brands burn $4,000 on a single creator who takes 2 weeks to deliver one angle, so he built a setup that runs photoreal ai girls live from his own webcam, no actresses, no studios, no makeup artists his monthly revenue hit $89,000 last month from a network of 7 ai personas across tiktok and instagram. the average ugc creator caps at $6k juggling 4 brand deals the breakdown: > hardware is the moat, but most people butcher the setup in the first frame. face mesh locked at 60fps with zero artifacting > persona comes first, mess this up and nothing saves it: name, backstory, voice tone, niche before a single clip is shot > face selection is not random. you a/b test features (eye spacing, jawline, hair contrast) because some faces convert better in 9:16 > you're picking who your audience trusts, not who looks cool. that's targeting baked into bone structure > real-time physics run before the script, this is what kills the uncanny valley that destroys watch time in 2 seconds > the filter has to survive the strap of a tank top, the texture of a knit cardigan, the hair flick > batching is the move 96% skip: one performance, multiple personas, three platforms > the system pushes 12 pieces before lunch while brands test 2 creators a week and wonder why their cpa sits at $94 the economics: each video costs $4 in compute, sells for $1,500 to $3,000, takes 14 minutes to produce. that's a 37,500% margin, while ugc agencies pay creators $400-800 per clip and net $200 after revisions one supplement brand generated 14 variants with 7 personas in 4 hours and found a winner in 36 hours without flying a creator to la. they were paying $1,200 per ugc video and burning $6,000/week on content that didn't scale. now they spend $210 for 14 variants and their cpa dropped from $89 to $27 the avatars hold real products, warm window light on the persona, cold neon on the operator, mouth shapes sync to consonants not just vowels just a webcam, a tracked face, and the discipline to move enough that the filter never has a chance to break
0:25

this guy built an ai-girl pipeline using real-time face filters, and d2c brands now pay him $2,000 per ugc video he got tired of watching brands burn $4,000 on a single creator who takes 2 weeks to deliver one angle, so he built a setup that runs photoreal ai girls live from his own webcam, no actresses, no studios, no makeup artists his monthly revenue hit $89,000 last month from a network of 7 ai personas across tiktok and instagram. the average ugc creator caps at $6k juggling 4 brand deals the breakdown: > hardware is the moat, but most people butcher the setup in the first frame. face mesh locked at 60fps with zero artifacting > persona comes first, mess this up and nothing saves it: name, backstory, voice tone, niche before a single clip is shot > face selection is not random. you a/b test features (eye spacing, jawline, hair contrast) because some faces convert better in 9:16 > you're picking who your audience trusts, not who looks cool. that's targeting baked into bone structure > real-time physics run before the script, this is what kills the uncanny valley that destroys watch time in 2 seconds > the filter has to survive the strap of a tank top, the texture of a knit cardigan, the hair flick > batching is the move 96% skip: one performance, multiple personas, three platforms > the system pushes 12 pieces before lunch while brands test 2 creators a week and wonder why their cpa sits at $94 the economics: each video costs $4 in compute, sells for $1,500 to $3,000, takes 14 minutes to produce. that's a 37,500% margin, while ugc agencies pay creators $400-800 per clip and net $200 after revisions one supplement brand generated 14 variants with 7 personas in 4 hours and found a winner in 36 hours without flying a creator to la. they were paying $1,200 per ugc video and burning $6,000/week on content that didn't scale. now they spend $210 for 14 variants and their cpa dropped from $89 to $27 the avatars hold real products, warm window light on the persona, cold neon on the operator, mouth shapes sync to consonants not just vowels just a webcam, a tracked face, and the discipline to move enough that the filter never has a chance to break

Kiyoro

31,137 görüntüleme • 4 ay önce

I built a Three.js rendering study inspired by Tiny Glade’s painterly aesthetic, and got it running at 120fps in the browser. Over the past few weeks, I’ve been studying how stylized games achieve that soft, handcrafted look in real time. Tiny Glade was a huge inspiration, and I wanted to use the browser as a constraint: no compute shaders, no native GPU access, and single-threaded JavaScript. As part of this study, I implemented: - GPU-driven instanced brick walls with procedural noise jitter and elastic build animations - Tree, bush, and flower rendering with billboard card expansion, wind sway, and grow animations - Procedural grass with terrain conformance and interactive push deformation - Animated water with layered noise, interactive ripples, and Fresnel-based reflections - Procedural terrain with slope-aware triplanar materials, dirt paths, and rocks - A 7-pass post-processing stack with TAA, bloom, depth of field, painterly filtering, ACES tonemapping, 3D LUT color grading, and film grain The hardest part wasn’t writing any single shader. It was making all of these systems work together at high frame rates inside WebGL, where every millisecond counts and performance problems compound quickly across animation, materials, post-processing, and scene management. Some techniques in this study were inspired by analyzing Tiny Glade’s rendering approach, while others were original implementations built from scratch from visual reference. That contrast taught me a lot: recreating an effect is one challenge, but designing your own shaders and systems to achieve a similar feel is a very different one. This is a private educational rendering study. Some temporary placeholder content is being used during the research phase, and any public or production version would use original or properly licensed assets. Huge credit to Pounce Light for the incredible art direction and rendering work in Tiny Glade: Three.js #gamedev #webgl #threejs #rendering #graphics #realtimerendering #shaderdev
7:21

I built a Three.js rendering study inspired by Tiny Glade’s painterly aesthetic, and got it running at 120fps in the browser. Over the past few weeks, I’ve been studying how stylized games achieve that soft, handcrafted look in real time. Tiny Glade was a huge inspiration, and I wanted to use the browser as a constraint: no compute shaders, no native GPU access, and single-threaded JavaScript. As part of this study, I implemented: - GPU-driven instanced brick walls with procedural noise jitter and elastic build animations - Tree, bush, and flower rendering with billboard card expansion, wind sway, and grow animations - Procedural grass with terrain conformance and interactive push deformation - Animated water with layered noise, interactive ripples, and Fresnel-based reflections - Procedural terrain with slope-aware triplanar materials, dirt paths, and rocks - A 7-pass post-processing stack with TAA, bloom, depth of field, painterly filtering, ACES tonemapping, 3D LUT color grading, and film grain The hardest part wasn’t writing any single shader. It was making all of these systems work together at high frame rates inside WebGL, where every millisecond counts and performance problems compound quickly across animation, materials, post-processing, and scene management. Some techniques in this study were inspired by analyzing Tiny Glade’s rendering approach, while others were original implementations built from scratch from visual reference. That contrast taught me a lot: recreating an effect is one challenge, but designing your own shaders and systems to achieve a similar feel is a very different one. This is a private educational rendering study. Some temporary placeholder content is being used during the research phase, and any public or production version would use original or properly licensed assets. Huge credit to Pounce Light for the incredible art direction and rendering work in Tiny Glade: Three.js #gamedev #webgl #threejs #rendering #graphics #realtimerendering #shaderdev

Ibrahim Boona

58,625 görüntüleme • 5 ay önce

For decades, biologists argued that birds migrate using magnetic fields, and that cryptochrome proteins in their eyes help them figure out where to fly. But the evidence for this has always been flimsy. In 1972, Wolfgang and Roswitha Wiltschko captured migratory European robins, put them in cages, covered the cages with a blanket, and wrapped electric coils around them. Once the birds lost their view of the sky, they still tried to move, or "hop," in the direction of their normal migration route. But when the Wiltschkos flipped the magnetic field around, the robins started hopping in random directions. They took this as evidence that, somehow, birds migrate using a magnetic sense. (Not bad!) In 2000, three theoretical biophysicists in Illinois, Ritz, Adem, and Schulten, proposed a mechanism for that magnetic sense. They argued that when blue light hits a receptor in the eye, it might create something called a "radical pair," locking two electrons into a spin state that a magnetic field could then nudge. They suggested that cryptochromes, light-sensitive proteins in the retina, might be responsible. (Speculative!) And then, in 2021, researchers apparently confirmed this! They took cryptochrome proteins from a type of migratory robin and put them in a test tube. They shone blue light at the proteins and found that this light induced them to form that transient "radical pair" state. And finally, they showed that magnetic fields could change this photochemistry where, in the presence of a magnetic field, the proteins formed fewer of these radical pairs, because the field forced a larger fraction of the excited molecules to ‘collapse’ back to their resting state. The experiment they used to measure this, though, has almost nothing to do with biology. You literally isolate the proteins, bombard them with a blue laser and, after each pulse, measure how much light the proteins absorb. For the robin cryptochrome protein, adding a magnetic field changed the absorbance *slightly.* But here’s the caveat: All of this was done in vitro, in a test tube, in a water-based buffer (rather than a cell). And, even worse, the experiment was done at 5 degrees Celsius (waaaay colder than the bird’s normal temperature) and at a low pH. And even after all this tinkering, they still *barely* saw a magnetic response! The news media didn't report many of these caveats. I randomly pulled one story from Science News and another from the University of Oxford, and neither even mentioned that the researchers ran the experiment at low temperature. The Oxford writeup actually hyped the result up more than the paper itself; that author wrote: “…the authors think the proteins involved could be significantly more sensitive in their native environment. In cells in the retina, the proteins are probably fixed and aligned, increasing their sensitivity to the direction of the magnetic field. Moreover, they are also likely to be associated with other proteins that could amplify the sensory signals." (Wow!) When Andrew York and Maria Ingaramo, two scientist working at Calico, heard about these results, they grew skeptical and decided to search for magnetically-responsive proteins — that actually work under physiological conditions — on their own. And that search, in turn, gave rise to Nonfiction Laboratories, a company that not only has created such proteins, but is now trying to commercialize them to make magnetically controlled cancer therapies that are only active near a tumor. The clip below is from my podcast.
2:53

For decades, biologists argued that birds migrate using magnetic fields, and that cryptochrome proteins in their eyes help them figure out where to fly. But the evidence for this has always been flimsy. In 1972, Wolfgang and Roswitha Wiltschko captured migratory European robins, put them in cages, covered the cages with a blanket, and wrapped electric coils around them. Once the birds lost their view of the sky, they still tried to move, or "hop," in the direction of their normal migration route. But when the Wiltschkos flipped the magnetic field around, the robins started hopping in random directions. They took this as evidence that, somehow, birds migrate using a magnetic sense. (Not bad!) In 2000, three theoretical biophysicists in Illinois, Ritz, Adem, and Schulten, proposed a mechanism for that magnetic sense. They argued that when blue light hits a receptor in the eye, it might create something called a "radical pair," locking two electrons into a spin state that a magnetic field could then nudge. They suggested that cryptochromes, light-sensitive proteins in the retina, might be responsible. (Speculative!) And then, in 2021, researchers apparently confirmed this! They took cryptochrome proteins from a type of migratory robin and put them in a test tube. They shone blue light at the proteins and found that this light induced them to form that transient "radical pair" state. And finally, they showed that magnetic fields could change this photochemistry where, in the presence of a magnetic field, the proteins formed fewer of these radical pairs, because the field forced a larger fraction of the excited molecules to ‘collapse’ back to their resting state. The experiment they used to measure this, though, has almost nothing to do with biology. You literally isolate the proteins, bombard them with a blue laser and, after each pulse, measure how much light the proteins absorb. For the robin cryptochrome protein, adding a magnetic field changed the absorbance *slightly.* But here’s the caveat: All of this was done in vitro, in a test tube, in a water-based buffer (rather than a cell). And, even worse, the experiment was done at 5 degrees Celsius (waaaay colder than the bird’s normal temperature) and at a low pH. And even after all this tinkering, they still *barely* saw a magnetic response! The news media didn't report many of these caveats. I randomly pulled one story from Science News and another from the University of Oxford, and neither even mentioned that the researchers ran the experiment at low temperature. The Oxford writeup actually hyped the result up more than the paper itself; that author wrote: “…the authors think the proteins involved could be significantly more sensitive in their native environment. In cells in the retina, the proteins are probably fixed and aligned, increasing their sensitivity to the direction of the magnetic field. Moreover, they are also likely to be associated with other proteins that could amplify the sensory signals." (Wow!) When Andrew York and Maria Ingaramo, two scientist working at Calico, heard about these results, they grew skeptical and decided to search for magnetically-responsive proteins — that actually work under physiological conditions — on their own. And that search, in turn, gave rise to Nonfiction Laboratories, a company that not only has created such proteins, but is now trying to commercialize them to make magnetically controlled cancer therapies that are only active near a tumor. The clip below is from my podcast.

