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Forza Horizon 6 VRMod MAJOR UPDATE v1.0.0-beta - AFR Frame Generation (Experimental) — NVIDIA only, makes OpenXR mode feel much smoother, toggles live while playing, turn it off if visuals look odd - brings your in headset FPS back to almost full from the halving effect Experimental upgrade which...

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lufz

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16,031 次观看 • 2 个月前 •via X (Twitter)

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In my previous post about the #Nioh3 demo, I mentioned that when the game isn’t consistently holding 60 FPS or 120 FPS, several issues can show up. Here’s a clearer breakdown of what's going on. The main reason is that the game speed and physics are tied to the frame rate. When you enable the 120 FPS cap, the engine start overreacting and pushes CPU usage very high, even if the game is still running at around 60 FPS (as shown in the first example). In the second clip, you can see the uneven, jittery camera movement I mentioned before. Notice how much smoother 60 FPS and 120 FPS look compared to the unlocked side. Also, camera movement at 60 FPS is slightly faster than at 120 FPS. In the third clip, player movement is slower when the frame rate is unlocked. This doesn’t happen all the time, but it shows up often enough to be noticeable. Because of how the Katana Engine behaves, the game is clearly designed around 60 FPS. Running at 120 FPS is possible, but it’s only recommended if your system can maintain that target almost all the time, which isn’t easy to achieve. There’s also an alternative workaround where you select the 60 (locked) option and enable Frame Generation (DLSS or FSR 3), as shown in the last clip. The downside is that DLSS Frame Generation tends to show the same stuttery look as when the frame rate isn’t holding a fixed target, likely due to Reflex keeping the frame rate slightly below target. FSR Frame Generation, on the other hand, looks much smoother and works better here.
1:17

In my previous post about the #Nioh3 demo, I mentioned that when the game isn’t consistently holding 60 FPS or 120 FPS, several issues can show up. Here’s a clearer breakdown of what's going on. The main reason is that the game speed and physics are tied to the frame rate. When you enable the 120 FPS cap, the engine start overreacting and pushes CPU usage very high, even if the game is still running at around 60 FPS (as shown in the first example). In the second clip, you can see the uneven, jittery camera movement I mentioned before. Notice how much smoother 60 FPS and 120 FPS look compared to the unlocked side. Also, camera movement at 60 FPS is slightly faster than at 120 FPS. In the third clip, player movement is slower when the frame rate is unlocked. This doesn’t happen all the time, but it shows up often enough to be noticeable. Because of how the Katana Engine behaves, the game is clearly designed around 60 FPS. Running at 120 FPS is possible, but it’s only recommended if your system can maintain that target almost all the time, which isn’t easy to achieve. There’s also an alternative workaround where you select the 60 (locked) option and enable Frame Generation (DLSS or FSR 3), as shown in the last clip. The downside is that DLSS Frame Generation tends to show the same stuttery look as when the frame rate isn’t holding a fixed target, likely due to Reflex keeping the frame rate slightly below target. FSR Frame Generation, on the other hand, looks much smoother and works better here.

BenchmarKing

17,820 次观看 • 6 个月前

Using Nano Banana Pro + Sora, I can now create a short video in just about one minute. I’ve been using Kling for a while to make short videos, and while the results can be great, the workflow has always felt a bit heavy for me. Previously, I had to export the video frame by frame as images, then send those keyframes into Kling’s first/last frame mode to generate the in-betweens. It worked, but it took a lot of time and small steps. Recently I realized I don’t necessarily need to do that anymore: now I can use Nano Banana Pro to generate the images, then send them directly to Sora to create the short video—no need to manually extract a specific frame. Another bonus is that Sora also handles basic sound design for you, which saves me from an extra round of editing and makes the whole process feel much lighter. This idea actually came from a post I saw this morning on Twitter by SD | AI Animation Storyteller, which gave me a new way of thinking about my workflow. I’m still experimenting, but so far it’s been a big improvement in efficiency for my use case. I’ve put the detailed steps I’m using in the comments in case anyone wants to try something similar.
0:24

Using Nano Banana Pro + Sora, I can now create a short video in just about one minute. I’ve been using Kling for a while to make short videos, and while the results can be great, the workflow has always felt a bit heavy for me. Previously, I had to export the video frame by frame as images, then send those keyframes into Kling’s first/last frame mode to generate the in-betweens. It worked, but it took a lot of time and small steps. Recently I realized I don’t necessarily need to do that anymore: now I can use Nano Banana Pro to generate the images, then send them directly to Sora to create the short video—no need to manually extract a specific frame. Another bonus is that Sora also handles basic sound design for you, which saves me from an extra round of editing and makes the whole process feel much lighter. This idea actually came from a post I saw this morning on Twitter by SD | AI Animation Storyteller, which gave me a new way of thinking about my workflow. I’m still experimenting, but so far it’s been a big improvement in efficiency for my use case. I’ve put the detailed steps I’m using in the comments in case anyone wants to try something similar.

underwood

46,400 次观看 • 8 个月前

Exclusive first look at Orbit. What is it? It's a new kind of brain/computer interface. It stimulates your brain from outside of your head, so no surgery needed like a Neuralink requires. This is a prototype, but they are building much smaller patches that will stick behind your ears. So, you'll wear them while in a new kind of AI-driven headset. You'll see many of those announced next year. These will be ready for 2026, so not a product you can buy right now, but should only cost a couple of hundred dollars at retail. What does it do? It messes with both your own motor system and how you feel about things while experiencing new realities in, say, a VR headset. When I got to wear it I felt myself leaning to the left or right. I could control that myself, or someone else (or an AI) could control me too. One mode made my body wig out, felt like a wave was going through my body. Sounds scary, but will enable a whole new range of VR/AR experiences that won't be possible without it. This has deep implications for how you feel when playing games, for instance. It also should be able to finally solve the "VR nausea" many feel when inside a VR headset. I filmed this on my Apple Vision Pro. If you have one I'll post a link to the 3D version of this video so you can enjoy there. A new kind of video of a new kind of device. My main reaction? Wow. Here is founder Steven Pang explaining it to me and giving me first press demo.
15:56

Exclusive first look at Orbit. What is it? It's a new kind of brain/computer interface. It stimulates your brain from outside of your head, so no surgery needed like a Neuralink requires. This is a prototype, but they are building much smaller patches that will stick behind your ears. So, you'll wear them while in a new kind of AI-driven headset. You'll see many of those announced next year. These will be ready for 2026, so not a product you can buy right now, but should only cost a couple of hundred dollars at retail. What does it do? It messes with both your own motor system and how you feel about things while experiencing new realities in, say, a VR headset. When I got to wear it I felt myself leaning to the left or right. I could control that myself, or someone else (or an AI) could control me too. One mode made my body wig out, felt like a wave was going through my body. Sounds scary, but will enable a whole new range of VR/AR experiences that won't be possible without it. This has deep implications for how you feel when playing games, for instance. It also should be able to finally solve the "VR nausea" many feel when inside a VR headset. I filmed this on my Apple Vision Pro. If you have one I'll post a link to the 3D version of this video so you can enjoy there. A new kind of video of a new kind of device. My main reaction? Wow. Here is founder Steven Pang explaining it to me and giving me first press demo.

