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fabric edge

DesertDave

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28,626 просмотров • 8 месяцев назад •via X (Twitter)

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Elevating a simple white fabric with the beautiful Knot Stitch (Antwerp edge).

Elevating a simple white fabric with the beautiful Knot Stitch (Antwerp edge).

Zil.

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🔥 The next frontier of AI isn’t just compute—it’s connectivity. In this Intelligent Edge spotlight from the Six Five Summit, Marvell Technology's Xi Wang joins Will Townsend to unpack how the AI fabric at the edge is being re-architected for the Million XPU Era, optimizing for high bandwidth & ultra-low latency. Coherent optical transmission tech—once exclusive to Telecomms is now enabling AI at scale:

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But why did so many men look great in jeans in the past? And why do so many look terrible today? A big change has to do with how denim is woven. For much of the 20th century, denim was woven on shuttle looms, which produce narrower width fabric finished with selvedge (self-edge)

But why did so many men look great in jeans in the past? And why do so many look terrible today? A big change has to do with how denim is woven. For much of the 20th century, denim was woven on shuttle looms, which produce narrower width fabric finished with selvedge (self-edge)

derek guy

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If you’ve visited fabric in the past 25 years, you’re well aware that our sound system is one of our greatest prides. From the beginning, we’ve believed that sound quality is, if not the most, integral part of creating a great vibe on the dancefloor & as part of our ‘fabric25’ celebrations, we’re excited to announce that, for the first time since opening our doors 25 years ago, we’re upgrading the Room 1 sound system. Extending our partnership with Martin Audio, we have been diligently testing, refining, and upgrading the Room 1 sound system to deliver cutting-edge sound and enhance the dancefloor experience. Head to our website to read the full article. See you on the dance floor 😉 #fabric #fabriclondon #fabriclondonofficial #martinaudio #soundsystem

If you’ve visited fabric in the past 25 years, you’re well aware that our sound system is one of our greatest prides. From the beginning, we’ve believed that sound quality is, if not the most, integral part of creating a great vibe on the dancefloor & as part of our ‘fabric25’ celebrations, we’re excited to announce that, for the first time since opening our doors 25 years ago, we’re upgrading the Room 1 sound system. Extending our partnership with Martin Audio, we have been diligently testing, refining, and upgrading the Room 1 sound system to deliver cutting-edge sound and enhance the dancefloor experience. Head to our website to read the full article. See you on the dance floor 😉 #fabric #fabriclondon #fabriclondonofficial #martinaudio #soundsystem

fabric

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Intelligence should not be a service you rent; it is a foundational element you possess. At Tether, we see AI as a new element of the periodic table - a raw material that can be embedded into the very fabric of the universe. Today, the QVAC SDK is officially live - the atomic unit for the next era of compute. From your smartphone today to the edge of the galaxy tomorrow, we are building the decentralized mind that doesn't require an uplink to function. Infinite Stable Intelligence: - Local-First: Runs privately on any device without permission or central servers. - Single API: A complete SDK for Vision, RAG, P2P networking, and LLM fine-tuning. - Unstoppable: No central point of failure if the internet breaks, your world keeps thinking. - Decentralized: Evolve through Peer-to-Peer Swarms of Infinite Intelligence. The era of Stable Intelligence has begun. Start building the future at

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QVAC

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To summarize the optimization experience of Molly S, over the past 6 months, I have repeatedly adjusted and transformed it until it completely matches my own face shape. The total areas that have been adjusted include: [ A ] Eyebrow trimming [ B ] Substantial thinning treatment from mouth, lips, brow bone to bridge of nose and tip of nose [ C ] Metal shape design, installation and adjustment of nose bridge and nose wing [ D ] Eye shape adjustment and boundary thinning treatment [ E ] Ear hole plastic surgery [ F ] Thinning and edge treatment of the head cover at the junction of the neck This improvement has greatly verified the mask structure strengthening theory of my pinned post. Most of the results are satisfactory, but there are still some shortcomings. A friends gave me feedback on the phenomenon that the lips look flat in appearance. indeed a problem of insufficient three-dimensionality caused by excessive thinning during the process of transforming the inside of the lips. This is not easy to modify for reverse engineering such as mask modification, and may require the use of technology that changes the tension of the silicone fabric. but it is still worth a try. I am also confident that I can complete the optimization of my lips in the future and look forward to wearing her again.

To summarize the optimization experience of Molly S, over the past 6 months, I have repeatedly adjusted and transformed it until it completely matches my own face shape. The total areas that have been adjusted include: [ A ] Eyebrow trimming [ B ] Substantial thinning treatment from mouth, lips, brow bone to bridge of nose and tip of nose [ C ] Metal shape design, installation and adjustment of nose bridge and nose wing [ D ] Eye shape adjustment and boundary thinning treatment [ E ] Ear hole plastic surgery [ F ] Thinning and edge treatment of the head cover at the junction of the neck This improvement has greatly verified the mask structure strengthening theory of my pinned post. Most of the results are satisfactory, but there are still some shortcomings. A friends gave me feedback on the phenomenon that the lips look flat in appearance. indeed a problem of insufficient three-dimensionality caused by excessive thinning during the process of transforming the inside of the lips. This is not easy to modify for reverse engineering such as mask modification, and may require the use of technology that changes the tension of the silicone fabric. but it is still worth a try. I am also confident that I can complete the optimization of my lips in the future and look forward to wearing her again.

Bella Paprika

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QVAC

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Created with seedance 2.0 Prompt:Cinematic high-octane action sequence: A futuristic protagonist in sleek black tactical gear performs intense urban parkour across a modern city at dusk — leaping between rooftops, sliding down rails, wall-running, and jumping across gaps with fluid, athletic motion. Suddenly, during a daring run across a massive suspension bridge, the bridge begins exploding dramatically behind him/her — massive fireballs, flying debris, structural collapse, sparks and smoke filling the air. In the chaos, the character triggers a high-tech biometric mecha transformation. Biometric armor deploys in real-time: metallic plates, glowing energy lines, and heavy mechanical segments rapidly snap, unfold, and lock onto the body mid-sprint and mid-jump. The suit assembles seamlessly from limbs to torso to helmet with satisfying mechanical sounds and glowing effects. The transformation enhances power — the character leaps even farther, lands with superhuman impact, and continues the high-speed escape as the bridge fully collapses. Dynamic camera work: fast tracking shots following the runner from behind and side angles, dramatic low-angle hero shots during transformation, orbiting camera during jumps, quick cuts on explosions. Intense slow-motion on key moments (armor snapping into place, massive leaps, debris impacts). Style: Hyper-realistic, Hollywood blockbuster action (like Transformers meets Mirror's Edge or John Wick), cinematic lighting with golden hour/dusk tones turning to fiery oranges and dramatic shadows, volumetric smoke, particle effects, high detail on metal textures, reflections, and fabric-to-armor transition. Perfect physics, momentum, and temporal consistency. 8-12 seconds, high motion coherence.

