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Global illumination with radiance cascades, now optimized, running at ca. 0.3 ms per frame (GTX 970 GPU). No denoising or temporal accumulation. Calculated from scratch each frame. Loving the technique. Link to the WIP paper: #gamedev #indiedev

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Mytino (Asbjørn L)

3,896 subscribers

168,274 görüntüleme • 2 yıl önce •via X (Twitter)

Oyun#gamedev#indiedev
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Mytino (Asbjørn L) profil fotoğrafı
Mytino (Asbjørn L)2 yıl önce

YouTube version of video:

Jan Orszulik profil fotoğrafı
Jan Orszulik2 yıl önce

Ok, I like this a lot! I am adding this to the list I want to investigate further, took a quick glance at PoE 2 related paper, limitations are perfectly acceptable. Great work, both this implementation and mainly original technique from Alexander.

Bino🔜 VFM Tales of Neverland profil fotoğrafı
Bino🔜 VFM Tales of Neverland2 yıl önce

how well this translates to 3D?

Mytino (Asbjørn L) profil fotoğrafı
Mytino (Asbjørn L)2 yıl önce

There are multiple ways of implementing it for 3D, such as the one used for Path of Exile 2 like Xor mentioned. The paper I linked has more information.

Mike Dailly™ 🏴󠁧󠁢󠁳󠁣󠁴󠁿🇺🇦🇵🇸💙 profil fotoğrafı
Mike Dailly™ 🏴󠁧󠁢󠁳󠁣󠁴󠁿🇺🇦🇵🇸💙2 yıl önce

That's damn fine work. ♥️

Zach profil fotoğrafı
Zach2 yıl önce

I sort of skimmed the article "Radiant 2d is capable of calculating per-pixel global illumination in 2d in a constant time of about 30ms on a GTX3060." Am I missing something? How are you accomplishing this in 0.3ms?

Jan Orszulik profil fotoğrafı
Jan Orszulik2 yıl önce

Hmmmmmm

DiTieM Games - Wishlist Dungeon of Astaroth profil fotoğrafı
DiTieM Games - Wishlist Dungeon of Astaroth2 yıl önce

what is the purpose of such fantastic visuals? game? engine? paper?

Mytino (Asbjørn L) profil fotoğrafı
Mytino (Asbjørn L)2 yıl önce

Thanks, mainly game :)

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#MichaelMovie took in an impressive $26.1M in North America over the weekend and returned to No. 1 at the box office chart in its fourth weekend. It also won the world over with a global fourth frame of $ 83.8M. The global running cume for Michael now stands at $ 703.9M.

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From International Space Station, we have a unique vantage point to observe lightning storms from directly above them. Much like from the ground, they appear as rapid, intense flashes that are over as quickly as they started. But, with the help of handheld cameras and a bit of practice (and, admittedly, some luck), we can capture these intense flashes with a very high frame rate then slow them down to see how the lightning propagates. It's lightning, in slow motion. This is one that occurred over Indonesia on 6/28. I shot it for a half second at 1/120 frame rate, so, 60 separate frames. I then compiled those frames into two videos: the first, in real-time, and the second, slowed down so that each frame is a half second to highlight the progression of the flash. Note the incredible burst of light in one frame, which includes what is likely a TLE on the upper left. A TLE, or Transient Luminous Event, is an electrical discharge that happens in the upper atmosphere above lightning storms (if you haven’t seen Nichole “Vapor” Ayers TLE photo from last week, head over to her page). As their name implies, these are transient, or short lived, phenomena – it appeared in only one frame of the sequence, lasting for no more than 1/120th of a second. The last photo is that single frame. Absolutely incredible.
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🌱 Spring gardeners are loving this clever zero-tool hack for building a raised garden bed. You grab special corner blocks from Lowe’s — or your favorite gardening or hardware store — that have four notches each. Slide in pre-cut lumber, two boards per side for height, and the whole frame snaps together in minutes with no screws, nails, or power tools required. The creator shows exactly how the boards lock into place. It took him just thirty minutes to finish the entire bed. What I really like about this raised garden bed, besides not having to use any tools to build it, is that you can make it any size you want just by cutting the boards to whatever length you need. Would you try building a raised garden bed this way, or do you already have a favorite no-fuss method?

End3of6Days9 (Helen) 🇺🇸

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📸 Back in the early days of the internet webcams were actually available quite quickly and the first one was invented in 1991 at the University of Cambridge Their first webcam was a famous "Coffee Camera" where people at the uni could see if the coffee pot was full or not, it ran for 10 years But quickly after people started using webcams for communication too, doing video calls with each other, as it obviously felt much more personal than just text chat. But the internet was very slow then so it had low frame rates, think 1 frame per second or maybe even 1 frame per multiple seconds I remember especially with MSN Messenger camming got big when I was in high school, you'd buy one for $30 usually from Logitech and connect it Now we all have a webcam integrated in our laptops, and it's a normal part of how we work, doing 1-on-1 or Zoom calls So I wanted to see if I could make modern webcams work on Windows 3.11 in your browser, so I asked Claude to generate its own WEBCAM.EXE while JavaScript pumps the Webcam feed from your computer into the DOS COM4 port And it works! And you can even print your face 😊 Try it on