Robert Scoble

207,997 次观看 • 1 年前

🚨 DID YOU KNOW the “security footage” released around the Trump assassination attempt may show signs of AI generation… and almost nobody is asking why? Not a conspiracy. Not a meme. Frame-by-frame anomalies. Visual artifacts. Timing problems. Continuity breaks. Publicly available footage. Open-source analysis. Good thing your boy lives in deep research. SO HERE’S THE PART THEY HOPE YOU NEVER SLOW DOWN ENOUGH TO NOTICE. In this full breakdown, I show: Possible AI-style motion artifacts hidden in plain sight Irregular shadow and lighting behavior Timing inconsistencies in the sequence Details in the footage that appear… off And why the official narrative may have major holes Because if this footage is authentic… it should withstand scrutiny. If it isn’t? That raises much bigger questions. Some platforms don’t seem eager for this analysis to circulate. Convenient. Watch the FULL video while it’s up. Then ask yourself: Was this real security footage… Or something manufactured to shape perception? The evidence is in the video. Decide for yourself. 👀 If you want, I can make it even more “Jesse On FIRE nuclear” with LEAKED / WHAT THEY DON’T WANT YOU TO SEE energy too.
19:59

🚨 DID YOU KNOW the “security footage” released around the Trump assassination attempt may show signs of AI generation… and almost nobody is asking why? Not a conspiracy. Not a meme. Frame-by-frame anomalies. Visual artifacts. Timing problems. Continuity breaks. Publicly available footage. Open-source analysis. Good thing your boy lives in deep research. SO HERE’S THE PART THEY HOPE YOU NEVER SLOW DOWN ENOUGH TO NOTICE. In this full breakdown, I show: Possible AI-style motion artifacts hidden in plain sight Irregular shadow and lighting behavior Timing inconsistencies in the sequence Details in the footage that appear… off And why the official narrative may have major holes Because if this footage is authentic… it should withstand scrutiny. If it isn’t? That raises much bigger questions. Some platforms don’t seem eager for this analysis to circulate. Convenient. Watch the FULL video while it’s up. Then ask yourself: Was this real security footage… Or something manufactured to shape perception? The evidence is in the video. Decide for yourself. 👀 If you want, I can make it even more “Jesse On FIRE nuclear” with LEAKED / WHAT THEY DON’T WANT YOU TO SEE energy too.

🔥Jesse ON FIRE🔥

19,224 次观看 • 3 个月前

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

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

ConsistentlyInconsistent

50,687 次观看 • 11 个月前

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.
0:23

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 次观看 • 7 个月前

I’ve finally applied #ViduQ3 to a narrative project for SquadBlast . It handles action sequences and explosions with a level of consistency I hadn’t seen before. I achieved camera movements I’ve had in mind for a long time that other models simply wouldn't allow me to implement. The Start-end frame option generates high-quality animations with great control, provided you choose the points wisely and give the model enough time to generate the full movement fluidly. Grok surprised me with its iteration speed. I use it to bring dynamism to establishing shots and dialogue scenes that require quick corrections. If the scene needs movement, it’s my first choice. For more paced scenes or dialogues in wide shots, I prefer Sora 2. It is better suited for maintaining character style in distant shots, where Grok tends to struggle. The music was created in Suno (Industrial Tech-Step). I was looking for a sense of movement through minor-key synth arpeggios and extreme reverb. The "Studio" feature allowed me to precisely control the intro length and the exact point where the kick hits. Finally, a huge thanks to Framer 🇱🇹 for the amazing work on Cartoon Hero and for helping me connect with the professional world, and to OscarAI for his SREFs. I didn't have much time to develop the art style from scratch, so I used one of the SREF he shares. It fit perfectly with the bluish palette and the Otomo-inspired retro sci-fi style I was aiming for. It easily saved me a full day of work. IF ANYONE HAS ANY TECHNICAL KNOW-HOW QUESTIONS RELATED TO ANY SEQUENCE FEEL FREE TO ASK IN THE COMMENTS.
1:35

I’ve finally applied #ViduQ3 to a narrative project for SquadBlast . It handles action sequences and explosions with a level of consistency I hadn’t seen before. I achieved camera movements I’ve had in mind for a long time that other models simply wouldn't allow me to implement. The Start-end frame option generates high-quality animations with great control, provided you choose the points wisely and give the model enough time to generate the full movement fluidly. Grok surprised me with its iteration speed. I use it to bring dynamism to establishing shots and dialogue scenes that require quick corrections. If the scene needs movement, it’s my first choice. For more paced scenes or dialogues in wide shots, I prefer Sora 2. It is better suited for maintaining character style in distant shots, where Grok tends to struggle. The music was created in Suno (Industrial Tech-Step). I was looking for a sense of movement through minor-key synth arpeggios and extreme reverb. The "Studio" feature allowed me to precisely control the intro length and the exact point where the kick hits. Finally, a huge thanks to Framer 🇱🇹 for the amazing work on Cartoon Hero and for helping me connect with the professional world, and to OscarAI for his SREFs. I didn't have much time to develop the art style from scratch, so I used one of the SREF he shares. It fit perfectly with the bluish palette and the Otomo-inspired retro sci-fi style I was aiming for. It easily saved me a full day of work. IF ANYONE HAS ANY TECHNICAL KNOW-HOW QUESTIONS RELATED TO ANY SEQUENCE FEEL FREE TO ASK IN THE COMMENTS.