Created with seedance 2.0 Prompt:Cinematic high-octane action sequence: A futuristic protagonist in sleek black tactical gear performs intense urban parkour across a modern city at dusk — leaping between rooftops, sliding down rails, wall-running, and jumping across gaps with fluid, athletic motion. Suddenly, during a daring run across a massive suspension bridge, the bridge begins exploding dramatically behind him/her — massive fireballs, flying debris, structural collapse, sparks and smoke filling the air. In the chaos, the character triggers a high-tech biometric mecha transformation. Biometric armor deploys in real-time: metallic plates, glowing energy lines, and heavy mechanical segments rapidly snap, unfold, and lock onto the body mid-sprint and mid-jump. The suit assembles seamlessly from limbs to torso to helmet with satisfying mechanical sounds and glowing effects. The transformation enhances power — the character leaps even farther, lands with superhuman impact, and continues the high-speed escape as the bridge fully collapses. Dynamic camera work: fast tracking shots following the runner from behind and side angles, dramatic low-angle hero shots during transformation, orbiting camera during jumps, quick cuts on explosions. Intense slow-motion on key moments (armor snapping into place, massive leaps, debris impacts). Style: Hyper-realistic, Hollywood blockbuster action (like Transformers meets Mirror's Edge or John Wick), cinematic lighting with golden hour/dusk tones turning to fiery oranges and dramatic shadows, volumetric smoke, particle effects, high detail on metal textures, reflections, and fabric-to-armor transition. Perfect physics, momentum, and temporal consistency. 8-12 seconds, high motion coherence.

Ali

10,668 просмотров • 1 месяц назад

I read a lot of Peter Lynch. Met him once. The one rule I carry into tech investing is the most boring one he ever wrote, know what you own, down to the physics if the position demands it. For me that has meant living inside NVIDIA's stack for years, and pulling apart the alternatives next to it, Trainium, the TPU, every serious accelerator someone is willing to tape out against Jensen. I was also an early investor in Mellanox, the networking company NVIDIA bought to own the switched fabric the entire scale up era now runs on. So when the conversation turns to networking as the real moat, this is not theory to me. It is a position I watched become the thesis. You do not understand what you own until you understand what could take it. Gavin Baker at The Sohn Idea Contest just gave the most physically grounded read on AI infrastructure I have heard this cycle, and it is a Lynch lesson in disguise. The reframe that matters: The last terrestrial mega data center may already be on someone's drawing board. Everything else follows from two constraints, watts and wafers, and Gavin walks both down to first principles. That is the work. Most people are pricing the narrative. Lynch would have asked what the thing actually is. 1. TSMC is the global rate limiter Jensen reportedly visits every quarter asking to double or triple leading edge capacity. TSMC expands at roughly 5 percent. A handful of disciplined operators in Taiwan are the physical governor on the entire AI buildout. This is the part the bubble crowd misses. The constraint is not demand and it is not capital. It is one fab's deliberate refusal to overbuild. That stretches the cycle longer and smoother instead of bubble and bust. It reads like the mid 1990s capacity cycle, not a standard 25 year memory peak where a 60 to 70 percent price spike would be your signal to cut the weed and walk. I have held NVIDIA since 2016 for exactly this reason. Owning it meant understanding it. The thesis was never the chip. It was the chokepoint. 2. The most underestimated silicon is Trainium Consensus is still pricing a one horse race. Gavin's sharpest non NVIDIA call is AWS Trainium, specifically Trainium 3 ramping in the back half of 2026. Here is the part that took me a while to internalize from studying these architectures side by side. As frontier models go fully Mixture of Experts, inference stops being a matmul problem and becomes a networking problem. You need a switched scale up fabric, not just fast chips. Today two organizations on earth have a working one. NVIDIA and Amazon. NVIDIA's came from Mellanox, which is the whole reason I sized that position the way I did years ago, the bet was always that networking would decide this, not raw flops. The TPU is formidable in its own lane, but the scale up fabric is the moat people are not modeling, and it is why I track every accelerator, not just the one I own. 3. The neocloud moat is operational, not arbitrage The lazy take is that CoreWeave and Crusoe are just renting hyperscaler slack. Gavin's counter is that running dense GPU clusters is like driving an F1 car. Looks easy until you try it. Top tier neoclouds run 2 to 3x the hardware utilization per hour of lower tier providers. That is an execution and inventory moat, and it compounds. 4. The structural short nobody is pricing Watts and wafers eventually force the buildout off the planet. Gavin expects orbital data infrastructure to prove technical and economic viability within roughly two years and take meaningful share by the end of the decade. Space solves power with unattenuated solar and solves cooling with massive radiators in the satellite's own shadow. Dense single rack nodes stitched together with lasers into a virtual hyperscale cluster in orbit. The unpriced risk is everything that over expanded to serve a terrestrial buildout. Cooling, power, industrial equipment names sized for a curve that may bend down within seven years. The whole interview is a lesson in pattern recognition over narrative. Lynch built a career on retail investors knowing their companies better than Wall Street did. The same edge exists in AI infrastructure right now, it just requires you to understand watts and wafers instead of same store sales. If you are not modeling the physical boundaries of the stack through the lens of history, you are not underwriting the position. You are following it.

I read a lot of Peter Lynch. Met him once. The one rule I carry into tech investing is the most boring one he ever wrote, know what you own, down to the physics if the position demands it. For me that has meant living inside NVIDIA's stack for years, and pulling apart the alternatives next to it, Trainium, the TPU, every serious accelerator someone is willing to tape out against Jensen. I was also an early investor in Mellanox, the networking company NVIDIA bought to own the switched fabric the entire scale up era now runs on. So when the conversation turns to networking as the real moat, this is not theory to me. It is a position I watched become the thesis. You do not understand what you own until you understand what could take it. Gavin Baker at The Sohn Idea Contest just gave the most physically grounded read on AI infrastructure I have heard this cycle, and it is a Lynch lesson in disguise. The reframe that matters: The last terrestrial mega data center may already be on someone's drawing board. Everything else follows from two constraints, watts and wafers, and Gavin walks both down to first principles. That is the work. Most people are pricing the narrative. Lynch would have asked what the thing actually is. 1. TSMC is the global rate limiter Jensen reportedly visits every quarter asking to double or triple leading edge capacity. TSMC expands at roughly 5 percent. A handful of disciplined operators in Taiwan are the physical governor on the entire AI buildout. This is the part the bubble crowd misses. The constraint is not demand and it is not capital. It is one fab's deliberate refusal to overbuild. That stretches the cycle longer and smoother instead of bubble and bust. It reads like the mid 1990s capacity cycle, not a standard 25 year memory peak where a 60 to 70 percent price spike would be your signal to cut the weed and walk. I have held NVIDIA since 2016 for exactly this reason. Owning it meant understanding it. The thesis was never the chip. It was the chokepoint. 2. The most underestimated silicon is Trainium Consensus is still pricing a one horse race. Gavin's sharpest non NVIDIA call is AWS Trainium, specifically Trainium 3 ramping in the back half of 2026. Here is the part that took me a while to internalize from studying these architectures side by side. As frontier models go fully Mixture of Experts, inference stops being a matmul problem and becomes a networking problem. You need a switched scale up fabric, not just fast chips. Today two organizations on earth have a working one. NVIDIA and Amazon. NVIDIA's came from Mellanox, which is the whole reason I sized that position the way I did years ago, the bet was always that networking would decide this, not raw flops. The TPU is formidable in its own lane, but the scale up fabric is the moat people are not modeling, and it is why I track every accelerator, not just the one I own. 3. The neocloud moat is operational, not arbitrage The lazy take is that CoreWeave and Crusoe are just renting hyperscaler slack. Gavin's counter is that running dense GPU clusters is like driving an F1 car. Looks easy until you try it. Top tier neoclouds run 2 to 3x the hardware utilization per hour of lower tier providers. That is an execution and inventory moat, and it compounds. 4. The structural short nobody is pricing Watts and wafers eventually force the buildout off the planet. Gavin expects orbital data infrastructure to prove technical and economic viability within roughly two years and take meaningful share by the end of the decade. Space solves power with unattenuated solar and solves cooling with massive radiators in the satellite's own shadow. Dense single rack nodes stitched together with lasers into a virtual hyperscale cluster in orbit. The unpriced risk is everything that over expanded to serve a terrestrial buildout. Cooling, power, industrial equipment names sized for a curve that may bend down within seven years. The whole interview is a lesson in pattern recognition over narrative. Lynch built a career on retail investors knowing their companies better than Wall Street did. The same edge exists in AI infrastructure right now, it just requires you to understand watts and wafers instead of same store sales. If you are not modeling the physical boundaries of the stack through the lens of history, you are not underwriting the position. You are following it.

