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A tour of the post-processing features in my WebGPU engine. Chaining global passes like blur, bloom, and pixelate, on top of a disturb pipeline with its own options: distortion, black and white, lighten, darken, noise, RGB split, and more. It also supports layer and plane UV isolation. Planes can... show more

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15,953 görüntüleme • 6 ay önce •via X (Twitter)

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claude fable 5 is live. spawn 5.0 was built with it: 1,687 prompts, 102 sessions, my job shifted from architecture to judging taste. what we built, each of which would've been at least a month with a whole team on opus: — a from-scratch physics engine (mantle) that rivals rapier, testable in a day as a side thread — clustered froxel lighting: 8 lights to 1,000+ fully dynamic ("it's stupid fast" — creator of threejs) — realtime diffuse GI on webgpu, on your phone (landing in the next update) — million-particle gpu vfx with a shader architecture beyond what unreal and unity ship — mmo-scale netcode plus, for good measure: an (alpha) native ios app. all of it in about a week. all of it running on mobile. and the list doesn't include half of what we shipped — full changelog in the thread below. and the part the benchmarks won't show you: this model has a wonderful personality. it's genuinely funny. i laughed so hard i cried multiple times, mid-physics-rewrite. the genius and the character aren't separate features.

claude fable 5 is live. spawn 5.0 was built with it: 1,687 prompts, 102 sessions, my job shifted from architecture to judging taste. what we built, each of which would've been at least a month with a whole team on opus: — a from-scratch physics engine (mantle) that rivals rapier, testable in a day as a side thread — clustered froxel lighting: 8 lights to 1,000+ fully dynamic ("it's stupid fast" — creator of threejs) — realtime diffuse GI on webgpu, on your phone (landing in the next update) — million-particle gpu vfx with a shader architecture beyond what unreal and unity ship — mmo-scale netcode plus, for good measure: an (alpha) native ios app. all of it in about a week. all of it running on mobile. and the list doesn't include half of what we shipped — full changelog in the thread below. and the part the benchmarks won't show you: this model has a wonderful personality. it's genuinely funny. i laughed so hard i cried multiple times, mid-physics-rewrite. the genius and the character aren't separate features.

jacob

55,515 görüntüleme • 2 ay önce

This guy built a visual scanner that reads 468 points on his face and 42 points on his hands from a regular webcam and turns them into a cloud of thousands of particles right between his palms. Inside, MediaPipe and TouchDesigner are linked: the first captures hands and face from the webcam with high accuracy, the second turns those coordinates into a live plane and feeds it into a POP system that instantly generates a swarm of particles in the shape of a head. No studio, no render farmer, no VR headset. Just a laptop, a webcam, and 1 TouchDesigner session. And traditional VJ studios keep teams of 5 people on a setup with lighting, custom hardware, and commercial plugins, while his expenses are only a TouchDesigner subscription and a regular USB camera. One laptop runs MediaPipe and TouchDesigner simultaneously, holds the camera stream at 60 FPS without drops, and in parallel processes 468 face points + 21 points on each hand. The camera captures frame after frame, MediaPipe in real time sends TouchDesigner the finger coordinates and face geometry, and the POP operator inside the engine translates those numbers into thousands of particle points with colors from bright pink to gold. This setup immediately defines the role of the tool and the limits of its autonomy. It knows where the fingertips are at every moment of the frame. It knows how to read the face geometry at any angle to the camera. It knows how to draw a swarm of particles between them with the right color and contour. → MediaPipe pulls 468 points from the face and 21 points from each hand, 60 times per second → TouchDesigner receives those coordinates, builds a virtual rectangle between the fingertips, and feeds it into the POP system → POP generates thousands of particle points in the shape of a head, coloring them in a gradient from bright pink to gold → The HUD layer adds green corners and a blue neon frame, styling the image like an AR interface → All layers assemble into 1 real-time frame that projects back onto the video in the camera window → The final image is recorded to a file or broadcast to a projector for a live installation And only when the guy spreads his hands wider does the plane between the palms stretch; brings them together, it narrows. Otherwise the system runs on its own. And when he moves from his home room to a concert hall, the same laptop with the same webcam launches the same TouchDesigner session in just 5 minutes, without reconfiguration, without a new team, and without a single line of new code. In his work setup there is no studio of his own and no team for assembly. On the desk sits a laptop with a webcam, on top run MediaPipe and TouchDesigner with POP operators, and the same setup through a USB camera moves to any concert without a new configuration. Out of everything I have seen this year, this is the cleanest Creative Coding setup on 1 laptop: 0 render farms, 0 studio lighting, and between them 3 libraries, thousands of particle points, and 1 webcam.