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AI TENNIS ANALYSIS. A FULL COMPUTER VISION SYSTEM. BUILT ON YOLO, PYTORCH, AND KEYPOINT EXTRACTION. Take any tennis match broadcast, any camera angle, any resolution. Feed it into the pipeline. YOLO detects both players and the tennis ball frame by frame. No manual labeling, no pre-annotated dataset. A fine-tuned YOLOv5 model trained on a Roboflow tennis ball dataset handles the ball - the hardest object to track in any sport. Tiny, fast, constantly occluded. The model finds it anyway. Trackers maintain identity across frames so Player 1 stays Player 1 from the first serve to match point. But detection is just the start. A ResNet50 CNN trained in PyTorch predicts court keypoints from every frame - the corners, service lines, baselines, net posts. Fourteen points that define the entire playing surface geometry. From those keypoints the system builds a homography matrix and warps the broadcast perspective into a top-down mini court with real coordinates. Now every player has a position in real space, not pixel space. Every frame becomes a measurement. Every rally becomes a dataset. Player movement speed - calculated from position deltas between frames, converted to meters per second through the homography. Ball shot speed - measured from the ball trajectory across consecutive detections. Number of shots per rally - counted automatically through ball direction changes. All of this rendered live on the video as an overlay. A mini court in the corner showing both players as dots moving in real time. Stats updating after every point. OpenCV handles the rendering. Pandas handles the math. PyTorch handles the intelligence. YOLO handles the eyes. No Hawkeye subscription, no court-embedded sensors, no tracking chips in the ball. A Python script, a trained model, and a GPU. The full code is on GitHub. The tutorial walks through every module - from ball detector training to court keypoint extraction to the final statistical overlay. Professional teams used to need broadcast deals and proprietary hardware for this kind of analysis. Now you build it in an afternoon with open-source tools. Trading here: Computer vision didn't just enter tennis. It made the expensive stuff free.

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0:24

Fast View Synthesis of Casual Videos paper page: Novel view synthesis from an in-the-wild video is difficult due to challenges like scene dynamics and lack of parallax. While existing methods have shown promising results with implicit neural radiance fields, they are slow to train and render. This paper revisits explicit video representations to synthesize high-quality novel views from a monocular video efficiently. We treat static and dynamic video content separately. Specifically, we build a global static scene model using an extended plane-based scene representation to synthesize temporally coherent novel video. Our plane-based scene representation is augmented with spherical harmonics and displacement maps to capture view-dependent effects and model non-planar complex surface geometry. We opt to represent the dynamic content as per-frame point clouds for efficiency. While such representations are inconsistency-prone, minor temporal inconsistencies are perceptually masked due to motion. We develop a method to quickly estimate such a hybrid video representation and render novel views in real time. Our experiments show that our method can render high-quality novel views from an in-the-wild video with comparable quality to state-of-the-art methods while being 100x faster in training and enabling real-time rendering.

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If you take a movement to unpack this visualization... You'll see how it simply breaks down how reality works. At frame 0 you have a static image. Everything is one, this is the monad. As soon as you hit frame 1 there is movement, there is change. Now you have two states, moving, or static. When Nikola Tesla says you can explain everything in frequency and vibration. The difference between frame 0 and 1, is vibration. The difference between movement and no movement. This is like binary logic we use in code which is made up of 0's and 1's. After frame 1, is when frequency emerges. Because the difference between frame 1 and all frames after is about how fast is the vibration/movement happening. If we skip forward to frame 50... You have a shape that begins to emerge, this is the 8 dots, then the 6 dots. Notice how unstable it is, it's 8 dots, then 6, then a moment with 4 in a rectangle These shapes are emergent properties. The first two emergent properties after the monad was vibration and frequency. Next comes shape (i'm skipping over rotation and direction). These shapes of dots can only exist when you have frequency and rotation. This frequency and rotation creates vortex energy. It's the same energy that things like your chakras use. Or the same energy we harness in devices like engines, airplanes, fans, blenders, hard drives, etc. It's also the same vortex energy you'll see in a tornado or hurricane. They are powered because they harness rotation and frequency(change/movement). Going back to the video, notice that it is inside the entire shape, the internal structure is manifesting before the external structure does. Then around frame 60 the hexagon of circles begins to rotate. First it was the two dots that moved and now it's a complex shape that is coming to life. This is a higher dimension (or lower depending on how you look at it) manifesting into existence. The internal state is "awakening" and experiencing it's own change like what happened to the whole shape in the first frames. But it is unstable. That's why it doesn't persist for long. If you think of the 8 dots being the octahedron, they map to the element of air. Air is in the material world, but it is not something you can see. The brief moments the 8 dots are visible is similar to that effect. They are only experienceable between a small frequency band of frames. Now here's where stability begins to appear in the internal structure. This is when the 4 dots appear. You'll see that the four dots, the square, is stable and persists the most visibly for the most amount of frames. The square represents earth in the platonic solids to elements mapping. Earth, is material, it's stable. We build our buildings in squares and with earth because it is a solid shape to build on. This visualization shows you why. Across different vibrations (frame rates) it can self sustain. Between this point and frame 180, you'll see a new emergent property. Which is depth. A new dimension is introduced at around frame 90 but really becomes visible at around frame 110. You can see a foreground and background. There is the shape of the dots, but also the triskellion wave happening in the background. Let's jump to frame 180. Notice how it is the same as frame 0 except... It's flashing. If you were paying attention, you'll notice you could see flashing at frame 90 and frame 120, but they didn't persist for long. At around 150 it started to reach stability and 180 it was solidified. Between frames 150 and 180 there is flashing, but the image is still moving. Only for a brief moment at frame 180 is the movement frozen and the flashing persists. Think of that like your computer screen. It's what your screen is doing right now as you read this. Even tho the text isn't moving, the screen is flashing at 60 or 120hz. The images appear on your device because this flashing brings things to life. The entire material realm and your physical body right now, is doing the same thing. While you look solid... You're flashing in and out of existence at very high frequencies. You can look at frame 180 and frame 0 as the same essence but it is the mid point between an octave change. In the video, the ying and yang was vertical, now it is horizontal. This is a phase shift. If you notice at exactly frame 180, the rotation freezes and then the direction of rotation changes. The process then repeats all the way to frame 360 but in the opposite sequence. Once it reaches frame 360, that is an octave change and the process repeats. Each time you repeat the process is a layering of the same patterns into higher octaves. This is the same as your chakras or how other things work. They are like russian nesting dolls where every octave is layering onto the next. The complexity of your body is a layering of basic principles that emerged in earlier stages. Your organs are built of systems that are built with cells that are built with proteins that are built with atoms and so on. The atoms, work just like your body at a basic level. Your body works just like the galaxies. At each level you'll have the same pattern. This is where the idea "As Above, So Below" from. The monad, splits in two, and so on and so on. One cell, splits into two through mitosis in the same logic. We could spend all day going through examples of how biology, physics, spirituality, etc. aren't really different. They are just categories that we use to dissect these frequencies and octaves of energy but they only start paying attention within the confines of materialism. The problem is, none of the sciences start at the root patterns. Because that is reserved for religion or spirituality. It's too woo-woo to take seriously so it's dismissed. And because of that... We're left ignorant on the simple explanations for how things work. Now you need some expert with tools you don't have access to in order to explain things. When you could be understanding them without the tools. The Yin and Yang symbol in this video is 3,000 years old. It's simple. Yet I just showed you how it explains deeper layers of reality.
1:59