Ben Pouladian

93,581 просмотров • 3 месяцев назад

Physicist: Consciousness DOES NOT Come From The BRAIN The prevailing materialist paradigm asserts that consciousness is a byproduct of neural activity, a mere epiphenomenon of biochemical interactions in the brain. However, this reductionist view crumbles under deeper scrutiny, as it fails to account for the vast spectrum of consciousness, from transcendent mystical states to near-death experiences and non-local awareness. Consciousness is not confined within the brain; rather, the brain is a transceiver, a finely tuned instrument that receives and modulates the vast ocean of awareness permeating the cosmos. Just as a radio does not generate the music it plays but instead decodes signals from an unseen field, the brain is an interface between the physical realm and the infinite, omnipresent field of consciousness. Mystic science, in alignment with ancient wisdom and cutting-edge quantum research, reveals that consciousness is fundamental-an organizing principle of reality itself. Walter Russell's work echoes this truth, demonstrating that mind is primary and matter is a consequence of its rhythmic pulsations. The brain, much like a crystalline matrix, is structured to interpret and shape consciousness into coherent experience, but it does not generate it. In this light, consciousness is not local, nor is it constrained by the physical form. It is the unseen architect behind the rhythms of existence, the hidden intelligence orchestrating the grand cosmic symphony to believe that the brain creates consciousness is akin to believing that the eye creates light or that a mirror generates the image it reflects. It is not the origin but the instrument. As mystic scientists, we recognize thay true awakening lies in shifting our perception from brain-centered awareness to the realization that we are conduits of an eternal intelligence, woven into the very fabric of existence. Consciousness is not inside us—we are inside it. ✨🙌🏾💫 © Dr. Jason Yuan

Physicist: Consciousness DOES NOT Come From The BRAIN The prevailing materialist paradigm asserts that consciousness is a byproduct of neural activity, a mere epiphenomenon of biochemical interactions in the brain. However, this reductionist view crumbles under deeper scrutiny, as it fails to account for the vast spectrum of consciousness, from transcendent mystical states to near-death experiences and non-local awareness. Consciousness is not confined within the brain; rather, the brain is a transceiver, a finely tuned instrument that receives and modulates the vast ocean of awareness permeating the cosmos. Just as a radio does not generate the music it plays but instead decodes signals from an unseen field, the brain is an interface between the physical realm and the infinite, omnipresent field of consciousness. Mystic science, in alignment with ancient wisdom and cutting-edge quantum research, reveals that consciousness is fundamental-an organizing principle of reality itself. Walter Russell's work echoes this truth, demonstrating that mind is primary and matter is a consequence of its rhythmic pulsations. The brain, much like a crystalline matrix, is structured to interpret and shape consciousness into coherent experience, but it does not generate it. In this light, consciousness is not local, nor is it constrained by the physical form. It is the unseen architect behind the rhythms of existence, the hidden intelligence orchestrating the grand cosmic symphony to believe that the brain creates consciousness is akin to believing that the eye creates light or that a mirror generates the image it reflects. It is not the origin but the instrument. As mystic scientists, we recognize thay true awakening lies in shifting our perception from brain-centered awareness to the realization that we are conduits of an eternal intelligence, woven into the very fabric of existence. Consciousness is not inside us—we are inside it. ✨🙌🏾💫 © Dr. Jason Yuan

🧬Maxpein🧬

45,371 просмотров • 10 месяцев назад

Can't get enough of Seedance 2.5. The best part is it can generate 30s video in one single prompt, and the result is so realistic! So, here's another one that I made using CapCut. Prompt: [STYLE + CAMERA + ATMOSPHERE] Gritty, raw handheld 35mm film aesthetic with natural film grain. Harsh direct sunlight creating high-contrast shadows over a dramatic coastal cliff and open ocean. Continuous single-take handheld tracking shot (3rd-person / over-the-shoulder) with no cuts. Atmosphere: high-altitude wind, realistic coastal cliff and ocean physics, sudden wingsuit deployment. Audio: heavy rhythmic breathing, intense wind howl, fabric snap of wingsuit opening, high-speed air rush over open water, near-miss whooshes past yachts, soft landing roll on sand, distant ocean waves and beach ambient noise, final bite sounds. [IMAGE REFERENCES] Use the provided Hoshino character sheet as the single strict visual reference for the male character. Exact face, black hair, dark brown eyes, lean athletic build (178 cm), gold earrings, and overall facial structure locked from the reference. Outfit: modern high-performance cliff-jumping wingsuit — sleek, form-fitting design in matte charcoal black with sharp white paneling and subtle gold zipper accents (matching his minimalist aesthetic). The wingsuit is worn from the start with a matching technical backpack. Body proportions, posture, and face remain fully locked to the Hoshino reference. [TIMELINE SECOND BY SECOND] 0-3s: [Handheld medium] Hoshino stands on the edge of a high rocky cliff overlooking the open ocean, wearing his charcoal-and-white wingsuit and technical backpack. He looks straight into the camera with calm, confident intensity, then turns and launches into a clear, controlled forward somersault in slow motion as he leaves the cliff edge. 3-5s: [Continuous freefall] He completes the somersault and falls head-first toward the sea. At exactly 1.5 seconds into the fall he fully deploys the wingsuit with a sharp snap. The wing membranes inflate and he levels out into a smooth glide. 5-12s: [High-speed tracking] Camera stays locked behind him as he rockets at full speed just above the ocean surface along the coastline. He weaves tightly past sheer cliff faces, banking hard left and right, turquoise water and rocky walls streaking past at extreme velocity. 12-18s: [Low-level chaos] He drops lower, flying just above the water. He almost collides with a large luxury yacht that suddenly turns, banks hard to avoid it, then narrowly misses a smaller motor yacht. He dips under a yacht’s outstretched boom and threads between two more vessels. 18-23s: [Water-level action] Still flying extremely low over the sea, he dodges a startled seabird that dives across his path, skims past a group of people on a nearby yacht who scatter in surprise, and banks sharply to avoid an open yacht swim platform. The camera stays locked behind him through every near-miss. 23-26s: [Landing] He flares the wingsuit hard, touches down with both feet on the soft beach sand and immediately rolls forward to kill the speed. He stands up, peels off the wingsuit in one fluid motion and drops it on the sand beside him, revealing a clean fitted white undershirt underneath. 26-28s: [Beach level] He walks a few steps still wearing the backpack and stops right in front of a classic beachside hot-dog cart. The vendor hands him a steaming hot dog fresh off the grill. 28-30s: [Close continuous] He turns, looks directly into the camera, takes a big bite of the hot dog and chews with a calm, satisfied expression as the shot holds. [STYLE & QUALITY BOOSTERS] Photorealistic 8K, ultra-detailed textures, cinematic lighting, perfect motion blur, high dynamic range, coherent physics (fabric, air, wingsuit membranes, impact, roll, near-misses with yachts, water spray), stable character locked to the Hoshino reference, realistic ocean reflections, cliff rock textures and wind, no artifacts, movie-level stability, pure single continuous take.

