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Been using TRUE FIREPOWER (NIKKE) as my guitar mocap tech testing ground. Here’s the updated instrumental version with all the new tech I’ve built recently! ✨Glowing Strap —Replaced the traditional guitar strap with a dynamic light beam. It intelligently fades and conforms to the body surface near shoulders and... chest, maintaining natural tension while completely eliminating clipping and clothing obstruction. Built with Catmull-Rom splines, my best answer to making virtual gear feel physically real. ✨String Dynamics — Strings now vibrate in sync with the actual performance. Bends and vibrato drive precise geometry deformation exactly where the fingers move. The stronger the bend, the brighter the white glow, mimicking real string reflection under tension. GPU-driven vertex displacement via custom Timeline tracks. ✨Gaze System Update — Eyes now track targets with natural eyelid follow. Looking down makes the lids droop realistically. Added blink detection to prevent eyelid clipping during blinks when looking down. ✨Leg IK Update — Foot is pulled downward to extend the knee, with a minimum bend angle to prevent lock-out. Deformation is subtly distributed across the whole leg, allowing the foot to reach its target without visible sliding or breaking the silhouette. #GuitarMocap #NIKKE #ギタリストVTubershow more

chacha🎸

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44,132 görüntüleme • 1 ay önce •via X (Twitter)

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🦵 Recovery Update: 2.5 Months Later It’s now been two and a half months since I badly twisted my knee during the summer holidays. At first, I thought it would be a minor setback—just a week or so of rest. But it turned out to be more serious, and I ended up needing surgery. Last Sunday marked nearly one month since the operation. I had a follow-up with the surgeon who said things are healing nicely and gave me the green light to start putting weight on my left leg and begin knee-bending exercises. This morning was my first physiotherapy session at the hospital—and wow, what an experience! The doctor strapped my leg into a machine that bends and straightens your knee for you. He set it to 70 degrees (which is as far as I can bend it for now), turned it on, handed me a panic button, and said “see you in an hour!” 😳 Every 50 seconds it bent to the limit. The pain was intense, but I kept going. When the doctor came back to check on me, I said (very British) “I’m fine.” So, naturally, he turned it up! 😩 Eventually, he noticed the pain in my face and dialled it back to 72 degrees. Small mercies! But the real pain came next—when he manually tried to bend my knee further. I actually cried out. He told me my knee is still very stiff and that full recovery might take many months. He’s given me some exercises to do at home, and I’m back in the “torture chamber” again next Thursday. Not looking forward to it—but I know this is the path to recovery. 🎯 My goal? To be walking (with a limp and a stick) in time for the Royal Blossom train trip to Hua Hin on 12 July. Whether I’ll manage to get up the train steps is another story… let’s see! #Thailand

🦵 Recovery Update: 2.5 Months Later It’s now been two and a half months since I badly twisted my knee during the summer holidays. At first, I thought it would be a minor setback—just a week or so of rest. But it turned out to be more serious, and I ended up needing surgery. Last Sunday marked nearly one month since the operation. I had a follow-up with the surgeon who said things are healing nicely and gave me the green light to start putting weight on my left leg and begin knee-bending exercises. This morning was my first physiotherapy session at the hospital—and wow, what an experience! The doctor strapped my leg into a machine that bends and straightens your knee for you. He set it to 70 degrees (which is as far as I can bend it for now), turned it on, handed me a panic button, and said “see you in an hour!” 😳 Every 50 seconds it bent to the limit. The pain was intense, but I kept going. When the doctor came back to check on me, I said (very British) “I’m fine.” So, naturally, he turned it up! 😩 Eventually, he noticed the pain in my face and dialled it back to 72 degrees. Small mercies! But the real pain came next—when he manually tried to bend my knee further. I actually cried out. He told me my knee is still very stiff and that full recovery might take many months. He’s given me some exercises to do at home, and I’m back in the “torture chamber” again next Thursday. Not looking forward to it—but I know this is the path to recovery. 🎯 My goal? To be walking (with a limp and a stick) in time for the Royal Blossom train trip to Hua Hin on 12 July. Whether I’ll manage to get up the train steps is another story… let’s see! #Thailand

Richard Barrow

15,303 görüntüleme • 1 yıl önce

I've been building a music player with Next.js for fun. Here's a quick demo of how it works (it's open source!) • Demo: • Code: If you want to learn more about how it's built, here's more details ↓ I'm using Postgres (with Drizzle) to store information about the songs and playlists. Audio and image files are stored in Vercel Blob (object storage), and the URLs are then referenced in the database. For the UI, I'm using shadcn/ui (so Tailwind CSS and Radix). This made it easy to copy/paste in some nice components, like the dropdown menus. I built the entire first version of the UI in v0 and then iterated from there, feeding it my Drizzle schema as a source in the project and having it scaffold some of the boilerplate for me: I added support for keyboard navigation (using arrow keys) or vim motions (j/k to go up/down, and h/l to go between playlists and tracks). Also, space to toggle the now playing song, and / to focus the search input. The search function has a nice utility to highlight the currently searched text on the page in yellow. Then, I was exploring how to pass metadata from my application to macOS or iOS. Turns out there's an API for that – MediaSession. Web apps can share metadata about what media is playing (title, artist, album artwork) and sync play/pause/seek with system media controls. Works across modern browsers — even integrates with iOS dynamic island and shows up on lock screens: I set up my app like a PWA – it has a manifest.json file, so it can be installed to my iOS home screen or added to my dock on macOS. On iOS, it then uses the full screen height `100dvh` (dynamic viewport) and has padding on the bottom for the safe area with the `env()` CSS function. Finally, I was able to use the Vercel AI SDK in a script to clean up the metadata on audio files I downloaded from YouTube. Bonus: I even was able to dogfood the React Compiler, which helped me fix a performance bug! That's all! It's fun to make personal software:

I've been building a music player with Next.js for fun. Here's a quick demo of how it works (it's open source!) • Demo: • Code: If you want to learn more about how it's built, here's more details ↓ I'm using Postgres (with Drizzle) to store information about the songs and playlists. Audio and image files are stored in Vercel Blob (object storage), and the URLs are then referenced in the database. For the UI, I'm using shadcn/ui (so Tailwind CSS and Radix). This made it easy to copy/paste in some nice components, like the dropdown menus. I built the entire first version of the UI in v0 and then iterated from there, feeding it my Drizzle schema as a source in the project and having it scaffold some of the boilerplate for me: I added support for keyboard navigation (using arrow keys) or vim motions (j/k to go up/down, and h/l to go between playlists and tracks). Also, space to toggle the now playing song, and / to focus the search input. The search function has a nice utility to highlight the currently searched text on the page in yellow. Then, I was exploring how to pass metadata from my application to macOS or iOS. Turns out there's an API for that – MediaSession. Web apps can share metadata about what media is playing (title, artist, album artwork) and sync play/pause/seek with system media controls. Works across modern browsers — even integrates with iOS dynamic island and shows up on lock screens: I set up my app like a PWA – it has a manifest.json file, so it can be installed to my iOS home screen or added to my dock on macOS. On iOS, it then uses the full screen height `100dvh` (dynamic viewport) and has padding on the bottom for the safe area with the `env()` CSS function. Finally, I was able to use the Vercel AI SDK in a script to clean up the metadata on audio files I downloaded from YouTube. Bonus: I even was able to dogfood the React Compiler, which helped me fix a performance bug! That's all! It's fun to make personal software:

Lee Robinson

118,242 görüntüleme • 1 yıl önce

一番最後の[Prompt for original image]の部分に画像生成に使用したPromptを入れると一貫性が増します。不要な場合は3行削ってしまっても大丈夫です。 --- Extreme wide-angle perspective and dynamic pose remix edit. This is an EDIT of the original image, not a new character. Use the original image as a strict reference for: – the person’s identity, hairstyle, and overall fashion style, – the general type of background and location (same street, same room, same beach, same kind of architecture, etc.). You are allowed to completely change the camera position, angle, and pose, but you must keep the scene in the SAME location and keep the SAME person and outfit design. Camera and perspective: – Use an ultra wide-angle or fisheye feeling lens (around 12–18mm full-frame look). – The camera angle MUST change significantly from the original: use dramatic angles such as • worm’s-eye view from directly below looking up, • bird’s-eye view from directly above looking down, • very low angle from the ground, • high angle from above, • tilted Dutch angles. – Always create strong foreshortening: body parts close to the lens look huge, while the rest of the body falls away in perspective. – The final result must look like a bold fashion or street photo, fully photorealistic, not illustration or anime. Background consistency: – Keep the same location as the original image: same street, same bridge, same room, same studio, same beach, same general structures and materials. – Do NOT replace the background with a completely different place. – Because the camera angle changes, it is allowed and expected that different parts of the environment become visible. – When new areas appear, extend the original environment logically (same buildings, fences, road markings, walls, colors, materials, lighting style), as if the camera moved within the same place. Body parts near the lens (1–2 parts, sometimes 3): – In each edit, choose ONE or TWO main body parts to be extremely close to the lens (sometimes even THREE in more complex poses). – Vary them from image to image, do NOT always use the same body part. – Allowed near-the-lens parts include: • one or both hands / fingers reaching toward the camera, • one or both feet / shoes / boots near the lens, • knees or thighs, • face very close to the lens, • shoulders or chest close to the lens in a leaning pose. – The chosen body parts should come extremely close to the lens, almost touching it, with visible skin texture, fabric texture, and realistic wide-angle distortion. Pose and overall body (complex and varied): – Create strong, cool, dynamic poses that match the extreme perspective. – Randomly use different pose types, including: • standing with one leg or one arm reaching toward the camera, • crouching or squatting low to the ground, • sitting on the floor or on objects, • lying on the ground with legs or feet toward the lens, • leaning forward aggressively toward the camera, • twisting the body, crossing legs, or arching the back for more dynamic lines. – Allow complex poses where: • both hands are near the lens forming shapes (peace signs, triangles, frames, pointing toward the viewer), • both feet are toward the lens, • one hand and one foot are both large in the foreground, • the face is close to the lens while hands or feet are also visible in perspective. – Maintain believable anatomy even with extreme foreshortening. Angle and attitude (randomized): – Randomize camera angle and orientation (up, down, side, Dutch tilt) while keeping the composition visually balanced and powerful. – Keep the vibe cool, confident, and fashion/editorial or street style, depending on the original outfit. – Facial expressions can vary (serious, playful, confident, mysterious), but must still look like the same person. Lighting and rendering: – Keep the general time of day and lighting mood similar to the original (night vs day, indoor vs outdoor, soft vs hard light), but you may enhance contrast and color to make the image punchy and dramatic. – Maintain realistic shadows and contact points with the ground or floor. – High-resolution, sharp details with clear skin texture, fabric weave, and material highlights. Variation and randomness: – Each edit should look noticeably different from the original image and from other edits, with different: • camera angles, • pose types, • which body parts are closest to the lens, • orientation (straight, tilted, from above, from below). – Avoid repeating the exact same single-foot-close-up composition; produce a wide variety of dynamic poses and angles. Strict rules: – Do NOT change the person into someone else. – Do NOT change the outfit type; only restyle it through pose, perspective, and small natural movement of clothing. – Do NOT move the scene to a completely different location; always stay in a plausible extension of the original place. – Do NOT add text, logos, watermarks, or graphic design elements. – Do NOT switch to painting, illustration, or anime style; keep it photorealistic. Overall: Transform the original photo into a dramatic, photorealistic, ultra wide-angle shot with an extreme camera angle (including views from directly below or above), where one or more body parts are right next to the lens and look huge, the rest of the body recedes in perspective, and the same person strikes a stylish, complex, powerful pose in a consistent, expanded version of the original environment. Also, below is the prompt for generating the original image. Please use it as a reference. [Prompt for original image] #nanobanana2