If you take a movement to unpack this visualization... You'll see how it simply breaks down how reality works. At frame 0 you have a static image. Everything is one, this is the monad. As soon as you hit frame 1 there is movement, there is change. Now you have two states, moving, or static. When Nikola Tesla says you can explain everything in frequency and vibration. The difference between frame 0 and 1, is vibration. The difference between movement and no movement. This is like binary logic we use in code which is made up of 0's and 1's. After frame 1, is when frequency emerges. Because the difference between frame 1 and all frames after is about how fast is the vibration/movement happening. If we skip forward to frame 50... You have a shape that begins to emerge, this is the 8 dots, then the 6 dots. Notice how unstable it is, it's 8 dots, then 6, then a moment with 4 in a rectangle These shapes are emergent properties. The first two emergent properties after the monad was vibration and frequency. Next comes shape (i'm skipping over rotation and direction). These shapes of dots can only exist when you have frequency and rotation. This frequency and rotation creates vortex energy. It's the same energy that things like your chakras use. Or the same energy we harness in devices like engines, airplanes, fans, blenders, hard drives, etc. It's also the same vortex energy you'll see in a tornado or hurricane. They are powered because they harness rotation and frequency(change/movement). Going back to the video, notice that it is inside the entire shape, the internal structure is manifesting before the external structure does. Then around frame 60 the hexagon of circles begins to rotate. First it was the two dots that moved and now it's a complex shape that is coming to life. This is a higher dimension (or lower depending on how you look at it) manifesting into existence. The internal state is "awakening" and experiencing it's own change like what happened to the whole shape in the first frames. But it is unstable. That's why it doesn't persist for long. If you think of the 8 dots being the octahedron, they map to the element of air. Air is in the material world, but it is not something you can see. The brief moments the 8 dots are visible is similar to that effect. They are only experienceable between a small frequency band of frames. Now here's where stability begins to appear in the internal structure. This is when the 4 dots appear. You'll see that the four dots, the square, is stable and persists the most visibly for the most amount of frames. The square represents earth in the platonic solids to elements mapping. Earth, is material, it's stable. We build our buildings in squares and with earth because it is a solid shape to build on. This visualization shows you why. Across different vibrations (frame rates) it can self sustain. Between this point and frame 180, you'll see a new emergent property. Which is depth. A new dimension is introduced at around frame 90 but really becomes visible at around frame 110. You can see a foreground and background. There is the shape of the dots, but also the triskellion wave happening in the background. Let's jump to frame 180. Notice how it is the same as frame 0 except... It's flashing. If you were paying attention, you'll notice you could see flashing at frame 90 and frame 120, but they didn't persist for long. At around 150 it started to reach stability and 180 it was solidified. Between frames 150 and 180 there is flashing, but the image is still moving. Only for a brief moment at frame 180 is the movement frozen and the flashing persists. Think of that like your computer screen. It's what your screen is doing right now as you read this. Even tho the text isn't moving, the screen is flashing at 60 or 120hz. The images appear on your device because this flashing brings things to life. The entire material realm and your physical body right now, is doing the same thing. While you look solid... You're flashing in and out of existence at very high frequencies. You can look at frame 180 and frame 0 as the same essence but it is the mid point between an octave change. In the video, the ying and yang was vertical, now it is horizontal. This is a phase shift. If you notice at exactly frame 180, the rotation freezes and then the direction of rotation changes. The process then repeats all the way to frame 360 but in the opposite sequence. Once it reaches frame 360, that is an octave change and the process repeats. Each time you repeat the process is a layering of the same patterns into higher octaves. This is the same as your chakras or how other things work. They are like russian nesting dolls where every octave is layering onto the next. The complexity of your body is a layering of basic principles that emerged in earlier stages. Your organs are built of systems that are built with cells that are built with proteins that are built with atoms and so on. The atoms, work just like your body at a basic level. Your body works just like the galaxies. At each level you'll have the same pattern. This is where the idea "As Above, So Below" from. The monad, splits in two, and so on and so on. One cell, splits into two through mitosis in the same logic. We could spend all day going through examples of how biology, physics, spirituality, etc. aren't really different. They are just categories that we use to dissect these frequencies and octaves of energy but they only start paying attention within the confines of materialism. The problem is, none of the sciences start at the root patterns. Because that is reserved for religion or spirituality. It's too woo-woo to take seriously so it's dismissed. And because of that... We're left ignorant on the simple explanations for how things work. Now you need some expert with tools you don't have access to in order to explain things. When you could be understanding them without the tools. The Yin and Yang symbol in this video is 3,000 years old. It's simple. Yet I just showed you how it explains deeper layers of reality.

