Video yükleniyor...

Video Yüklenemedi

Bu video yüklenirken bir sorun oluştu. Bu geçici bir ağ sorunundan kaynaklanıyor olabilir veya video kullanılamıyor olabilir.

Ana Sayfaya Dön

90 DEGREE TURN WALKTHROUGH~ PART 1: Separation 🧵 I'm splitting these into two three parts; Separation, X Angle and Y Angle. To more clearly explain, i'll probably make a video for part 2 + 3 so it might take longer 🙏 (1/4) Model artist: @/cyannida VTuber: @/iijensii #Live2D

🥐 Navira

2,482 subscribers

27,037 görüntüleme • 2 yıl önce •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

0 Yorum

Yorum bulunmuyor

Orijinal gönderinin yorumları burada görünecek

Benzer Videolar

I've been going down the WarpFusion rabbit-hole. Outside of Kaiber, which makes a completely different style of video, I think WF is the best video-to-video model out there. But it appears complicated on the surface. So I'm learning it so I can turn around and teach what I learn. For this one, I used the same snapping video that I used in the past. This took about 2-hours and $20 to make. LOL. But I'll get all these various settings dialed in and then make a YouTube video about how to use it. I'm nowhere near Mrboofy level yet though. ;)

I've been going down the WarpFusion rabbit-hole. Outside of Kaiber, which makes a completely different style of video, I think WF is the best video-to-video model out there. But it appears complicated on the surface. So I'm learning it so I can turn around and teach what I learn. For this one, I used the same snapping video that I used in the past. This took about 2-hours and $20 to make. LOL. But I'll get all these various settings dialed in and then make a YouTube video about how to use it. I'm nowhere near Mrboofy level yet though. ;)

Matt Wolfe

131,360 görüntüleme • 3 yıl önce

Ok so I was actually working on this so my wife would let me keep Linux on this 2-in-1 tablet PC. Completely vibe coded but it borrows the same philosophy where SUPER + SHIFT + Key is for applications while SUPER + CTRL + Key is for system stuff (btop, bluetooth, etc) - i.e., separation of concerns. Here it's 1 finger for scrolling within the app, 2 fingers for rearranging the windows, 3 fingers for app-level manipulation like fullscreen, dismiss, etc. 4 fingers for workspaces. Same "just sit down and learn it bitch" UX but actually quite good and better than iOS once you get used to it. Just a first pass though - I should really join the Discord and see if someone else is working on this. I'm not sure if this should land in Hyprland or as an Omarchy plugin. And no I'm not trying to make a political statement, that's just an awesome mouse pad. Recorded this video earlier to show my wife lol.

Ok so I was actually working on this so my wife would let me keep Linux on this 2-in-1 tablet PC. Completely vibe coded but it borrows the same philosophy where SUPER + SHIFT + Key is for applications while SUPER + CTRL + Key is for system stuff (btop, bluetooth, etc) - i.e., separation of concerns. Here it's 1 finger for scrolling within the app, 2 fingers for rearranging the windows, 3 fingers for app-level manipulation like fullscreen, dismiss, etc. 4 fingers for workspaces. Same "just sit down and learn it bitch" UX but actually quite good and better than iOS once you get used to it. Just a first pass though - I should really join the Discord and see if someone else is working on this. I'm not sure if this should land in Hyprland or as an Omarchy plugin. And no I'm not trying to make a political statement, that's just an awesome mouse pad. Recorded this video earlier to show my wife lol.

gabe.algo

13,992 görüntüleme • 1 ay önce

Let me explain the agent loop, simple It's the core of every agentic system, and the part most people overcomplicate It's just this: 1. Send messages to the model 2. Model responds, maybe calls a tool 3. You run the tool 4. Append the result back to messages 5. Repeat until stop_reason is end_turn Step 4 is the whole thing, the write-back is what makes it an agent The model has to see what actually happened before it decides the next move That's the entire loop... understand this cold before you reach for a framework