Niko McCarty.

21,714 görüntüleme • 1 ay önce

Created With Grok Imagine. ●. The Ring World - Stillness, silence 1. Nebula Birthplace - Star formation 2. The Pillars - Birth, creation 3. The Storm - Isolation, turbulence 4. The Wanderer - Eternal journey 5. The Threshold - Edge of reality 6. The Collision - Time meaningless 7. The Abyss - Forever stares back 8. The Pale Blue Dot - Home grok imagine prompts used: [ { "id": 0, "title": "The Ring World", "prompt": "A gas giant's rings stretching to infinity, seen edge-on as razor-thin lines of pale gold and silver ice extending beyond comprehension into the void. The planet itself is a massive sphere of muted amber and slate grey storms, half in shadow, half catching distant starlight. The rings cast a whisper-thin shadow band across the planet's face. Everything floats in absolute silence and stillness against crushing black emptiness. A single moon, small and pale, drifts in the middle distance. The scale is vertigo-inducing - the rings could wrap around everything you've ever known. Cinematic composition, extreme wide shot, deep atmospheric blacks, soft diffused lighting, melancholic and vast, jewel-tone highlights on ring particles catching light, 8K, anamorphic lens, cosmic sublime aesthetic." }, { "id": 1, "title": "Nebula Birthplace", "prompt": "A breathtaking view of the Carina Nebula's star-forming pillars, towering columns of cosmic dust and hydrogen gas illuminated by the fierce ultraviolet radiation of newborn blue-white stars. The pillars rise like ancient cathedral spires against a backdrop of deep crimson and burnt orange gas clouds, with delicate tendrils of teal and magenta plasma curling at their edges. Thousands of pinpoint stars scatter across the scene like diamond dust, while a brilliant central cluster of young O-type stars blazes with intense blue-white light, casting dramatic shadows through the translucent dust lanes. Wispy shock fronts of superheated gas glow in electric blue where stellar winds collide with denser material. Ultra high resolution, photorealistic astrophotography style, Hubble Space Telescope quality." }, { "id": 2, "title": "The Pillars", "prompt": "Colossal pillars of cosmic dust rising from an infinite void, monolithic towers of deep indigo and midnight blue stretching impossibly tall against the blackness of space. Edges glow with ethereal bioluminescent teal and soft magenta where newborn stars ignite within, light bleeding through translucent layers of gas like lanterns behind silk. Thousands of stars scattered like crushed diamonds across absolute darkness. Scale is incomprehensible - each pillar contains worlds. Soft god rays pierce through gaps in the dust. Cinematic wide shot, extreme depth, atmospheric haze creating layers of distance, moody dramatic lighting, deep blacks crushing into the void, jewel-tone luminosity, 8K, anamorphic lens quality, awe-inspiring cosmic sublime aesthetic." }, { "id": 3, "title": "The Storm", "prompt": "A massive planetary storm seen from orbit, a swirling vortex of deep sapphire blue and electric teal gases spinning slowly in the darkness. The eye of the storm reveals darker layers beneath - navy, cobalt, almost black. High altitude cloud wisps of pale white ice crystals streak across the surface at impossible speeds, frozen in this moment. The planet's limb curves away into shadow, a thin bright arc of atmospheric haze glowing where day meets night. Everything else is void - pure crushing blackness surrounding this lonely turbulent world. Cinematic close orbit view, moody and isolated, deep rich blues against absolute black, soft diffused lighting from distant sun, atmospheric and melancholic, 8K, anamorphic lens quality, cosmic sublime aesthetic." }, { "id": 4, "title": "The Wanderer", "prompt": "A comet drifting through the inner solar system, its ancient dark nucleus trailing twin tails that stretch across the entire frame and beyond. The dust tail sweeps in a graceful arc of pale gold and cream, while the ion tail streams straight back in ghostly electric blue, both dissolving into the infinite black. The nucleus itself is a small dark heart of primordial ice, barely visible, jets of sublimating gas creating a soft teal-white coma glow around it. It has traveled for billions of years through absolute nothing to reach this moment. Loneliness incarnate. Cinematic composition, sense of vast journey and isolation, soft ethereal glow against crushing void, muted jewel tones, atmospheric and melancholic, 8K, anamorphic lens, cosmic sublime aesthetic." }, { "id": 5, "title": "The Threshold", "prompt": "The event horizon of a supermassive black hole, reality distorting at the edge of existence. A thin brilliant ring of superheated gas - white-hot fading to deep amber and crimson - orbits at nearly light speed, smeared into a perfect glowing halo by gravitational lensing. Behind it, stars are warped and duplicated, stretched into arcs and rings around the perfect circular darkness at the center. The black hole itself is absence - not black but nothing, a hole in the universe where light falls forever. The accretion disk reflects faintly in the gravitationally mirrored space above and below. Staring into infinity. Cinematic composition, reality-bending distortion, warm accretion glow against absolute crushing void, terrifying and beautiful, 8K, anamorphic lens, cosmic sublime aesthetic." }, { "id": 6, "title": "The Collision", "prompt": "Two galaxies passing through each other in slow gravitational embrace, their spiral arms stretched and distorted into sweeping tidal ribbons of light. Stars by the billions flow like luminous rivers between the merging cores - streams of pale gold, soft blue, and distant white pulling across hundreds of thousands of light-years of void. Where the cores approach, intense knots of newborn stars blaze in clusters of soft cyan and magenta. Dark dust lanes create dramatic silhouettes against the glowing stellar streams. The interaction has been happening for millions of years and will continue for millions more. Time is meaningless at this scale. Cinematic extreme wide shot, incomprehensible scale, soft ethereal luminosity, jewel tones against absolute black void, 8K, anamorphic, cosmic sublime aesthetic." }, { "id": 7, "title": "The Abyss", "prompt": "A vast cosmic void stretching infinitely in all directions, an endless expanse of deep black punctuated by distant pinpricks of starlight. In the foreground, a swirling nebula of ethereal gas and dust glows softly in shades of violet, indigo, and midnight blue, illuminated from within by the faint light of newborn stars. Wisps of iridescent teal and magenta drift through the darkness like ghostly tendrils, creating a sense of depth and mystery. The scale is incomprehensible - this is a place where entire galaxies could fit within the frame. You are small. You are nothing. You are staring into forever and forever stares back. Cinematic wide shot, extreme depth, atmospheric haze creating layers of distance, moody dramatic lighting, deep blacks crushing into infinite void, soft ethereal bioluminescence, jewel-tone nebula glow against absolute darkness, 8K, anamorphic lens, cosmic sublime aesthetic." }, { "id": 8, "title": "The Pale Blue Dot", "prompt": "Earth seen from four billion miles away, a tiny pale blue-white speck barely visible against the absolute black void of deep space. No detail, no continents, no clouds - just a faint luminous point of soft cyan light, smaller than a grain of sand, floating in endless nothing. The frame is almost entirely pure black emptiness with the tiny distant Earth off-center, barely there, almost lost. A subtle scattered band of faint light crosses the frame diagonally - ancient sunlight diffused through interplanetary dust. The loneliness is overwhelming. The fragility is heartbreaking. Everything that ever lived, loved, or mattered exists on that barely-visible point of light. Minimalist composition, extreme negative space, 90% pure black void, tiny distant pale blue dot, Voyager 1 perspective, melancholic and profound, 8K, anamorphic lens, cosmic sublime aesthetic." } ]
0:54