VoxelPlot

17,771 次观看 • 6 个月前

I used Seedance Enterprise 2.5 to create this AI rap music video. One thing I noticed during testing was that I spent less time regenerating shots. I got the result on the second attempt. I was getting usable results more consistently, which made the workflow feel faster and more cost-effective. The authenticity struck me profoundly, Seedance 2.5 captures micro‑expressions and subtle eye shifts that feel unscripted — the kind of nuance that usually gets lost in AI, but here makes every frame read as a real performance. The 30-second generation made the creative process feel much more natural. The motion, lighting, and camera movement felt more natural, making it easier to focus on storytelling instead of fixing every scene. I can also see how pairing it with SeedAudio would make the overall AI music video workflow even more seamless. Support for multimodal references and localized editing helped keep the visuals consistent while making refinements much easier. Overall, Seedance 2.5 feels less like a shot generator and more like a creative tool for cinematic storytelling and music videos. Seedance 2.5 API is about to launch on BytePlus, and Lumina will also roll out Seedance 2.5 soon
0:30

I used Seedance Enterprise 2.5 to create this AI rap music video. One thing I noticed during testing was that I spent less time regenerating shots. I got the result on the second attempt. I was getting usable results more consistently, which made the workflow feel faster and more cost-effective. The authenticity struck me profoundly, Seedance 2.5 captures micro‑expressions and subtle eye shifts that feel unscripted — the kind of nuance that usually gets lost in AI, but here makes every frame read as a real performance. The 30-second generation made the creative process feel much more natural. The motion, lighting, and camera movement felt more natural, making it easier to focus on storytelling instead of fixing every scene. I can also see how pairing it with SeedAudio would make the overall AI music video workflow even more seamless. Support for multimodal references and localized editing helped keep the visuals consistent while making refinements much easier. Overall, Seedance 2.5 feels less like a shot generator and more like a creative tool for cinematic storytelling and music videos. Seedance 2.5 API is about to launch on BytePlus, and Lumina will also roll out Seedance 2.5 soon

Zara

28,952 次观看 • 11 天前

I got to try Grok 4.5 in early access in Cursor for the past few days and I absolutely enjoyed it. It feels like Opus 4.8 at 2x the speed at a much cheaper price point. I tasked it to brainstorm > plan > implement a big feature for my game (this act 1 boss fight) and it did not disappoint. - It is much smarter than Composer 2.5, during planning mode, it is able to think through my request more robustly, ensuring that edge cases are covered and makes sure to ask the right questions to confirm with me first. - It is much better at brainstorming ideas/suggestions, similar to Opus 4.8, though I think Fable still edges out a little when it comes to brainstorming ideas and suggestions - It is FAST. probably the fastest of all frontier models (Opus 4.8, GPT 5.5 etc), which makes it a joy to build with, because I can stay in the flow - It has much improved visual/animation capabilities than Composer 2.5, it can code up animations (i wanted an explosion animation with particle effects) with much, much better visuals, animation movement and timing. This is a big leap and I was so happy to see this improvement. - The best part for me is that I can just use the same model from planning down to execution without switching to a lower cost model because the price point is cheaper than other frontier models. I'll be testing this model with more challenging tasks in the next few days but I think this is going to be my main driver for vibe coding for a while. Also, its nice to see Grok back in the race. 🙌
0:34

I got to try Grok 4.5 in early access in Cursor for the past few days and I absolutely enjoyed it. It feels like Opus 4.8 at 2x the speed at a much cheaper price point. I tasked it to brainstorm > plan > implement a big feature for my game (this act 1 boss fight) and it did not disappoint. - It is much smarter than Composer 2.5, during planning mode, it is able to think through my request more robustly, ensuring that edge cases are covered and makes sure to ask the right questions to confirm with me first. - It is much better at brainstorming ideas/suggestions, similar to Opus 4.8, though I think Fable still edges out a little when it comes to brainstorming ideas and suggestions - It is FAST. probably the fastest of all frontier models (Opus 4.8, GPT 5.5 etc), which makes it a joy to build with, because I can stay in the flow - It has much improved visual/animation capabilities than Composer 2.5, it can code up animations (i wanted an explosion animation with particle effects) with much, much better visuals, animation movement and timing. This is a big leap and I was so happy to see this improvement. - The best part for me is that I can just use the same model from planning down to execution without switching to a lower cost model because the price point is cheaper than other frontier models. I'll be testing this model with more challenging tasks in the next few days but I think this is going to be my main driver for vibe coding for a while. Also, its nice to see Grok back in the race. 🙌

Danny Limanseta

1,417,825 次观看 • 1 个月前

Crimson Desert first impressions. The Open World is massive, it feels alive and it definitely holds up to my expectations when it comes to visuals. I know some reviewers have said the game takes up to 8 hours before it gets good but honestly I immediately fell in love with it and immediately started exploring. I found the puzzles and combat awesome to play with, once you get used to the controls which feel overwhelming at first, especially remembering all of them which can be a hassle first. The main protagonist Cliff hasn't clicked with me yet, right now I feel like he's just confused and there's not so much depth that he offers, I hope that will change as I progress through the story. The story itself and quests are quite interesting and I've actually had a good laugh in the beginning of the game when you have to help a couple struggling to clean the chimney. There are definitely some issues though, I feel like the starting stamina drains too quickly especially if you're using your wings to fly, if you run out of stamina while flying and fall into waters, Cliff will almost immediately drown because the Stamina bar is empty. I haven't encountered any bugs, crashes or stutters as of yet, however there are some ghosting issues when you enter buildings which can be quite distracting. Ray Regeneration on AMD GPUs tanks the performance so I just turned it off completely and instead I'm playing on Ultra Settings, which is a bummer because that tech looked very promising and made quite the difference when it came to visuals. Another weird issue that I had is trying to enter some doors or starting conversations with story character, the button to initiate the conversation wouldn't appear unless I went away and came back to a specific position before starting it. Some other issues include pop-in issues, camera movement and double NPCs with the same voice-lines if you greet them. Overall I think its a good start to a video-game that is quite massive in scale, there are still many things that I'll have to do and progress through before I give a conclusive opinion in this game.
1:19

Crimson Desert first impressions. The Open World is massive, it feels alive and it definitely holds up to my expectations when it comes to visuals. I know some reviewers have said the game takes up to 8 hours before it gets good but honestly I immediately fell in love with it and immediately started exploring. I found the puzzles and combat awesome to play with, once you get used to the controls which feel overwhelming at first, especially remembering all of them which can be a hassle first. The main protagonist Cliff hasn't clicked with me yet, right now I feel like he's just confused and there's not so much depth that he offers, I hope that will change as I progress through the story. The story itself and quests are quite interesting and I've actually had a good laugh in the beginning of the game when you have to help a couple struggling to clean the chimney. There are definitely some issues though, I feel like the starting stamina drains too quickly especially if you're using your wings to fly, if you run out of stamina while flying and fall into waters, Cliff will almost immediately drown because the Stamina bar is empty. I haven't encountered any bugs, crashes or stutters as of yet, however there are some ghosting issues when you enter buildings which can be quite distracting. Ray Regeneration on AMD GPUs tanks the performance so I just turned it off completely and instead I'm playing on Ultra Settings, which is a bummer because that tech looked very promising and made quite the difference when it came to visuals. Another weird issue that I had is trying to enter some doors or starting conversations with story character, the button to initiate the conversation wouldn't appear unless I went away and came back to a specific position before starting it. Some other issues include pop-in issues, camera movement and double NPCs with the same voice-lines if you greet them. Overall I think its a good start to a video-game that is quite massive in scale, there are still many things that I'll have to do and progress through before I give a conclusive opinion in this game.