一番最後の[Prompt for original image]の部分に画像生成に使用したPromptを入れると一貫性が増します。不要な場合は3行削ってしまっても大丈夫です。 --- Extreme wide-angle perspective and dynamic pose remix edit. This is an EDIT of the original image, not a new character. Use the original image as a strict reference for: – the person’s identity, hairstyle, and overall fashion style, – the general type of background and location (same street, same room, same beach, same kind of architecture, etc.). You are allowed to completely change the camera position, angle, and pose, but you must keep the scene in the SAME location and keep the SAME person and outfit design. Camera and perspective: – Use an ultra wide-angle or fisheye feeling lens (around 12–18mm full-frame look). – The camera angle MUST change significantly from the original: use dramatic angles such as • worm’s-eye view from directly below looking up, • bird’s-eye view from directly above looking down, • very low angle from the ground, • high angle from above, • tilted Dutch angles. – Always create strong foreshortening: body parts close to the lens look huge, while the rest of the body falls away in perspective. – The final result must look like a bold fashion or street photo, fully photorealistic, not illustration or anime. Background consistency: – Keep the same location as the original image: same street, same bridge, same room, same studio, same beach, same general structures and materials. – Do NOT replace the background with a completely different place. – Because the camera angle changes, it is allowed and expected that different parts of the environment become visible. – When new areas appear, extend the original environment logically (same buildings, fences, road markings, walls, colors, materials, lighting style), as if the camera moved within the same place. Body parts near the lens (1–2 parts, sometimes 3): – In each edit, choose ONE or TWO main body parts to be extremely close to the lens (sometimes even THREE in more complex poses). – Vary them from image to image, do NOT always use the same body part. – Allowed near-the-lens parts include: • one or both hands / fingers reaching toward the camera, • one or both feet / shoes / boots near the lens, • knees or thighs, • face very close to the lens, • shoulders or chest close to the lens in a leaning pose. – The chosen body parts should come extremely close to the lens, almost touching it, with visible skin texture, fabric texture, and realistic wide-angle distortion. Pose and overall body (complex and varied): – Create strong, cool, dynamic poses that match the extreme perspective. – Randomly use different pose types, including: • standing with one leg or one arm reaching toward the camera, • crouching or squatting low to the ground, • sitting on the floor or on objects, • lying on the ground with legs or feet toward the lens, • leaning forward aggressively toward the camera, • twisting the body, crossing legs, or arching the back for more dynamic lines. – Allow complex poses where: • both hands are near the lens forming shapes (peace signs, triangles, frames, pointing toward the viewer), • both feet are toward the lens, • one hand and one foot are both large in the foreground, • the face is close to the lens while hands or feet are also visible in perspective. – Maintain believable anatomy even with extreme foreshortening. Angle and attitude (randomized): – Randomize camera angle and orientation (up, down, side, Dutch tilt) while keeping the composition visually balanced and powerful. – Keep the vibe cool, confident, and fashion/editorial or street style, depending on the original outfit. – Facial expressions can vary (serious, playful, confident, mysterious), but must still look like the same person. Lighting and rendering: – Keep the general time of day and lighting mood similar to the original (night vs day, indoor vs outdoor, soft vs hard light), but you may enhance contrast and color to make the image punchy and dramatic. – Maintain realistic shadows and contact points with the ground or floor. – High-resolution, sharp details with clear skin texture, fabric weave, and material highlights. Variation and randomness: – Each edit should look noticeably different from the original image and from other edits, with different: • camera angles, • pose types, • which body parts are closest to the lens, • orientation (straight, tilted, from above, from below). – Avoid repeating the exact same single-foot-close-up composition; produce a wide variety of dynamic poses and angles. Strict rules: – Do NOT change the person into someone else. – Do NOT change the outfit type; only restyle it through pose, perspective, and small natural movement of clothing. – Do NOT move the scene to a completely different location; always stay in a plausible extension of the original place. – Do NOT add text, logos, watermarks, or graphic design elements. – Do NOT switch to painting, illustration, or anime style; keep it photorealistic. Overall: Transform the original photo into a dramatic, photorealistic, ultra wide-angle shot with an extreme camera angle (including views from directly below or above), where one or more body parts are right next to the lens and look huge, the rest of the body recedes in perspective, and the same person strikes a stylish, complex, powerful pose in a consistent, expanded version of the original environment. Also, below is the prompt for generating the original image. Please use it as a reference. [Prompt for original image] #nanobanana2

AI Girl's Photo Studio

20,684 görüntüleme • 8 ay önce

👀Remember my post about freckles? If freckles mean melanin is coming out from the brain toward the skin to catch more sunlight (UV), then vitiligo is the opposite… it means melanin is leaving the skin going back in. 🤔 But why? 💡 When the Light Code Turns Toxic 😬 When skin is deprived of natural full-spectrum sunlight during the day and bombarded with toxic blue light at the wrong times (after sunset), the relationship between melanin, mitochondria, and repair systems collapses. The skin no longer “feels safe,” and melanin begins to migrate inside, away from the surface that’s now under photonic war attack. ⚙️ How It Works? Melanin acts like Nature’s solar panel. ☀️ If sunlight is good 👍🏻 full-spectrum, morning-rich, UV balanced with infrared and melanin says: “It’s safe. I’ll go to the surface and make energy.” But when the light is bad 👎🏻fake, blue, flickering, unbalanced, or constant at night, melanin says: “Retreat! The signal is toxic. Protect the core.” 🧬 Let’s Go a Little Deeper Melanin = Antenna, not Paint. ☣️ Pleb Kruse = BTC foundationalist in exile 🟩🔆 reminds us that melanin is a semiconductor, not a color pigment. It absorbs photons, converts them into electron flow, and manages redox, especially through the quartet of sunlight, DHA, grounding, and darkness. YES, darkness. It links the surface (skin, eyes, retina) to the core (brain and mitochondria) through light signals that we get through our environment. Freckles appear when the environment asks for more light capture. They’re an adaptive response to strong, natural light and other factors; our skin sending out more antennas to gather photons(go to take a look at my freckles post). 👹Vitiligo Appears When the Environment Turns Hostile When the body is flooded with blue/LED light, EMFs, and deprived of UV and IR(infrared), the photon code becomes chaotic. The body reads this as toxic light; signals that don’t match the natural solar spectrum. With poor redox and weak mitochondria, vitiligo appears. The brain sends a new command: “Pull melanin back inside. Protect the neurons, glands, and mitochondrial core. Mayday in progress.” Vitiligo isn’t pigment loss; it’s pigment relocation. Melanin retreats from a toxic light environment back into the body’s sanctuary to protect vital organs like the brain and heart; the organs that use the most light (energy). When the host avoid the sun and can no longer generate or store enough light, biology makes a trade: to preserve the core, the surface must be sacrificed. 🏔️ Example: Imagine being trapped on Mount Everest. To keep the core warm, the body sacrifices fingers, toes, ears, and nose; the areas with the least circulation, the ones less vital for survival. Vitiligo works the same way. When the light environment turns very hostile, the skin becomes the sacrifice. The pigment(melanin, the molecule that keeps energy flowing) go back inward to defend the core’s energetic integrity. It’s not failure; it’s a strategic withdrawal to protect life’s inner flame 🔥 The skin loses color; not as a malfunction, but as a defensive retreat mechanism 👀 a biological survival move. 🧭 And what creates it? A broken light–circadian–mitochondrial communication loop. When sunlight, magnetism, and redox fall apart, the skin–brain photonic link collapses. Freckles, melanoma, and vitiligo become they are expressions of the same imbalance; different responses to a distorted light environment. 🔋 How to Fix It? Repair the Redox 👇🏻 Rebuild light coherence. See sunrise daily( this one is NOT NEGOTIABLE, why? Go to my post on “Why Sunrise is no-negotiable for your CTA” and you know why) Avoid artificial light after dark. Ground. Eat DHA-rich seafood. Honor darkness. It’s Nature’s operating system update. Protect yourself from EMFs…. When the surface feels safe again and when real sunlight, magnetism, and rhythm return; melanin will come back home. 🏠

👀Remember my post about freckles? If freckles mean melanin is coming out from the brain toward the skin to catch more sunlight (UV), then vitiligo is the opposite… it means melanin is leaving the skin going back in. 🤔 But why? 💡 When the Light Code Turns Toxic 😬 When skin is deprived of natural full-spectrum sunlight during the day and bombarded with toxic blue light at the wrong times (after sunset), the relationship between melanin, mitochondria, and repair systems collapses. The skin no longer “feels safe,” and melanin begins to migrate inside, away from the surface that’s now under photonic war attack. ⚙️ How It Works? Melanin acts like Nature’s solar panel. ☀️ If sunlight is good 👍🏻 full-spectrum, morning-rich, UV balanced with infrared and melanin says: “It’s safe. I’ll go to the surface and make energy.” But when the light is bad 👎🏻fake, blue, flickering, unbalanced, or constant at night, melanin says: “Retreat! The signal is toxic. Protect the core.” 🧬 Let’s Go a Little Deeper Melanin = Antenna, not Paint. ☣️ Pleb Kruse = BTC foundationalist in exile 🟩🔆 reminds us that melanin is a semiconductor, not a color pigment. It absorbs photons, converts them into electron flow, and manages redox, especially through the quartet of sunlight, DHA, grounding, and darkness. YES, darkness. It links the surface (skin, eyes, retina) to the core (brain and mitochondria) through light signals that we get through our environment. Freckles appear when the environment asks for more light capture. They’re an adaptive response to strong, natural light and other factors; our skin sending out more antennas to gather photons(go to take a look at my freckles post). 👹Vitiligo Appears When the Environment Turns Hostile When the body is flooded with blue/LED light, EMFs, and deprived of UV and IR(infrared), the photon code becomes chaotic. The body reads this as toxic light; signals that don’t match the natural solar spectrum. With poor redox and weak mitochondria, vitiligo appears. The brain sends a new command: “Pull melanin back inside. Protect the neurons, glands, and mitochondrial core. Mayday in progress.” Vitiligo isn’t pigment loss; it’s pigment relocation. Melanin retreats from a toxic light environment back into the body’s sanctuary to protect vital organs like the brain and heart; the organs that use the most light (energy). When the host avoid the sun and can no longer generate or store enough light, biology makes a trade: to preserve the core, the surface must be sacrificed. 🏔️ Example: Imagine being trapped on Mount Everest. To keep the core warm, the body sacrifices fingers, toes, ears, and nose; the areas with the least circulation, the ones less vital for survival. Vitiligo works the same way. When the light environment turns very hostile, the skin becomes the sacrifice. The pigment(melanin, the molecule that keeps energy flowing) go back inward to defend the core’s energetic integrity. It’s not failure; it’s a strategic withdrawal to protect life’s inner flame 🔥 The skin loses color; not as a malfunction, but as a defensive retreat mechanism 👀 a biological survival move. 🧭 And what creates it? A broken light–circadian–mitochondrial communication loop. When sunlight, magnetism, and redox fall apart, the skin–brain photonic link collapses. Freckles, melanoma, and vitiligo become they are expressions of the same imbalance; different responses to a distorted light environment. 🔋 How to Fix It? Repair the Redox 👇🏻 Rebuild light coherence. See sunrise daily( this one is NOT NEGOTIABLE, why? Go to my post on “Why Sunrise is no-negotiable for your CTA” and you know why) Avoid artificial light after dark. Ground. Eat DHA-rich seafood. Honor darkness. It’s Nature’s operating system update. Protect yourself from EMFs…. When the surface feels safe again and when real sunlight, magnetism, and rhythm return; melanin will come back home. 🏠