Created With Grok Imagine. ●. The Ring World - Stillness, silence 1. Nebula Birthplace - Star formation 2. The Pillars - Birth, creation 3. The Storm - Isolation, turbulence 4. The Wanderer - Eternal journey 5. The Threshold - Edge of reality 6. The Collision - Time meaningless 7. The Abyss - Forever stares back 8. The Pale Blue Dot - Home grok imagine prompts used: [ { "id": 0, "title": "The Ring World", "prompt": "A gas giant's rings stretching to infinity, seen edge-on as razor-thin lines of pale gold and silver ice extending beyond comprehension into the void. The planet itself is a massive sphere of muted amber and slate grey storms, half in shadow, half catching distant starlight. The rings cast a whisper-thin shadow band across the planet's face. Everything floats in absolute silence and stillness against crushing black emptiness. A single moon, small and pale, drifts in the middle distance. The scale is vertigo-inducing - the rings could wrap around everything you've ever known. Cinematic composition, extreme wide shot, deep atmospheric blacks, soft diffused lighting, melancholic and vast, jewel-tone highlights on ring particles catching light, 8K, anamorphic lens, cosmic sublime aesthetic." }, { "id": 1, "title": "Nebula Birthplace", "prompt": "A breathtaking view of the Carina Nebula's star-forming pillars, towering columns of cosmic dust and hydrogen gas illuminated by the fierce ultraviolet radiation of newborn blue-white stars. The pillars rise like ancient cathedral spires against a backdrop of deep crimson and burnt orange gas clouds, with delicate tendrils of teal and magenta plasma curling at their edges. Thousands of pinpoint stars scatter across the scene like diamond dust, while a brilliant central cluster of young O-type stars blazes with intense blue-white light, casting dramatic shadows through the translucent dust lanes. Wispy shock fronts of superheated gas glow in electric blue where stellar winds collide with denser material. Ultra high resolution, photorealistic astrophotography style, Hubble Space Telescope quality." }, { "id": 2, "title": "The Pillars", "prompt": "Colossal pillars of cosmic dust rising from an infinite void, monolithic towers of deep indigo and midnight blue stretching impossibly tall against the blackness of space. Edges glow with ethereal bioluminescent teal and soft magenta where newborn stars ignite within, light bleeding through translucent layers of gas like lanterns behind silk. Thousands of stars scattered like crushed diamonds across absolute darkness. Scale is incomprehensible - each pillar contains worlds. Soft god rays pierce through gaps in the dust. Cinematic wide shot, extreme depth, atmospheric haze creating layers of distance, moody dramatic lighting, deep blacks crushing into the void, jewel-tone luminosity, 8K, anamorphic lens quality, awe-inspiring cosmic sublime aesthetic." }, { "id": 3, "title": "The Storm", "prompt": "A massive planetary storm seen from orbit, a swirling vortex of deep sapphire blue and electric teal gases spinning slowly in the darkness. The eye of the storm reveals darker layers beneath - navy, cobalt, almost black. High altitude cloud wisps of pale white ice crystals streak across the surface at impossible speeds, frozen in this moment. The planet's limb curves away into shadow, a thin bright arc of atmospheric haze glowing where day meets night. Everything else is void - pure crushing blackness surrounding this lonely turbulent world. Cinematic close orbit view, moody and isolated, deep rich blues against absolute black, soft diffused lighting from distant sun, atmospheric and melancholic, 8K, anamorphic lens quality, cosmic sublime aesthetic." }, { "id": 4, "title": "The Wanderer", "prompt": "A comet drifting through the inner solar system, its ancient dark nucleus trailing twin tails that stretch across the entire frame and beyond. The dust tail sweeps in a graceful arc of pale gold and cream, while the ion tail streams straight back in ghostly electric blue, both dissolving into the infinite black. The nucleus itself is a small dark heart of primordial ice, barely visible, jets of sublimating gas creating a soft teal-white coma glow around it. It has traveled for billions of years through absolute nothing to reach this moment. Loneliness incarnate. Cinematic composition, sense of vast journey and isolation, soft ethereal glow against crushing void, muted jewel tones, atmospheric and melancholic, 8K, anamorphic lens, cosmic sublime aesthetic." }, { "id": 5, "title": "The Threshold", "prompt": "The event horizon of a supermassive black hole, reality distorting at the edge of existence. A thin brilliant ring of superheated gas - white-hot fading to deep amber and crimson - orbits at nearly light speed, smeared into a perfect glowing halo by gravitational lensing. Behind it, stars are warped and duplicated, stretched into arcs and rings around the perfect circular darkness at the center. The black hole itself is absence - not black but nothing, a hole in the universe where light falls forever. The accretion disk reflects faintly in the gravitationally mirrored space above and below. Staring into infinity. Cinematic composition, reality-bending distortion, warm accretion glow against absolute crushing void, terrifying and beautiful, 8K, anamorphic lens, cosmic sublime aesthetic." }, { "id": 6, "title": "The Collision", "prompt": "Two galaxies passing through each other in slow gravitational embrace, their spiral arms stretched and distorted into sweeping tidal ribbons of light. Stars by the billions flow like luminous rivers between the merging cores - streams of pale gold, soft blue, and distant white pulling across hundreds of thousands of light-years of void. Where the cores approach, intense knots of newborn stars blaze in clusters of soft cyan and magenta. Dark dust lanes create dramatic silhouettes against the glowing stellar streams. The interaction has been happening for millions of years and will continue for millions more. Time is meaningless at this scale. Cinematic extreme wide shot, incomprehensible scale, soft ethereal luminosity, jewel tones against absolute black void, 8K, anamorphic, cosmic sublime aesthetic." }, { "id": 7, "title": "The Abyss", "prompt": "A vast cosmic void stretching infinitely in all directions, an endless expanse of deep black punctuated by distant pinpricks of starlight. In the foreground, a swirling nebula of ethereal gas and dust glows softly in shades of violet, indigo, and midnight blue, illuminated from within by the faint light of newborn stars. Wisps of iridescent teal and magenta drift through the darkness like ghostly tendrils, creating a sense of depth and mystery. The scale is incomprehensible - this is a place where entire galaxies could fit within the frame. You are small. You are nothing. You are staring into forever and forever stares back. Cinematic wide shot, extreme depth, atmospheric haze creating layers of distance, moody dramatic lighting, deep blacks crushing into infinite void, soft ethereal bioluminescence, jewel-tone nebula glow against absolute darkness, 8K, anamorphic lens, cosmic sublime aesthetic." }, { "id": 8, "title": "The Pale Blue Dot", "prompt": "Earth seen from four billion miles away, a tiny pale blue-white speck barely visible against the absolute black void of deep space. No detail, no continents, no clouds - just a faint luminous point of soft cyan light, smaller than a grain of sand, floating in endless nothing. The frame is almost entirely pure black emptiness with the tiny distant Earth off-center, barely there, almost lost. A subtle scattered band of faint light crosses the frame diagonally - ancient sunlight diffused through interplanetary dust. The loneliness is overwhelming. The fragility is heartbreaking. Everything that ever lived, loved, or mattered exists on that barely-visible point of light. Minimalist composition, extreme negative space, 90% pure black void, tiny distant pale blue dot, Voyager 1 perspective, melancholic and profound, 8K, anamorphic lens, cosmic sublime aesthetic." } ]

tetsuo

714,269 görüntüleme • 8 ay önce

The Giant American Manta Ray The Manta Ray is, without exaggeration, the most fascinating underwater drone ever built. Since I’ve been talking a lot about the seas lately and new Chinese technologies, it’s worth remembering that the United States is finalizing tests on something truly groundbreaking. Imagine a metal manta ray with a 14-meter wingspan and weighing nearly 30 tons that can be launched from any pier in the world and then simply disappears for months, or even years without ever needing a mother ship, refueling, or a crew. It glides through the ocean in absolute silence, carrying tons of sensors, mines, torpedoes, and electronic warfare equipment. It can hibernate on the seabed when it wants to save energy and surface when it needs to receive orders via satellite. This giant can deploy smaller units connected by fiber-optic cables or using acoustic communication. Estimates suggest it could travel 18,000 km or more with solid-state batteries. The secret lies in its hybrid propulsion system: the primary mode is buoyancy-driven gliding. It fills ballast tanks with seawater, dives at an angle, then expels the water and rises, converting vertical motion into horizontal forward movement with almost zero energy consumption most of the time. Only a few minutes of pump operation are needed per cycle. When it needs to maneuver quickly or sprint, it switches to conventional propellers. This combination enables autonomy that can last years, especially because the vehicle has energy-harvesting systems that capture power from the ocean’s thermal gradient (warm surface water, cold deep water) and possibly from ocean currents too. It’s a technological marvel unlike anything we’ve seen before in the military domain. The vehicle is transported in standard shipping containers and can be assembled in the field in just a few days and this means the United States can deploy it anywhere in the world without relying on large naval bases. When it enters operational service (expected between 2028 and 2032), the U.S. Navy will gain a capability far beyond any current UUV. The Manta Ray doesn’t need to return, makes no noise, leaves no logistical trace, and can loiter for extended periods waiting for orders or simply monitoring key routes. But it’s not all smooth sailing. Chinese researchers from Northwestern Polytechnical University claim they have been developing biomimetic manta ray UUVs since 2006, with six prototypes ranging from 10 to 700 kg. According to them, in 2023 a 460 kg prototype successfully passed a 1,025-meter depth test in the South China Sea, and multiple variants have completed 60-day underwater gliding missions. That’s still a much shorter endurance than the American prototype has demonstrated so far, possibly because the objectives aren’t identical. My impression is that these are somewhat different projects. While the Chinese appear to focus mainly on swarm-capable units (with potential applications in underwater reconnaissance, anti-submarine, and anti-ship tasks), the Americans are developing a single large platform optimized for long-term persistent monitoring. The U.S. project is a 30-ton drone; the Chinese ones are 10–700 kg. China also claims that in 2025 it began testing swarms of these vehicles near coral reef areas, suggesting the start of a direct race with the Americans. The fact is that more and more unmanned underwater vehicles are emerging every day, and they will pose a major threat, especially to large manned submarines. A small 100 kg UUV could damage the rudder, propeller, or another critical point of a multi-billion-dollar nuclear submarine. After a series of canceled programs in recent years, the Pentagon desperately needs a big, innovative success like the Manta Ray to reinforce its reputation for effective program management.
0:43

The Giant American Manta Ray The Manta Ray is, without exaggeration, the most fascinating underwater drone ever built. Since I’ve been talking a lot about the seas lately and new Chinese technologies, it’s worth remembering that the United States is finalizing tests on something truly groundbreaking. Imagine a metal manta ray with a 14-meter wingspan and weighing nearly 30 tons that can be launched from any pier in the world and then simply disappears for months, or even years without ever needing a mother ship, refueling, or a crew. It glides through the ocean in absolute silence, carrying tons of sensors, mines, torpedoes, and electronic warfare equipment. It can hibernate on the seabed when it wants to save energy and surface when it needs to receive orders via satellite. This giant can deploy smaller units connected by fiber-optic cables or using acoustic communication. Estimates suggest it could travel 18,000 km or more with solid-state batteries. The secret lies in its hybrid propulsion system: the primary mode is buoyancy-driven gliding. It fills ballast tanks with seawater, dives at an angle, then expels the water and rises, converting vertical motion into horizontal forward movement with almost zero energy consumption most of the time. Only a few minutes of pump operation are needed per cycle. When it needs to maneuver quickly or sprint, it switches to conventional propellers. This combination enables autonomy that can last years, especially because the vehicle has energy-harvesting systems that capture power from the ocean’s thermal gradient (warm surface water, cold deep water) and possibly from ocean currents too. It’s a technological marvel unlike anything we’ve seen before in the military domain. The vehicle is transported in standard shipping containers and can be assembled in the field in just a few days and this means the United States can deploy it anywhere in the world without relying on large naval bases. When it enters operational service (expected between 2028 and 2032), the U.S. Navy will gain a capability far beyond any current UUV. The Manta Ray doesn’t need to return, makes no noise, leaves no logistical trace, and can loiter for extended periods waiting for orders or simply monitoring key routes. But it’s not all smooth sailing. Chinese researchers from Northwestern Polytechnical University claim they have been developing biomimetic manta ray UUVs since 2006, with six prototypes ranging from 10 to 700 kg. According to them, in 2023 a 460 kg prototype successfully passed a 1,025-meter depth test in the South China Sea, and multiple variants have completed 60-day underwater gliding missions. That’s still a much shorter endurance than the American prototype has demonstrated so far, possibly because the objectives aren’t identical. My impression is that these are somewhat different projects. While the Chinese appear to focus mainly on swarm-capable units (with potential applications in underwater reconnaissance, anti-submarine, and anti-ship tasks), the Americans are developing a single large platform optimized for long-term persistent monitoring. The U.S. project is a 30-ton drone; the Chinese ones are 10–700 kg. China also claims that in 2025 it began testing swarms of these vehicles near coral reef areas, suggesting the start of a direct race with the Americans. The fact is that more and more unmanned underwater vehicles are emerging every day, and they will pose a major threat, especially to large manned submarines. A small 100 kg UUV could damage the rudder, propeller, or another critical point of a multi-billion-dollar nuclear submarine. After a series of canceled programs in recent years, the Pentagon desperately needs a big, innovative success like the Manta Ray to reinforce its reputation for effective program management.