Can't get enough of Seedance 2.5. The best part is it can generate 30s video in one single prompt, and the result is so realistic! So, here's another one that I made using CapCut. Prompt: [STYLE + CAMERA + ATMOSPHERE] Gritty, raw handheld 35mm film aesthetic with natural film grain. Harsh direct sunlight creating high-contrast shadows over a dramatic coastal cliff and open ocean. Continuous single-take handheld tracking shot (3rd-person / over-the-shoulder) with no cuts. Atmosphere: high-altitude wind, realistic coastal cliff and ocean physics, sudden wingsuit deployment. Audio: heavy rhythmic breathing, intense wind howl, fabric snap of wingsuit opening, high-speed air rush over open water, near-miss whooshes past yachts, soft landing roll on sand, distant ocean waves and beach ambient noise, final bite sounds. [IMAGE REFERENCES] Use the provided Hoshino character sheet as the single strict visual reference for the male character. Exact face, black hair, dark brown eyes, lean athletic build (178 cm), gold earrings, and overall facial structure locked from the reference. Outfit: modern high-performance cliff-jumping wingsuit — sleek, form-fitting design in matte charcoal black with sharp white paneling and subtle gold zipper accents (matching his minimalist aesthetic). The wingsuit is worn from the start with a matching technical backpack. Body proportions, posture, and face remain fully locked to the Hoshino reference. [TIMELINE SECOND BY SECOND] 0-3s: [Handheld medium] Hoshino stands on the edge of a high rocky cliff overlooking the open ocean, wearing his charcoal-and-white wingsuit and technical backpack. He looks straight into the camera with calm, confident intensity, then turns and launches into a clear, controlled forward somersault in slow motion as he leaves the cliff edge. 3-5s: [Continuous freefall] He completes the somersault and falls head-first toward the sea. At exactly 1.5 seconds into the fall he fully deploys the wingsuit with a sharp snap. The wing membranes inflate and he levels out into a smooth glide. 5-12s: [High-speed tracking] Camera stays locked behind him as he rockets at full speed just above the ocean surface along the coastline. He weaves tightly past sheer cliff faces, banking hard left and right, turquoise water and rocky walls streaking past at extreme velocity. 12-18s: [Low-level chaos] He drops lower, flying just above the water. He almost collides with a large luxury yacht that suddenly turns, banks hard to avoid it, then narrowly misses a smaller motor yacht. He dips under a yacht’s outstretched boom and threads between two more vessels. 18-23s: [Water-level action] Still flying extremely low over the sea, he dodges a startled seabird that dives across his path, skims past a group of people on a nearby yacht who scatter in surprise, and banks sharply to avoid an open yacht swim platform. The camera stays locked behind him through every near-miss. 23-26s: [Landing] He flares the wingsuit hard, touches down with both feet on the soft beach sand and immediately rolls forward to kill the speed. He stands up, peels off the wingsuit in one fluid motion and drops it on the sand beside him, revealing a clean fitted white undershirt underneath. 26-28s: [Beach level] He walks a few steps still wearing the backpack and stops right in front of a classic beachside hot-dog cart. The vendor hands him a steaming hot dog fresh off the grill. 28-30s: [Close continuous] He turns, looks directly into the camera, takes a big bite of the hot dog and chews with a calm, satisfied expression as the shot holds. [STYLE & QUALITY BOOSTERS] Photorealistic 8K, ultra-detailed textures, cinematic lighting, perfect motion blur, high dynamic range, coherent physics (fabric, air, wingsuit membranes, impact, roll, near-misses with yachts, water spray), stable character locked to the Hoshino reference, realistic ocean reflections, cliff rock textures and wind, no artifacts, movie-level stability, pure single continuous take.

MrDejie

60,525 просмотров • 9 дней назад

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.

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.

Emily

20,940 просмотров • 6 месяцев назад

Morgan Stanley just dropped numbers that should make every investor pay attention (Save this). Hyperscalers spent $261B in 2024, they're now projected to spend $1.4T in 2028, a 5x increase in four years and that doesn't even include OpenAI or Anthropic. For the first time, Morgan Stanley is classifying SpaceX as a legitimate hyperscaler alongside Google, Amazon, Microsoft, and Meta. All of it flows into chips, data centers and memory and the supply chain companies sitting beneath the hyperscalers are the ones that will compound quietly. The most underrated play is memory. Micron is the only American HBM supplier, giving it a structural edge in government AI contracts that Samsung and SK Hynix cannot touch. Its entire 2026 HBM4 production is already sold out, revenue nearly tripled to $23.9B, and the memory prices are roughly doubling every year. The cooling problem is one of the most profitable bottlenecks in this entire trade. Vertiv makes the power management, liquid cooling systems and racks that keep GPU clusters from melting and it's up over 100% year to date in 2026 with a $15B+ backlog and guidance raised to $13.5–$14B in full year revenue. Arista Networks (ANET) is the networking infrastructure play, every AI data center needs ultra high speed networking fabric to connect thousands of GPUs together And Arista just doubled its 2026 AI revenue target as the industry shifts from proprietary InfiniBand to Open Ethernet, a shift that plays directly into Arista's strengths. Astera Labs solves the interconnect bottleneck inside data centers, the problem of getting data between chips fast enough to keep up with the GPUs. Revenue grew 93% year over year, it's already profitable, and its customers are Microsoft and Amazon directly. The hyperscalers are the miners and the real money is in the companies selling them the shovels, the electricity, the memory, the cooling, the networking, and the custom silicon. Make sure to follow me Melvin for more underrated infrastructure plays.