This guy built a visual scanner that reads 468 points on his face and 42 points on his hands from a regular webcam and turns them into a cloud of thousands of particles right between his palms. Inside, MediaPipe and TouchDesigner are linked: the first captures hands and face from the webcam with high accuracy, the second turns those coordinates into a live plane and feeds it into a POP system that instantly generates a swarm of particles in the shape of a head. No studio, no render farmer, no VR headset. Just a laptop, a webcam, and 1 TouchDesigner session. And traditional VJ studios keep teams of 5 people on a setup with lighting, custom hardware, and commercial plugins, while his expenses are only a TouchDesigner subscription and a regular USB camera. One laptop runs MediaPipe and TouchDesigner simultaneously, holds the camera stream at 60 FPS without drops, and in parallel processes 468 face points + 21 points on each hand. The camera captures frame after frame, MediaPipe in real time sends TouchDesigner the finger coordinates and face geometry, and the POP operator inside the engine translates those numbers into thousands of particle points with colors from bright pink to gold. This setup immediately defines the role of the tool and the limits of its autonomy. It knows where the fingertips are at every moment of the frame. It knows how to read the face geometry at any angle to the camera. It knows how to draw a swarm of particles between them with the right color and contour. → MediaPipe pulls 468 points from the face and 21 points from each hand, 60 times per second → TouchDesigner receives those coordinates, builds a virtual rectangle between the fingertips, and feeds it into the POP system → POP generates thousands of particle points in the shape of a head, coloring them in a gradient from bright pink to gold → The HUD layer adds green corners and a blue neon frame, styling the image like an AR interface → All layers assemble into 1 real-time frame that projects back onto the video in the camera window → The final image is recorded to a file or broadcast to a projector for a live installation And only when the guy spreads his hands wider does the plane between the palms stretch; brings them together, it narrows. Otherwise the system runs on its own. And when he moves from his home room to a concert hall, the same laptop with the same webcam launches the same TouchDesigner session in just 5 minutes, without reconfiguration, without a new team, and without a single line of new code. In his work setup there is no studio of his own and no team for assembly. On the desk sits a laptop with a webcam, on top run MediaPipe and TouchDesigner with POP operators, and the same setup through a USB camera moves to any concert without a new configuration. Out of everything I have seen this year, this is the cleanest Creative Coding setup on 1 laptop: 0 render farms, 0 studio lighting, and between them 3 libraries, thousands of particle points, and 1 webcam.

Blaze

38,242 görüntüleme • 3 ay önce

SplitPaneKit This is something I've wanted to componentize for a while. We've seen this pattern appear in a few apps now, I even use it at Abode. It has a couple "gotcha" moments with performance and optimisation while animating separate or child views with the drag and translation of the split views, handling breakpoints etc, I thought I'd put it into a nice package. I actually made quite a few optimisations from how I handle this with Abode in this package. So might need to implement it over there😅 As before, right now its UIKit only, but SwiftUI host will likely come over the next few days as I make improvements and final changes to the initial API from feedback. - Draggable split-pane interface - Custom breakpoints or built-in presets - Scroll view integration - drag from content or handle - Coordinated animations with pan-effecting views - UIKit

SplitPaneKit This is something I've wanted to componentize for a while. We've seen this pattern appear in a few apps now, I even use it at Abode. It has a couple "gotcha" moments with performance and optimisation while animating separate or child views with the drag and translation of the split views, handling breakpoints etc, I thought I'd put it into a nice package. I actually made quite a few optimisations from how I handle this with Abode in this package. So might need to implement it over there😅 As before, right now its UIKit only, but SwiftUI host will likely come over the next few days as I make improvements and final changes to the initial API from feedback. - Draggable split-pane interface - Custom breakpoints or built-in presets - Scroll view integration - drag from content or handle - Coordinated animations with pan-effecting views - UIKit