Jamal ☯︎ 🔆🧘🏽🧠

13,149 görüntüleme • 3 ay önce

look what a single consumer GPU just built. gave Qwen3.5-35B-A3B one prompt: build a cloud GPU marketplace with pricing cards, deploy templates, and a benchmark leaderboard. it planned the layout, wrote the animations, populated the data, and served it. one shot. one HTML file. then i told it to iterate. split the hero, add a floating GPU with neural network animation. glassmorphism on the cards. done. done. done. three rounds, no confusion, no regressions. 4-bit quantized. 19.7 GB. single RTX 3090. full coding agent claude code harness running on localhost. no API calls leaving my machine. no subscription. no rate limits. earlier today i pointed it at my own production website. it curled the HTML, found every broken link, and told me "pretty shell, empty core. would not recommend." then built a better version from scratch. local inference stops being a demo when you actually steer it. the models are there. they understand intent. but you have to meet them halfway with good prompts, clear context, and real project structure. that's the skill gap now. not the models. the steering. more experiments coming. i genuinely cannot stop playing with this thing.
0:33

look what a single consumer GPU just built. gave Qwen3.5-35B-A3B one prompt: build a cloud GPU marketplace with pricing cards, deploy templates, and a benchmark leaderboard. it planned the layout, wrote the animations, populated the data, and served it. one shot. one HTML file. then i told it to iterate. split the hero, add a floating GPU with neural network animation. glassmorphism on the cards. done. done. done. three rounds, no confusion, no regressions. 4-bit quantized. 19.7 GB. single RTX 3090. full coding agent claude code harness running on localhost. no API calls leaving my machine. no subscription. no rate limits. earlier today i pointed it at my own production website. it curled the HTML, found every broken link, and told me "pretty shell, empty core. would not recommend." then built a better version from scratch. local inference stops being a demo when you actually steer it. the models are there. they understand intent. but you have to meet them halfway with good prompts, clear context, and real project structure. that's the skill gap now. not the models. the steering. more experiments coming. i genuinely cannot stop playing with this thing.

Sudo su

37,201 görüntüleme • 4 ay önce

Multi-Track Timeline Control for Text-Driven 3D Human Motion Generation paper page: Recent advances in generative modeling have led to promising progress on synthesizing 3D human motion from text, with methods that can generate character animations from short prompts and specified durations. However, using a single text prompt as input lacks the fine-grained control needed by animators, such as composing multiple actions and defining precise durations for parts of the motion. To address this, we introduce the new problem of timeline control for text-driven motion synthesis, which provides an intuitive, yet fine-grained, input interface for users. Instead of a single prompt, users can specify a multi-track timeline of multiple prompts organized in temporal intervals that may overlap. This enables specifying the exact timings of each action and composing multiple actions in sequence or at overlapping intervals. To generate composite animations from a multi-track timeline, we propose a new test-time denoising method. This method can be integrated with any pre-trained motion diffusion model to synthesize realistic motions that accurately reflect the timeline. At every step of denoising, our method processes each timeline interval (text prompt) individually, subsequently aggregating the predictions with consideration for the specific body parts engaged in each action. Experimental comparisons and ablations validate that our method produces realistic motions that respect the semantics and timing of given text prompts.
0:21

Multi-Track Timeline Control for Text-Driven 3D Human Motion Generation paper page: Recent advances in generative modeling have led to promising progress on synthesizing 3D human motion from text, with methods that can generate character animations from short prompts and specified durations. However, using a single text prompt as input lacks the fine-grained control needed by animators, such as composing multiple actions and defining precise durations for parts of the motion. To address this, we introduce the new problem of timeline control for text-driven motion synthesis, which provides an intuitive, yet fine-grained, input interface for users. Instead of a single prompt, users can specify a multi-track timeline of multiple prompts organized in temporal intervals that may overlap. This enables specifying the exact timings of each action and composing multiple actions in sequence or at overlapping intervals. To generate composite animations from a multi-track timeline, we propose a new test-time denoising method. This method can be integrated with any pre-trained motion diffusion model to synthesize realistic motions that accurately reflect the timeline. At every step of denoising, our method processes each timeline interval (text prompt) individually, subsequently aggregating the predictions with consideration for the specific body parts engaged in each action. Experimental comparisons and ablations validate that our method produces realistic motions that respect the semantics and timing of given text prompts.