🌞Light Me Away 💫

31,229 görüntüleme • 10 ay önce

The single-leg RDL ( or as some may call a hip hinge) is one of my favourite unilateral movements for building strength and control through the entire posterior chain, from your mid/lower back, to the glutes and hamstrings. Most athletes focus on just getting strong under load and while that’s important, there’s another key piece that often gets overlooked: creating length and extension through the whole body. Think about creating distance between your rear heel and the top of your head that’s where the magic happens. Here’s how I like to coach this movement: 1️⃣ RDL box-assisted with a slider — This gives your athlete a stable base to feel supported while learning to reach through that back leg. It’s a semi-passive way to build the right pattern safely. 2️⃣ Foam roller progression — Now we add a bit more difficulty. Holding a foam roller between your rear foot and same side hand forces you to stay long and connected from head to heel. 3️⃣ Banded active correction — Here, we make it active. Pressing your rear foot into the band creates that intentional extension and full-body engagement. Once your athlete has mastered these three progressions, they’re ready to load the real RDL — and you’ll notice better balance, smoother control, and a stronger hinge pattern overall. Remember: the goal isn’t just to move heavy weight, it’s to move well first. When athletes learn to own the movement, performance follows.

The single-leg RDL ( or as some may call a hip hinge) is one of my favourite unilateral movements for building strength and control through the entire posterior chain, from your mid/lower back, to the glutes and hamstrings. Most athletes focus on just getting strong under load and while that’s important, there’s another key piece that often gets overlooked: creating length and extension through the whole body. Think about creating distance between your rear heel and the top of your head that’s where the magic happens. Here’s how I like to coach this movement: 1️⃣ RDL box-assisted with a slider — This gives your athlete a stable base to feel supported while learning to reach through that back leg. It’s a semi-passive way to build the right pattern safely. 2️⃣ Foam roller progression — Now we add a bit more difficulty. Holding a foam roller between your rear foot and same side hand forces you to stay long and connected from head to heel. 3️⃣ Banded active correction — Here, we make it active. Pressing your rear foot into the band creates that intentional extension and full-body engagement. Once your athlete has mastered these three progressions, they’re ready to load the real RDL — and you’ll notice better balance, smoother control, and a stronger hinge pattern overall. Remember: the goal isn’t just to move heavy weight, it’s to move well first. When athletes learn to own the movement, performance follows.

Lorne Goldenberg

27,325 görüntüleme • 10 ay önce

Strong legs are the foundations of a stable posture, yet many let theirs weaken over time. You lose your ability to move and stand upright. Much of my work with chronic pain clients involves strengthening the legs. This video shows 8 essential lower body motions: 1- Hip Extensions Standing upright involves straightening your torso to align it with your lower body, an extension of your hips executed by your Glutes and Hamstrings. The problem is you sit on these muscles all day, weakening them over the years to the point where they fail to do their job. Your lower back picks up the slack against its will and becomes overworked. I'll start chronic pain clients with Hip Bridges on the floor to ensure everything is balanced, then progress to Hip Thrusts and eventually Standing exercises like the Romanian Deadlift. As for the Deadlift off the floor, those are great if you can access a barbell or kettlebell. - Hip Bridge (0:05) - Hip Thrust (0:11) - Romanian Deadlift (0:17) - Deadlift (0:23) 2- Split Squats Split Squats are excellent for strengthening the knees. In the case of a chronic pain client, I use them to stretch the quad and Hip Flexors of the back leg, which are often extremely stiff due to sitting. This stiffness makes the body collapse forward and is often the limiting factor when people try this exercise for the first time. I'll start someone with the Front Foot elevated because it's easier on the front leg and gives a great stretch, then progress to flat and rear foot elevated. - Front foot elevated (0:30) - Flat (0:36) - Rear-foot elevated (0:42.2) 3- Lunges Lunges are the dynamic version of the Split Squat. Besides being excellent for strengthening your leg muscles, the one thing I love about this exercise is that it teaches you how to brace yourself as your foot lands. Many people lack the core strength to absorb an impact. Lunges develop that shock absorption capacity, especially when done with weights. Ensure you have mastered the Split Squats before doing them, and use different directions to target your muscles differently. - Forward (0:48) - Back (0:54.7) - Side (1:07) 4- Squats The king of all exercises is crucial for your ascension. The vertical motion improves your ability to overcome the world's weight crashing down upon you. It's also an amazing Glute and Quad stretch in the bottom position. I'll start chronic pain clients with the bodyweight variation before progressing them to weighted and eventually one-legged, also known as Pistol Squats. Doing one leg at a time is one of the best ways to balance your body's left and right sides from head to toe. - Body weight (1:12.5) - Loaded (1:19) - Pistol (1:25.5) 5- Step-ups Step-ups are amongst my favorite one-sided exercises to strengthen the Glutes and Quads. They are excellent for improving the stability of your hips and abdominal muscles. Use the Front and Lateral variations to maximize your results. - Front (1:31.5) - Lateral (1:38) 6 - Leg Curls Leg Curls strengthen the lower attachment of your Hamstrings. They are an integral part of my knee and lower back recovery programs because many people are weak due to sitting. I'll have chronic pain clients use a towel to create muscle resistance, though you can do them standing to get some much-needed blood flow. The best way to benefit from this exercise is by using an exercise ball or a machine at the gym. - Standing (1:43) - Towel (1:49) - Exercise ball (1:55.4) - Machine (2:02.1) 7- Adductions The inner thigh muscles become problematic when people sit with their legs crossed. They either get stiff or weak depending on whether you cross one leg over the other or with your foot on the opposite knee. I love Copenhagen Planks to restore the balance in your adductors. - Knee-bent (2:08.8) - Straight-leg (2:14) 8- Calf Raises The ankles are the cornerstone of your posture because they affect the alignment of every other joint above. Strong Calves are essential to their stability, yet many omit them from their workouts. Standing Calf Raises also strengthen the knees from behind. Doing the Donkey variation, you'll feel an intense stretch from the knee to the ankle. Seated Calf Raises work a different lower leg muscle essential to pump blood back up from your feet. - Standing (2:20.5) - Donkey (2:26.6) - Seated (2:33.3) Include these 8 types of motions in your routine as an insurance policy against serious mobility problems down the line. Keeping your legs strong ensures a stable posture and quality movements, two crucial factors for a high quality of life.

Strong legs are the foundations of a stable posture, yet many let theirs weaken over time. You lose your ability to move and stand upright. Much of my work with chronic pain clients involves strengthening the legs. This video shows 8 essential lower body motions: 1- Hip Extensions Standing upright involves straightening your torso to align it with your lower body, an extension of your hips executed by your Glutes and Hamstrings. The problem is you sit on these muscles all day, weakening them over the years to the point where they fail to do their job. Your lower back picks up the slack against its will and becomes overworked. I'll start chronic pain clients with Hip Bridges on the floor to ensure everything is balanced, then progress to Hip Thrusts and eventually Standing exercises like the Romanian Deadlift. As for the Deadlift off the floor, those are great if you can access a barbell or kettlebell. - Hip Bridge (0:05) - Hip Thrust (0:11) - Romanian Deadlift (0:17) - Deadlift (0:23) 2- Split Squats Split Squats are excellent for strengthening the knees. In the case of a chronic pain client, I use them to stretch the quad and Hip Flexors of the back leg, which are often extremely stiff due to sitting. This stiffness makes the body collapse forward and is often the limiting factor when people try this exercise for the first time. I'll start someone with the Front Foot elevated because it's easier on the front leg and gives a great stretch, then progress to flat and rear foot elevated. - Front foot elevated (0:30) - Flat (0:36) - Rear-foot elevated (0:42.2) 3- Lunges Lunges are the dynamic version of the Split Squat. Besides being excellent for strengthening your leg muscles, the one thing I love about this exercise is that it teaches you how to brace yourself as your foot lands. Many people lack the core strength to absorb an impact. Lunges develop that shock absorption capacity, especially when done with weights. Ensure you have mastered the Split Squats before doing them, and use different directions to target your muscles differently. - Forward (0:48) - Back (0:54.7) - Side (1:07) 4- Squats The king of all exercises is crucial for your ascension. The vertical motion improves your ability to overcome the world's weight crashing down upon you. It's also an amazing Glute and Quad stretch in the bottom position. I'll start chronic pain clients with the bodyweight variation before progressing them to weighted and eventually one-legged, also known as Pistol Squats. Doing one leg at a time is one of the best ways to balance your body's left and right sides from head to toe. - Body weight (1:12.5) - Loaded (1:19) - Pistol (1:25.5) 5- Step-ups Step-ups are amongst my favorite one-sided exercises to strengthen the Glutes and Quads. They are excellent for improving the stability of your hips and abdominal muscles. Use the Front and Lateral variations to maximize your results. - Front (1:31.5) - Lateral (1:38) 6 - Leg Curls Leg Curls strengthen the lower attachment of your Hamstrings. They are an integral part of my knee and lower back recovery programs because many people are weak due to sitting. I'll have chronic pain clients use a towel to create muscle resistance, though you can do them standing to get some much-needed blood flow. The best way to benefit from this exercise is by using an exercise ball or a machine at the gym. - Standing (1:43) - Towel (1:49) - Exercise ball (1:55.4) - Machine (2:02.1) 7- Adductions The inner thigh muscles become problematic when people sit with their legs crossed. They either get stiff or weak depending on whether you cross one leg over the other or with your foot on the opposite knee. I love Copenhagen Planks to restore the balance in your adductors. - Knee-bent (2:08.8) - Straight-leg (2:14) 8- Calf Raises The ankles are the cornerstone of your posture because they affect the alignment of every other joint above. Strong Calves are essential to their stability, yet many omit them from their workouts. Standing Calf Raises also strengthen the knees from behind. Doing the Donkey variation, you'll feel an intense stretch from the knee to the ankle. Seated Calf Raises work a different lower leg muscle essential to pump blood back up from your feet. - Standing (2:20.5) - Donkey (2:26.6) - Seated (2:33.3) Include these 8 types of motions in your routine as an insurance policy against serious mobility problems down the line. Keeping your legs strong ensures a stable posture and quality movements, two crucial factors for a high quality of life.