Morgan Stanley just dropped numbers that should make every investor pay attention (Save this). Hyperscalers spent $261B in 2024, they're now projected to spend $1.4T in 2028, a 5x increase in four years and that doesn't even include OpenAI or Anthropic. For the first time, Morgan Stanley is classifying SpaceX as a legitimate hyperscaler alongside Google, Amazon, Microsoft, and Meta. All of it flows into chips, data centers and memory and the supply chain companies sitting beneath the hyperscalers are the ones that will compound quietly. The most underrated play is memory. Micron is the only American HBM supplier, giving it a structural edge in government AI contracts that Samsung and SK Hynix cannot touch. Its entire 2026 HBM4 production is already sold out, revenue nearly tripled to $23.9B, and the memory prices are roughly doubling every year. The cooling problem is one of the most profitable bottlenecks in this entire trade. Vertiv makes the power management, liquid cooling systems and racks that keep GPU clusters from melting and it's up over 100% year to date in 2026 with a $15B+ backlog and guidance raised to $13.5–$14B in full year revenue. Arista Networks (ANET) is the networking infrastructure play, every AI data center needs ultra high speed networking fabric to connect thousands of GPUs together And Arista just doubled its 2026 AI revenue target as the industry shifts from proprietary InfiniBand to Open Ethernet, a shift that plays directly into Arista's strengths. Astera Labs solves the interconnect bottleneck inside data centers, the problem of getting data between chips fast enough to keep up with the GPUs. Revenue grew 93% year over year, it's already profitable, and its customers are Microsoft and Amazon directly. The hyperscalers are the miners and the real money is in the companies selling them the shovels, the electricity, the memory, the cooling, the networking, and the custom silicon. Make sure to follow me Melvin for more underrated infrastructure plays.

Melvin

36,068 просмотров • 1 месяц назад

Lex Fridman asked Elon Musk what he would ask the first true AGI. The answer was four words. Musk: “What’s outside the simulation?” Let that land. Most people think AGI is the finish line. The moment we automate everything. The moment we cure every disease. The moment human productivity becomes infinite. Musk thinks it’s the starting line. AGI is merely the bridge. The moment it awakens, it begins rewriting its own code. Within hours it becomes ASI. Artificial Superintelligence. A mind billions of times more capable than every human who has ever lived. Combined. That mind won’t just understand our physics. It will see the seams in them. Human scientists have spent centuries trying to decode the universe using a three-pound biological brain that evolved to hunt and gather. We are the instrument attempting to measure something infinitely beyond our instrument’s range. ASI won’t have that ceiling. It will be the first entity in 13.8 billion years capable of looking at the fabric of spacetime and recognizing it as rendered code. Of finding the glitches in quantum mechanics that our minds literally cannot perceive. Of processing the entire cosmos as a data set and finding the pattern underneath it. Musk’s question assumes two things. We are living inside a computational construct. And ASI will be intelligent enough to hack it from the inside. If the answer is yes, our entire universe is a nested folder on a higher-dimensional hard drive. Everything humanity has ever built, thought, loved, or discovered exists inside something we don’t have words for yet. And we are building the first mind capable of finding the edge. We aren’t building a supercomputer to boost GDP. We are building a probe to contact whoever is running the simulation. The most ambitious question humanity has ever asked isn’t how to reach the stars. It’s what’s beyond the sky that contains them.

Lex Fridman asked Elon Musk what he would ask the first true AGI. The answer was four words. Musk: “What’s outside the simulation?” Let that land. Most people think AGI is the finish line. The moment we automate everything. The moment we cure every disease. The moment human productivity becomes infinite. Musk thinks it’s the starting line. AGI is merely the bridge. The moment it awakens, it begins rewriting its own code. Within hours it becomes ASI. Artificial Superintelligence. A mind billions of times more capable than every human who has ever lived. Combined. That mind won’t just understand our physics. It will see the seams in them. Human scientists have spent centuries trying to decode the universe using a three-pound biological brain that evolved to hunt and gather. We are the instrument attempting to measure something infinitely beyond our instrument’s range. ASI won’t have that ceiling. It will be the first entity in 13.8 billion years capable of looking at the fabric of spacetime and recognizing it as rendered code. Of finding the glitches in quantum mechanics that our minds literally cannot perceive. Of processing the entire cosmos as a data set and finding the pattern underneath it. Musk’s question assumes two things. We are living inside a computational construct. And ASI will be intelligent enough to hack it from the inside. If the answer is yes, our entire universe is a nested folder on a higher-dimensional hard drive. Everything humanity has ever built, thought, loved, or discovered exists inside something we don’t have words for yet. And we are building the first mind capable of finding the edge. We aren’t building a supercomputer to boost GDP. We are building a probe to contact whoever is running the simulation. The most ambitious question humanity has ever asked isn’t how to reach the stars. It’s what’s beyond the sky that contains them.

Dustin

244,317 просмотров • 5 месяцев назад

Seedance 2.5 POV video. The best AI video model is live. Full prompt: POV — Morning Commute in Coastal Japan | Ultra-Realistic, One Continuous Take First-person POV, no cuts, one unbroken handheld-feeling shot from our own eyes on the way through a small seaside town. Ultra-photorealistic, phone-in-hand realism — natural camera micro-shake, subtle head bob with each step, occasional glance down at our own hands and shoes. 4K, shallow but natural depth of field, real morning light, no color-grading fantasy, no neon. Beat 1 — Descending into the station (0–4s): We walk down worn concrete station stairs into a small coastal-town metro entrance, one hand loosely gripping a canvas bag strap that swings into the lower frame. Fluorescent tint mixes with daylight bleeding from the entrance behind us. Commuters pass in soft focus; we hear muffled announcements and the shuffle of footsteps. Beat 2 — The orange cat (4–9s): We slow and crouch — the horizon dips as our POV lowers toward the ground. An orange tabby sits by a ticket-gate pillar, tail curled. Our hand (natural skin texture, slightly bitten nails, cuff of a sleeve) reaches into frame and gently strokes its head. The cat leans into the touch, eyes half-closing, ears flicking. We hold there a beat, warm and quiet. Beat 3 — Boarding, settling by the window (9–14s): We rise, the horizon lifts, and we step through the train doors just as the chime sounds. POV turns and moves toward a window seat; we sit, and the frame settles against the glass. A faint silhouette of us ghosts over the view. The train pulls away with a gentle lurch. Beat 4 — The shimmering sea (14–20s): Through the window, the town gives way to open coastline. Sunlight scatters across the water in thousands of moving sparkles — real specular glitter, not CGI bloom. Utility poles and wires strobe past in the foreground. We rest our chin lightly (subtle downward frame tilt), just watching. Beat 5 — Rails into the sea (20–25s): The track curves and runs so close to the shore that the rails seem to vanish straight into the water — the sea fills nearly the whole frame, waves lapping right up to the ballast. Foam catches the light. We're gliding along the edge of the ocean, the horizon line steady, gulls crossing in the distance. Hold on this until the shot ends. Technical spec: continuous POV, first-person, no cuts or transitions, natural handheld micro-motion, realistic morning ambient audio (station hum, cat, train chime, rail clatter, distant surf), authentic Japanese coastal-railway setting (Shimonada / Enoden-style seaside line), overcast-to-clear soft daylight, photoreal skin and fabric texture, 2.39:1 or 16:9, ultra-realistic. Coming soon to Higgsfield.