Patricia Marins

48,963 görüntüleme • 9 ay önce

sonnet 5 vs sonnet 4.6 vs opus 4.8 vs glm 5.2 – frontend tasks dropped sonnet 5 into a quick test today. same three prompts to all four models, single-shot html/canvas, no edits: • objects falling on a trampoline • rockets playing tennis • a slingshot breaking bottles ranked by speed (total across the 3 tasks): 1. opus 4.8 – 15m 09s 2. sonnet 5 – 16m 05s 3. glm 5.2 – 27m 18s 4. sonnet 4.6 – 35m 06s ranked by code shortness (total loc): 1. sonnet 5 – 1794 2. opus 4.8 – 2063 3. sonnet 4.6 – 2182 4. glm 5.2 – 3285 sonnet 5 came out on top here – leanest code overall and a near-tie for fastest it was also the most creative. in every task it added something none of the others did: – kept the trampoline vibrating after the objects landed – drew a +1 next to the rocket that scored the point – turned the slingshot to face the next bottle before each shot opus 4.8 evaluated the code sonnet 5 produced. four things stood out: • the sphere is a fake, and that's the smart move. the cube and star are real 3d meshes with proper culling and shading, but the ball is just a flat shaded circle. a lit sphere looks identical from every angle, so building it in 3d would burn compute for zero visible payoff. knowing where not to bother is its own kind of skill • weight actually means something on the trampoline. the star is heavy, so it barely bounces and dents the mat hard. the ball is light, so it's lively and leaves a shallow dip. the three objects aren't just different shapes – they have different temperaments, and the physics is what gives them that • the slingshot is framed like a shot, not just drawn. the handle is anchored below the bottom of the screen and runs off-frame, so it reads as something you're holding rather than a sprite parked in the scene. that's a staging instinct, not a rendering one • the paddle ai forward-simulates the ball to predict where it'll land, then adds a deliberate error bias (roughly 1 in 5 shots is a real miss). that's why scoring looks natural instead of robotic – plus four distinct fault types with a catch-all so a rally never hangs without a result bottom line: sonnet 5 does more with less. fastest tier, leanest code, and the only one that added small touches nobody asked for follow thehype. for 24/7 ai news, analysis and breakdowns
0:37

sonnet 5 vs sonnet 4.6 vs opus 4.8 vs glm 5.2 – frontend tasks dropped sonnet 5 into a quick test today. same three prompts to all four models, single-shot html/canvas, no edits: • objects falling on a trampoline • rockets playing tennis • a slingshot breaking bottles ranked by speed (total across the 3 tasks): 1. opus 4.8 – 15m 09s 2. sonnet 5 – 16m 05s 3. glm 5.2 – 27m 18s 4. sonnet 4.6 – 35m 06s ranked by code shortness (total loc): 1. sonnet 5 – 1794 2. opus 4.8 – 2063 3. sonnet 4.6 – 2182 4. glm 5.2 – 3285 sonnet 5 came out on top here – leanest code overall and a near-tie for fastest it was also the most creative. in every task it added something none of the others did: – kept the trampoline vibrating after the objects landed – drew a +1 next to the rocket that scored the point – turned the slingshot to face the next bottle before each shot opus 4.8 evaluated the code sonnet 5 produced. four things stood out: • the sphere is a fake, and that's the smart move. the cube and star are real 3d meshes with proper culling and shading, but the ball is just a flat shaded circle. a lit sphere looks identical from every angle, so building it in 3d would burn compute for zero visible payoff. knowing where not to bother is its own kind of skill • weight actually means something on the trampoline. the star is heavy, so it barely bounces and dents the mat hard. the ball is light, so it's lively and leaves a shallow dip. the three objects aren't just different shapes – they have different temperaments, and the physics is what gives them that • the slingshot is framed like a shot, not just drawn. the handle is anchored below the bottom of the screen and runs off-frame, so it reads as something you're holding rather than a sprite parked in the scene. that's a staging instinct, not a rendering one • the paddle ai forward-simulates the ball to predict where it'll land, then adds a deliberate error bias (roughly 1 in 5 shots is a real miss). that's why scoring looks natural instead of robotic – plus four distinct fault types with a catch-all so a rally never hangs without a result bottom line: sonnet 5 does more with less. fastest tier, leanest code, and the only one that added small touches nobody asked for follow thehype. for 24/7 ai news, analysis and breakdowns

thehype.

14,518 görüntüleme • 3 ay önce

most people still don't comprehend how far AI video has come. no memory between clips used to mean every cut reset the scene, drifted, redrew itself. that's basically solved now if you build around it right this whole ad is one continuous WHITEBOARD, 9 chained clips, and the marker ink never moves, never redraws, never resets to a blank board. here's exactly how, so you can build your own version of this for any product the trick: OMNI flash has a hard 10 second limit per clip and zero memory of the clip before it. so you harvest the last frame of clip N, the board exactly as it looks at that instant, and feed it in as the starting frame of clip N+1. that's the entire mechanism. no cuts, no set, just a hand, a marker, and one continuous illusion the flow: - map your script to the arc: symptom, invisible cause, mechanism, solution, real product - write the VO as one continuous read, then split it into beats, ~20-25 words max per clip, one drawing action per clip - build a board map first, what's written and drawn on each row, so nothing collides as it fills up - generate clip 1, harvest its last frame, chain into clip 2, repeat - once the board gets dense (4-5 clips of ink in), "match the board" - stops being enough instruction. name every existing element explicitly, state a hard no-touch rule, and point at your target by position, not just by text, or the model will grab the wrong line - save the reveal for last: a real product photo beats a drawn one almost every time PROMPT: locked blocks, paste verbatim into every single clip STYLE: "Real documentary UGC footage, static locked camera on a dry-erase whiteboard, one real human hand and forearm only, never show a face or body. A single black marker is used for the entire clip, no color changes, no marker switching. Marker ink renders as genuine dry-erase marker, not a digital text or motion-graphic overlay. Handwriting is plain block capitals, legible at a glance. Icons stay minimal and schematic, one simple recognizable shape only. No captions, no subtitles, no on-screen text beyond what the hand physically writes or draws. ASPECT: 9:16 vertical." VOICE: "VOICEOVER (calm, warm, explanatory, American English, mid-30s):" opening clip, full prompt: "An 8-second locked-camera whiteboard explainer, vertical 9:16. Open on a blank white dry-erase board, static tripod shot, no camera movement, no zoom. 00:00-00:05: The hand writes your hook headline in black marker, plain block capitals, upper-left, then underlines it, natural handwriting speed, ink appears stroke by stroke, slight squeak. 00:05-00:08: The hand draws one small icon, upper-right. VOICEOVER: your hook line. AUDIO: marker squeak, quiet room tone underneath. No music. [STYLE LOCK]" every clip after that opens with "use the attached image, [clip N-1]'s final frame, as the opening frame, match the exact board state precisely" before describing the one new action for that beat
0:47

most people still don't comprehend how far AI video has come. no memory between clips used to mean every cut reset the scene, drifted, redrew itself. that's basically solved now if you build around it right this whole ad is one continuous WHITEBOARD, 9 chained clips, and the marker ink never moves, never redraws, never resets to a blank board. here's exactly how, so you can build your own version of this for any product the trick: OMNI flash has a hard 10 second limit per clip and zero memory of the clip before it. so you harvest the last frame of clip N, the board exactly as it looks at that instant, and feed it in as the starting frame of clip N+1. that's the entire mechanism. no cuts, no set, just a hand, a marker, and one continuous illusion the flow: - map your script to the arc: symptom, invisible cause, mechanism, solution, real product - write the VO as one continuous read, then split it into beats, ~20-25 words max per clip, one drawing action per clip - build a board map first, what's written and drawn on each row, so nothing collides as it fills up - generate clip 1, harvest its last frame, chain into clip 2, repeat - once the board gets dense (4-5 clips of ink in), "match the board" - stops being enough instruction. name every existing element explicitly, state a hard no-touch rule, and point at your target by position, not just by text, or the model will grab the wrong line - save the reveal for last: a real product photo beats a drawn one almost every time PROMPT: locked blocks, paste verbatim into every single clip STYLE: "Real documentary UGC footage, static locked camera on a dry-erase whiteboard, one real human hand and forearm only, never show a face or body. A single black marker is used for the entire clip, no color changes, no marker switching. Marker ink renders as genuine dry-erase marker, not a digital text or motion-graphic overlay. Handwriting is plain block capitals, legible at a glance. Icons stay minimal and schematic, one simple recognizable shape only. No captions, no subtitles, no on-screen text beyond what the hand physically writes or draws. ASPECT: 9:16 vertical." VOICE: "VOICEOVER (calm, warm, explanatory, American English, mid-30s):" opening clip, full prompt: "An 8-second locked-camera whiteboard explainer, vertical 9:16. Open on a blank white dry-erase board, static tripod shot, no camera movement, no zoom. 00:00-00:05: The hand writes your hook headline in black marker, plain block capitals, upper-left, then underlines it, natural handwriting speed, ink appears stroke by stroke, slight squeak. 00:05-00:08: The hand draws one small icon, upper-right. VOICEOVER: your hook line. AUDIO: marker squeak, quiet room tone underneath. No music. [STYLE LOCK]" every clip after that opens with "use the attached image, [clip N-1]'s final frame, as the opening frame, match the exact board state precisely" before describing the one new action for that beat

Lad

78,404 görüntüleme • 1 ay önce

🔴 This may be the most important post I’ve ever written. Please read to the end. Whether you support Elon Musk and Department of Government Efficiency… or you can’t stand them… this isn’t about sides anymore. This is about truth. This is about our country. And this is about your future. 🎥 I just watched one of the most shocking and emotional interviews I’ve seen in years. . Elon Musk and a team of patriots — engineers, former CEOs, veterans, billionaires, tech visionaries — have stepped into the belly of the beast: the federal government. They didn’t go in with weapons. They went in with courage, intellect, and conviction. And what they found? It should shake every American to their core. 📉 Retirement paperwork stored in a literal cave — 22,000 filing cabinets deep underground. 📉 $1 BILLION for a simple online survey — something you could make with SurveyMonkey for $10k. 📉 15 MILLION+ dead people marked as alive in the system — some still receiving benefits. 📉 Babies — yes, babies — receiving fraudulent small business loans. 📉 $500 BILLION a year in waste, fraud, and "improper payments." 📉 One single bank account — with over $800 BILLION — used to pay every federal expense, without oversight. 📉 IRS has 1,400 employees whose only job is handing out laptops and cellphones… 12 times over. This is not a joke. This is how your tax dollars are spent. And for decades, no one has had the guts to clean it up — until now. 💥 DOGE is cutting $4 BILLION in waste per day. Not someday. Not hypothetically. Today. Right now. In real time. They are not cutting your Social Security. They are not destroying Medicare or hurting the vulnerable. They are fixing the system so those programs actually survive. 💔 And here’s the part that broke me — the end of the interview and Elon's words, For What? See the clip below. Bret Baier looked at the team and asked: “Why are you all doing this? You don’t have to be here.” And the answers came… “Because if we don’t… the ship of America sinks.” “Because our kids — and your kids — are going to inherit the debt, the rot, the collapse.” “Because someone had to do something… and no one else would.” They left their companies. Their families. Their comfort. Not for power. Not for money. But because they still believe in the soul of America. 🧠 And now… I want to speak directly to you, whoever you are reading this. Whether you love Elon Musk or hate him… Whether you think Trump is a savior or the villain… Whether you’re red, blue, or tired of it all… Ask yourself: ⚠️ Do you really believe this kind of waste is okay? ⚠️ Do you really think babies should be getting loans while veterans wait months for retirement checks? ⚠️ Do you think a system like this can survive another 5 years? 2 years? 1? The mainstream media will call this reckless. They’ll say it’s illegal. Unconstitutional. But when asked to name a single cost-saving initiative they disagree with… they fall silent. Because they can’t. We are watching a peaceful revolution unfold. And the ones who scream the loudest… are often the ones losing control. So I challenge you — no matter your beliefs — to look at the facts. Watch the full video in the first comment See the truth. Put away the propaganda. Feel the heart behind this mission. You’ll see this isn’t about Elon. It’s about the grandmother finally getting her check on time. The disabled veteran not having to wait months. The scientist who can finally do research without 27 layers of broken systems. 🤝 If you’ve ever loved this country, if you’ve ever wanted to save it, This is your moment to pay attention. Because the real question is no longer “What is DOGE doing?” The real question is: Why did no one do this sooner? And why are so many trying to stop it now? 🇺🇸 We must fix this. For our parents. For our children. For our country.
7:25