Let me explain the agent loop, simple It's the core of every agentic system, and the part most people overcomplicate It's just this: 1. Send messages to the model 2. Model responds, maybe calls a tool 3. You run the tool 4. Append the result back to messages 5. Repeat until stop_reason is end_turn Step 4 is the whole thing, the write-back is what makes it an agent The model has to see what actually happened before it decides the next move That's the entire loop... understand this cold before you reach for a framework

Daniel San

12,514 görüntüleme • 3 ay önce

🚨BROKEN PASS PART 2🚨 GK->CB->CB———————>ST->Goal✅ 1) From goal kick pass to CB 2) Pass it to your other CB 3) Do an R1 Square pass (RB X on Xbox) with full power first time and aim the pass in behind the opponents CBs. 4) Go and score✅ Drop a ❤️ and follow for more!🤝

🚨BROKEN PASS PART 2🚨 GK->CB->CB———————>ST->Goal✅ 1) From goal kick pass to CB 2) Pass it to your other CB 3) Do an R1 Square pass (RB X on Xbox) with full power first time and aim the pass in behind the opponents CBs. 4) Go and score✅ Drop a ❤️ and follow for more!🤝

TS7Boosting

420,782 görüntüleme • 1 yıl önce

We got early access to the Gemini Omni API Google is calling this model "Nano Banana for video" 3 things we built with it👇 1. Landscaping proposal from customer video. Customer submits a video of the current lot. Hyperagent designs and renders the transformation. Perfect realism, no surreal changes to the surroundings. 2. Animated professor who explains your dashboards. Hyperagent runs analysis on a business question, then generates an explainer video to walkthrough the findings. 3. 8-bit morning briefing. Hyperagent builds morning briefings based on calendar, email/chat, and market intel. Then generates a sidescrolling platformer video showing the goals you'll clear today. Our take: > Video has been a vastly underused input for agents. This is the first model to make video directly malleable to our agents. > Get more imaginative with your outputs. How could a video artifact make the work more memorable or playful? coming soon to Hyperagent

We got early access to the Gemini Omni API Google is calling this model "Nano Banana for video" 3 things we built with it👇 1. Landscaping proposal from customer video. Customer submits a video of the current lot. Hyperagent designs and renders the transformation. Perfect realism, no surreal changes to the surroundings. 2. Animated professor who explains your dashboards. Hyperagent runs analysis on a business question, then generates an explainer video to walkthrough the findings. 3. 8-bit morning briefing. Hyperagent builds morning briefings based on calendar, email/chat, and market intel. Then generates a sidescrolling platformer video showing the goals you'll clear today. Our take: > Video has been a vastly underused input for agents. This is the first model to make video directly malleable to our agents. > Get more imaginative with your outputs. How could a video artifact make the work more memorable or playful? coming soon to Hyperagent

Hyperagent

325,111 görüntüleme • 2 ay önce

AI video is moving from one-off experiments to repeatable production workflows. Dreamina Seedance 2.5 is coming soon to the Dreamina platform. For creative and marketing teams, the upcoming model will bring: 1. Up to 50 multimodal references Combine images, videos, audio, and other creative directions in one generation. 2. Up to 30 seconds of continuous video Create longer scenes with more room for product stories and brand narratives. 3. White-model and green-screen references Improve control over movement, composition, and visual direction. 4. Multilingual creation Adapt content for more global markets. 5. Precise local editing Refine specific parts without recreating the entire video. The result: a more flexible path from creative brief to finished content. 👉 #dreamina #dreaminapartner #seedance #dreaminaseedance25

codemarch

78,823 görüntüleme • 1 ay önce

a🧵on how to do the movable crater tech, You will learn this step by step, It should only take a couple of minutes to do it so lock in, Simple Overview: 1) Draw a black texture that represents a crack (use lasso or draw then fill tool) 2) Use a png to svg converter to make it into svg (you MUST make the crack black!) 3) Make the mesh of the crater 4) Export it as fbx and Import it in Roblox Studio 5) Create a viewport put the thing inside play with some lighting,material of crater n ur done 6) Make another viewport and make it so that it duplicates the character of the player every frame and puts in the viewport so that you can see it to be above the crater viewport Now for the detailed tutorial:

a🧵on how to do the movable crater tech, You will learn this step by step, It should only take a couple of minutes to do it so lock in, Simple Overview: 1) Draw a black texture that represents a crack (use lasso or draw then fill tool) 2) Use a png to svg converter to make it into svg (you MUST make the crack black!) 3) Make the mesh of the crater 4) Export it as fbx and Import it in Roblox Studio 5) Create a viewport put the thing inside play with some lighting,material of crater n ur done 6) Make another viewport and make it so that it duplicates the character of the player every frame and puts in the viewport so that you can see it to be above the crater viewport Now for the detailed tutorial:

QwinkleTee

40,103 görüntüleme • 1 yıl önce

Some personal/professional news: I'm launching "When the Facts Change - economics and politics in a fast-changing world". Click on the link in my X biography to read my first post. I'll obviously continue to write my weekly "Economics Agenda" column for the Telegraph, and co-present the "Planet Normal" podcast each week with the brilliant Allison Pearson I've been encouraged by lots of people, not least on X, to do more writing and broadcasting. So here goes .... "When the Facts Change" will initially be limited to written posts. But, as I find my feet, I'll add audio and video content too. So please check out my launch post via the link in my X biog and feel free to share this news. 🧵 1/2

Some personal/professional news: I'm launching "When the Facts Change - economics and politics in a fast-changing world". Click on the link in my X biography to read my first post. I'll obviously continue to write my weekly "Economics Agenda" column for the Telegraph, and co-present the "Planet Normal" podcast each week with the brilliant Allison Pearson I've been encouraged by lots of people, not least on X, to do more writing and broadcasting. So here goes .... "When the Facts Change" will initially be limited to written posts. But, as I find my feet, I'll add audio and video content too. So please check out my launch post via the link in my X biog and feel free to share this news. 🧵 1/2

Liam Halligan

416,441 görüntüleme • 1 yıl önce

GPT-4o static ads that ACTUALLY convert. I spent 7+ hrs on this 13 min video.👇 Get it now 1. Like + Comment GPT Ads 2. Connect with Aniruddha Mishra (Ani) 3. Repost for instant access Why? Because ChatGPT-generated ads are outperforming traditional creative. Here’s what you’ll find inside the video: 1. The exact research process I follow 2. The prompts I used (yes, copy-paste ready) 3. The frameworks that consistently drive results 4. The mistakes most people make - and how to avoid them This isn’t a fluff tutorial. It’s the exact process that’s working right now. Want better performing ads? This walkthrough might change the game for you. P.S. The video’s only 13 minutes. But it took me hours to make sure every minute was worth it.

GPT-4o static ads that ACTUALLY convert. I spent 7+ hrs on this 13 min video.👇 Get it now 1. Like + Comment GPT Ads 2. Connect with Aniruddha Mishra (Ani) 3. Repost for instant access Why? Because ChatGPT-generated ads are outperforming traditional creative. Here’s what you’ll find inside the video: 1. The exact research process I follow 2. The prompts I used (yes, copy-paste ready) 3. The frameworks that consistently drive results 4. The mistakes most people make - and how to avoid them This isn’t a fluff tutorial. It’s the exact process that’s working right now. Want better performing ads? This walkthrough might change the game for you. P.S. The video’s only 13 minutes. But it took me hours to make sure every minute was worth it.

Aniruddha Mishra (Ani)

44,465 görüntüleme • 1 yıl önce

Late Night @NotebookLM release notes from a busy week! 1. Slide Decks 🎉 - the freedom it gives you to turn anything into a story is incredible. Probably the first Nano Banana Pro fully dependent product. People are exploring fonts, styles, tips & tricks, but most of all stoke. so cool to see! 2. Infographics 🎉- capture the true essence of your sources in a creative but informative single image. You can use the Custom prompt to also make amazing Worksheets to accompany a lesson! Tobi talked about it. Maybe we should make question and answer sheets a clear option 3. Custom Style prompting for Visual Overviews - direct access to the model... 4. Thinking UX! this one was a while coming but we're gonna roll out a mvp and get moving (hoho). More informative soon. 5. Longer custom personas. You can now go up to 5k chars instead of the previous measly 500.... If you need more, LMK. 6. a bit "bold", but the "create notebook +" button at the top of every notebook. We'll probably collapse this into a smaller affordance, but wanted to get a quick workflow enhancer in there for people that don't know how to get to the homescreen. We'll do more on workflows. 7. Shout out to the TPUs which are definitely melting, and thank you all for the enthusiasm this week! More soon!