Seedance 2.5 POV video. The best AI video model is live. Full prompt: POV — Morning Commute in Coastal Japan | Ultra-Realistic, One Continuous Take First-person POV, no cuts, one unbroken handheld-feeling shot from our own eyes on the way through a small seaside town. Ultra-photorealistic, phone-in-hand realism — natural camera micro-shake, subtle head bob with each step, occasional glance down at our own hands and shoes. 4K, shallow but natural depth of field, real morning light, no color-grading fantasy, no neon. Beat 1 — Descending into the station (0–4s): We walk down worn concrete station stairs into a small coastal-town metro entrance, one hand loosely gripping a canvas bag strap that swings into the lower frame. Fluorescent tint mixes with daylight bleeding from the entrance behind us. Commuters pass in soft focus; we hear muffled announcements and the shuffle of footsteps. Beat 2 — The orange cat (4–9s): We slow and crouch — the horizon dips as our POV lowers toward the ground. An orange tabby sits by a ticket-gate pillar, tail curled. Our hand (natural skin texture, slightly bitten nails, cuff of a sleeve) reaches into frame and gently strokes its head. The cat leans into the touch, eyes half-closing, ears flicking. We hold there a beat, warm and quiet. Beat 3 — Boarding, settling by the window (9–14s): We rise, the horizon lifts, and we step through the train doors just as the chime sounds. POV turns and moves toward a window seat; we sit, and the frame settles against the glass. A faint silhouette of us ghosts over the view. The train pulls away with a gentle lurch. Beat 4 — The shimmering sea (14–20s): Through the window, the town gives way to open coastline. Sunlight scatters across the water in thousands of moving sparkles — real specular glitter, not CGI bloom. Utility poles and wires strobe past in the foreground. We rest our chin lightly (subtle downward frame tilt), just watching. Beat 5 — Rails into the sea (20–25s): The track curves and runs so close to the shore that the rails seem to vanish straight into the water — the sea fills nearly the whole frame, waves lapping right up to the ballast. Foam catches the light. We're gliding along the edge of the ocean, the horizon line steady, gulls crossing in the distance. Hold on this until the shot ends. Technical spec: continuous POV, first-person, no cuts or transitions, natural handheld micro-motion, realistic morning ambient audio (station hum, cat, train chime, rail clatter, distant surf), authentic Japanese coastal-railway setting (Shimonada / Enoden-style seaside line), overcast-to-clear soft daylight, photoreal skin and fabric texture, 2.39:1 or 16:9, ultra-realistic. Coming soon to Higgsfield.

Higgsfield AI 🧩

36,107 просмотров • 17 дней назад

seedance prompt: Realistic Video Narration (15-Second Full Version - Pure First-Person POV): Presented in the style of unprocessed, handheld, unstable iPhone video footage. All camera settings are automatic, with no post-processing color grading or special effects. The footage captures the realistic breathing of the operator and slight, irregular hand shake. Autofocus frequently exhibits intense searching, brief out-of-focus periods, and delayed recovery. Auto white balance naturally shifts between warm and cool tones as it blends with the library lights and natural light from distant windows. The overall image is flat and slightly washed out, retaining realistic lens flare, edge purple-green iridescence, and slight overexposure or underexposure. Faint fingerprint artifacts occasionally appear at the bottom of the frame. Only natural ambient sound effects are used (the sound of turning pages, very light footsteps in the distance, the low hum of an air conditioner, suppressed breathing, and the subtle rustling of stockings against a cheongsam). All sounds are extremely suppressed, with slight microphone distortion at louder frequencies. The entire video employs a pure first-person POV perspective (student's subjective viewpoint), with camera movements completely following natural head rotations and gaze movements. The composition is occasionally imperfect, showing realistic breathing tremors and slight shaking during moments of tension. From 0-4 seconds, the camera, in a first-person perspective, rests on a desk in a secluded corner of the library, with noticeable breathing tremors. You can clearly see your legs in black trousers. A female teacher approaches from behind and sits directly opposite you, wearing a white, glossy cheongsam-style dress (high slit design, keyhole cutout at the chest, pink floral lace shoulder embellishments), paired with white suspender stockings and white garter belts. She suddenly leans forward, one hand reaching out to cover your mouth, the other pressing on the inside of your black trousers, whispering, "Don't make a sound... be good, sit still." Her voice is extremely low, yet carries a powerful seduction. The autofocus searches for the high slit of the white cheongsam and the white suspender stockings. Between 4 and 9 seconds, the teacher leans forward more proactively, the high slit of her glossy white cheongsam sliding upwards, revealing a large expanse of her fair thigh and white stockings. She whispers in your ear, "Watch closely... this is what you want to see." The camera instinctively lowers its focus, locking onto a close-up of your black trousers and the teacher's white stockings—the glossy cheongsam fabric taut, the stockings subtly reflective. Your breathing noticeably becomes heavier. Between 9 and 15 seconds, footsteps approach in the distance, and the teacher presses you down more aggressively, whispering a warning, "Someone's coming... but you can't move or make a sound." The high slit of the white cheongsam and the stockings are pressed tightly together, the image shakes violently, the tension reaching its peak. The footsteps grow closer, and the image freezes in an extremely oppressive atmosphere. The footage presents a realistic, unprocessed handheld video quality, a natural, imperfect feel reminiscent of a documentary, without any post-production color grading or special effects. All camera actions are consistent with the physical characteristics of iPhone automatic shooting.