AK

126,585 görüntüleme • 2 yıl önce

Jesus Christ, jnmartin has officially implemented his first big improvement over the N64 original for the Sega Dreamcast port of Mario Kart 64! Now the jumpotron monitor screens in Wario Stadium and and Luigi Raceway are updating at a full 30FPS, or 6x the framerate of the N64! ...and he's doing this entirely in software with the DC's SH4 CPU performing slow, direct VRAM reads from the framebuffer into a temporary buffer in system RAM which is later passed to OpenGL which transfers it back into VRAM to update the jumpotron texture with... and the freaking Dreamcast doesn't drop a frame doing all this shit! Might want to keep that in mind, as a community... That accessing texture memory or the framebuffer directly from the SH4 via the "uint16_t vram_s[]" symbol that the video API within KallistiOS exposes, while comparatively slow, is not actually so slow as to be unrealistic for a well-optimized game to do anything useful with... very interesting!
0:26

Jesus Christ, jnmartin has officially implemented his first big improvement over the N64 original for the Sega Dreamcast port of Mario Kart 64! Now the jumpotron monitor screens in Wario Stadium and and Luigi Raceway are updating at a full 30FPS, or 6x the framerate of the N64! ...and he's doing this entirely in software with the DC's SH4 CPU performing slow, direct VRAM reads from the framebuffer into a temporary buffer in system RAM which is later passed to OpenGL which transfers it back into VRAM to update the jumpotron texture with... and the freaking Dreamcast doesn't drop a frame doing all this shit! Might want to keep that in mind, as a community... That accessing texture memory or the framebuffer directly from the SH4 via the "uint16_t vram_s[]" symbol that the video API within KallistiOS exposes, while comparatively slow, is not actually so slow as to be unrealistic for a well-optimized game to do anything useful with... very interesting!

Falco Girgis

24,032 görüntüleme • 1 yıl önce

How to build chemistry in seconds: This is a great example of challenging, What challenging does is maintain the tension, it’s “fighting for position” Which really, what you’re avoiding is collapsing into her frame. She is trying to prize frame herself. “You wish you had this number” A lot of guys either collapse into her frame “Yeah I do, what’s your number” Or they just outright deny “No I don’t” Both suboptimal. You want to deny without qualifying yourself. Tease her back - “You’re mumbling I can’t even understand you” “Numbah?” “What’s a numbah?” Misinterpret “What you said you want my number? You can’t have it yet” Reframing the interaction knocks her off the pedestal without triggering her, or coming across try hard. What he did was perfect. Next, “Why are you getting so close to me” He’s challenging her prize frame, starting shit for more tension. “I didn’t give you permission. Stop touching my titties” Guys are gonna be like wtf is wrong with his voice But the intent and frame of your words matter more than the base. (Though a good voice still helps) “You like me already” Prize framing himself. But it’s also just him expressing his observation. “Yeah you wish I liked you” The girl now challenging the prize frame. And instead of going back and forth, another thing you can do is just call her bluff. He moved in closer to her and she broke instantly, wanting to kiss him. “I can’t kiss you right now” The only reason she didn’t was most likely a logistics issue. (Notice her looking over, checking who’s still around) He continues the challenging “Get out of here” “No you get out of here” Again - it’s more bluffing and calling out the frame He wants to stamp the fact that she likes him although it’s bit of an overextension. She’s starting to get tired of it and needs the interaction to move forward. “You want this or not because if not we’re gonna go home” The thing is he keeps playing around the “do you like me” frame Which is good to keep up the tension (which this girl likes) but it also keeps the interaction at a standstill. And eventually it will stall out and break. At this point - the opposition frame hurts your outcome more than it benefits. A better path forward is either to lead - pull her, help her with her logistics, move her away from friends, etc Or at the very least, instead of fighting for position, provoke escalation. “You can’t handle me ;)” “No you can’t handle me” Get her to challenge you and you can call her bluff to escalate like what happened earlier when he walked towards her. “Stop looking at me like I won’t do something to you right now ;)” Provoke, challenge her to set up the escalation window and it breaks the dancing around of who likes who while still maintaining tension. But bottom line, this interaction is a great example. Challenging = chemistry.
0:43