Late Night @NotebookLM release notes from a busy week! 1. Slide Decks 🎉 - the freedom it gives you to turn anything into a story is incredible. Probably the first Nano Banana Pro fully dependent product. People are exploring fonts, styles, tips & tricks, but most of all stoke. so cool to see! 2. Infographics 🎉- capture the true essence of your sources in a creative but informative single image. You can use the Custom prompt to also make amazing Worksheets to accompany a lesson! Tobi talked about it. Maybe we should make question and answer sheets a clear option 3. Custom Style prompting for Visual Overviews - direct access to the model... 4. Thinking UX! this one was a while coming but we're gonna roll out a mvp and get moving (hoho). More informative soon. 5. Longer custom personas. You can now go up to 5k chars instead of the previous measly 500.... If you need more, LMK. 6. a bit "bold", but the "create notebook +" button at the top of every notebook. We'll probably collapse this into a smaller affordance, but wanted to get a quick workflow enhancer in there for people that don't know how to get to the homescreen. We'll do more on workflows. 7. Shout out to the TPUs which are definitely melting, and thank you all for the enthusiasm this week! More soon!

Simon

46,847 görüntüleme • 9 ay önce

Exploring diff visuals with Gen2. I'm amazed at how it takes a single block image to build neon streets, structures, and entire cityscapes. Anybody else toying with AI tonight⁉️ AI Art Workflow: 1. Crafted starting image in #Midjourney 2. Generated a 4-sec video with #Gen2 (no text prompt) 3. Extended first 4 secs to 18 secs 4. Repeated steps 2-3 twice, each time using the final frame from the previous 18-sec video to start the next 18-secs run 5. Merged all three 18-sec videos in #FinalCut Pro 6. Adjusted speed for fluidity 7. Final version published here is a 54-sec journey distilled into a 16-sec video with 🎶 #AIart #AIArtCommunity

Exploring diff visuals with Gen2. I'm amazed at how it takes a single block image to build neon streets, structures, and entire cityscapes. Anybody else toying with AI tonight⁉️ AI Art Workflow: 1. Crafted starting image in #Midjourney 2. Generated a 4-sec video with #Gen2 (no text prompt) 3. Extended first 4 secs to 18 secs 4. Repeated steps 2-3 twice, each time using the final frame from the previous 18-sec video to start the next 18-secs run 5. Merged all three 18-sec videos in #FinalCut Pro 6. Adjusted speed for fluidity 7. Final version published here is a 54-sec journey distilled into a 16-sec video with 🎶 #AIart #AIArtCommunity

Dave Villalva

47,946 görüntüleme • 3 yıl önce

Month 1: $0 Month 2: $0 Month 3: $205 Month 4: 50,532 This is what actually happens when you stop overthinking and start a faceless YouTube channel the right way. Most people quit in the first 60 days because they see zero results and assume it doesn’t work. But the ones who push through the first two months with consistency usually see their first real payout in month 3. Here’s the simple system that makes this possible: Step 1: Pick one proven niche (history, facts, motivation, or luxury) and stick to it. Step 2: Use AI to generate 30 video ideas in one sitting so you never run out of content. Step 3: Outsource or use AI to create the videos (script + voice + editing) so you can upload consistently without burning out. Step 4: Upload 3–5 videos per week and stay consistent for 90 days without checking analytics every day. The first two months are almost always quiet. The third month is where most people either quit or finally get paid. If you’re willing to be patient for 90 days, this model still works extremely well in 2026. Watch the full breakdown in the video.