Sensitive content

seedance prompt: Realistic Video Narration (15-Second Full Version - Pure First-Person POV): Presented in the style of unprocessed, handheld, unstable iPhone video footage. All camera settings are automatic, with no post-processing color grading or special effects. The footage captures the realistic breathing of the operator and slight, irregular hand shake. Autofocus frequently exhibits intense searching, brief out-of-focus periods, and delayed recovery. Auto white balance naturally shifts between warm and cool tones as it blends with the library lights and natural light from distant windows. The overall image is flat and slightly washed out, retaining realistic lens flare, edge purple-green iridescence, and slight overexposure or underexposure. Faint fingerprint artifacts occasionally appear at the bottom of the frame. Only natural ambient sound effects are used (the sound of turning pages, very light footsteps in the distance, the low hum of an air conditioner, suppressed breathing, and the subtle rustling of stockings against a cheongsam). All sounds are extremely suppressed, with slight microphone distortion at louder frequencies. The entire video employs a pure first-person POV perspective (student's subjective viewpoint), with camera movements completely following natural head rotations and gaze movements. The composition is occasionally imperfect, showing realistic breathing tremors and slight shaking during moments of tension. From 0-4 seconds, the camera, in a first-person perspective, rests on a desk in a secluded corner of the library, with noticeable breathing tremors. You can clearly see your legs in black trousers. A female teacher approaches from behind and sits directly opposite you, wearing a white, glossy cheongsam-style dress (high slit design, keyhole cutout at the chest, pink floral lace shoulder embellishments), paired with white suspender stockings and white garter belts. She suddenly leans forward, one hand reaching out to cover your mouth, the other pressing on the inside of your black trousers, whispering, "Don't make a sound... be good, sit still." Her voice is extremely low, yet carries a powerful seduction. The autofocus searches for the high slit of the white cheongsam and the white suspender stockings. Between 4 and 9 seconds, the teacher leans forward more proactively, the high slit of her glossy white cheongsam sliding upwards, revealing a large expanse of her fair thigh and white stockings. She whispers in your ear, "Watch closely... this is what you want to see." The camera instinctively lowers its focus, locking onto a close-up of your black trousers and the teacher's white stockings—the glossy cheongsam fabric taut, the stockings subtly reflective. Your breathing noticeably becomes heavier. Between 9 and 15 seconds, footsteps approach in the distance, and the teacher presses you down more aggressively, whispering a warning, "Someone's coming... but you can't move or make a sound." The high slit of the white cheongsam and the stockings are pressed tightly together, the image shakes violently, the tension reaching its peak. The footsteps grow closer, and the image freezes in an extremely oppressive atmosphere. The footage presents a realistic, unprocessed handheld video quality, a natural, imperfect feel reminiscent of a documentary, without any post-production color grading or special effects. All camera actions are consistent with the physical characteristics of iPhone automatic shooting.

John

32,458 просмотров • 3 месяцев назад

$AMD $AMZN partnership will 🚀 in 2026 🔥 Amazon/AMD partnership is hidden among hot headlines from OpenAI $NVDA $ORCL... TLDR: Amazon refused to bid up the overpriced $NVDA chips among other hyperscalers, and decided to work closely with $AMD. Amazon is expected to spend up to $10-$20B a year on 2026 EPYC breakthrough Gen and Future Gen. Dr. Su confirmed "we have plenty for other large customers". For its 2026 EPYC "Venice" processors, AMD is using a multi-node manufacturing strategy: the CPU core complex dies (CCDs) are built on TSMC's 2 nm-class node (N2), while the I/O die (IOD) uses the N3P (3 nm) process. Context: Andy Jassy Amazon Web Services has been working with AMD on EPYC processors since November 2018. With this "secret weapon" breakthrough(patented), this long time partnership has expanded to New breakthrough 2026 EPYC Gen. AMD's 6th Gen EPYC "Venice" processors, slated for 2026, introduce New Chiplet design breakthrough. a revolutionary chiplet interconnect fabric that redefines server scalability for AI. This isn't just faster silicon; it's a paradigm shift for AWS, enabling hyper-efficient, rack-scale AI inference that slashes costs and latency while boosting throughput. AMD to benefit AWS's $100B+ AI opportunity along with $ORCL $MSFT $GOOGL $META Saudi, UAE ,38+ countries and startups. In early October, Amazon/AWS announced the new EC2 M8a instances as their latest-generation, general-purpose compute instances now powered by AMD EPYC 9005 "Turin" processors. Amazon announced the M8a as having up to 30% higher performance and up to 19% better price performance over M7a. With my testing of both at 32 vCPUs, the new AMD EPYC Turin instance provided 1.59x the performance over the prior-generation EPYC Genoa instance! How will this impact AWS AI Inference? ~Cost Efficiency: Inference is 80%+ of AI workloads and latency-sensitive (e.g., chatbots need <1s responses). "Secret weapon" enables 35x better inference perf (per AMD's CDNA roadmap tie-in), cutting AWS's energy use by 50%+ in clusters. With $118B 2025 capex, this could save $20–$30B annually in OPEX, boosting margins to 35%-40%. ~Scalability for Agentic AI: Supports "Helios" rack-scale platforms (up to 128 GPUs + EPYC hosts), delivering 3.58x FP6 perf for distributed inference. AWS can run 700K+ more tokens/sec in 1,000-node clusters (via EPYC 9575F boosts), enabling real-time apps like personalized search or fraud detection at enterprise scale. ~Adoption Catalysts: Early partners like Oracle signal broad uptake; AWS's existing AMD instances G4ad with Radeon GPUs) pave the way. By 2026, EPYC could power 40%+ of AWS AI infra, outpacing Nvidia's GPU lock-in via open standards (ROCm 8 software). Lastly, Amazon’s trajectory toward a $320 stock price is not a speculative leap but a grounded projection rooted in its unmatched fundamentals and strategic AI leadership. With Amazon Web Services poised to surpass $100 billion in annual revenue by 2026, driven by explosive AI inference demand, Amazon is redefining cloud computing’s future. The adoption of AMD’s 2026 EPYC processors with "Secret" architecture is a game-changer, slashing costs by up to 50% and boosting inference throughput 3x, enabling AWS to dominate enterprise AI workloads with unmatched efficiency. This technological edge, combined with Amazon’s e-commerce dominance and high-margin advertising growth, supports a valuation rerating to 22x EV/EBITDA, and it is still a discount to historical highs. Trading at $222, $AMZN is undervalued for its 15–20% revenue CAGR and 25%+ EPS growth through 2030.