NikTek

93,414 次观看 • 4 个月前

** Sega Genesis 3D engine update 8.5 ** A smaller update - Scrolling left or right of the sprite based background is implemented along with X camera shifting of the 3d plane. The Exodus emulator has been used with sprite boxing enabled so you can see the background sprites making up the object ( their outlines ) and how they move to tilt the image . The background is made up of 112 sprites (51 are multiplexed in that number as the Genesis is limited to 80 without mulitplexing eg basically re-using sprite hardware as the screen is being drawn ) . In a 6 x 17 sprite grid of 16x32 pixel high sprites. If the tilt affect was not neccessary or only 1/2 the angle of tilt effect was needed, I could get away with 1/2 the number of sprites and just used 32x32 sprites instead. I think the tilt effect adds a bit to movement however. This is very similar to how a Neo Geo would build its backgrounds up - in 16 pixel strips however its sprites are tall as the screen or more but the concept of making backgrounds up in 16 pixel wide strips is similar. The NG uses sprites to build any background layers required. Here on the Genesis the reason is rendering is much faster using both the 3d planes and using a total sprite background for this engine. Initially i had a lot of things breaking when I tried to move the camera in the X dimension much , as i'd optimised the vertex transform path heavily and once beyond a certain camera offset the X value was wrapping around causing a lot of breakage in the rendering. Thankfully solved that issue without marginal impact to cpu . It still needs work , perspectives are a bit wrong etc but it won't be hard to fix. Also found some rendering speeds ups, about 8% by optimising fully onscreen quads and optimising the clearing of the frame buffers more efficiently. Toni Gálvez - Megastyle - BG. has been hard at work on HUD elements and more 3d models so will have something to show for that soon. #SGDK #SegaMegadrive #SegaGenesis
0:28

** Sega Genesis 3D engine update 8.5 ** A smaller update - Scrolling left or right of the sprite based background is implemented along with X camera shifting of the 3d plane. The Exodus emulator has been used with sprite boxing enabled so you can see the background sprites making up the object ( their outlines ) and how they move to tilt the image . The background is made up of 112 sprites (51 are multiplexed in that number as the Genesis is limited to 80 without mulitplexing eg basically re-using sprite hardware as the screen is being drawn ) . In a 6 x 17 sprite grid of 16x32 pixel high sprites. If the tilt affect was not neccessary or only 1/2 the angle of tilt effect was needed, I could get away with 1/2 the number of sprites and just used 32x32 sprites instead. I think the tilt effect adds a bit to movement however. This is very similar to how a Neo Geo would build its backgrounds up - in 16 pixel strips however its sprites are tall as the screen or more but the concept of making backgrounds up in 16 pixel wide strips is similar. The NG uses sprites to build any background layers required. Here on the Genesis the reason is rendering is much faster using both the 3d planes and using a total sprite background for this engine. Initially i had a lot of things breaking when I tried to move the camera in the X dimension much , as i'd optimised the vertex transform path heavily and once beyond a certain camera offset the X value was wrapping around causing a lot of breakage in the rendering. Thankfully solved that issue without marginal impact to cpu . It still needs work , perspectives are a bit wrong etc but it won't be hard to fix. Also found some rendering speeds ups, about 8% by optimising fully onscreen quads and optimising the clearing of the frame buffers more efficiently. Toni Gálvez - Megastyle - BG. has been hard at work on HUD elements and more 3d models so will have something to show for that soon. #SGDK #SegaMegadrive #SegaGenesis

Shannon Birt

21,170 次观看 • 20 天前

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 次观看 • 4 个月前

I started using Blender through MCP about two weeks ago, and I quickly realized that you can build almost anything with AI. This model was created using Blender, Hunyuan3D, Gemini, and ChatGPT. Here’s how I did it: I opened Gemini, uploaded an image of the Gundam model, and asked it to generate a clean front-view image. I uploaded that front view to ChatGPT and asked it to generate two additional angles: a back view and a 45-degree front-left view. I went to: I signed up with my email and translated the page into English. Then I opened Image to 3D and selected the multi-image option. You’ll see a diagram of a whale from several angles. Upload each reference image in its corresponding position, such as front, 45-degree front-left, and back. I selected the 1.5M-face option. This produces a very high-poly model, but don’t worry, we’ll fix that next. Once the generation is complete, download the model as a GLB file. From the Hunyuan homepage, open 3D Studio using one of the dropdown menus. Select the topology or retopology tool and upload your GLB. I chose the High setting to preserve as much detail as possible. After a few seconds, the model was retopologized. It kept most of its visual detail while using far fewer polygons. The original head and rifle didn’t look very good, so I generated them separately. I returned to ChatGPT and created dedicated reference images for the Gundam’s head and rifle. I generated each part individually in Hunyuan at the 1.5M setting, then ran both through the same retopology process. Next came the textures. Open the texture section, select the multi-image option, and upload the same reference images according to the whale orientation indicators. However, instead of using the original clean textures, I asked ChatGPT to recreate them with wear, rust stains, scratches, and other surface damage. This gave the Gundam a much older and more authentic appearance. Once every part was textured, I imported everything into Blender. You can ask Codex through MCP to remove the original head and rifle, or you can do it manually. Select the main model and press Tab to enter Edit Mode. Press 3 to enable face selection, then press C to activate Circle Select. Paint over the faces belonging to the original helmet or rifle. You can press X to delete those faces or P to separate them into another object. Then position the newly generated, more detailed head and rifle in their place. I demonstrate this process in one of my older videos. And that’s it. You now have a very cool 3D Gundam model! Afterward, I created the cockpit, separated the model into movable sections, and rigged everything for use in my Three.js game. That process deserves its own tutorial, though. If anyone wants to see it, let me know. Or just ask your AI, I guess. They seem to know everything these days. xD
0:24