🔴 This may be the most important post I’ve ever written. Please read to the end. Whether you support Elon Musk and Department of Government Efficiency… or you can’t stand them… this isn’t about sides anymore. This is about truth. This is about our country. And this is about your future. 🎥 I just watched one of the most shocking and emotional interviews I’ve seen in years. . Elon Musk and a team of patriots — engineers, former CEOs, veterans, billionaires, tech visionaries — have stepped into the belly of the beast: the federal government. They didn’t go in with weapons. They went in with courage, intellect, and conviction. And what they found? It should shake every American to their core. 📉 Retirement paperwork stored in a literal cave — 22,000 filing cabinets deep underground. 📉 $1 BILLION for a simple online survey — something you could make with SurveyMonkey for $10k. 📉 15 MILLION+ dead people marked as alive in the system — some still receiving benefits. 📉 Babies — yes, babies — receiving fraudulent small business loans. 📉 $500 BILLION a year in waste, fraud, and "improper payments." 📉 One single bank account — with over $800 BILLION — used to pay every federal expense, without oversight. 📉 IRS has 1,400 employees whose only job is handing out laptops and cellphones… 12 times over. This is not a joke. This is how your tax dollars are spent. And for decades, no one has had the guts to clean it up — until now. 💥 DOGE is cutting $4 BILLION in waste per day. Not someday. Not hypothetically. Today. Right now. In real time. They are not cutting your Social Security. They are not destroying Medicare or hurting the vulnerable. They are fixing the system so those programs actually survive. 💔 And here’s the part that broke me — the end of the interview and Elon's words, For What? See the clip below. Bret Baier looked at the team and asked: “Why are you all doing this? You don’t have to be here.” And the answers came… “Because if we don’t… the ship of America sinks.” “Because our kids — and your kids — are going to inherit the debt, the rot, the collapse.” “Because someone had to do something… and no one else would.” They left their companies. Their families. Their comfort. Not for power. Not for money. But because they still believe in the soul of America. 🧠 And now… I want to speak directly to you, whoever you are reading this. Whether you love Elon Musk or hate him… Whether you think Trump is a savior or the villain… Whether you’re red, blue, or tired of it all… Ask yourself: ⚠️ Do you really believe this kind of waste is okay? ⚠️ Do you really think babies should be getting loans while veterans wait months for retirement checks? ⚠️ Do you think a system like this can survive another 5 years? 2 years? 1? The mainstream media will call this reckless. They’ll say it’s illegal. Unconstitutional. But when asked to name a single cost-saving initiative they disagree with… they fall silent. Because they can’t. We are watching a peaceful revolution unfold. And the ones who scream the loudest… are often the ones losing control. So I challenge you — no matter your beliefs — to look at the facts. Watch the full video in the first comment See the truth. Put away the propaganda. Feel the heart behind this mission. You’ll see this isn’t about Elon. It’s about the grandmother finally getting her check on time. The disabled veteran not having to wait months. The scientist who can finally do research without 27 layers of broken systems. 🤝 If you’ve ever loved this country, if you’ve ever wanted to save it, This is your moment to pay attention. Because the real question is no longer “What is DOGE doing?” The real question is: Why did no one do this sooner? And why are so many trying to stop it now? 🇺🇸 We must fix this. For our parents. For our children. For our country.

Francois Leclerc

40,507 görüntüleme • 1 yıl önce

The Wrong Date 😳 A short story cum drama using Seedance and GPT on OpenArt Director Prompt : Create an ultra-realistic 90-second cinematic romantic comedy featuring the same young East Asian woman throughout the entire sequence. Maintain identical facial features, soft shoulder-length black hair with bangs, glowing skin, body proportions, and natural expressions in every scene. She wears a fitted white sleeveless crop top, light blue denim shorts, white sneakers, a pearl choker, delicate bracelets, rings, and carries a small white shoulder bag. Premium Korean drama aesthetic, warm natural lighting, realistic performances, cinematic handheld and gimbal camera work, shallow depth of field, soft color grading, and photorealistic 4K HDR. The film opens with the girl waking up in her cozy bedroom after hearing a notification. She excitedly reads a message on her phone from someone she recently matched with that says, "See you at 5 PM." She smiles, stretches happily, and begins getting ready. She styles her hair, applies light makeup, chooses her favorite outfit, sprays perfume, checks herself in the mirror, grabs her handbag, and leaves home feeling excited. She walks through sunny city streets toward a stylish café. Warm afternoon light fills the streets as she happily imagines meeting him for the first time. She orders an iced coffee and waits by the window. Every time the café door opens, she looks up with excitement, but each time it is someone else. Minutes pass and her smile slowly fades. Finally, she leaves the café feeling embarrassed and disappointed. As she steps outside, she accidentally bumps into a handsome young man carrying two iced coffees. One cup spills slightly onto both of them. They immediately apologize before bursting into laughter. He offers her the second untouched coffee and jokingly says, "Looks like this one was meant for you." They begin walking together through a peaceful park, talking naturally as if they've known each other for years. They laugh about funny childhood stories, feed pigeons, browse a small bookstore, share street snacks, and take playful selfies together. Their chemistry grows effortlessly while the afternoon turns into golden hour. During their walk, she casually checks her phone again and suddenly freezes. She realizes the original message actually said "Tomorrow at 5 PM." She laughs uncontrollably and shows him the screen. He laughs too before smiling warmly and saying, "Good... because otherwise we never would've met." As evening arrives, they continue walking side by side along a beautiful riverside promenade. City lights begin reflecting on the water while the sunset paints the sky orange and pink. They stop at the railing, quietly watching the skyline. He gently reaches for her hand. She smiles, accepts without hesitation, and they continue walking together toward the glowing city lights. The final cinematic shot slowly pulls back as they disappear into the sunset hand in hand, laughing together, suggesting that the best moments sometimes begin with the wrong plan. Natural ambient audio only: bedroom ambience, birds chirping, footsteps, café chatter, coffee pouring, distant traffic, park ambience, laughter, bookstore pages turning, river breeze, soft city sounds, and evening ambience. No background music, no subtitles, no logos, no watermarks, and no on-screen text. Premium Korean drama cinematography, realistic emotions, elegant camera movements, shallow depth of field, warm cinematic color grading, 16:9 widescreen, 4K HDR. #director #openart
1:30

The Wrong Date 😳 A short story cum drama using Seedance and GPT on OpenArt Director Prompt : Create an ultra-realistic 90-second cinematic romantic comedy featuring the same young East Asian woman throughout the entire sequence. Maintain identical facial features, soft shoulder-length black hair with bangs, glowing skin, body proportions, and natural expressions in every scene. She wears a fitted white sleeveless crop top, light blue denim shorts, white sneakers, a pearl choker, delicate bracelets, rings, and carries a small white shoulder bag. Premium Korean drama aesthetic, warm natural lighting, realistic performances, cinematic handheld and gimbal camera work, shallow depth of field, soft color grading, and photorealistic 4K HDR. The film opens with the girl waking up in her cozy bedroom after hearing a notification. She excitedly reads a message on her phone from someone she recently matched with that says, "See you at 5 PM." She smiles, stretches happily, and begins getting ready. She styles her hair, applies light makeup, chooses her favorite outfit, sprays perfume, checks herself in the mirror, grabs her handbag, and leaves home feeling excited. She walks through sunny city streets toward a stylish café. Warm afternoon light fills the streets as she happily imagines meeting him for the first time. She orders an iced coffee and waits by the window. Every time the café door opens, she looks up with excitement, but each time it is someone else. Minutes pass and her smile slowly fades. Finally, she leaves the café feeling embarrassed and disappointed. As she steps outside, she accidentally bumps into a handsome young man carrying two iced coffees. One cup spills slightly onto both of them. They immediately apologize before bursting into laughter. He offers her the second untouched coffee and jokingly says, "Looks like this one was meant for you." They begin walking together through a peaceful park, talking naturally as if they've known each other for years. They laugh about funny childhood stories, feed pigeons, browse a small bookstore, share street snacks, and take playful selfies together. Their chemistry grows effortlessly while the afternoon turns into golden hour. During their walk, she casually checks her phone again and suddenly freezes. She realizes the original message actually said "Tomorrow at 5 PM." She laughs uncontrollably and shows him the screen. He laughs too before smiling warmly and saying, "Good... because otherwise we never would've met." As evening arrives, they continue walking side by side along a beautiful riverside promenade. City lights begin reflecting on the water while the sunset paints the sky orange and pink. They stop at the railing, quietly watching the skyline. He gently reaches for her hand. She smiles, accepts without hesitation, and they continue walking together toward the glowing city lights. The final cinematic shot slowly pulls back as they disappear into the sunset hand in hand, laughing together, suggesting that the best moments sometimes begin with the wrong plan. Natural ambient audio only: bedroom ambience, birds chirping, footsteps, café chatter, coffee pouring, distant traffic, park ambience, laughter, bookstore pages turning, river breeze, soft city sounds, and evening ambience. No background music, no subtitles, no logos, no watermarks, and no on-screen text. Premium Korean drama cinematography, realistic emotions, elegant camera movements, shallow depth of field, warm cinematic color grading, 16:9 widescreen, 4K HDR. #director #openart