Alex Bernier

696,634 görüntüleme • 2 yıl önce

I’m ready to provide an update to the entire sports community. Earlier this year, with your voices behind me, you were able to help me land a meeting with Michael Rubin and the executive team from Fanatics. I came in with an open book sharing fan frustrations, but I also walked out with a deeper understanding of the complexity behind the scenes and realized there is a lot of misinformation out there. It’s a pretty crazy business and it became clear that fans and leaders at Fanatics needed a direct line to each other. Not a one-way street, but a real back-and-forth dialogue. More of a boots on the ground, grassroots approach with fans all over the country, given that every city has a different fan culture and fandom within each team in every city is also different from the other. When I shared this with Michael he liked the concept. He told me he had heard some similar sentiments from fans that he already regularly talks to and asked me to go back and expand further. So I started meeting with local sports businesses and fans in Boston, figuring out how to make this real. I knew we needed local community involvement, a network that could channel voices from fans everywhere, allow Fanatics to share progress updates in a regular way. Through many discussions and ideas we finally birthed our concept…The Fan Advisory Network At the end of the day, the fans are the ones keeping the sports world spinning. We have the loudest voices out there, and we needed to figure out a way to have a real dialogue, not just a one-way street. I drafted a breakdown built around getting more direct local community involvement, fielding both the positives and the negatives from all fans, and allowing Fanatics to share progress updates with the community. After submitting the action plan, I got the green light. Fanatics is moving forward with the Fan Advisory Network. I’ve spent the last several weeks behind the scenes turning the initial proposal into something real. We’re doing a planned regional rollout, starting in Boston and the Northeast, then spreading wider. Three words drive everything we’re building: Community, Transparency, and Accountability. To make sure the sports community’s voices are heard while we properly grow the Fan Advisory Network, I’m stepping into a role with Fanatics as their first ever Community Leader. My primary focus will be on the Boston fandom and community. I work for you. The sports community. Getting boots on the ground is what this whole initiative is about. As I work to build up the Fan Advisory Network in Boston, Fanatics is also looking to get more involvement from local fans across the globe to truly see success. The Fan Advisory Network is coming to your cities, and we want you to be a part of this movement. Let’s build something that creates serious change. Fanatics will soon be launching an open call for Fan Advisory Network members in our first launch cities. Keep your eyes peeled for it and join in on adding your voice to the next chapter for Fanatics. LET’S FUCKING GOOOOOO!

I’m ready to provide an update to the entire sports community. Earlier this year, with your voices behind me, you were able to help me land a meeting with Michael Rubin and the executive team from Fanatics. I came in with an open book sharing fan frustrations, but I also walked out with a deeper understanding of the complexity behind the scenes and realized there is a lot of misinformation out there. It’s a pretty crazy business and it became clear that fans and leaders at Fanatics needed a direct line to each other. Not a one-way street, but a real back-and-forth dialogue. More of a boots on the ground, grassroots approach with fans all over the country, given that every city has a different fan culture and fandom within each team in every city is also different from the other. When I shared this with Michael he liked the concept. He told me he had heard some similar sentiments from fans that he already regularly talks to and asked me to go back and expand further. So I started meeting with local sports businesses and fans in Boston, figuring out how to make this real. I knew we needed local community involvement, a network that could channel voices from fans everywhere, allow Fanatics to share progress updates in a regular way. Through many discussions and ideas we finally birthed our concept…The Fan Advisory Network At the end of the day, the fans are the ones keeping the sports world spinning. We have the loudest voices out there, and we needed to figure out a way to have a real dialogue, not just a one-way street. I drafted a breakdown built around getting more direct local community involvement, fielding both the positives and the negatives from all fans, and allowing Fanatics to share progress updates with the community. After submitting the action plan, I got the green light. Fanatics is moving forward with the Fan Advisory Network. I’ve spent the last several weeks behind the scenes turning the initial proposal into something real. We’re doing a planned regional rollout, starting in Boston and the Northeast, then spreading wider. Three words drive everything we’re building: Community, Transparency, and Accountability. To make sure the sports community’s voices are heard while we properly grow the Fan Advisory Network, I’m stepping into a role with Fanatics as their first ever Community Leader. My primary focus will be on the Boston fandom and community. I work for you. The sports community. Getting boots on the ground is what this whole initiative is about. As I work to build up the Fan Advisory Network in Boston, Fanatics is also looking to get more involvement from local fans across the globe to truly see success. The Fan Advisory Network is coming to your cities, and we want you to be a part of this movement. Let’s build something that creates serious change. Fanatics will soon be launching an open call for Fan Advisory Network members in our first launch cities. Keep your eyes peeled for it and join in on adding your voice to the next chapter for Fanatics. LET’S FUCKING GOOOOOO!

Babz

99,669 görüntüleme • 3 ay önce

Why the character movement in my custom game engine felt janky and how I fixed it. In a game engine, most often, a character moves using the physics engine. Meaning, the player is not just a coordinate in space but a physical body. It has velocity, it handles collisions, and it interacts with the world. Now, as you might know, physics engines need stability. If you run them at variable framerates, things start breaking. Objects phase through walls or fly off into space because the math becomes unpredictable. This is why most game engines lock their physics loop to a 60Hz fixed rate. But here’s the problem: If you have a high-end system, you don't want to limit it at 60 FPS. That's a waste of good hardware. Now, that said, if the GPU is rendering at 144 FPS but the player's position (physics driven) only updates 60 times a second, it creates a micro-stutter that ruins the "smooth" feel of the game. A good way to fix this is to treat the character as two separate things: 1. The Physics Body (Invisible part): This is the "real" character. It lives in the 60Hz physics world, it moves the player and handles collisions. 2. The Visual Model and Camera (Visible part): This is what the player actually sees. It doesn't care about collisions, its only job is to look nice and smooth at whatever framerate the GPU is pushing. Once you have this separation, you can use interpolation to keep them in sync. Every time the physics clock ticks, you save the previous position of the invisible body before moving it to the new one. Between those ticks, calculate how far we are between the last physics update and the next one. By using this to drive the visible parts of the game, the stutters disappear. The physics loop stays fixed behind the scenes, while the visuals slide smoothly between the snapshots. Example: - Right after a tick: blend_weight= 0.0 (The visual model stays at the old physics position). - Halfway to the next: blend_weight= 0.5 (The visual model slides to the middle point). - Just before the next: blend_weight= 0.9 (The visual model is almost at the new physics position). Pro-Tip A critical mistake I made initially, and one many devs make, is parenting the camera and visible parts directly to the player body. If you do this, the camera inherits the discrete 60Hz physics movement by default. In that setup, interpolation won't work because the camera is "stuck" to the physics clock. For this fix to work you must decouple the camera and visuals from the body and move them separately. Player movement processing in Detis Engine: - fixed_process: Physics runs at 60Hz. Handles collisions and raw movement. - process: Variable rate. Mainly used for player input caching in the player case. - late_process: Variable rate. Handles interpolated camera movement after physics and everything else is done being processed. - render. Submits the final interpolated transforms to the GPU. The test environment in the video is running on an old 2070-based laptop. Hopefully the video compression won't introduce any stutter... I’m sharing this in hopes it helps a fellow dev. Cheers.

Why the character movement in my custom game engine felt janky and how I fixed it. In a game engine, most often, a character moves using the physics engine. Meaning, the player is not just a coordinate in space but a physical body. It has velocity, it handles collisions, and it interacts with the world. Now, as you might know, physics engines need stability. If you run them at variable framerates, things start breaking. Objects phase through walls or fly off into space because the math becomes unpredictable. This is why most game engines lock their physics loop to a 60Hz fixed rate. But here’s the problem: If you have a high-end system, you don't want to limit it at 60 FPS. That's a waste of good hardware. Now, that said, if the GPU is rendering at 144 FPS but the player's position (physics driven) only updates 60 times a second, it creates a micro-stutter that ruins the "smooth" feel of the game. A good way to fix this is to treat the character as two separate things: 1. The Physics Body (Invisible part): This is the "real" character. It lives in the 60Hz physics world, it moves the player and handles collisions. 2. The Visual Model and Camera (Visible part): This is what the player actually sees. It doesn't care about collisions, its only job is to look nice and smooth at whatever framerate the GPU is pushing. Once you have this separation, you can use interpolation to keep them in sync. Every time the physics clock ticks, you save the previous position of the invisible body before moving it to the new one. Between those ticks, calculate how far we are between the last physics update and the next one. By using this to drive the visible parts of the game, the stutters disappear. The physics loop stays fixed behind the scenes, while the visuals slide smoothly between the snapshots. Example: - Right after a tick: blend_weight= 0.0 (The visual model stays at the old physics position). - Halfway to the next: blend_weight= 0.5 (The visual model slides to the middle point). - Just before the next: blend_weight= 0.9 (The visual model is almost at the new physics position). Pro-Tip A critical mistake I made initially, and one many devs make, is parenting the camera and visible parts directly to the player body. If you do this, the camera inherits the discrete 60Hz physics movement by default. In that setup, interpolation won't work because the camera is "stuck" to the physics clock. For this fix to work you must decouple the camera and visuals from the body and move them separately. Player movement processing in Detis Engine: - fixed_process: Physics runs at 60Hz. Handles collisions and raw movement. - process: Variable rate. Mainly used for player input caching in the player case. - late_process: Variable rate. Handles interpolated camera movement after physics and everything else is done being processed. - render. Submits the final interpolated transforms to the GPU. The test environment in the video is running on an old 2070-based laptop. Hopefully the video compression won't introduce any stutter... I’m sharing this in hopes it helps a fellow dev. Cheers.