I started using Blender through MCP about two weeks ago, and I quickly realized that you can build almost anything with AI. This model was created using Blender, Hunyuan3D, Gemini, and ChatGPT. Here’s how I did it: I opened Gemini, uploaded an image of the Gundam model, and asked it to generate a clean front-view image. I uploaded that front view to ChatGPT and asked it to generate two additional angles: a back view and a 45-degree front-left view. I went to: I signed up with my email and translated the page into English. Then I opened Image to 3D and selected the multi-image option. You’ll see a diagram of a whale from several angles. Upload each reference image in its corresponding position, such as front, 45-degree front-left, and back. I selected the 1.5M-face option. This produces a very high-poly model, but don’t worry, we’ll fix that next. Once the generation is complete, download the model as a GLB file. From the Hunyuan homepage, open 3D Studio using one of the dropdown menus. Select the topology or retopology tool and upload your GLB. I chose the High setting to preserve as much detail as possible. After a few seconds, the model was retopologized. It kept most of its visual detail while using far fewer polygons. The original head and rifle didn’t look very good, so I generated them separately. I returned to ChatGPT and created dedicated reference images for the Gundam’s head and rifle. I generated each part individually in Hunyuan at the 1.5M setting, then ran both through the same retopology process. Next came the textures. Open the texture section, select the multi-image option, and upload the same reference images according to the whale orientation indicators. However, instead of using the original clean textures, I asked ChatGPT to recreate them with wear, rust stains, scratches, and other surface damage. This gave the Gundam a much older and more authentic appearance. Once every part was textured, I imported everything into Blender. You can ask Codex through MCP to remove the original head and rifle, or you can do it manually. Select the main model and press Tab to enter Edit Mode. Press 3 to enable face selection, then press C to activate Circle Select. Paint over the faces belonging to the original helmet or rifle. You can press X to delete those faces or P to separate them into another object. Then position the newly generated, more detailed head and rifle in their place. I demonstrate this process in one of my older videos. And that’s it. You now have a very cool 3D Gundam model! Afterward, I created the cockpit, separated the model into movable sections, and rigged everything for use in my Three.js game. That process deserves its own tutorial, though. If anyone wants to see it, let me know. Or just ask your AI, I guess. They seem to know everything these days. xD

Spectro

77,885 次观看 • 21 天前

Thank you to the Grammy Hall of Fame and to my friends at the Grammy Museum and the Ray Charles foundation for this incredible honor. This is without question one of the greatest honors of my career. It is both humbling or inspiring to receive this level or recognition for doing the creative work that a believe in most, the work that I was called to do within culture, the legacy that we have inherited from pioneers whose work in architecting sound expanded our musical universe while still honoring tradition and profoundly impacted humanity beyond just popularity or trends. As Ray Charles once said "I never wanted to be famous; I only wanted to be great". Being a HOF for The Ray Charles "Architect Of Sound" Award speaks directly to what I believe most about the power we have to shape sound in a way that inspires greatness, hope and allows us pathways to dignify each other. In reflecting on where his music came from Ray said "My music had roots which I'd dug up from my own childhood, musical roots buried in the darkest soil." From my early days as a child in the deep south I know exactly what he's talking about and how much it means to carry it forward. For this and more is why I dedicate this honor to my parents who were able to join me last night at the Grammy Hall Of Fame! I'll see y'all out there on tour soon very soon as we keep building bridges through sound ♥️
0:33

Thank you to the Grammy Hall of Fame and to my friends at the Grammy Museum and the Ray Charles foundation for this incredible honor. This is without question one of the greatest honors of my career. It is both humbling or inspiring to receive this level or recognition for doing the creative work that a believe in most, the work that I was called to do within culture, the legacy that we have inherited from pioneers whose work in architecting sound expanded our musical universe while still honoring tradition and profoundly impacted humanity beyond just popularity or trends. As Ray Charles once said "I never wanted to be famous; I only wanted to be great". Being a HOF for The Ray Charles "Architect Of Sound" Award speaks directly to what I believe most about the power we have to shape sound in a way that inspires greatness, hope and allows us pathways to dignify each other. In reflecting on where his music came from Ray said "My music had roots which I'd dug up from my own childhood, musical roots buried in the darkest soil." From my early days as a child in the deep south I know exactly what he's talking about and how much it means to carry it forward. For this and more is why I dedicate this honor to my parents who were able to join me last night at the Grammy Hall Of Fame! I'll see y'all out there on tour soon very soon as we keep building bridges through sound ♥️

jon batiste

16,613 次观看 • 1 年前

The sense of presence in VR is something amazing. And it is what convinces me that sooner or later, VR will succeed. VR is now in one of its down moments. That's why, in these harsh days, I wanted to get back to feeling what made me fall in love with this technology: presence and immersion. I took some very good-looking PCVR experiences, like Half-Life: Alyx, or AirCar, and tried them at the maximum resolution possible on my Dell Pro Max T2 Tower, featuring an #NVIDIA RTX 6000 graphics card. Until a few months ago, I was using my old laptop, which started to show throttling issues, so I was used to lowering the render resolution, while this time, I was moving the slider up and up. The results have been astonishing: even a demo like AirCar made me in awe again, and Half-Life: Alyx was as immersive as I have ever tried it. As much as I love standalone VR, because I think it helped a lot in democratizing the technology, the WOW sensation that you can try on PCVR today is still unbeatable. Probably a good compromise between the two can be cloud rendering, but we still have to wait for it to become a reality. The sense of being somewhere else is a wonderful sensation, and everyone I demoed VR to all these years has been amazed by it, too. And every day, something makes me feel "there" (like today), I remember why I love this technology and why one day it will have a higher adoption. Sure, there are a lot of problems to solve, but I'm convinced one day it will happen. When? Well, it is always 5 to 10 years, every year... #VirtualReality #VR #technology [Disclaimer: I mentioned the PC model because I'm a #DellProPrecision ambassador, and I have been given the PC to do tests and experiments and share my results. There is no monetary compensation or sales affiliation related to this post]
0:29

The sense of presence in VR is something amazing. And it is what convinces me that sooner or later, VR will succeed. VR is now in one of its down moments. That's why, in these harsh days, I wanted to get back to feeling what made me fall in love with this technology: presence and immersion. I took some very good-looking PCVR experiences, like Half-Life: Alyx, or AirCar, and tried them at the maximum resolution possible on my Dell Pro Max T2 Tower, featuring an #NVIDIA RTX 6000 graphics card. Until a few months ago, I was using my old laptop, which started to show throttling issues, so I was used to lowering the render resolution, while this time, I was moving the slider up and up. The results have been astonishing: even a demo like AirCar made me in awe again, and Half-Life: Alyx was as immersive as I have ever tried it. As much as I love standalone VR, because I think it helped a lot in democratizing the technology, the WOW sensation that you can try on PCVR today is still unbeatable. Probably a good compromise between the two can be cloud rendering, but we still have to wait for it to become a reality. The sense of being somewhere else is a wonderful sensation, and everyone I demoed VR to all these years has been amazed by it, too. And every day, something makes me feel "there" (like today), I remember why I love this technology and why one day it will have a higher adoption. Sure, there are a lot of problems to solve, but I'm convinced one day it will happen. When? Well, it is always 5 to 10 years, every year... #VirtualReality #VR #technology [Disclaimer: I mentioned the PC model because I'm a #DellProPrecision ambassador, and I have been given the PC to do tests and experiments and share my results. There is no monetary compensation or sales affiliation related to this post]