Synthia

54,708 görüntüleme • 2 ay önce

How much cleaning is too much cleaning? Make your video like this using Product commercial skill on FlovaAI Model used: Seedance 2.0 prompt A 60-second 3D Pixar-style animated commercial for 7UP Extra Fizz. Bright, vibrant, highly expressive cartoon rendering with smooth exaggerated animation, big emotional faces, soft rounded shapes, rich saturated colors, and cinematic lighting. Vertical smartphone aspect ratio with dynamic camera moves (sweeping low angles, playful tracking shots, extreme close-ups on expressions). *Setting:* A sunny, modern Western suburban home with open-plan living spaces, light wooden floors, white walls with geometric wood accent panels, large windows letting in golden afternoon light, and a cozy, slightly cluttered family feel. *Characters:* •⁠ ⁠Mom: Mid-50s Western woman, warm but dramatic, short stylish brown hair with a few gray streaks, wearing a soft beige cardigan over a patterned blouse and jeans. •⁠ ⁠Daughter: Early-20s, long reddish-brown hair in a high ponytail, wearing an olive-green polo shirt, gold heart necklace, and baggy light-wash jeans. Highly expressive Pixar-style face that goes from annoyed → exhausted → pure joy. *Scene breakdown:* 0–6s: Close-up of a vintage green rotary phone on a glossy side table. Mom appears in the background holding the handset, eyes wide with urgency, waving her free hand dramatically as she speaks in English: “The guests are coming in an hour! Honey, hurry up! Clean every single fan blade, one by one — please, please, go go go!” 6–12s: Cut to the daughter on the living-room sofa, scrolling on a peach smartphone. Her face scrunches into a classic Pixar annoyed expression (eyebrows knitted, mouth twisted). She lets out a big exaggerated sigh. 12–22s: Mom marches in holding a green-handled mop, gesturing wildly. Daughter climbs a bright red stepladder and starts cleaning a dark wooden ceiling fan. She meticulously wipes each blade with a white cloth, her face showing increasing determination mixed with irritation. Camera circles around her as dust motes float in the light. She then dusts the geometric wooden wall panels with a long grey duster, dramatically wiping sweat from her forehead with a big cartoonish gesture. 22–32s: Daughter now wears bright yellow rubber gloves. She crouches inside a wide-open stainless-steel refrigerator, vigorously scrubbing the white interior walls and shelves with a green microfiber cloth. Several green 7UP bottles are clearly visible on the door shelves. Her expression is pure focused effort, tongue slightly sticking out in concentration. 32–42s: Outside on the front porch steps under a soft evening sky. Mom stands in the doorway still urging. Daughter holds the mop, shoulders slumped, and complains with big exaggerated exhaustion: “Mom, the stairs too?! This is getting a little extra!” She continues, voice rising: “I’m completely wiped from all this extra cleaning!” 42–52s: Extreme close-up of the daughter’s tired face. She reaches for a cold green 7UP Extra Fizz bottle. With a satisfying twist and loud fizzy “PSSSHT!” sound effect, she opens it. Bubbles and tiny water droplets spray in a playful Pixar-style flourish. She takes a long, refreshing drink. Her entire face transforms — eyes light up, cheeks glow, a huge genuine smile spreads as energy returns to her body. She does a little joyful bounce. 52–60s: Dynamic heroic product shot. The icy-cold 7UP Extra Fizz bottle rises against a bright blue sky. Dramatic water splash and exploding bubbles surround it in exaggerated, sparkling 3D animation. Bold, playful on-screen text pops in with a bounce: “INTRODUCING 7UP EXTRA FIZZ” next to the classic 7UP logo. Soft upbeat music swells into a fresh, fizzy climax. *Overall tone & style:* Warm, relatable, slightly comedic family chaos that feels like a Pixar short, transitioning into pure refreshing joy. Exaggerated facial expressions, squash-and-stretch animation, vibrant green product highlights, smooth camera movement, clear English dialogue, and upbeat background music that builds from stressed household energy to sparkling refreshment. #FlovaBrandstormand
1:00

How much cleaning is too much cleaning? Make your video like this using Product commercial skill on FlovaAI Model used: Seedance 2.0 prompt A 60-second 3D Pixar-style animated commercial for 7UP Extra Fizz. Bright, vibrant, highly expressive cartoon rendering with smooth exaggerated animation, big emotional faces, soft rounded shapes, rich saturated colors, and cinematic lighting. Vertical smartphone aspect ratio with dynamic camera moves (sweeping low angles, playful tracking shots, extreme close-ups on expressions). *Setting:* A sunny, modern Western suburban home with open-plan living spaces, light wooden floors, white walls with geometric wood accent panels, large windows letting in golden afternoon light, and a cozy, slightly cluttered family feel. *Characters:* •⁠ ⁠Mom: Mid-50s Western woman, warm but dramatic, short stylish brown hair with a few gray streaks, wearing a soft beige cardigan over a patterned blouse and jeans. •⁠ ⁠Daughter: Early-20s, long reddish-brown hair in a high ponytail, wearing an olive-green polo shirt, gold heart necklace, and baggy light-wash jeans. Highly expressive Pixar-style face that goes from annoyed → exhausted → pure joy. *Scene breakdown:* 0–6s: Close-up of a vintage green rotary phone on a glossy side table. Mom appears in the background holding the handset, eyes wide with urgency, waving her free hand dramatically as she speaks in English: “The guests are coming in an hour! Honey, hurry up! Clean every single fan blade, one by one — please, please, go go go!” 6–12s: Cut to the daughter on the living-room sofa, scrolling on a peach smartphone. Her face scrunches into a classic Pixar annoyed expression (eyebrows knitted, mouth twisted). She lets out a big exaggerated sigh. 12–22s: Mom marches in holding a green-handled mop, gesturing wildly. Daughter climbs a bright red stepladder and starts cleaning a dark wooden ceiling fan. She meticulously wipes each blade with a white cloth, her face showing increasing determination mixed with irritation. Camera circles around her as dust motes float in the light. She then dusts the geometric wooden wall panels with a long grey duster, dramatically wiping sweat from her forehead with a big cartoonish gesture. 22–32s: Daughter now wears bright yellow rubber gloves. She crouches inside a wide-open stainless-steel refrigerator, vigorously scrubbing the white interior walls and shelves with a green microfiber cloth. Several green 7UP bottles are clearly visible on the door shelves. Her expression is pure focused effort, tongue slightly sticking out in concentration. 32–42s: Outside on the front porch steps under a soft evening sky. Mom stands in the doorway still urging. Daughter holds the mop, shoulders slumped, and complains with big exaggerated exhaustion: “Mom, the stairs too?! This is getting a little extra!” She continues, voice rising: “I’m completely wiped from all this extra cleaning!” 42–52s: Extreme close-up of the daughter’s tired face. She reaches for a cold green 7UP Extra Fizz bottle. With a satisfying twist and loud fizzy “PSSSHT!” sound effect, she opens it. Bubbles and tiny water droplets spray in a playful Pixar-style flourish. She takes a long, refreshing drink. Her entire face transforms — eyes light up, cheeks glow, a huge genuine smile spreads as energy returns to her body. She does a little joyful bounce. 52–60s: Dynamic heroic product shot. The icy-cold 7UP Extra Fizz bottle rises against a bright blue sky. Dramatic water splash and exploding bubbles surround it in exaggerated, sparkling 3D animation. Bold, playful on-screen text pops in with a bounce: “INTRODUCING 7UP EXTRA FIZZ” next to the classic 7UP logo. Soft upbeat music swells into a fresh, fizzy climax. *Overall tone & style:* Warm, relatable, slightly comedic family chaos that feels like a Pixar short, transitioning into pure refreshing joy. Exaggerated facial expressions, squash-and-stretch animation, vibrant green product highlights, smooth camera movement, clear English dialogue, and upbeat background music that builds from stressed household energy to sparkling refreshment. #FlovaBrandstormand

Sharon Riley

156,326 görüntüleme • 2 ay önce

My 7 Day Aesthetic Split Mon: Upper Chest + Side Delts + Biceps Tue: Back Width + Triceps Wed: Delts Only Thu: Legs + Core Fri: Pump Day Sat: Arms + Cardio Sun: Light Legs + Recovery (Below will be my entire workout / weight lifting plan + nutrition breakdown) Be sure to add 30min cardio after every weight lifting session. Incline: Max Speed: 2.5 - 3 This is focused on width, capped shoulders, chest shelf, tight waist, and staying athletic year round. 7 Day Aesthetic Split Monday: Upper Chest + Side Delts + Biceps Incline DB Press Incline Smith Press High to Low Cable Fly DB Laterals Cable Laterals Seated DB Curl Hammer Curl Tuesday: Back Width + Triceps Pull Ups / Assisted Pull Ups Wide Grip Lat Pulldown Single Arm Lat Pulldown Single Arm Row Rope Pushdown Tricep Pulldowns Dips Wednesday: Delts Only Seated DB Shoulder Press DB Laterals Cable Laterals Rear Delt Fly Face Pulls Shrugs Thursday: Legs + Core Walking Lunges Squats Deadlift Leg Curl Hamstring Curl Calves Hanging Knee Raise Cable Crunch Friday: Aesthetic Pump Day Incline Press Pull Ups Cable Fly Row Variation Laterals Rear Delts Pushup Burnout Saturday: Arms + Cardio EZ Curl Incline Curl Rope Hammer Curl Skull Crushers Pushdowns Overhead Cable Extensions Incline Treadmill 25 min Sunday: Legs Light + Recovery Leg Press Extensions Hamstring Curl Calves Core Circuit Walk 30 min Meal plan for the week, I like to switch it every now and than from ground turkey to ground beef, filet mignons steaks and chicken. You can use white rice or sweet potato’s as your carbs Use this meal plan as a foundation, not a limitation. Per Meal: - 200g 97/3 Ground Turkey (raw) - 100g Cooked White Rice - 90g Mixed Vegetables Macros per meal: Protein: 44g Carbs: 28g Fat: 6-8g Calories: ~400 kcal Daily Target: Protein: 190g Carbs: 140g Fat: Less than 50g This is a clean, simple structure built around high protein, controlled carbs, lower fats, and foods that are easy to prep consistently. That alone can change a lot for people. The real key is adjusting it to your bodyweight, goals, activity level, and timeline. Fat loss, muscle gain, maintenance… all require different numbers. Use ChatGPT and ask something like dis: “I weigh ___ lbs, I’m ___ height, I train ___ days a week, and my goal is to lose fat / gain muscle / maintain. Use this meal plan as a base and adjust my calories, protein, carbs, fats, and portion sizes.” That prompt alone can save you months of guessing, use my workout plan + meal plan for 5-6 months. I promise you, you will drop weight and chisel up Start with structure. Adjust with data. Stay consistent. My peptide stack: Retatrutide Appetite down. Fat loss up. Blood sugar support. This one helps people move different when discipline meets science. Tesamorelin Targets stubborn visceral fat and can help tighten the midsection. Recovery + body composition play. MOTS-c Mitochondria support. Better energy production, endurance, and metabolic efficiency. Feel like your engine got tuned up. BPC-157 Recovery weapon. People use it for joints, tendons, gut health, and healing nagging injuries that slow progress. GHK-cu Skin, hair, healing. Known for regeneration support and helping you look healthier while recovering better. AHK-cu Mostly talked about for hair support. Used for scalp health, follicles, and helping promote thicker growth over time. It isn’t rocket science, it’s just consistency. I’m no where near where I want to be. Still need maybe 7-8 months of dieting to get down to 10-12% body fat and than I’ll maintain from there.
0:47