Ioannis Koukourakis

48,636 görüntüleme • 7 ay önce

Today marks an important day in OpenPhone (now Quo)'s history. We’re officially becoming a 2-product company. I’m excited to introduce Sona, our voice AI agent! 🎉 So what exactly is Sona? Think of it as your always-available team member that answers calls when your human team can't. It has natural conversations with your customers and collects all the information your sales team needs to follow up effectively, completely eliminating missed calls. What makes Sona special is that it's built right into your OpenPhone system where your team already collaborates. No more call forwarding to external services or losing visibility into what's happening. And you can easily review and audit its performance with full transcripts and AI-generated summaries of every call. We're already serving 60k+ businesses with OpenPhone, and I'm excited that we're now able to bring Sona to all of them. For the last 7 years, we've been focused on building our business phone system, gaining product-market fit, and scaling our team. But today, we're entering a whole new chapter with the launch of Sona. Every SaaS founder knows they'll eventually need a second product—some do it too early and get distracted, others too late when growth stalls. For us, this moment feels just right. I'm excited for what's possible with Sona and thought I'd create a Sona experience for the Founder to Founder newsletter. I trained Sona based on the content of the newsletter and all the posts that I've published. And now anyone can call and get information or ask questions about the newsletter without me having to be available to answer. Give it a try by calling 434-FOUNDER or (434) 368-6337 Would love to hear what you think! I'll leave more information about Sona in the comments.

Today marks an important day in OpenPhone (now Quo)'s history. We’re officially becoming a 2-product company. I’m excited to introduce Sona, our voice AI agent! 🎉 So what exactly is Sona? Think of it as your always-available team member that answers calls when your human team can't. It has natural conversations with your customers and collects all the information your sales team needs to follow up effectively, completely eliminating missed calls. What makes Sona special is that it's built right into your OpenPhone system where your team already collaborates. No more call forwarding to external services or losing visibility into what's happening. And you can easily review and audit its performance with full transcripts and AI-generated summaries of every call. We're already serving 60k+ businesses with OpenPhone, and I'm excited that we're now able to bring Sona to all of them. For the last 7 years, we've been focused on building our business phone system, gaining product-market fit, and scaling our team. But today, we're entering a whole new chapter with the launch of Sona. Every SaaS founder knows they'll eventually need a second product—some do it too early and get distracted, others too late when growth stalls. For us, this moment feels just right. I'm excited for what's possible with Sona and thought I'd create a Sona experience for the Founder to Founder newsletter. I trained Sona based on the content of the newsletter and all the posts that I've published. And now anyone can call and get information or ask questions about the newsletter without me having to be available to answer. Give it a try by calling 434-FOUNDER or (434) 368-6337 Would love to hear what you think! I'll leave more information about Sona in the comments.

Daryna Kulya

17,544 görüntüleme • 1 yıl önce

Since 2020, the athletes I’ve trained have earned 32 college scholarships, including some of the biggest programs in the country. One player I helped completely rework her movement went on to become the 2022 ACC Player of the Year. What makes it special is that I’m not connected to any organization, and I don’t have hundreds of athletes cycling through. My training happens in a Little League cage, no tech, no Rapsodo, no bat speed sensors. Everything I teach comes down to one thing: learning how to move from the center out. Five years ago, I realized we were training like everyone else chasing one swing method, one path and all my hitters started to look the same. I knew something was missing. That’s when I dove into movement science, retrained my own body, and discovered that real development doesn’t come from mechanics or cookie-cutter paths. I’ve never been one to settle. Today, I have a few trusted mentors across the country whom I speak with daily about movement and hitting, and I’ve spent significant time learning from them. Most parents and coaches think the next “best drill” will fix a player’s swing. What they don’t understand is that a tool starting in the hands cannot fix the swing. Real development starts from the middle out controlling center mass first. Start at the hands or barrel, and you fight the body’s natural movement. The swing doesn’t happen overnight. Consistency and true swing change come from years of learning how to move properly. When athletes get strong, develop great habits, and understand how to control their center, development skyrockets. Stay patient. Stay consistent. Prioritize movement over results. The swing is built on movement, not mechanics. Control your center, and the rest of the body follows. Adjustability, power, and consistency all start here. At the end of the day, I don’t care what a swing looks like I care how the body moves. Every athlete who trains here learns to control their center, adapt to every pitch, and build a swing that works naturally. Control your center. Control your swing. Be the best version of yourself.

Since 2020, the athletes I’ve trained have earned 32 college scholarships, including some of the biggest programs in the country. One player I helped completely rework her movement went on to become the 2022 ACC Player of the Year. What makes it special is that I’m not connected to any organization, and I don’t have hundreds of athletes cycling through. My training happens in a Little League cage, no tech, no Rapsodo, no bat speed sensors. Everything I teach comes down to one thing: learning how to move from the center out. Five years ago, I realized we were training like everyone else chasing one swing method, one path and all my hitters started to look the same. I knew something was missing. That’s when I dove into movement science, retrained my own body, and discovered that real development doesn’t come from mechanics or cookie-cutter paths. I’ve never been one to settle. Today, I have a few trusted mentors across the country whom I speak with daily about movement and hitting, and I’ve spent significant time learning from them. Most parents and coaches think the next “best drill” will fix a player’s swing. What they don’t understand is that a tool starting in the hands cannot fix the swing. Real development starts from the middle out controlling center mass first. Start at the hands or barrel, and you fight the body’s natural movement. The swing doesn’t happen overnight. Consistency and true swing change come from years of learning how to move properly. When athletes get strong, develop great habits, and understand how to control their center, development skyrockets. Stay patient. Stay consistent. Prioritize movement over results. The swing is built on movement, not mechanics. Control your center, and the rest of the body follows. Adjustability, power, and consistency all start here. At the end of the day, I don’t care what a swing looks like I care how the body moves. Every athlete who trains here learns to control their center, adapt to every pitch, and build a swing that works naturally. Control your center. Control your swing. Be the best version of yourself.

John Sangillo

26,549 görüntüleme • 9 ay önce

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 görüntüleme • 3 ay önce

Here's why $NEAR is a no-brainer in 2025 👇 Everybody loves NEAR Protocol and there is a reason for that (or many). Near is well-positioned to be one of the leading blockchain ecosystems this year. Let’s explore the “whys”. TIMESTAMPS Quick Bio – 00:00:15 Inflation Reduction Proposal – 00:00:43 Technically Speaking – 00:02:40 Near Intents – 00:03:37 Chain Signatures and AI – 00:04:39 Decentralization and DeFi – 00:05:59 I have my Near account since March 2023, but it has been inactive for a while, as I was focused on other stuff. However, the recent inflation halving proposal by HOT DAO (HOT Protocol 🔥) and LiNEAR (LiNEAR Protocol) brought my eyes back to the project and I really like what I’m seeing. So, here’s my first point. If this proposal passes, NEAR could lead the way in what appears to be a market trend of improving the tokenomics, as more and more experts realize holders have been overpaying for these networks' security, with a too high supply inflation. Solana tried something similar, but the proposal was rejected. In my opinion, validators voting favorably to that show a commitment to the chain for the long term. On the other hand, voting against it signals a short-term vision focused on milking the emissions as much as possible, at the ecosystem’s expense. The voting currently goes with 28% “YEA” votes, needing 66.76% to pass. Most of the validators who already cast their votes went with the yes. 2pilot, avb, openshards, qbit, sicmundus, fox, and intear are, so far, the only seven who voted “NAY”. This proposal has the vocal support of most influential figures in the Near ecosystem, including the Near Foundation (NEAR Foundation), led by Illia (root.near) (🇺🇦, ⋈), which makes me believe it will pass and show the power of the halving in getting the market’s attention and presenting a huge investment asymmetry for the native token right now. Is this everything I like about NEAR? Definitely not. This is just what got me looking at it again, just to discover a (very much) thriving ecosystem, full of interesting things happening at the same time. I’ll mention a few, but there is (much) more. Technically speaking, Near is a high-performance blockchain, with really low fees and one of the fastest finalities, with 600ms block time and approximately 1.8s finality. It also has my favorite architecture for internet-scale scalability, using sharding, while keeping a high decentralization standard. As a learning programmer, Near also has one of the best dev experiences (in my limited opinion). The documentation is clear, has a logical journey, presenting from the basic anatomy in details to more complex SDKs and tools. I’m also in love with the near-cli-rs. A command line interface program written in Rust for seamless interaction with the Near blockchain. Allowing wallet creation, chain query, sending transactions, staking, smart contract calls, and more. Near Intents. This was the second thing to get my attention, while studying the project again, and it sets a whole new standard for blockchain interactions, especially cross-chain. Basically, users can declare an intention (for example, swap Ethereum-USDT to Bitcoin) and a network of solvers, running on Near, will find the best path to accomplish this task. We recently saw an impressive 465k-worth swap happening in exactly this example, paying 0.55% of trading fees to thorswap.near and swapkit.near. According to a Dune Dashboard, the protocol accumulates nearly $400 million in volume since its launch not long ago, in November 2024. *obs.: half this volume was achieved in the last month. Massive! Near Intents is possible due to two other very interesting things: (i) Chain abstraction, and (ii) a solid AI infrastructure. Chain abstraction (via Chain Signatures) is a powerful interoperability feature, allowing Near to friendly connect different blockchains as if they were part of a single network. Users and devs benefit from wallet, address, fees, and cross-chain bridges abstractions - not even noticing they are interacting with multiple chains. One wallet that powers everything. Powered by Near. On AI, Near is just built differently. Not for the hype, but for the solution. The team has been looking for AI solutions much before the ChatGPT fever. Actually, they started as an AI company, pivoting to blockchain later. So, being one of the most promising networks for the growing AI economy was just the natural path to follow. There is an extensive and super complete research piece on that topic, recently published by Reflexivity Research (Reflexivity Research) on July 1st. It presents Near as an AI-optimized blockchain, covering AITP, Shade Agents, x402, Near Intents, and more. Definitely worth the reading. Wrapping up this content with one more aspect that really matters to me is how Near remains truthful to decentralization, data ownership, censorship-resistance and open-source primitives that have been increasingly abandoned by other key players. A simple example of that is how the Near Foundation decided to deprecate its public APIs, encouraging the surge of a more decentralized and competitive market of SaaS projects, with a highlight to Lava Network, that recently appeared in my timeline talking about that. DeFi is also huge on Near, leveraging all the previous properties I mentioned, creating a truly decentralized liquidity pool via Rhea Finance, connected with other chains like BTC, Ethereum, ZCash, and more. All that contributes to Near having the second-largest monthly active addresses, with nearly 50 million, only losing to Solana’s nearly 90 million. In the meantime, NEAR, the token, is not even at the 30rd position by market cap. Crazy stuff. To (finally) wrap it up, I also want to mention Near’s consensus decentralization. While having a low node-count, the network has a Nakamoto Coefficient of 11, which is not bad at all. Surely, there is still room for improvement, which is possible as becoming a validator is accessible staking and hardware-wise. If you liked this content, make sure to click the like bottom and share it around. Follow me on X or subscribe to my YouTube channel, both at vinibarbosabr. See ya!