How to build chemistry in seconds: This is a great example of challenging, What challenging does is maintain the tension, it’s “fighting for position” Which really, what you’re avoiding is collapsing into her frame. She is trying to prize frame herself. “You wish you had this number” A lot of guys either collapse into her frame “Yeah I do, what’s your number” Or they just outright deny “No I don’t” Both suboptimal. You want to deny without qualifying yourself. Tease her back - “You’re mumbling I can’t even understand you” “Numbah?” “What’s a numbah?” Misinterpret “What you said you want my number? You can’t have it yet” Reframing the interaction knocks her off the pedestal without triggering her, or coming across try hard. What he did was perfect. Next, “Why are you getting so close to me” He’s challenging her prize frame, starting shit for more tension. “I didn’t give you permission. Stop touching my titties” Guys are gonna be like wtf is wrong with his voice But the intent and frame of your words matter more than the base. (Though a good voice still helps) “You like me already” Prize framing himself. But it’s also just him expressing his observation. “Yeah you wish I liked you” The girl now challenging the prize frame. And instead of going back and forth, another thing you can do is just call her bluff. He moved in closer to her and she broke instantly, wanting to kiss him. “I can’t kiss you right now” The only reason she didn’t was most likely a logistics issue. (Notice her looking over, checking who’s still around) He continues the challenging “Get out of here” “No you get out of here” Again - it’s more bluffing and calling out the frame He wants to stamp the fact that she likes him although it’s bit of an overextension. She’s starting to get tired of it and needs the interaction to move forward. “You want this or not because if not we’re gonna go home” The thing is he keeps playing around the “do you like me” frame Which is good to keep up the tension (which this girl likes) but it also keeps the interaction at a standstill. And eventually it will stall out and break. At this point - the opposition frame hurts your outcome more than it benefits. A better path forward is either to lead - pull her, help her with her logistics, move her away from friends, etc Or at the very least, instead of fighting for position, provoke escalation. “You can’t handle me ;)” “No you can’t handle me” Get her to challenge you and you can call her bluff to escalate like what happened earlier when he walked towards her. “Stop looking at me like I won’t do something to you right now ;)” Provoke, challenge her to set up the escalation window and it breaks the dancing around of who likes who while still maintaining tension. But bottom line, this interaction is a great example. Challenging = chemistry.

The Rizz Report

36,696 görüntüleme • 1 ay önce

Hey everyone, today I want to introduce a project that’s aiming to redefine how we access compute for AI — it’s called GPUAI. 🔶 GPUAI: Unlocking Global GPU Power for the AI Era GPUAI isn’t just another GPU marketplace or leasing service. It’s a fully decentralized protocol that connects idle GPU resources around the world — from gaming PCs to data center clusters — and transforms them into a high-performance compute network for AI workloads. 🧠 Why does it matter? Right now, the biggest bottleneck in AI isn’t algorithms — it’s access to compute. Training and running models requires massive GPU power, but it’s locked up in centralized cloud platforms, expensive and hard to access for smaller teams. With GPUAI, anyone can tap into a global GPU pool that’s: ✅ Fully decentralized ✅ Reputation-based and smart contract coordinated ✅ Encrypted and secure ✅ Token-incentivized — meaning contributors get rewarded in $GPUAI 📈 For developers, it’s a flexible way to access GPU compute for training, inference, and more — without cloud lock-in. 💰 For GPU owners, it’s a chance to monetize idle hardware that would otherwise go unused. The protocol is live, the apps are active, and the ecosystem is growing fast. 🌐 Try it yourself at 📖 Learn more on 🎮 Play our community games at This is real infrastructure for the future of AI, not hype. Follow them and explore their mission of decentralized computing at Tell me what you think - if you have a GPU, you can start profiting now. #GPUAI #Web3Infrastructure #AIComputing #DePIN #Decentralization
1:25

Hey everyone, today I want to introduce a project that’s aiming to redefine how we access compute for AI — it’s called GPUAI. 🔶 GPUAI: Unlocking Global GPU Power for the AI Era GPUAI isn’t just another GPU marketplace or leasing service. It’s a fully decentralized protocol that connects idle GPU resources around the world — from gaming PCs to data center clusters — and transforms them into a high-performance compute network for AI workloads. 🧠 Why does it matter? Right now, the biggest bottleneck in AI isn’t algorithms — it’s access to compute. Training and running models requires massive GPU power, but it’s locked up in centralized cloud platforms, expensive and hard to access for smaller teams. With GPUAI, anyone can tap into a global GPU pool that’s: ✅ Fully decentralized ✅ Reputation-based and smart contract coordinated ✅ Encrypted and secure ✅ Token-incentivized — meaning contributors get rewarded in $GPUAI 📈 For developers, it’s a flexible way to access GPU compute for training, inference, and more — without cloud lock-in. 💰 For GPU owners, it’s a chance to monetize idle hardware that would otherwise go unused. The protocol is live, the apps are active, and the ecosystem is growing fast. 🌐 Try it yourself at 📖 Learn more on 🎮 Play our community games at This is real infrastructure for the future of AI, not hype. Follow them and explore their mission of decentralized computing at Tell me what you think - if you have a GPU, you can start profiting now. #GPUAI #Web3Infrastructure #AIComputing #DePIN #Decentralization

The Crypto GEMs

69,984 görüntüleme • 1 yıl önce

Rookie EMF mistake: Airbnb edition... You're checking the magnetic fields on the bed with everything off- no loads running. It might look perfectly fine. But you could be missing a hidden wiring error that spikes fields exactly when you need good sleep most. Here's why it matters...A "load" is just any appliance drawing current- like a space heater, AC unit, or fan. Last weekend at an A-frame rental, the bed surface read a clean ~0.3 mG with no loads. Turn on the space heater? Same spot jumped to 1.24 mG. Not ideal for overnight exposure. Digging deeper showed sloppy wiring, def not done by a pro or to code, which created elevated fields only under load. The key takeaway for EMF-conscious travelers: In sleeping areas, especially if you'll run heat, AC, or other loads at night, test magnetic fields both before and after turning them on. P.S. This is a separate issue from direct fields emitted by the appliance itself, like from a nearby fan or compressor.
0:27