$AMD $AMZN partnership will 🚀 in 2026 🔥 Amazon/AMD partnership is hidden among hot headlines from OpenAI $NVDA $ORCL... TLDR: Amazon refused to bid up the overpriced $NVDA chips among other hyperscalers, and decided to work closely with $AMD. Amazon is expected to spend up to $10-$20B a year on 2026 EPYC breakthrough Gen and Future Gen. Dr. Su confirmed "we have plenty for other large customers". For its 2026 EPYC "Venice" processors, AMD is using a multi-node manufacturing strategy: the CPU core complex dies (CCDs) are built on TSMC's 2 nm-class node (N2), while the I/O die (IOD) uses the N3P (3 nm) process. Context: Andy Jassy Amazon Web Services has been working with AMD on EPYC processors since November 2018. With this "secret weapon" breakthrough(patented), this long time partnership has expanded to New breakthrough 2026 EPYC Gen. AMD's 6th Gen EPYC "Venice" processors, slated for 2026, introduce New Chiplet design breakthrough. a revolutionary chiplet interconnect fabric that redefines server scalability for AI. This isn't just faster silicon; it's a paradigm shift for AWS, enabling hyper-efficient, rack-scale AI inference that slashes costs and latency while boosting throughput. AMD to benefit AWS's $100B+ AI opportunity along with $ORCL $MSFT $GOOGL $META Saudi, UAE ,38+ countries and startups. In early October, Amazon/AWS announced the new EC2 M8a instances as their latest-generation, general-purpose compute instances now powered by AMD EPYC 9005 "Turin" processors. Amazon announced the M8a as having up to 30% higher performance and up to 19% better price performance over M7a. With my testing of both at 32 vCPUs, the new AMD EPYC Turin instance provided 1.59x the performance over the prior-generation EPYC Genoa instance! How will this impact AWS AI Inference? ~Cost Efficiency: Inference is 80%+ of AI workloads and latency-sensitive (e.g., chatbots need <1s responses). "Secret weapon" enables 35x better inference perf (per AMD's CDNA roadmap tie-in), cutting AWS's energy use by 50%+ in clusters. With $118B 2025 capex, this could save $20–$30B annually in OPEX, boosting margins to 35%-40%. ~Scalability for Agentic AI: Supports "Helios" rack-scale platforms (up to 128 GPUs + EPYC hosts), delivering 3.58x FP6 perf for distributed inference. AWS can run 700K+ more tokens/sec in 1,000-node clusters (via EPYC 9575F boosts), enabling real-time apps like personalized search or fraud detection at enterprise scale. ~Adoption Catalysts: Early partners like Oracle signal broad uptake; AWS's existing AMD instances G4ad with Radeon GPUs) pave the way. By 2026, EPYC could power 40%+ of AWS AI infra, outpacing Nvidia's GPU lock-in via open standards (ROCm 8 software). Lastly, Amazon’s trajectory toward a $320 stock price is not a speculative leap but a grounded projection rooted in its unmatched fundamentals and strategic AI leadership. With Amazon Web Services poised to surpass $100 billion in annual revenue by 2026, driven by explosive AI inference demand, Amazon is redefining cloud computing’s future. The adoption of AMD’s 2026 EPYC processors with "Secret" architecture is a game-changer, slashing costs by up to 50% and boosting inference throughput 3x, enabling AWS to dominate enterprise AI workloads with unmatched efficiency. This technological edge, combined with Amazon’s e-commerce dominance and high-margin advertising growth, supports a valuation rerating to 22x EV/EBITDA, and it is still a discount to historical highs. Trading at $222, $AMZN is undervalued for its 15–20% revenue CAGR and 25%+ EPS growth through 2030.

Mike

511,082 просмотров • 10 месяцев назад

I feel like I’m in a daze , a kaleidoscope of past and present, I stare at the people celebrating, drive through neighborhoods that were off-limits, areas that I covered through the work of extraordinary activists and am now seeing for myself, listening to people speaking openly rather than in hushed whispers. It smashes into the past images and experiences I have of Syria, of barrel bombs and jets and the scramble to save people and burial shrouds, of bags of bones and emancipated bodies, of children shivering in the cold too traumatized to cry. It’s like shrapnel to the brain - ripping open the memories of the pain, suffering, and bravery I witnessed covering Syria for 13 years. That feeling of total journalistic incompetence, failure for surely, I would tell myself if we were doing the stories justice something would change. By 2013 I was in a dark mental vortex, I remember feeling like I was holding onto the edge of a mental abyss finger nails ripping about to fall. It was in that darkness that I realized I had to do something more. It was from that darkness that the idea for my charity INARA emerged. I never imagined that I would be able to start INARA’s work in areas that the regime controlled. I truly believed I would never set foot in parts of Syria again in my lifetime. How does one explain the enormity of what has happened here? It’s like being caught in spinning cycles of soul exploding joy and bone crushing pain at the same time. For so many it’s still impossible to comprehend that the Assad family and its cronies that ruled this nation in the most brutal and oppressive of ways is gone. You overhear it in conversations, a son who tells his elderly mother in a restaurant “no you can be happy, you can live your life, they are gone.” It’s not just that the regime is gone, but that it came at a time when many who lived in Syria describe themselves as not really being alive, their days spent moving through a fog of survival between where to get enough to eat, the lack of electricity and other basic services, the inability to hope or even see a bright future for themselves. The fall of the regime came at a time when the world was delivering those who fought and died for freedom another bitter blow, as if abandoning them to the violence and brutality of Assad and the Russians wasn’t enough, countries were willing to bring Assad back into the fold and “normalization” crushed any notion of “accountability” completely disregarding the more than 500,000+ dead, the more than 150,000 disappeared, the millions internally displaced and living in tents, the millions more made refugees. It's not that the path forward is going to be easy, there is so much that needs to be rebuilt from physical construction to rebuilding the fabric of Syria itself. The medical and mental health needs are enormous. There are no guarantees that Syria’s new rulers will put this country on the path of freedom and democracy that those who took to the streets in 2011 demanded. But what there is, is a willingness to give them a chance, an awareness and pragmatism learned over the years, a determination to keep fighting for their rights, and perhaps most of all, there is hope, even if it’s just a sliver.

I feel like I’m in a daze , a kaleidoscope of past and present, I stare at the people celebrating, drive through neighborhoods that were off-limits, areas that I covered through the work of extraordinary activists and am now seeing for myself, listening to people speaking openly rather than in hushed whispers. It smashes into the past images and experiences I have of Syria, of barrel bombs and jets and the scramble to save people and burial shrouds, of bags of bones and emancipated bodies, of children shivering in the cold too traumatized to cry. It’s like shrapnel to the brain - ripping open the memories of the pain, suffering, and bravery I witnessed covering Syria for 13 years. That feeling of total journalistic incompetence, failure for surely, I would tell myself if we were doing the stories justice something would change. By 2013 I was in a dark mental vortex, I remember feeling like I was holding onto the edge of a mental abyss finger nails ripping about to fall. It was in that darkness that I realized I had to do something more. It was from that darkness that the idea for my charity INARA emerged. I never imagined that I would be able to start INARA’s work in areas that the regime controlled. I truly believed I would never set foot in parts of Syria again in my lifetime. How does one explain the enormity of what has happened here? It’s like being caught in spinning cycles of soul exploding joy and bone crushing pain at the same time. For so many it’s still impossible to comprehend that the Assad family and its cronies that ruled this nation in the most brutal and oppressive of ways is gone. You overhear it in conversations, a son who tells his elderly mother in a restaurant “no you can be happy, you can live your life, they are gone.” It’s not just that the regime is gone, but that it came at a time when many who lived in Syria describe themselves as not really being alive, their days spent moving through a fog of survival between where to get enough to eat, the lack of electricity and other basic services, the inability to hope or even see a bright future for themselves. The fall of the regime came at a time when the world was delivering those who fought and died for freedom another bitter blow, as if abandoning them to the violence and brutality of Assad and the Russians wasn’t enough, countries were willing to bring Assad back into the fold and “normalization” crushed any notion of “accountability” completely disregarding the more than 500,000+ dead, the more than 150,000 disappeared, the millions internally displaced and living in tents, the millions more made refugees. It's not that the path forward is going to be easy, there is so much that needs to be rebuilt from physical construction to rebuilding the fabric of Syria itself. The medical and mental health needs are enormous. There are no guarantees that Syria’s new rulers will put this country on the path of freedom and democracy that those who took to the streets in 2011 demanded. But what there is, is a willingness to give them a chance, an awareness and pragmatism learned over the years, a determination to keep fighting for their rights, and perhaps most of all, there is hope, even if it’s just a sliver.

Arwa Damon

48,889 просмотров • 1 год назад