Month 1: $0 Month 2: $0 Month 3: $205 Month 4: 50,532 This is what actually happens when you stop overthinking and start a faceless YouTube channel the right way. Most people quit in the first 60 days because they see zero results and assume it doesn’t work. But the ones who push through the first two months with consistency usually see their first real payout in month 3. Here’s the simple system that makes this possible: Step 1: Pick one proven niche (history, facts, motivation, or luxury) and stick to it. Step 2: Use AI to generate 30 video ideas in one sitting so you never run out of content. Step 3: Outsource or use AI to create the videos (script + voice + editing) so you can upload consistently without burning out. Step 4: Upload 3–5 videos per week and stay consistent for 90 days without checking analytics every day. The first two months are almost always quiet. The third month is where most people either quit or finally get paid. If you’re willing to be patient for 90 days, this model still works extremely well in 2026. Watch the full breakdown in the video.

Frogify

45,789 görüntüleme • 2 ay önce

I've been working a lot with SAM3 and the Momentum Human Rig (MHR). I finally integrated it into the data I'm working with Rerun. The progression I've taken looks as follows SAM3 + SAM3D-body on 1. a single image 2. a set of multiple images 3. a single video 4. A multiview video capture I took inspiration from the SAM3D-body paper and built a multiview fitting optimization pipeline. This pipeline involves using the 2D keypoints from the single-view pipeline, triangulating them, and employing an L1 loss between the 2D/3D keypoints. The temporal stability isn't great, so that's the next portion I'm going to focus on. One really frustrating thing about SAM3D-body is the lack of per-joint confidence values. It makes it harder to deal with occlusions. I'm probably going to need to use a separate model, or maybe add a confidence head.

I've been working a lot with SAM3 and the Momentum Human Rig (MHR). I finally integrated it into the data I'm working with Rerun. The progression I've taken looks as follows SAM3 + SAM3D-body on 1. a single image 2. a set of multiple images 3. a single video 4. A multiview video capture I took inspiration from the SAM3D-body paper and built a multiview fitting optimization pipeline. This pipeline involves using the 2D keypoints from the single-view pipeline, triangulating them, and employing an L1 loss between the 2D/3D keypoints. The temporal stability isn't great, so that's the next portion I'm going to focus on. One really frustrating thing about SAM3D-body is the lack of per-joint confidence values. It makes it harder to deal with occlusions. I'm probably going to need to use a separate model, or maybe add a confidence head.

Pablo Vela

43,354 görüntüleme • 7 ay önce

Slideshow clipping has to be the chillest business model you can really be making $5k - $15k+ a month running 10 TikTok accounts and have complete location freedom + make more than you would working a job you can literally just go to content rewards, pick a saas or brand to promote, for example skin care buy 5 aged TT accounts to start with connect US proxy / sim find videos in the niche the product is in for example skin care steal the hook of the video and content inside it and turn it into a slideshow for example: “skin care tips for broke girls” generate the images with NBP by finding a Pinterest image and getting the JSON from Gemini or ChatGPT promote the product as another “glow up” tip Post 1 a day from the start and as the accounts get more warm boost it to 2-3 + scale to more accounts If you can’t make your first $5k doing this then there is no hope

Pounds

15,415 görüntüleme • 7 ay önce

➡️It's a little embarrassing to share, but I feel like it took me way to long to realize the better workflow with rigging. So here's a little #live2d tip for those beginner artists that clicked for me a while back! I used to rig all body, clothing, and accessories for one given area all at once, but I think it ended up being inconsistent to other parts of the model. My workflow was slower too. 😬 It's similar to the inconsistencies you'd get by not drawing the bone structures of your character drawing, and just trying to draw the clothes right away. Body parts can sometimes seem to not line up, especially as a newer artist. It's a small change, but rigging only the nude base in full and then slowly adding one clothing part at a time makes the entire rigging process easier.😄 I know it seems really obvious, but I actually didn't start doing this until early last year. Everything comes together much faster and much more consistently, so definitely give it a try! Hope you enjoy this #vtuber leg rigging ☺️