My 7 Day Aesthetic Split Mon: Upper Chest + Side Delts + Biceps Tue: Back Width + Triceps Wed: Delts Only Thu: Legs + Core Fri: Pump Day Sat: Arms + Cardio Sun: Light Legs + Recovery (Below will be my entire workout / weight lifting plan + nutrition breakdown) Be sure to add 30min cardio after every weight lifting session. Incline: Max Speed: 2.5 - 3 This is focused on width, capped shoulders, chest shelf, tight waist, and staying athletic year round. 7 Day Aesthetic Split Monday: Upper Chest + Side Delts + Biceps Incline DB Press Incline Smith Press High to Low Cable Fly DB Laterals Cable Laterals Seated DB Curl Hammer Curl Tuesday: Back Width + Triceps Pull Ups / Assisted Pull Ups Wide Grip Lat Pulldown Single Arm Lat Pulldown Single Arm Row Rope Pushdown Tricep Pulldowns Dips Wednesday: Delts Only Seated DB Shoulder Press DB Laterals Cable Laterals Rear Delt Fly Face Pulls Shrugs Thursday: Legs + Core Walking Lunges Squats Deadlift Leg Curl Hamstring Curl Calves Hanging Knee Raise Cable Crunch Friday: Aesthetic Pump Day Incline Press Pull Ups Cable Fly Row Variation Laterals Rear Delts Pushup Burnout Saturday: Arms + Cardio EZ Curl Incline Curl Rope Hammer Curl Skull Crushers Pushdowns Overhead Cable Extensions Incline Treadmill 25 min Sunday: Legs Light + Recovery Leg Press Extensions Hamstring Curl Calves Core Circuit Walk 30 min Meal plan for the week, I like to switch it every now and than from ground turkey to ground beef, filet mignons steaks and chicken. You can use white rice or sweet potato’s as your carbs Use this meal plan as a foundation, not a limitation. Per Meal: - 200g 97/3 Ground Turkey (raw) - 100g Cooked White Rice - 90g Mixed Vegetables Macros per meal: Protein: 44g Carbs: 28g Fat: 6-8g Calories: ~400 kcal Daily Target: Protein: 190g Carbs: 140g Fat: Less than 50g This is a clean, simple structure built around high protein, controlled carbs, lower fats, and foods that are easy to prep consistently. That alone can change a lot for people. The real key is adjusting it to your bodyweight, goals, activity level, and timeline. Fat loss, muscle gain, maintenance… all require different numbers. Use ChatGPT and ask something like dis: “I weigh ___ lbs, I’m ___ height, I train ___ days a week, and my goal is to lose fat / gain muscle / maintain. Use this meal plan as a base and adjust my calories, protein, carbs, fats, and portion sizes.” That prompt alone can save you months of guessing, use my workout plan + meal plan for 5-6 months. I promise you, you will drop weight and chisel up Start with structure. Adjust with data. Stay consistent. My peptide stack: Retatrutide Appetite down. Fat loss up. Blood sugar support. This one helps people move different when discipline meets science. Tesamorelin Targets stubborn visceral fat and can help tighten the midsection. Recovery + body composition play. MOTS-c Mitochondria support. Better energy production, endurance, and metabolic efficiency. Feel like your engine got tuned up. BPC-157 Recovery weapon. People use it for joints, tendons, gut health, and healing nagging injuries that slow progress. GHK-cu Skin, hair, healing. Known for regeneration support and helping you look healthier while recovering better. AHK-cu Mostly talked about for hair support. Used for scalp health, follicles, and helping promote thicker growth over time. It isn’t rocket science, it’s just consistency. I’m no where near where I want to be. Still need maybe 7-8 months of dieting to get down to 10-12% body fat and than I’ll maintain from there.

AYCE

11,503 görüntüleme • 5 ay önce

Here's a devlog made by an anonymous Chinese fan replicating the surprisingly brand new technique that I developed for detecting asteroids which wound up being so powerful that it can easily track Stealth Fighters from over 100km away even when it’s only using three $30 webcams as sensors meaning it easily outperforms all modern stealth tracking techniques in precision, range and cost. And while this demo is using optical light, this same technique which I call pixel motion to voxel projection, can be used interchangeably with thermal infrared cameras to work at night and also majorly boosts the effectiveness of radar allowing you to track fighters much more effectively through clouds and over the horizon. This technique will also always eventually give the exact location of the target even if the image is blurry as those blurs will always average out from the different perspectives into revealing the precise location of the target in the voxel grid. There is definitely a Mandela effect with this technique as it feels as though it should already exist, especially because at first as it sounds like it is performing triangulation (which has existed for years and is what we do for mocap and tennis ball tracking). But triangulation is entirely separate to this as triangulations only works if you have already identified where the ball is in a 2D image because you’re able to rely on being able to use at least 2 separate high quality cameras which are much closer to the ball making the ball’s apparent size much much bigger and therefore gives you hundreds of pixels to work with which makes it much easier to use object recognition techniques to recognize where it is in the image aka in 2D and then you’re just using the other cameras view to project out lines which intersect in 3D to find out where the ball is in 3D. The major difference is that pixel motion to voxel projection allows you to find where the object is in 3D without having already found it in 2D which is an unbelievable difference as it allows you to use much lower quality cameras together to accumulate data together into 3D space. If this seem like it doesn’t mean much then what it actually means is that you don’t understand what I’m saying as what I’m saying means a LOT in practical terms as it means you go from having to use an imaging system that has to be able to image the object to the point that it is over a hundred total pixels in surface area to have enough data to recognize it to instead be able to use something that is only images the object to be 1 pixel in surface area and only changes the brightness value by 1 value every now and then. I’d recommend an amazing video by DST studios called “Lowlight cameras can’t defeat stealth” if you want a great video which goes over the difficulty of even using telescopes to recognize stealth fighters and why this is so impressive compared to other techniques and ironically it is what inspired me to realize the asteroid tracker I was working on actually could do this. Which brings me to the point that if this wasn’t a new technique then not only would there be at least one example of an asteroid survey that points distant telescopes at the same place at the same time in order to be able to add the light together to detect asteroids which as I was shocked to learn isn’t a thing despite the fact that it would make detecting asteroids trivial by comparison to modern 2D imaging while also having no impact on the normal scientific operations of those surveys other than small changes to scheduling. But there would also be an example of a drone tracker that uses this instead of using the aforementioned high quality zoomable telescope which has to be able to zoom in close enough to be able to recognize a drone. If you want to tell me that this is something that already exists give me an exact example of a product that uses it, not the general outline of a concept that you think it is, the actual product and then also tell me the asteroid survey that uses distant telescopes that point at the exact same place at the exact same time because I can guarantee that if you google what you think uses this you won’t even find the steps of subtracting the images from each other to get motion and will definitely not get the added step of projecting that motion into a voxel grid (It would blow your mind if you found out how Xbox kinect cameras work.) Also I want to make it clear, I’m not saying you should just use web cams to do this, I’m just using them as an example to show you the power of this in reality you would probably want to use 5 high quality zoomable thermal cameras which pan across the sky in sync with each other which due to using lower frequency are much less prone to the Rayleigh scattering that scatters visible light at 150 or so km away and again, you can also use this to majorly upgrade radar. Pretty much all of the problems you could think of for this are incredibly easy to overcome if you apply even a small amount of brainpower into fixing the problem. And yes, this gives you the exact location down to the meter of whatever you are tracking even if the image is blurry as those blurs will always average out to the exact location down to the meter in the voxel grid. Which is what makes this technique so powerful since the cost of adding each camera to The network grows linearly while the rate at which each camera gives more information grows exponentially due to the increasing unlikeliness of all of them having more movement in the same place. And given the size of the cameras it really wouldn’t be that hard to hide and network these cameras together in other countries and on sea buoys to know where planes are everywhere in the world. Which brings me to the point that I personally really don’t care about the military uses of this technology, if all it could do is precisely track stealth fighters then I wouldn’t have cared enough to work on it, I could have used any of the many other life saving techniques as the subject of the video, stealth fighters just sounds the most clickable and the scale of the problem is more intuitive to most people and if I did use any of those as subjects for the demo it would inevitably result in the stealth fighter technique being figured out anyway and all of the other uses are so useful that I don't think anyone would reasonably complain about the upside. The real purpose of this video is that since this is a new technique that hasn’t been used to detect stealth fighters despite the billions we have spent on that, then what else can you apply this to that could go on to improve billions of people’s lives that you or others are working on. For example this also allows you to majorly improve the effectiveness of cryo electron microscopy and CT scanners. This part also is kind of hard to explain as it also sounds like it exists but again, when you look through all of the places where you think it is being used you will find that it wasn’t. What I’m saying here isn’t that this is a Radon transform or gaussian splat or whatever, I’m saying that this is able to get new information that wasn’t being accessed before due to the added information about depth you get from the correlation of movement between each perspective which adds to the information that you already have. This allows you to directly subtract foreground and background objects as well as noise faster than you would be able to before and works better than super resolution for your images since super resolution won’t remove foreground and background objects like this does and instead just scales up target, foreground and background objects indiscriminately. And while with enough data Radon transforms or other scanning techniques would eventually get you a correct answer this will get you there a lot faster since those are mostly averaging techniques which average out noise whereas this gets you the ability to directly subtract noise. I’m not expecting you to think that this would do anything but if you try it for yourself you will find that it does majorly improve your ability to perform 3d scans. Again, cryo EM is a field where you would expect this technique to exist but when you look through all the papers on the topic there is no mention of tilting the grid slightly in order to be able to change your perspective slightly on the order of the feature size (if you tilt the grid then you only need precision on the order of an arc minute to do this) and doing multiple exposures from multiple different known tilts and then using those difference images to correlate depth from motion. In fact, in cryo EM you would normally want to do the opposite of this and have your exposures all taken from the same grid angle and just use the variations in how many of the same proteins are oriented in order to be able to scan them for a 3D model but this will generate you far more data faster. There is so much information that I can’t really explain in text so if you have any questions such as why this hasn’t been made before then they will most likely be answered in the video I originally posted which I have added to the end of the first Devlog for your convenience. And again, pretty much all of the problems with the technique can be fixed with a little bit of brainpower, in reality you would probably want to use 5 high quality zoomable thermal cameras which pan across the sky in sync with each other which due to using lower frequency are much less prone to the Rayleigh scattering that scatters visible light at 150 or so km away and again, you can also use this to majorly upgrade radar.
18:48