TonyVT SkarredGhost

28,931 次观看 • 4 个月前

*THE FOUNDATION* This is the pre-order launch for The Foundation course and associated community. The Foundation is a 12+ hour structured course giving you everything you need to establish the right framework for trading crypto. I cover a range of topics: - Introduction to the space - What Tools you need - Applying Technical Analysis - Identifying what type of trader you are - How to build a system - How to grow a portfolio - Risk Management in reality - When to be aggressive - Attack vs Defence - PSYCHOLOGY + Much more. If you're someone who wants to join in trading in this space, or someone who has been here a while but doesn't have the correct foundations established, I hope this product will satisfy your learning. I've written this as a crypto trader, someone who speaks the language and understands the markets. Not as some babypips tradfi crossover with boring references and examples. There are multiple tiers available and each come with different perks. I'll let you browse those. For now this is a pre-order and pricing is discounted on what it will be at launch which is scheduled for the first week of January 2024. This is a one-time payment course and does not have any subscription or recurring payment. YOU WILL NOT BE CHARGED UNTIL THE COURSE IS LIVE IN JANUARY. I REPEAT, YOU WILL NOT BE CHARGED. This pre-order system is to give me a chance to gauge interest, to ensure we have some members in the Discord when we go live and to allow me to speak about the course over the next month while having a place to link interested people. Thanks for the support during the creation of this to those guys who helped contribute ideas, proof read, set up the topics and to give me the boost to putting this out there (in January) Thank you to Bold for doing all of the graphics work for this as well. I've attached a video where I speak a little more about everything. If you have any questions please drop them here and I'll do my best to answer as many of them as possible. LINK TO PREORDER:
11:32

*THE FOUNDATION* This is the pre-order launch for The Foundation course and associated community. The Foundation is a 12+ hour structured course giving you everything you need to establish the right framework for trading crypto. I cover a range of topics: - Introduction to the space - What Tools you need - Applying Technical Analysis - Identifying what type of trader you are - How to build a system - How to grow a portfolio - Risk Management in reality - When to be aggressive - Attack vs Defence - PSYCHOLOGY + Much more. If you're someone who wants to join in trading in this space, or someone who has been here a while but doesn't have the correct foundations established, I hope this product will satisfy your learning. I've written this as a crypto trader, someone who speaks the language and understands the markets. Not as some babypips tradfi crossover with boring references and examples. There are multiple tiers available and each come with different perks. I'll let you browse those. For now this is a pre-order and pricing is discounted on what it will be at launch which is scheduled for the first week of January 2024. This is a one-time payment course and does not have any subscription or recurring payment. YOU WILL NOT BE CHARGED UNTIL THE COURSE IS LIVE IN JANUARY. I REPEAT, YOU WILL NOT BE CHARGED. This pre-order system is to give me a chance to gauge interest, to ensure we have some members in the Discord when we go live and to allow me to speak about the course over the next month while having a place to link interested people. Thanks for the support during the creation of this to those guys who helped contribute ideas, proof read, set up the topics and to give me the boost to putting this out there (in January) Thank you to Bold for doing all of the graphics work for this as well. I've attached a video where I speak a little more about everything. If you have any questions please drop them here and I'll do my best to answer as many of them as possible. LINK TO PREORDER:

Cold Blooded Shiller

249,459 次观看 • 2 年前

p.s: a long read but worth. love it every time taynew talk about their relationship dynamic, can literally sit all day long hearing the whole thing ♡ 💬 Did Hin told Te beforehand about cheek-to-cheek or Tay just got attacked by Hin? 🐳 No discussion before, Hin just did it. You guys must be know my personality and Hin’s personality well already. I’m the type who— how do I say it, I have to think before doing. Here’s the thing, I just took Enneagram course. Before, it was just self-taught and I knew my type, but after meeting this guru and got to dive in deeply, turns out I’m actually the type I never thought of before. As well as New. These Enneagram types are truly something we should study super deeply because it can shift depends on wings and arrows point that show in stress or relaxed situation, but finding our real true type is so difficult to find. I got Type 5, which the knowledge type, I’d feel less secure when I think my knowledge is not enough. I’ve always thought I was Type 9, the peacemaker, turns out I’m Type 5. So what I’m trying to say is, we have completely different personalities, New is the jumper one. He doesn’t like doing lot of practice, you know, doing the same thing over and over. He’s that, “Don’t put too much thought into it, just do it.” which actually can be a good side of him at some point. He won’t think much and let his instinct works. I’d say that both of our personalities got its own good and bad side. New can use his intuition, more realistic, you know, he can be a thing the way he wanted it to be—I can’t find the right words. But that’s not how I am, I tend to use my head too much, which actually can be an obstacle for my profession at some points. I won’t be able to jump when at one point I have to jump, because I’m too afraid of my unpreparedness and feel less secured. My head needs it to be structured about what to do for me to have a courage to do it. Instead, New will be like, “Like this and this, ok let’s do it.” As I said, these two personalities has its own good and bad side to be working in this industry. Thus, in growing up we have to adapt and pick each other good side to fulfill what we lack of. I have to learn how to jump, New has to learn how to be more structured and secured. I have to learn to think less, because after thinking much, in the end it never really give good results anyway. Every single time, I always do it better during practice than the real performance because I think too much. This is such a really bad side for someone who uses their head too much. For New, he always do it better in the real performance than practice, every single time. But “Faak Jai” is maybe the first performance I think I did it (better on real day). At that time, I tried to think the way New did, to focus on the present, and I’m proud of myself to can actually do it. It’s probably my first time ever since working in this industry to actually feel that kind of feeling. So about the cheek-to-cheek, yeah I think this is the perfect dynamics of TayNew, how I’m the overthinker one, while Hin always doing things not under control. Like, it’s a mix of well-prepared and spontaneity in both of us together. For example, if it’s New alone, it won’t look that smooth and look that well-prepared. On the other hand, if it’s me alone, there won’t gonna be such a magic moment that comes spontaneously. New fill things up and make things more perfect. If it were two people with the same personality like me, it’d be too rigid. This is the good side of having a work partner with different personality as us.
5:51