Here's why $NEAR is a no-brainer in 2025 👇 Everybody loves NEAR Protocol and there is a reason for that (or many). Near is well-positioned to be one of the leading blockchain ecosystems this year. Let’s explore the “whys”. TIMESTAMPS Quick Bio – 00:00:15 Inflation Reduction Proposal – 00:00:43 Technically Speaking – 00:02:40 Near Intents – 00:03:37 Chain Signatures and AI – 00:04:39 Decentralization and DeFi – 00:05:59 I have my Near account since March 2023, but it has been inactive for a while, as I was focused on other stuff. However, the recent inflation halving proposal by HOT DAO (HOT Protocol 🔥) and LiNEAR (LiNEAR Protocol) brought my eyes back to the project and I really like what I’m seeing. So, here’s my first point. If this proposal passes, NEAR could lead the way in what appears to be a market trend of improving the tokenomics, as more and more experts realize holders have been overpaying for these networks' security, with a too high supply inflation. Solana tried something similar, but the proposal was rejected. In my opinion, validators voting favorably to that show a commitment to the chain for the long term. On the other hand, voting against it signals a short-term vision focused on milking the emissions as much as possible, at the ecosystem’s expense. The voting currently goes with 28% “YEA” votes, needing 66.76% to pass. Most of the validators who already cast their votes went with the yes. 2pilot, avb, openshards, qbit, sicmundus, fox, and intear are, so far, the only seven who voted “NAY”. This proposal has the vocal support of most influential figures in the Near ecosystem, including the Near Foundation (NEAR Foundation), led by Illia (root.near) (🇺🇦, ⋈), which makes me believe it will pass and show the power of the halving in getting the market’s attention and presenting a huge investment asymmetry for the native token right now. Is this everything I like about NEAR? Definitely not. This is just what got me looking at it again, just to discover a (very much) thriving ecosystem, full of interesting things happening at the same time. I’ll mention a few, but there is (much) more. Technically speaking, Near is a high-performance blockchain, with really low fees and one of the fastest finalities, with 600ms block time and approximately 1.8s finality. It also has my favorite architecture for internet-scale scalability, using sharding, while keeping a high decentralization standard. As a learning programmer, Near also has one of the best dev experiences (in my limited opinion). The documentation is clear, has a logical journey, presenting from the basic anatomy in details to more complex SDKs and tools. I’m also in love with the near-cli-rs. A command line interface program written in Rust for seamless interaction with the Near blockchain. Allowing wallet creation, chain query, sending transactions, staking, smart contract calls, and more. Near Intents. This was the second thing to get my attention, while studying the project again, and it sets a whole new standard for blockchain interactions, especially cross-chain. Basically, users can declare an intention (for example, swap Ethereum-USDT to Bitcoin) and a network of solvers, running on Near, will find the best path to accomplish this task. We recently saw an impressive 465k-worth swap happening in exactly this example, paying 0.55% of trading fees to thorswap.near and swapkit.near. According to a Dune Dashboard, the protocol accumulates nearly $400 million in volume since its launch not long ago, in November 2024. *obs.: half this volume was achieved in the last month. Massive! Near Intents is possible due to two other very interesting things: (i) Chain abstraction, and (ii) a solid AI infrastructure. Chain abstraction (via Chain Signatures) is a powerful interoperability feature, allowing Near to friendly connect different blockchains as if they were part of a single network. Users and devs benefit from wallet, address, fees, and cross-chain bridges abstractions - not even noticing they are interacting with multiple chains. One wallet that powers everything. Powered by Near. On AI, Near is just built differently. Not for the hype, but for the solution. The team has been looking for AI solutions much before the ChatGPT fever. Actually, they started as an AI company, pivoting to blockchain later. So, being one of the most promising networks for the growing AI economy was just the natural path to follow. There is an extensive and super complete research piece on that topic, recently published by Reflexivity Research (Reflexivity Research) on July 1st. It presents Near as an AI-optimized blockchain, covering AITP, Shade Agents, x402, Near Intents, and more. Definitely worth the reading. Wrapping up this content with one more aspect that really matters to me is how Near remains truthful to decentralization, data ownership, censorship-resistance and open-source primitives that have been increasingly abandoned by other key players. A simple example of that is how the Near Foundation decided to deprecate its public APIs, encouraging the surge of a more decentralized and competitive market of SaaS projects, with a highlight to Lava Network, that recently appeared in my timeline talking about that. DeFi is also huge on Near, leveraging all the previous properties I mentioned, creating a truly decentralized liquidity pool via Rhea Finance, connected with other chains like BTC, Ethereum, ZCash, and more. All that contributes to Near having the second-largest monthly active addresses, with nearly 50 million, only losing to Solana’s nearly 90 million. In the meantime, NEAR, the token, is not even at the 30rd position by market cap. Crazy stuff. To (finally) wrap it up, I also want to mention Near’s consensus decentralization. While having a low node-count, the network has a Nakamoto Coefficient of 11, which is not bad at all. Surely, there is still room for improvement, which is possible as becoming a validator is accessible staking and hardware-wise. If you liked this content, make sure to click the like bottom and share it around. Follow me on X or subscribe to my YouTube channel, both at vinibarbosabr. See ya!

Vini B |「 thecoding 」

40,183 görüntüleme • 1 yıl önce

Thermodynamic computing is here There is a new computing paradigm emerging from the noise, and its arrival may be as significant as the dawn of deep learning or the advent of cloud virtualization. A new company, Extropic, has just launched its first thermodynamic computer, a device they call a TSU, or Thermal Sampling Unit. While the web is already filling with deep technical dives, what’s more important for most of us is building a clear intuition for what this technology is, how it’s fundamentally different from anything that’s come before, and why it’s generating so much excitement. This isn’t just another chip; it’s a new way to think about computation itself. Seeing is Believing: Solving Puzzles in One Shot To understand what a TSU does, let’s look at two classic, notoriously difficult computer science problems: Sudoku and the Eight Queens problem. When you or I solve a Sudoku, we use a process of sequential logic, guess-and-check, and backtracking. We make an assumption, follow its logical conclusion, and if we hit a dead end, we erase and try again. A classical computer does the same, just much faster. A TSU, however, approaches this in a completely different way. Using a TSU simulator, one can “program” the problem by first clamping the known values—the clues already on the board. Then, you program in the constraints: no duplicate numbers in any row, column, or 3x3 square. With the problem thus defined, the TSU doesn’t “search” for a solution; it anneals one. In a single computational step, the solution simply emerges, backfilling all the empty squares correctly. The same principle applies to the Eight Queens problem, a challenge to place eight queens on a chessboard so that none can attack any other. This is a complex combinatorial problem with 92 distinct solutions. A classical computer would have to iteratively search for these. A TSU, by contrast, can be programmed with the constraints (the “anti-affinity” between queens on the same row, column, or diagonal) and then set to sample the “solution space.” In this context, a valid solution is one with a “problem energy” of zero. The TSU’s physical nature allows it to naturally find these zero-energy states. A simulation of this process shows the TSU discovering all 92 unique solutions, demonstrating its ability to not just find an answer, but to explore the entire landscape of all correct answers. This is a fundamentally new approach, one that bypasses the brute-force, iterative methods we’ve relied on for decades. The Physics of Computation: Using Noise, Not Fighting It This new power comes from a radical design philosophy. For the last 70 years, computing has been about one thing: order. We build chips that are deterministic, logical, and precise. The great enemy has always been noise, heat, and randomness. We spend billions on cooling and error correction to eliminate these very things. Quantum computing, in many ways, is the ultimate expression of this, requiring temperatures near absolute zero to eliminate all thermal noise and achieve quantum coherence. Thermodynamic computing is the polar opposite. It doesn’t fight the noise; it uses it. The TSU is built on the understanding that the natural, stochastic noise from “leaky” transistors—the very randomness we’ve tried to engineer out of existence—is itself a powerful computational resource. Think of it this way: a GPU, which is central to today’s AI, has to simulate noise. When a generative AI model creates a new image or sentence, it’s using complex algorithms to fake randomness. The TSU doesn’t need to fake it; it harnesses the actual physical randomness of thermodynamics. It is a piece of hardware that directly computes with probability. This makes it a hybrid, sitting somewhere between a purely analog computer (which might use light or sound waves to compute) and a digital GPU. It’s a physical device that leverages the laws of physics itself to find solutions, rather than just using logic gates to simulate them. From a Lost Hiker to a Million Bouncy Balls Perhaps the best way to build intuition is with a metaphor. Imagine that solving a complex optimization problem is like trying to find the lowest point of altitude in a 100-square-mile mountainous landscape. Classical computing, using an algorithm like gradient descent, is like being a single hiker dropped into this landscape at night. You have no map or satellite view. All you have is an altimeter and the sensation of the slope under your feet. You can only take one step at a time, always walking downhill, hoping you don’t get stuck in a small local valley when the true, lowest canyon is miles away. Thermodynamic computing is a completely different approach. It’s like having a million bouncy balls and a helicopter. You drop all million balls simultaneously across the entire 100-square-mile landscape. Then, you “turn on an earthquake,” shaking the entire system. The balls bounce and jostle, but as the shaking (the “annealing”) subsides, where do they all end up? They naturally settle into the lowest points. The balls that collect in the deepest valley represent the optimal solution. The TSU is, in essence, a physical device for dropping those million balls at once and letting the laws of thermodynamics find the lowest “energy” state for you, all at the same time. Beyond Puzzles: The Real-World Impact This is far more than just a clever way to solve brain teasers. This ability to instantly find the lowest energy state for a complex, constrained system has staggering real-world applications. One of the most immediate is protein folding. Companies like Google’s DeepMind have made incredible progress with AI like AlphaFold, which predicts protein structures. But this is still a predictive model trained on existing data. A TSU could potentially solve the folding problem directly, treating the protein as a system of atomic affinities and repulsions and finding its most stable, lowest-energy configuration almost instantaneously. This could revolutionize drug discovery and materials science. An even more profound possibility lies in nuclear fusion. One of the greatest engineering challenges in history is controlling the superheated plasma within a tokamak reactor. This requires shaping unimaginably complex magnetic containment fields in real-time to prevent the plasma from touching the reactor walls. This is a real-time optimization problem so complex it’s currently beyond our capabilities. A TSU, however, could be fast enough. Its ability to compute with electricity itself, rather than abstracting the problem through layers of software, might allow it to update the magnetic fields fast enough to stabilize the fusion reaction. One could even imagine a future where thermodynamic computing elements are built directly into the tokamak’s walls, allowing the reactor to physically and intelligently react to the plasma’s state in real time. A ‘GPT-2 Moment’ for a New Era It’s easy to become numb to hype, but what we are witnessing with the TSU feels different. This is what you might call a “GPT-2 moment.” For those who were there, GPT-2 was the first generative AI model that wasn’t just a toy; it was the first time you could play with it at home and see the spark of true generative intelligence. It was the precursor that pointed directly to the GPT-3 and ChatGPT revolution that has since changed the world. This TSU has that same feel. It’s the “SDK” for a new computing paradigm. This technology is as different from classical computing as quantum computing is, but with a critical difference: a team of 15 built this in two years, and it runs at room temperature on your desk. Quantum computing has seen decades of work and billions in funding, and it still hasn’t produced a commercially viable, scalable machine. The TSU is here now. Based on a two-decade-long career at the cutting edge of technology—from seeing the obvious future of virtualization in 2007 to an early conviction in deep learning and GPT—this has all the same hallmarks of a fundamental, world-changing shift. We are not just building faster calculators; we are learning to compute with the universe itself. Pay close attention to this. This is the next big thing.