➡️It's a little embarrassing to share, but I feel like it took me way to long to realize the better workflow with rigging. So here's a little #live2d tip for those beginner artists that clicked for me a while back! I used to rig all body, clothing, and accessories for one given area all at once, but I think it ended up being inconsistent to other parts of the model. My workflow was slower too. 😬 It's similar to the inconsistencies you'd get by not drawing the bone structures of your character drawing, and just trying to draw the clothes right away. Body parts can sometimes seem to not line up, especially as a newer artist. It's a small change, but rigging only the nude base in full and then slowly adding one clothing part at a time makes the entire rigging process easier.😄 I know it seems really obvious, but I actually didn't start doing this until early last year. Everything comes together much faster and much more consistently, so definitely give it a try! Hope you enjoy this #vtuber leg rigging ☺️

Yoona 主人公 | Live2D | COMMS OPEN

25,317 görüntüleme • 8 ay önce

MLP in PyTorch by hand ✍️ ~ 7 steps walkthrough below Goal: fill in every blank in the PyTorch code to build a multi-layer perceptron. 1. Given Let us start with a code template on the left and the network it is supposed to build on the right. Every blank in the code can be worked out from the picture. 2. Linear layer We count: 3 features in, 4 features out. So the weight matrix is 4 by 3. There is an extra column for the biases, which means bias = T. 3. ReLU Let us apply the activation. ReLU crosses out the negatives, so -1 becomes 0. 4. Linear layer The input size is 4, because that is what the previous layer put out. The output size is 2. A 2 by 4 weight matrix, and this time no extra column, so bias = F. 5. ReLU We cross out the negatives again. 6. Linear layer Two features in, five out. A 5 by 2 weight matrix, with a bias column, so bias = T. 7. Sigmoid Let us finish. Sigmoid squashes the raw scores (3, 0, -2, 5, -5) into probabilities between 0 and 1. You have just implemented a three-layer deep neural network by hand. ✍️ == Story == Three years ago I gave this exercise to my students, to connect the code to the math. They found it odd. Every other AI course they were taking lived inside a Jupyter notebook, and here I was handing out paper. Three years later, my colleagues are the ones rushing to move their materials to paper. The exercise has not changed. Paper still asks the one thing a notebook lets you skip: do you actually understand what the code is doing? If you can tell me why the weight matrix is 4 by 3, and why bias is F on the second layer, you understand nn.Linear better than someone who has been copy-pasting it for a year. 💾 Save this post! #AIbyHand #PyTorch #DeepLearning

MLP in PyTorch by hand ✍️ ~ 7 steps walkthrough below Goal: fill in every blank in the PyTorch code to build a multi-layer perceptron. 1. Given Let us start with a code template on the left and the network it is supposed to build on the right. Every blank in the code can be worked out from the picture. 2. Linear layer We count: 3 features in, 4 features out. So the weight matrix is 4 by 3. There is an extra column for the biases, which means bias = T. 3. ReLU Let us apply the activation. ReLU crosses out the negatives, so -1 becomes 0. 4. Linear layer The input size is 4, because that is what the previous layer put out. The output size is 2. A 2 by 4 weight matrix, and this time no extra column, so bias = F. 5. ReLU We cross out the negatives again. 6. Linear layer Two features in, five out. A 5 by 2 weight matrix, with a bias column, so bias = T. 7. Sigmoid Let us finish. Sigmoid squashes the raw scores (3, 0, -2, 5, -5) into probabilities between 0 and 1. You have just implemented a three-layer deep neural network by hand. ✍️ == Story == Three years ago I gave this exercise to my students, to connect the code to the math. They found it odd. Every other AI course they were taking lived inside a Jupyter notebook, and here I was handing out paper. Three years later, my colleagues are the ones rushing to move their materials to paper. The exercise has not changed. Paper still asks the one thing a notebook lets you skip: do you actually understand what the code is doing? If you can tell me why the weight matrix is 4 by 3, and why bias is F on the second layer, you understand nn.Linear better than someone who has been copy-pasting it for a year. 💾 Save this post! #AIbyHand #PyTorch #DeepLearning

Tom Yeh

13,318 görüntüleme • 2 ay önce