Here's a devlog made by an anonymous Chinese fan replicating the surprisingly brand new technique that I developed for detecting asteroids which wound up being so powerful that it can easily track Stealth Fighters from over 100km away even when it’s only using three $30 webcams as sensors meaning it easily outperforms all modern stealth tracking techniques in precision, range and cost. And while this demo is using optical light, this same technique which I call pixel motion to voxel projection, can be used interchangeably with thermal infrared cameras to work at night and also majorly boosts the effectiveness of radar allowing you to track fighters much more effectively through clouds and over the horizon. This technique will also always eventually give the exact location of the target even if the image is blurry as those blurs will always average out from the different perspectives into revealing the precise location of the target in the voxel grid. There is definitely a Mandela effect with this technique as it feels as though it should already exist, especially because at first as it sounds like it is performing triangulation (which has existed for years and is what we do for mocap and tennis ball tracking). But triangulation is entirely separate to this as triangulations only works if you have already identified where the ball is in a 2D image because you’re able to rely on being able to use at least 2 separate high quality cameras which are much closer to the ball making the ball’s apparent size much much bigger and therefore gives you hundreds of pixels to work with which makes it much easier to use object recognition techniques to recognize where it is in the image aka in 2D and then you’re just using the other cameras view to project out lines which intersect in 3D to find out where the ball is in 3D. The major difference is that pixel motion to voxel projection allows you to find where the object is in 3D without having already found it in 2D which is an unbelievable difference as it allows you to use much lower quality cameras together to accumulate data together into 3D space. If this seem like it doesn’t mean much then what it actually means is that you don’t understand what I’m saying as what I’m saying means a LOT in practical terms as it means you go from having to use an imaging system that has to be able to image the object to the point that it is over a hundred total pixels in surface area to have enough data to recognize it to instead be able to use something that is only images the object to be 1 pixel in surface area and only changes the brightness value by 1 value every now and then. I’d recommend an amazing video by DST studios called “Lowlight cameras can’t defeat stealth” if you want a great video which goes over the difficulty of even using telescopes to recognize stealth fighters and why this is so impressive compared to other techniques and ironically it is what inspired me to realize the asteroid tracker I was working on actually could do this. Which brings me to the point that if this wasn’t a new technique then not only would there be at least one example of an asteroid survey that points distant telescopes at the same place at the same time in order to be able to add the light together to detect asteroids which as I was shocked to learn isn’t a thing despite the fact that it would make detecting asteroids trivial by comparison to modern 2D imaging while also having no impact on the normal scientific operations of those surveys other than small changes to scheduling. But there would also be an example of a drone tracker that uses this instead of using the aforementioned high quality zoomable telescope which has to be able to zoom in close enough to be able to recognize a drone. If you want to tell me that this is something that already exists give me an exact example of a product that uses it, not the general outline of a concept that you think it is, the actual product and then also tell me the asteroid survey that uses distant telescopes that point at the exact same place at the exact same time because I can guarantee that if you google what you think uses this you won’t even find the steps of subtracting the images from each other to get motion and will definitely not get the added step of projecting that motion into a voxel grid (It would blow your mind if you found out how Xbox kinect cameras work.) Also I want to make it clear, I’m not saying you should just use web cams to do this, I’m just using them as an example to show you the power of this in reality you would probably want to use 5 high quality zoomable thermal cameras which pan across the sky in sync with each other which due to using lower frequency are much less prone to the Rayleigh scattering that scatters visible light at 150 or so km away and again, you can also use this to majorly upgrade radar. Pretty much all of the problems you could think of for this are incredibly easy to overcome if you apply even a small amount of brainpower into fixing the problem. And yes, this gives you the exact location down to the meter of whatever you are tracking even if the image is blurry as those blurs will always average out to the exact location down to the meter in the voxel grid. Which is what makes this technique so powerful since the cost of adding each camera to The network grows linearly while the rate at which each camera gives more information grows exponentially due to the increasing unlikeliness of all of them having more movement in the same place. And given the size of the cameras it really wouldn’t be that hard to hide and network these cameras together in other countries and on sea buoys to know where planes are everywhere in the world. Which brings me to the point that I personally really don’t care about the military uses of this technology, if all it could do is precisely track stealth fighters then I wouldn’t have cared enough to work on it, I could have used any of the many other life saving techniques as the subject of the video, stealth fighters just sounds the most clickable and the scale of the problem is more intuitive to most people and if I did use any of those as subjects for the demo it would inevitably result in the stealth fighter technique being figured out anyway and all of the other uses are so useful that I don't think anyone would reasonably complain about the upside. The real purpose of this video is that since this is a new technique that hasn’t been used to detect stealth fighters despite the billions we have spent on that, then what else can you apply this to that could go on to improve billions of people’s lives that you or others are working on. For example this also allows you to majorly improve the effectiveness of cryo electron microscopy and CT scanners. This part also is kind of hard to explain as it also sounds like it exists but again, when you look through all of the places where you think it is being used you will find that it wasn’t. What I’m saying here isn’t that this is a Radon transform or gaussian splat or whatever, I’m saying that this is able to get new information that wasn’t being accessed before due to the added information about depth you get from the correlation of movement between each perspective which adds to the information that you already have. This allows you to directly subtract foreground and background objects as well as noise faster than you would be able to before and works better than super resolution for your images since super resolution won’t remove foreground and background objects like this does and instead just scales up target, foreground and background objects indiscriminately. And while with enough data Radon transforms or other scanning techniques would eventually get you a correct answer this will get you there a lot faster since those are mostly averaging techniques which average out noise whereas this gets you the ability to directly subtract noise. I’m not expecting you to think that this would do anything but if you try it for yourself you will find that it does majorly improve your ability to perform 3d scans. Again, cryo EM is a field where you would expect this technique to exist but when you look through all the papers on the topic there is no mention of tilting the grid slightly in order to be able to change your perspective slightly on the order of the feature size (if you tilt the grid then you only need precision on the order of an arc minute to do this) and doing multiple exposures from multiple different known tilts and then using those difference images to correlate depth from motion. In fact, in cryo EM you would normally want to do the opposite of this and have your exposures all taken from the same grid angle and just use the variations in how many of the same proteins are oriented in order to be able to scan them for a 3D model but this will generate you far more data faster. There is so much information that I can’t really explain in text so if you have any questions such as why this hasn’t been made before then they will most likely be answered in the video I originally posted which I have added to the end of the first Devlog for your convenience. And again, pretty much all of the problems with the technique can be fixed with a little bit of brainpower, in reality you would probably want to use 5 high quality zoomable thermal cameras which pan across the sky in sync with each other which due to using lower frequency are much less prone to the Rayleigh scattering that scatters visible light at 150 or so km away and again, you can also use this to majorly upgrade radar.

ConsistentlyInconsistent

50,925 görüntüleme • 1 yıl önce

STOP PAYING FOR MOTION DESIGN SOFTWARE opus 5.5 one shot every frame of this in code, no after effects im open sourcing the whole template for free plug in your product and it recreates this steal the prompt ↓ Ask me for: the one question a user asks my product and its one-line answer, two album covers, a royalty-free song around 110 BPM with a quiet intro and a hard drop (Mixkit, free for commercial use), and my logo for the ending. If I skip any, use the defaults: "is this all code?" / "yes. every frame.", two atmospheric photos, Mixkit "Head Bang". A 22 second square loop, 1440x1440 at 60fps, 2D only, one continuous take. Nothing ever cuts: every scene grows out of the last, and every gesture physically carries the camera into the next world. Every morph glides for 0.8s on cubic-bezier(.45,0,.15,1) and the camera zoom rides the same curve, so shapes change so smoothly you barely notice. Content dissolves in the back half of each glide. One gesture per scene. Look: a warm light stage (#f3f3f0 to #e3e3de), black UI, the app world dark (#121212) tinted from the current album cover, one green accent (#1ed760). Geist for UI, the real macOS pointer, soft layered shadows that grow with the shape's height. Banned: hard cuts, bouncy springs, particles, glows, zooming in and straight back out, holds longer than 1s, anything that looks like a template. Beats are the song's, and the press lands on its drop. Generate: the cursor clicks, the pill glides into a spinner, then a check. Chat: the check splits into three typing dots (goo). The left dot flies up into the question bubble and types it, the right one flies down into the reply. Both contract back into dots while gliding in and pour into the middle one. Play: the middle dot bends into a play triangle, point by point. The cursor presses it on the drop: a white button pops in under the click and the dark app floods out around it, so the leftover white becomes the play button. The camera pulls back to reveal the full now-playing screen: big cover, title, heart (liked, fills green), progress, controls, volume. Swipe: the cursor drags the cover sideways, the next track slides in, and the whole app retints from the new cover. Drag: the camera glides to the volume. The cursor drags it to max and keeps pulling: the bar rubber-bands and drags the camera sideways out of the app, tracking the knob across a dark dotted canvas. Chart: the line lands and bends up into a green chart while the number counts up. The volume knob becomes its last point. Dive: the cursor clicks that point and the camera dives into it until the light stage fills the frame. Ending: an "Ask [my product]" button grows out of the light, thins into a line, and the line fans out into my logo (default: the Claude spark, six copies rotating into twelve rays in Claude orange). It folds back into the line, which thickens into Generate. Last frame = first frame. 1. One HTML canvas. Everything is a pure function of time inside seek(t): no timers, no state between frames. 2. A camera with position and log-space zoom. Scenes live side by side in one world, so a pan really travels. 3. Goo: blur + alpha threshold on an offscreen layer for the split and the merges. 4. Floods are circles that grow from whatever caused them to the farthest corner in about 0.4s, and the colour switch happens underneath them. 5. Sound: before the press the song plays through a low-pass filter, like it's in the next room, and opens up to full on the drop. A downloaded Mixkit SFX for every event, each placed by its measured peak. Loudnorm to -14 LUFS. 6. Render with Playwright at 60fps with 4 motion-blur subframes, 12 on the fast pan. Then scan every frame for single-frame jumps and fix each one. A handoff between two drawings only works once the first one has fully landed, or it pops. The cursor must stay on whatever it drags, even while it stretches. A counter or tooltip that changes every frame smears under motion blur, so swap whole values. Ask me for the inputs, then show me the beat map and 6 stills (chat, play, app, drag, chart, logo) before you render.
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STOP PAYING FOR MOTION DESIGN SOFTWARE opus 5.5 one shot every frame of this in code, no after effects im open sourcing the whole template for free plug in your product and it recreates this steal the prompt ↓ Ask me for: the one question a user asks my product and its one-line answer, two album covers, a royalty-free song around 110 BPM with a quiet intro and a hard drop (Mixkit, free for commercial use), and my logo for the ending. If I skip any, use the defaults: "is this all code?" / "yes. every frame.", two atmospheric photos, Mixkit "Head Bang". A 22 second square loop, 1440x1440 at 60fps, 2D only, one continuous take. Nothing ever cuts: every scene grows out of the last, and every gesture physically carries the camera into the next world. Every morph glides for 0.8s on cubic-bezier(.45,0,.15,1) and the camera zoom rides the same curve, so shapes change so smoothly you barely notice. Content dissolves in the back half of each glide. One gesture per scene. Look: a warm light stage (#f3f3f0 to #e3e3de), black UI, the app world dark (#121212) tinted from the current album cover, one green accent (#1ed760). Geist for UI, the real macOS pointer, soft layered shadows that grow with the shape's height. Banned: hard cuts, bouncy springs, particles, glows, zooming in and straight back out, holds longer than 1s, anything that looks like a template. Beats are the song's, and the press lands on its drop. Generate: the cursor clicks, the pill glides into a spinner, then a check. Chat: the check splits into three typing dots (goo). The left dot flies up into the question bubble and types it, the right one flies down into the reply. Both contract back into dots while gliding in and pour into the middle one. Play: the middle dot bends into a play triangle, point by point. The cursor presses it on the drop: a white button pops in under the click and the dark app floods out around it, so the leftover white becomes the play button. The camera pulls back to reveal the full now-playing screen: big cover, title, heart (liked, fills green), progress, controls, volume. Swipe: the cursor drags the cover sideways, the next track slides in, and the whole app retints from the new cover. Drag: the camera glides to the volume. The cursor drags it to max and keeps pulling: the bar rubber-bands and drags the camera sideways out of the app, tracking the knob across a dark dotted canvas. Chart: the line lands and bends up into a green chart while the number counts up. The volume knob becomes its last point. Dive: the cursor clicks that point and the camera dives into it until the light stage fills the frame. Ending: an "Ask [my product]" button grows out of the light, thins into a line, and the line fans out into my logo (default: the Claude spark, six copies rotating into twelve rays in Claude orange). It folds back into the line, which thickens into Generate. Last frame = first frame. 1. One HTML canvas. Everything is a pure function of time inside seek(t): no timers, no state between frames. 2. A camera with position and log-space zoom. Scenes live side by side in one world, so a pan really travels. 3. Goo: blur + alpha threshold on an offscreen layer for the split and the merges. 4. Floods are circles that grow from whatever caused them to the farthest corner in about 0.4s, and the colour switch happens underneath them. 5. Sound: before the press the song plays through a low-pass filter, like it's in the next room, and opens up to full on the drop. A downloaded Mixkit SFX for every event, each placed by its measured peak. Loudnorm to -14 LUFS. 6. Render with Playwright at 60fps with 4 motion-blur subframes, 12 on the fast pan. Then scan every frame for single-frame jumps and fix each one. A handoff between two drawings only works once the first one has fully landed, or it pops. The cursor must stay on whatever it drags, even while it stretches. A counter or tooltip that changes every frame smears under motion blur, so swap whole values. Ask me for the inputs, then show me the beat map and 6 stills (chat, play, app, drag, chart, logo) before you render.

zero

40,573 görüntüleme • 1 gün önce