Thermodynamic computing is here There is a new computing paradigm emerging from the noise, and its arrival may be as significant as the dawn of deep learning or the advent of cloud virtualization. A new company, Extropic, has just launched its first thermodynamic computer, a device they call a TSU, or Thermal Sampling Unit. While the web is already filling with deep technical dives, what’s more important for most of us is building a clear intuition for what this technology is, how it’s fundamentally different from anything that’s come before, and why it’s generating so much excitement. This isn’t just another chip; it’s a new way to think about computation itself. Seeing is Believing: Solving Puzzles in One Shot To understand what a TSU does, let’s look at two classic, notoriously difficult computer science problems: Sudoku and the Eight Queens problem. When you or I solve a Sudoku, we use a process of sequential logic, guess-and-check, and backtracking. We make an assumption, follow its logical conclusion, and if we hit a dead end, we erase and try again. A classical computer does the same, just much faster. A TSU, however, approaches this in a completely different way. Using a TSU simulator, one can “program” the problem by first clamping the known values—the clues already on the board. Then, you program in the constraints: no duplicate numbers in any row, column, or 3x3 square. With the problem thus defined, the TSU doesn’t “search” for a solution; it anneals one. In a single computational step, the solution simply emerges, backfilling all the empty squares correctly. The same principle applies to the Eight Queens problem, a challenge to place eight queens on a chessboard so that none can attack any other. This is a complex combinatorial problem with 92 distinct solutions. A classical computer would have to iteratively search for these. A TSU, by contrast, can be programmed with the constraints (the “anti-affinity” between queens on the same row, column, or diagonal) and then set to sample the “solution space.” In this context, a valid solution is one with a “problem energy” of zero. The TSU’s physical nature allows it to naturally find these zero-energy states. A simulation of this process shows the TSU discovering all 92 unique solutions, demonstrating its ability to not just find an answer, but to explore the entire landscape of all correct answers. This is a fundamentally new approach, one that bypasses the brute-force, iterative methods we’ve relied on for decades. The Physics of Computation: Using Noise, Not Fighting It This new power comes from a radical design philosophy. For the last 70 years, computing has been about one thing: order. We build chips that are deterministic, logical, and precise. The great enemy has always been noise, heat, and randomness. We spend billions on cooling and error correction to eliminate these very things. Quantum computing, in many ways, is the ultimate expression of this, requiring temperatures near absolute zero to eliminate all thermal noise and achieve quantum coherence. Thermodynamic computing is the polar opposite. It doesn’t fight the noise; it uses it. The TSU is built on the understanding that the natural, stochastic noise from “leaky” transistors—the very randomness we’ve tried to engineer out of existence—is itself a powerful computational resource. Think of it this way: a GPU, which is central to today’s AI, has to simulate noise. When a generative AI model creates a new image or sentence, it’s using complex algorithms to fake randomness. The TSU doesn’t need to fake it; it harnesses the actual physical randomness of thermodynamics. It is a piece of hardware that directly computes with probability. This makes it a hybrid, sitting somewhere between a purely analog computer (which might use light or sound waves to compute) and a digital GPU. It’s a physical device that leverages the laws of physics itself to find solutions, rather than just using logic gates to simulate them. From a Lost Hiker to a Million Bouncy Balls Perhaps the best way to build intuition is with a metaphor. Imagine that solving a complex optimization problem is like trying to find the lowest point of altitude in a 100-square-mile mountainous landscape. Classical computing, using an algorithm like gradient descent, is like being a single hiker dropped into this landscape at night. You have no map or satellite view. All you have is an altimeter and the sensation of the slope under your feet. You can only take one step at a time, always walking downhill, hoping you don’t get stuck in a small local valley when the true, lowest canyon is miles away. Thermodynamic computing is a completely different approach. It’s like having a million bouncy balls and a helicopter. You drop all million balls simultaneously across the entire 100-square-mile landscape. Then, you “turn on an earthquake,” shaking the entire system. The balls bounce and jostle, but as the shaking (the “annealing”) subsides, where do they all end up? They naturally settle into the lowest points. The balls that collect in the deepest valley represent the optimal solution. The TSU is, in essence, a physical device for dropping those million balls at once and letting the laws of thermodynamics find the lowest “energy” state for you, all at the same time. Beyond Puzzles: The Real-World Impact This is far more than just a clever way to solve brain teasers. This ability to instantly find the lowest energy state for a complex, constrained system has staggering real-world applications. One of the most immediate is protein folding. Companies like Google’s DeepMind have made incredible progress with AI like AlphaFold, which predicts protein structures. But this is still a predictive model trained on existing data. A TSU could potentially solve the folding problem directly, treating the protein as a system of atomic affinities and repulsions and finding its most stable, lowest-energy configuration almost instantaneously. This could revolutionize drug discovery and materials science. An even more profound possibility lies in nuclear fusion. One of the greatest engineering challenges in history is controlling the superheated plasma within a tokamak reactor. This requires shaping unimaginably complex magnetic containment fields in real-time to prevent the plasma from touching the reactor walls. This is a real-time optimization problem so complex it’s currently beyond our capabilities. A TSU, however, could be fast enough. Its ability to compute with electricity itself, rather than abstracting the problem through layers of software, might allow it to update the magnetic fields fast enough to stabilize the fusion reaction. One could even imagine a future where thermodynamic computing elements are built directly into the tokamak’s walls, allowing the reactor to physically and intelligently react to the plasma’s state in real time. A ‘GPT-2 Moment’ for a New Era It’s easy to become numb to hype, but what we are witnessing with the TSU feels different. This is what you might call a “GPT-2 moment.” For those who were there, GPT-2 was the first generative AI model that wasn’t just a toy; it was the first time you could play with it at home and see the spark of true generative intelligence. It was the precursor that pointed directly to the GPT-3 and ChatGPT revolution that has since changed the world. This TSU has that same feel. It’s the “SDK” for a new computing paradigm. This technology is as different from classical computing as quantum computing is, but with a critical difference: a team of 15 built this in two years, and it runs at room temperature on your desk. Quantum computing has seen decades of work and billions in funding, and it still hasn’t produced a commercially viable, scalable machine. The TSU is here now. Based on a two-decade-long career at the cutting edge of technology—from seeing the obvious future of virtualization in 2007 to an early conviction in deep learning and GPT—this has all the same hallmarks of a fundamental, world-changing shift. We are not just building faster calculators; we are learning to compute with the universe itself. Pay close attention to this. This is the next big thing.

David Shapiro (L/0)

83,649 görüntüleme • 9 ay önce

Peter Thiel gave a speech in a Hilton in 2010 that holds the keys to unlocking the source of many of America’s most severe problems. Key quote: “The task in this world… where politics has become so broken… is to find a way to escape from it. It’s not a way to fix it.” Palantir is currently tightening its grip around all of our data. Elon Musk is diverting untold billions into a Mars fantasy. All of the anarchist, antidemocratic ideas of the PayPal Mafia and the “Dark Enlightenment”—to use technology as an “escape”—were already well in process 15 years ago. —The internet as “alternate virtual reality” so you don’t have to “constantly convince people.” This is why he funded Satoshi (Bitcoin), MAGA3X (Pizzagate, Q), and pushed Musk to buy Twitter —PayPal (now blockchain/crypto/BTC) was to “overturn the monetary system” —“Escape” now more often referred to as “exit” —“Autonomous countries” now known as the “network state” JD Vance is a full member of the cult of the broligarchs. Unfortunately, this has been a very thorough coup and they have backup. It’s worth really absorbing what the living Antichrist, Peter Thiel, is saying here: “I don't think despair is the only answer. And I don't think, and it's because I don't think politics is the only way to go. And my thinking on this, you know, started to take a turn towards a more optimistic perspective in the mid to late '90s when I got involved in the tech boom in Silicon Valley. I ended up being the co-founder of a company called PayPal where -- and the initial founding vision was that we were going to use technology to change the whole world and basically overturn on the monetary system of the world. And, you know, we can debate on how much it succeeded or how little it succeeded. And there were parts of it that I think have worked, and parts of it were, you know, the jury is still out. But the basic idea was that we could never win an election on getting certain things. Because we were in such a small minority. But maybe you could actually unilaterally change the world without having to constantly convince people and beg people and plead with people who are never going to agree with you through a technological means. And this is where I think technology is this incredible alternative to politics. And, you know, there are a number of different technologies we can outline, but the task in this world where politics has become so broken and so dysfunctional is to find a way to escape from it. It's not a way to fix it. It is a way to escape. And there are, you know, a number of different options. I think the promising one of the 1990s and this last decade has been to escape onto the Internet and to sort of create an alternate virtual reality. Questions, of course, is still how does it intersect with the real world? There are, I think, escaping to outer space is a promise, although I think the space technology is not quite there. So I think that's sort of for the second half of the 21st century. I think we can try to, you know, create autonomous countries on oceans, underwater, all sorts of other spaces. But I think technology is the vehicle for how we should be looking to escape and move beyond politics as we find it today.”