Rookie EMF mistake: Airbnb edition... You're checking the magnetic fields on the bed with everything off- no loads running. It might look perfectly fine. But you could be missing a hidden wiring error that spikes fields exactly when you need good sleep most. Here's why it matters...A "load" is just any appliance drawing current- like a space heater, AC unit, or fan. Last weekend at an A-frame rental, the bed surface read a clean ~0.3 mG with no loads. Turn on the space heater? Same spot jumped to 1.24 mG. Not ideal for overnight exposure. Digging deeper showed sloppy wiring, def not done by a pro or to code, which created elevated fields only under load. The key takeaway for EMF-conscious travelers: In sleeping areas, especially if you'll run heat, AC, or other loads at night, test magnetic fields both before and after turning them on. P.S. This is a separate issue from direct fields emitted by the appliance itself, like from a nearby fan or compressor.

🔌🛜⚡EMF Expert | Optimal Dwelling Spaces ☀️💧🧲

33,913 görüntüleme • 7 ay önce

Turn one product photo into a finished video ad. Storyboard to video with sound in minutes - inside a chat. Drop in a product photo and one sentence. Minutes later: a 9-frame storyboard, then a finished video ad with sound, ready to run. Powered by GPT Image 2 → Seedance 2.0 - one of the strongest storyboard-to-video pairings available right now, both in one chat at Why it's different: → No subscription. Most Seedance providers lock you into a monthly plan whether you make one clip or a hundred. Sogni charges per generation on a people-powered consumer GPU network. → Agent-native. Run the whole pipeline from Claude, Codex, or Hermes - "turn this into a 9-shot storyboard video" straight from your terminal. → Right model for the job. Frontier models when you need them, open-source models like LTX 2.3 when you don't. One photo. One sentence. One finished ad. Your move ↓
0:56

Turn one product photo into a finished video ad. Storyboard to video with sound in minutes - inside a chat. Drop in a product photo and one sentence. Minutes later: a 9-frame storyboard, then a finished video ad with sound, ready to run. Powered by GPT Image 2 → Seedance 2.0 - one of the strongest storyboard-to-video pairings available right now, both in one chat at Why it's different: → No subscription. Most Seedance providers lock you into a monthly plan whether you make one clip or a hundred. Sogni charges per generation on a people-powered consumer GPU network. → Agent-native. Run the whole pipeline from Claude, Codex, or Hermes - "turn this into a 9-shot storyboard video" straight from your terminal. → Right model for the job. Frontier models when you need them, open-source models like LTX 2.3 when you don't. One photo. One sentence. One finished ad. Your move ↓

Sogni.ai

1,089,334 görüntüleme • 1 ay önce

FAU Erlangen-Nürnberg presents TRIPS Trilinear Point Splatting for Real-Time Radiance Field Rendering paper page: Point-based radiance field rendering has demonstrated impressive results for novel view synthesis, offering a compelling blend of rendering quality and computational efficiency. However, also latest approaches in this domain are not without their shortcomings. 3D Gaussian Splatting [Kerbl and Kopanas et al. 2023] struggles when tasked with rendering highly detailed scenes, due to blurring and cloudy artifacts. On the other hand, ADOP [R\"uckert et al. 2022] can accommodate crisper images, but the neural reconstruction network decreases performance, it grapples with temporal instability and it is unable to effectively address large gaps in the point cloud. In this paper, we present TRIPS (Trilinear Point Splatting), an approach that combines ideas from both Gaussian Splatting and ADOP. The fundamental concept behind our novel technique involves rasterizing points into a screen-space image pyramid, with the selection of the pyramid layer determined by the projected point size. This approach allows rendering arbitrarily large points using a single trilinear write. A lightweight neural network is then used to reconstruct a hole-free image including detail beyond splat resolution. Importantly, our render pipeline is entirely differentiable, allowing for automatic optimization of both point sizes and positions. Our evaluation demonstrate that TRIPS surpasses existing state-of-the-art methods in terms of rendering quality while maintaining a real-time frame rate of 60 frames per second on readily available hardware. This performance extends to challenging scenarios, such as scenes featuring intricate geometry, expansive landscapes, and auto-exposed footage.
0:21

FAU Erlangen-Nürnberg presents TRIPS Trilinear Point Splatting for Real-Time Radiance Field Rendering paper page: Point-based radiance field rendering has demonstrated impressive results for novel view synthesis, offering a compelling blend of rendering quality and computational efficiency. However, also latest approaches in this domain are not without their shortcomings. 3D Gaussian Splatting [Kerbl and Kopanas et al. 2023] struggles when tasked with rendering highly detailed scenes, due to blurring and cloudy artifacts. On the other hand, ADOP [R\"uckert et al. 2022] can accommodate crisper images, but the neural reconstruction network decreases performance, it grapples with temporal instability and it is unable to effectively address large gaps in the point cloud. In this paper, we present TRIPS (Trilinear Point Splatting), an approach that combines ideas from both Gaussian Splatting and ADOP. The fundamental concept behind our novel technique involves rasterizing points into a screen-space image pyramid, with the selection of the pyramid layer determined by the projected point size. This approach allows rendering arbitrarily large points using a single trilinear write. A lightweight neural network is then used to reconstruct a hole-free image including detail beyond splat resolution. Importantly, our render pipeline is entirely differentiable, allowing for automatic optimization of both point sizes and positions. Our evaluation demonstrate that TRIPS surpasses existing state-of-the-art methods in terms of rendering quality while maintaining a real-time frame rate of 60 frames per second on readily available hardware. This performance extends to challenging scenarios, such as scenes featuring intricate geometry, expansive landscapes, and auto-exposed footage.