p.s: a long read but worth. love it every time taynew talk about their relationship dynamic, can literally sit all day long hearing the whole thing ♡ 💬 Did Hin told Te beforehand about cheek-to-cheek or Tay just got attacked by Hin? 🐳 No discussion before, Hin just did it. You guys must be know my personality and Hin’s personality well already. I’m the type who— how do I say it, I have to think before doing. Here’s the thing, I just took Enneagram course. Before, it was just self-taught and I knew my type, but after meeting this guru and got to dive in deeply, turns out I’m actually the type I never thought of before. As well as New. These Enneagram types are truly something we should study super deeply because it can shift depends on wings and arrows point that show in stress or relaxed situation, but finding our real true type is so difficult to find. I got Type 5, which the knowledge type, I’d feel less secure when I think my knowledge is not enough. I’ve always thought I was Type 9, the peacemaker, turns out I’m Type 5. So what I’m trying to say is, we have completely different personalities, New is the jumper one. He doesn’t like doing lot of practice, you know, doing the same thing over and over. He’s that, “Don’t put too much thought into it, just do it.” which actually can be a good side of him at some point. He won’t think much and let his instinct works. I’d say that both of our personalities got its own good and bad side. New can use his intuition, more realistic, you know, he can be a thing the way he wanted it to be—I can’t find the right words. But that’s not how I am, I tend to use my head too much, which actually can be an obstacle for my profession at some points. I won’t be able to jump when at one point I have to jump, because I’m too afraid of my unpreparedness and feel less secured. My head needs it to be structured about what to do for me to have a courage to do it. Instead, New will be like, “Like this and this, ok let’s do it.” As I said, these two personalities has its own good and bad side to be working in this industry. Thus, in growing up we have to adapt and pick each other good side to fulfill what we lack of. I have to learn how to jump, New has to learn how to be more structured and secured. I have to learn to think less, because after thinking much, in the end it never really give good results anyway. Every single time, I always do it better during practice than the real performance because I think too much. This is such a really bad side for someone who uses their head too much. For New, he always do it better in the real performance than practice, every single time. But “Faak Jai” is maybe the first performance I think I did it (better on real day). At that time, I tried to think the way New did, to focus on the present, and I’m proud of myself to can actually do it. It’s probably my first time ever since working in this industry to actually feel that kind of feeling. So about the cheek-to-cheek, yeah I think this is the perfect dynamics of TayNew, how I’m the overthinker one, while Hin always doing things not under control. Like, it’s a mix of well-prepared and spontaneity in both of us together. For example, if it’s New alone, it won’t look that smooth and look that well-prepared. On the other hand, if it’s me alone, there won’t gonna be such a magic moment that comes spontaneously. New fill things up and make things more perfect. If it were two people with the same personality like me, it’d be too rigid. This is the good side of having a work partner with different personality as us.

deeコ

22,979 次观看 • 5 个月前

This is probably the most complex workflow I’ve ever built, only with open-source tools. It took my 4 days. It takes four inputs: author, title, and style; and generates a full visual animated story in one click in ComfyUI . I worked on it for four days. There are still some bugs, but here’s the first preview. Here’s a quick breakdown: - The four inputs are sent to LLMs with precise instructions to generate: first, prompts for images and image modifications; second, prompts for animations; third, prompts for generating music. - All voices are generated from the text and timed precisely, as they determine the length of each animation segment. - The first image and video are generated to serve as the title, but also as the guide for all other images created for the video. - Titles and subtitles are also added automatically in Comfy. - I also developed a lot of custom nodes for minor frame calculations, mostly to match audio and video. - The full system is a large loop that, for each line of text, generates an image and then a video from that image. The loop was the hardest part to build in this workflow, so it can process either a 20-second video or a 2-minute video with the same input. - There are multiple combinations of LLMs that try to understand the text in the best way to provide the best prompts for images and video. - The final video is assembled entirely within ComfyUI. - The music is generated based on the LLM output and matches the exact timing of the full animation. - Done! For reference, this workflow uses a lot of models and only works on an RTX 6000 Pro with plenty of RAM. My goal is not to replace humans, as I’ll try to explain later, this workflow is highly controlled and can be adapted or reworked at any point by real artists! My aim was to create a tool that can animate text in one go, allowing the AI some freedom while keeping a strict flow. I don’t know yet how I’ll share this workflow with people, I still need to polish it properly, but maybe through Patreon. Anyway, I hope you enjoy my research, and let’s always keep pushing further! :)
0:55

This is probably the most complex workflow I’ve ever built, only with open-source tools. It took my 4 days. It takes four inputs: author, title, and style; and generates a full visual animated story in one click in ComfyUI . I worked on it for four days. There are still some bugs, but here’s the first preview. Here’s a quick breakdown: - The four inputs are sent to LLMs with precise instructions to generate: first, prompts for images and image modifications; second, prompts for animations; third, prompts for generating music. - All voices are generated from the text and timed precisely, as they determine the length of each animation segment. - The first image and video are generated to serve as the title, but also as the guide for all other images created for the video. - Titles and subtitles are also added automatically in Comfy. - I also developed a lot of custom nodes for minor frame calculations, mostly to match audio and video. - The full system is a large loop that, for each line of text, generates an image and then a video from that image. The loop was the hardest part to build in this workflow, so it can process either a 20-second video or a 2-minute video with the same input. - There are multiple combinations of LLMs that try to understand the text in the best way to provide the best prompts for images and video. - The final video is assembled entirely within ComfyUI. - The music is generated based on the LLM output and matches the exact timing of the full animation. - Done! For reference, this workflow uses a lot of models and only works on an RTX 6000 Pro with plenty of RAM. My goal is not to replace humans, as I’ll try to explain later, this workflow is highly controlled and can be adapted or reworked at any point by real artists! My aim was to create a tool that can animate text in one go, allowing the AI some freedom while keeping a strict flow. I don’t know yet how I’ll share this workflow with people, I still need to polish it properly, but maybe through Patreon. Anyway, I hope you enjoy my research, and let’s always keep pushing further! :)