Peter Thiel gave a speech in a Hilton in 2010 that holds the keys to unlocking the source of many of America’s most severe problems. Key quote: “The task in this world… where politics has become so broken… is to find a way to escape from it. It’s not a way to fix it.” Palantir is currently tightening its grip around all of our data. Elon Musk is diverting untold billions into a Mars fantasy. All of the anarchist, antidemocratic ideas of the PayPal Mafia and the “Dark Enlightenment”—to use technology as an “escape”—were already well in process 15 years ago. —The internet as “alternate virtual reality” so you don’t have to “constantly convince people.” This is why he funded Satoshi (Bitcoin), MAGA3X (Pizzagate, Q), and pushed Musk to buy Twitter —PayPal (now blockchain/crypto/BTC) was to “overturn the monetary system” —“Escape” now more often referred to as “exit” —“Autonomous countries” now known as the “network state” JD Vance is a full member of the cult of the broligarchs. Unfortunately, this has been a very thorough coup and they have backup. It’s worth really absorbing what the living Antichrist, Peter Thiel, is saying here: “I don't think despair is the only answer. And I don't think, and it's because I don't think politics is the only way to go. And my thinking on this, you know, started to take a turn towards a more optimistic perspective in the mid to late '90s when I got involved in the tech boom in Silicon Valley. I ended up being the co-founder of a company called PayPal where -- and the initial founding vision was that we were going to use technology to change the whole world and basically overturn on the monetary system of the world. And, you know, we can debate on how much it succeeded or how little it succeeded. And there were parts of it that I think have worked, and parts of it were, you know, the jury is still out. But the basic idea was that we could never win an election on getting certain things. Because we were in such a small minority. But maybe you could actually unilaterally change the world without having to constantly convince people and beg people and plead with people who are never going to agree with you through a technological means. And this is where I think technology is this incredible alternative to politics. And, you know, there are a number of different technologies we can outline, but the task in this world where politics has become so broken and so dysfunctional is to find a way to escape from it. It's not a way to fix it. It is a way to escape. And there are, you know, a number of different options. I think the promising one of the 1990s and this last decade has been to escape onto the Internet and to sort of create an alternate virtual reality. Questions, of course, is still how does it intersect with the real world? There are, I think, escaping to outer space is a promise, although I think the space technology is not quite there. So I think that's sort of for the second half of the 21st century. I think we can try to, you know, create autonomous countries on oceans, underwater, all sorts of other spaces. But I think technology is the vehicle for how we should be looking to escape and move beyond politics as we find it today.”

Jim Stewartson, Decelerationist 🇨🇦🇺🇦🇺🇸

156,800 görüntüleme • 1 yıl önce

Here is the Geometry Nodes Weighted Normals with Laplacian Blur on a full character (a vroid). It easily improves the shading even on game topology with almost no setup. I built this as part of my quest to improve real time toon shading. 3D anime models are popular, but use of dynamic light is rare even among high quality vtuber models. This is for several reasons, but a big one is simply that it takes a lot of Custom Normals work to make 3D cel shading not look like a jagged mess (other pieces of the puzzle are issues like deformations, multiple lights, etc). And fixing Normals is tedious, especially on existing game topology. I have focused on proxy meshes for priority areas like character faces, but they aren't an efficient solution for the whole body + outfit. I wanted something I could just throw on any model and make it at least not a jagged mess anymore even if it wasn't perfect. As you can see from this clip, this does that very well! And vertex groups can be used to control the style of the effect and power. It still can't smooth beyond what the topology density can support, but the topo itself is no longer a problem (for higher res, could be run on a subdivided version of the model and then baked to a Normal Map.) The only changes I made to this model were adding a weld modifier to merge split edges during interpolation, and a vertex group to select the skirt. I have not yet added full handling and logic for detecting edges with big angles like the skirt, or for handling boundaries like on the hair, so both those areas can get better too. You can also see that while it successfully smooths out the Face, it isn't really stylistically correct there. That is still best done with a proxy mesh to define a new shape. This is part of the tools I am working on for Fondant. We are putting together a Blender Addon to release this + a proxy mesh tool for the face, and are working on resolving other problems in-engine to fully bring dynamic light to real time 3D toon shading. Give us a follow, and send them a DM if you are interested in testing these tools as they develop!

Here is the Geometry Nodes Weighted Normals with Laplacian Blur on a full character (a vroid). It easily improves the shading even on game topology with almost no setup. I built this as part of my quest to improve real time toon shading. 3D anime models are popular, but use of dynamic light is rare even among high quality vtuber models. This is for several reasons, but a big one is simply that it takes a lot of Custom Normals work to make 3D cel shading not look like a jagged mess (other pieces of the puzzle are issues like deformations, multiple lights, etc). And fixing Normals is tedious, especially on existing game topology. I have focused on proxy meshes for priority areas like character faces, but they aren't an efficient solution for the whole body + outfit. I wanted something I could just throw on any model and make it at least not a jagged mess anymore even if it wasn't perfect. As you can see from this clip, this does that very well! And vertex groups can be used to control the style of the effect and power. It still can't smooth beyond what the topology density can support, but the topo itself is no longer a problem (for higher res, could be run on a subdivided version of the model and then baked to a Normal Map.) The only changes I made to this model were adding a weld modifier to merge split edges during interpolation, and a vertex group to select the skirt. I have not yet added full handling and logic for detecting edges with big angles like the skirt, or for handling boundaries like on the hair, so both those areas can get better too. You can also see that while it successfully smooths out the Face, it isn't really stylistically correct there. That is still best done with a proxy mesh to define a new shape. This is part of the tools I am working on for Fondant. We are putting together a Blender Addon to release this + a proxy mesh tool for the face, and are working on resolving other problems in-engine to fully bring dynamic light to real time 3D toon shading. Give us a follow, and send them a DM if you are interested in testing these tools as they develop!

aVersionOfReality

14,679 görüntüleme • 1 yıl önce

📍 A Brazilian fan shared her story and the moment she felt very proud of being Afra's fan 🤍 "I want to share a moment that made me very proud to be a fan of Afra. I study at the Faculty of Fine Arts here in Brazil, and we had an exam in which we needed to prepare a report analyzing a scene with a focus on facial expressions in acting. I chose Afra’s scene in the series Sister’s Daughters (Kardeş Çocukları) — the coal storage scene — and I deeply analyzed her emotional control, the subtle changes in her face, and the way she conveyed such intense feelings. After everyone presented their work, the professor selected three that he considered the strongest... and mine was among them. The best part: he was so impressed with Afra’s performance that he started using her as an example whenever he explained something about expression and performance. He would play her scenes in class and analyze her technique in front of everyone. In that moment, my pride couldn’t fit inside me… it felt like I wasn’t just presenting an assignment, but presenting to my classmates and professor a talent that I truly admire and respect. ❤️" When I was a student, there was a time when, like the girl from Brazil, I introduced Afra to my professor and classmates for a body language analysis class, and I still remember the expressions my classmates made when they saw her performance. At the end of the class, my professor asked me for a list of series Afra had acted in. Before the end of the semester, she mentioned she was watching YalıÇapkını, and she could tell her growth as an actress was a fascinating process to watch. Here are some of the qualities we point out at class and I added some of this as an example for the scene the girl from Brazil mentioned 🧿✨ Afra's qualities and facial expression technique stand out in several ways: Emotional control with subtlety: Afra doesn’t overplay emotions, she balances intensity with restraint. Even in highly charged scenes, she maintains precise control, letting feelings emerge gradually rather than explosively, which makes them more believable and relatable. Micro-expressions that carry weight: She uses tiny, almost imperceptible facial shifts a slight tightening of the lips, a flicker in the eyes, or a micro-raise of an eyebrow to signal deep inner change. These small details invite the audience to lean in, paying closer attention. Layered emotion: Afra often plays more than one emotion at a time for example, fear mixed with defiance, or sadness under a brave facade. This complexity makes her characters feel multidimensional. Seamless transition between emotions: As in the “coal storage” scene mentioned in the post, she can move from calm to broken, or from fragile to determined, without abrupt shifts. The changes are so smooth they feel like a natural emotional progression. Eyes as the emotional core: Afra’s gaze is often the strongest storytelling element in her scenes. She can convey longing, pain, or joy without a single word. Her eyes tend to “speak” before her dialogue does, preparing the audience for what’s coming. Harmonizing face, body, and voice: While the post focuses on facial expression, Afra’s full performance often matches micro facial changes with subtle body language, a shift in posture, a small hand movement, which reinforces what the face is saying. Authenticity: Perhaps her most distinctive quality: she doesn’t “look like she’s acting.” Her expressions feel spontaneous, as though we’re watching real thoughts and feelings rather than rehearsed gestures. #AfraSaraçoğlu AfraSaraçoğlu

📍 A Brazilian fan shared her story and the moment she felt very proud of being Afra's fan 🤍 "I want to share a moment that made me very proud to be a fan of Afra. I study at the Faculty of Fine Arts here in Brazil, and we had an exam in which we needed to prepare a report analyzing a scene with a focus on facial expressions in acting. I chose Afra’s scene in the series Sister’s Daughters (Kardeş Çocukları) — the coal storage scene — and I deeply analyzed her emotional control, the subtle changes in her face, and the way she conveyed such intense feelings. After everyone presented their work, the professor selected three that he considered the strongest... and mine was among them. The best part: he was so impressed with Afra’s performance that he started using her as an example whenever he explained something about expression and performance. He would play her scenes in class and analyze her technique in front of everyone. In that moment, my pride couldn’t fit inside me… it felt like I wasn’t just presenting an assignment, but presenting to my classmates and professor a talent that I truly admire and respect. ❤️" When I was a student, there was a time when, like the girl from Brazil, I introduced Afra to my professor and classmates for a body language analysis class, and I still remember the expressions my classmates made when they saw her performance. At the end of the class, my professor asked me for a list of series Afra had acted in. Before the end of the semester, she mentioned she was watching YalıÇapkını, and she could tell her growth as an actress was a fascinating process to watch. Here are some of the qualities we point out at class and I added some of this as an example for the scene the girl from Brazil mentioned 🧿✨ Afra's qualities and facial expression technique stand out in several ways: Emotional control with subtlety: Afra doesn’t overplay emotions, she balances intensity with restraint. Even in highly charged scenes, she maintains precise control, letting feelings emerge gradually rather than explosively, which makes them more believable and relatable. Micro-expressions that carry weight: She uses tiny, almost imperceptible facial shifts a slight tightening of the lips, a flicker in the eyes, or a micro-raise of an eyebrow to signal deep inner change. These small details invite the audience to lean in, paying closer attention. Layered emotion: Afra often plays more than one emotion at a time for example, fear mixed with defiance, or sadness under a brave facade. This complexity makes her characters feel multidimensional. Seamless transition between emotions: As in the “coal storage” scene mentioned in the post, she can move from calm to broken, or from fragile to determined, without abrupt shifts. The changes are so smooth they feel like a natural emotional progression. Eyes as the emotional core: Afra’s gaze is often the strongest storytelling element in her scenes. She can convey longing, pain, or joy without a single word. Her eyes tend to “speak” before her dialogue does, preparing the audience for what’s coming. Harmonizing face, body, and voice: While the post focuses on facial expression, Afra’s full performance often matches micro facial changes with subtle body language, a shift in posture, a small hand movement, which reinforces what the face is saying. Authenticity: Perhaps her most distinctive quality: she doesn’t “look like she’s acting.” Her expressions feel spontaneous, as though we’re watching real thoughts and feelings rather than rehearsed gestures. #AfraSaraçoğlu AfraSaraçoğlu

Afra Saraçoğlu World Fan Club

36,159 görüntüleme • 1 yıl önce