AK

45,459 görüntüleme • 2 yıl önce

On December 15, 2023, LME copper settled at $8,471 per tonne ($3.85 per pound). Today, May 25, 2026, the LME price is $13,660 per tonne, with U.S. copper trading (at a premium) at around $6.46 per pound. That’s a rise of over 60% in just two and a half years. The $15,000 per tonne threshold, needed to incentivise meaningful new supply, which I highlighted back in 2023, is now less than 10% away. Yet global copper supply is weaker today and costs are higher. Meanwhile, the demand for copper from the world’s two largest economies is unprecedented. In the US, potential Section 232 tariffs have put imported copper in the crosshairs, while in Asia we’re entering peak Chinese demand season. There are no semiconductors, no data centers, no electrification without copper… which is why the price of the world’s essential electrical conductor now trades in tandem with Nvidia and the AI boom. Add to the mix EVs, robotics, and defense demand, and copper’s future price direction is clear. In another two and a half years, $20,000 per tonne or $9+ per pound is realistic. Watch the LME warehouses closely and see where the metal actually moves… the world is finally waking up to the true value of copper.
0:28

On December 15, 2023, LME copper settled at $8,471 per tonne ($3.85 per pound). Today, May 25, 2026, the LME price is $13,660 per tonne, with U.S. copper trading (at a premium) at around $6.46 per pound. That’s a rise of over 60% in just two and a half years. The $15,000 per tonne threshold, needed to incentivise meaningful new supply, which I highlighted back in 2023, is now less than 10% away. Yet global copper supply is weaker today and costs are higher. Meanwhile, the demand for copper from the world’s two largest economies is unprecedented. In the US, potential Section 232 tariffs have put imported copper in the crosshairs, while in Asia we’re entering peak Chinese demand season. There are no semiconductors, no data centers, no electrification without copper… which is why the price of the world’s essential electrical conductor now trades in tandem with Nvidia and the AI boom. Add to the mix EVs, robotics, and defense demand, and copper’s future price direction is clear. In another two and a half years, $20,000 per tonne or $9+ per pound is realistic. Watch the LME warehouses closely and see where the metal actually moves… the world is finally waking up to the true value of copper.

Robert Friedland

55,934 görüntüleme • 2 ay önce

So how is the Sega Dreamcast's very own native port of Mario Kart 64 coming along? Well, lets take a look at some footage I just captured directly from my DC of jnmartin's latest build! Minor texture corruption is still present on some of the sprites here and there, plus there's no audio yet, BUT MY OH MY! She's running like a dream and looks SHARP as hell at with progressive scan at twice the resolution! You'll immediately notice virtually all of the texture corruption on the text and UI sprites have been fixed. You can now actually see your item box, and clouds are drawn properly in the background, rather than over the top of the scene in the foreground. Somehow, along with fixing all of this in the past few days, jnmartin has also found the time to get the monitors in the backgrounds of Luigi's Raceway and Wario Stadium correctly projecting a view of the scene onto their screens. This somewhat-advanced effect (for the time) was actually done on the N64 (in this game) WITHOUT doing a secondary render-to-texture pass, which requires submitting the scene a second time to the GPU. Instead, the framebuffer was divided into small, tiled chunks (1/6 of its total size), with only a single small chunk getting updated per frame. This way, the amount of direct VRAM access from the CPU (which is typically slow as hell) is kept to a minimum within the duration of a particular frame, with multiple frames being required to update the entire screen. But anyway, she's starting to look and play incredibly well, and those of us with early access to the builds have been thoroughly enjoying revisiting this title on our favorite platform!
1:44

So how is the Sega Dreamcast's very own native port of Mario Kart 64 coming along? Well, lets take a look at some footage I just captured directly from my DC of jnmartin's latest build! Minor texture corruption is still present on some of the sprites here and there, plus there's no audio yet, BUT MY OH MY! She's running like a dream and looks SHARP as hell at with progressive scan at twice the resolution! You'll immediately notice virtually all of the texture corruption on the text and UI sprites have been fixed. You can now actually see your item box, and clouds are drawn properly in the background, rather than over the top of the scene in the foreground. Somehow, along with fixing all of this in the past few days, jnmartin has also found the time to get the monitors in the backgrounds of Luigi's Raceway and Wario Stadium correctly projecting a view of the scene onto their screens. This somewhat-advanced effect (for the time) was actually done on the N64 (in this game) WITHOUT doing a secondary render-to-texture pass, which requires submitting the scene a second time to the GPU. Instead, the framebuffer was divided into small, tiled chunks (1/6 of its total size), with only a single small chunk getting updated per frame. This way, the amount of direct VRAM access from the CPU (which is typically slow as hell) is kept to a minimum within the duration of a particular frame, with multiple frames being required to update the entire screen. But anyway, she's starting to look and play incredibly well, and those of us with early access to the builds have been thoroughly enjoying revisiting this title on our favorite platform!

Falco Girgis

45,600 görüntüleme • 1 yıl önce