Lovis Odin

58,841 次观看 • 10 个月前

yall think black hat sauce is methods wtf do you think is the base for those methods? It's making them believe and feel false realities > If you want real black hat alpha, this is it. YOU WANT your VSLs or marketing campaigns to have a high CVR, AOV & retention (mrr in the backend) black hat methods get to these means in many ways like (fake authority using ai for clebs, back end mrr, fake promises, etc) >> however you can overcome the need for all of this while getting the same end results by just curating the reality of the VSL and experience in general to fit what those methods would have done. like for example - how would we be able to invoke a first time experience ecstasy of emotion in a vsl? > not only will this make the experience of the ad unique but also give you a platform to create a real authority figure that matches the belief of a cleb. from my experience I've found the way to do this is visually, auditorily, and ofc with your creatives. As yall know for my VSLs I try to take very unique different angles, with very specific visuals that back it up. and if you have trouble with this, you're literally in the perfect time in the world. You can use sora 2, put in your theme & ideas and ask it to be creative, include 100 different shots/scenes (add a aesthetic source image to make the generations 100x better) and boom. You have so many different frames and angles to get inspired by. > Also with MRR, you know one neurochemical that boosts the fuck out of CVR & retention? makes you trust more in a offer, promise, and changes your consciousness in ways that subsequently makes you spend more? its oxytocin. best example that I always use. the Charity water VSL (search up on yt). $700m off of MRR how? because of how touching and deep it hit. those types of narratives and experiences is what secretes oxytocin. And that's one legit real way you can boost your mrr and keep it long term if your angle is tied in a way to keep eliciting that reaction. It can be for any offer or product, happy or sad (best to stick with happy unless for a charity vsl like this one, or if yk what you're doing). > However remember one chemical change doesn't mean everything. There are tons of different states of mind you can put someone in, but they won't led to the results you want unless you include Specifics (on the offer, promises, and social proofs/belief elements) A big idea & unique angle and a proposition that ties in the creative --> to a reason showing that they NEED to buy this offer for whatever reason. >>> these changes and efforts we go to make a VSL work, doesn't pull it's weight & potential if we don't see it through a lens of economic game theory. over the last 28 years or so "several lines of experimentation have discovered that our goal- directed behaviors can be under “unconscious control” (Custers & Aarts, 2010)" The unconscious mind is the foundation for all your customers actions, they act because the deeper sections of their brains pick up a cue run it through memory, and pre biologically embedded risk/reward and elimination scenarios to see if this new stimuli is similar/relevant to past stimuli that has aided in spreading it's genes in the past (i.e. been useful to the past generations which led to this trait being past on over and over again) For your purposes, the way to use this to your advantage and to activate it in a positive sense so it guides your customer to a conversion is to implement visual & auditory cues in your VSL that mirror the goal and desire/outcome they so deeply desire. this can be done by the language you use (copy), visuals/b roll etc. this will overlap with prefrontal–striatal loops as conscious intent ≈ 72 % making your customer already feel and get a grasp of their desires This is where belief and proofs come in, they all go hand in hand and strengthen the end goal (to buy). _____ also another note for the unique angle, drop off of CVRs happens also when a customer gets sight of a familiar stimulus in a VSL/offer (could be anything) even if they don't think of it consciously, the brain processes everything happening which is directed to be a data point for thought, through a memory check and relation test. If in the past, you had a bad experience with that stimulus, or something similar. The brain will count the offer as invalid with the outcome of lowering belief and seeing the future outcome as achievable. _______ more data on this inside also one of the biggest needle movers is tension in VSLs, include that in everything. 🥂
1:10

yall think black hat sauce is methods wtf do you think is the base for those methods? It's making them believe and feel false realities > If you want real black hat alpha, this is it. YOU WANT your VSLs or marketing campaigns to have a high CVR, AOV & retention (mrr in the backend) black hat methods get to these means in many ways like (fake authority using ai for clebs, back end mrr, fake promises, etc) >> however you can overcome the need for all of this while getting the same end results by just curating the reality of the VSL and experience in general to fit what those methods would have done. like for example - how would we be able to invoke a first time experience ecstasy of emotion in a vsl? > not only will this make the experience of the ad unique but also give you a platform to create a real authority figure that matches the belief of a cleb. from my experience I've found the way to do this is visually, auditorily, and ofc with your creatives. As yall know for my VSLs I try to take very unique different angles, with very specific visuals that back it up. and if you have trouble with this, you're literally in the perfect time in the world. You can use sora 2, put in your theme & ideas and ask it to be creative, include 100 different shots/scenes (add a aesthetic source image to make the generations 100x better) and boom. You have so many different frames and angles to get inspired by. > Also with MRR, you know one neurochemical that boosts the fuck out of CVR & retention? makes you trust more in a offer, promise, and changes your consciousness in ways that subsequently makes you spend more? its oxytocin. best example that I always use. the Charity water VSL (search up on yt). $700m off of MRR how? because of how touching and deep it hit. those types of narratives and experiences is what secretes oxytocin. And that's one legit real way you can boost your mrr and keep it long term if your angle is tied in a way to keep eliciting that reaction. It can be for any offer or product, happy or sad (best to stick with happy unless for a charity vsl like this one, or if yk what you're doing). > However remember one chemical change doesn't mean everything. There are tons of different states of mind you can put someone in, but they won't led to the results you want unless you include Specifics (on the offer, promises, and social proofs/belief elements) A big idea & unique angle and a proposition that ties in the creative --> to a reason showing that they NEED to buy this offer for whatever reason. >>> these changes and efforts we go to make a VSL work, doesn't pull it's weight & potential if we don't see it through a lens of economic game theory. over the last 28 years or so "several lines of experimentation have discovered that our goal- directed behaviors can be under “unconscious control” (Custers & Aarts, 2010)" The unconscious mind is the foundation for all your customers actions, they act because the deeper sections of their brains pick up a cue run it through memory, and pre biologically embedded risk/reward and elimination scenarios to see if this new stimuli is similar/relevant to past stimuli that has aided in spreading it's genes in the past (i.e. been useful to the past generations which led to this trait being past on over and over again) For your purposes, the way to use this to your advantage and to activate it in a positive sense so it guides your customer to a conversion is to implement visual & auditory cues in your VSL that mirror the goal and desire/outcome they so deeply desire. this can be done by the language you use (copy), visuals/b roll etc. this will overlap with prefrontal–striatal loops as conscious intent ≈ 72 % making your customer already feel and get a grasp of their desires This is where belief and proofs come in, they all go hand in hand and strengthen the end goal (to buy). _____ also another note for the unique angle, drop off of CVRs happens also when a customer gets sight of a familiar stimulus in a VSL/offer (could be anything) even if they don't think of it consciously, the brain processes everything happening which is directed to be a data point for thought, through a memory check and relation test. If in the past, you had a bad experience with that stimulus, or something similar. The brain will count the offer as invalid with the outcome of lowering belief and seeing the future outcome as achievable. _______ more data on this inside also one of the biggest needle movers is tension in VSLs, include that in everything. 🥂

Krma

37,202 次观看 • 10 个月前