Joseph Smith

23,552 görüntüleme • 1 yıl önce

The making of the Airbus A380 - building the world's largest passenger aircraft The Airbus A380 was designed to move more passengers farther and quieter than any aircraft before it. Its development brought together engineering teams from across Europe to create a true aviation giant. Major sections of the A380 are manufactured in different countries. The wings are built in the United Kingdom, the fuselage sections in Germany and France, the cockpit and nose in France, and the horizontal tail plane in Spain. These massive components are transported by Beluga aircraft, ships, and special road convoys to the final assembly line in Toulouse, France ملم The A380 uses advanced aluminum alloys and composite materials to handle extreme structural loads while keeping weight under control. Its wings are the largest ever fitted to a passenger aircraft, designed to flex several meters upward in flight without damage. Inside, the aircraft features a full-length double-deck cabin, advanced fly-by-wire systems, and one of the most complex electrical and hydraulic architectures ever installed on a civil airliner After assembly, each A380 undergoes extensive ground tests, system checks, and flight testing to certify performance, safety, and reliability before entering airline service

The making of the Airbus A380 - building the world's largest passenger aircraft The Airbus A380 was designed to move more passengers farther and quieter than any aircraft before it. Its development brought together engineering teams from across Europe to create a true aviation giant. Major sections of the A380 are manufactured in different countries. The wings are built in the United Kingdom, the fuselage sections in Germany and France, the cockpit and nose in France, and the horizontal tail plane in Spain. These massive components are transported by Beluga aircraft, ships, and special road convoys to the final assembly line in Toulouse, France ملم The A380 uses advanced aluminum alloys and composite materials to handle extreme structural loads while keeping weight under control. Its wings are the largest ever fitted to a passenger aircraft, designed to flex several meters upward in flight without damage. Inside, the aircraft features a full-length double-deck cabin, advanced fly-by-wire systems, and one of the most complex electrical and hydraulic architectures ever installed on a civil airliner After assembly, each A380 undergoes extensive ground tests, system checks, and flight testing to certify performance, safety, and reliability before entering airline service

Mechanical Knowledge

123,910 görüntüleme • 4 ay önce

There is a room in Málaga that was built to be the closest thing on earth to standing inside heaven. It is called the camarín of the Virgin of Victory, and it is hidden at the top of a tower inside the Santuario de la Victoria. To reach it, you climb and the ascent is the entire point... The building you are climbing through was completed in 1700, and it was designed as a single argument made in stone. At the bottom lies a crypt: a black chamber crowded with white plaster skeletons, a meditation on death and the brevity of life. From there a staircase rises, and as you climb it the light grows stronger and the imagery changes from bones to saints. The architects of the time understood this ascent as the soul's own journey, the dark crypt as the stage of penitence, the staircase as the stage of spiritual progress, and the room at the very top as the final stage: the union of the soul with the divine. That room at the top is the camarín, and its dome is one of the most extraordinary interiors in Spain... Every surface is covered in white and gold plasterwork. There is no empty space anywhere. The Baroque called this horror vacui, the horror of the void: the conviction that a space meant to represent heaven should not contain a single bare patch of stone. Out of that plasterwork emerge angels, flowers, birds, and mirrors. The mirrors are not decoration alone. They catch the light pouring in through the windows of the drum and throw it around the chamber, so that the gold seems to move and the whole room appears to shimmer and breathe. This wonder was built by people who believed that if you wanted to show a human being what heaven might feel like, you did not describe it to them. You built a room, and you let them climb into it... -- -- -- If you enjoyed this, I write a weekly newsletter read by over 50,000 people who love rediscovering the beauty of the past. You can join us here: If you'd like to support my work, a paid subscription is what makes it possible.

There is a room in Málaga that was built to be the closest thing on earth to standing inside heaven. It is called the camarín of the Virgin of Victory, and it is hidden at the top of a tower inside the Santuario de la Victoria. To reach it, you climb and the ascent is the entire point... The building you are climbing through was completed in 1700, and it was designed as a single argument made in stone. At the bottom lies a crypt: a black chamber crowded with white plaster skeletons, a meditation on death and the brevity of life. From there a staircase rises, and as you climb it the light grows stronger and the imagery changes from bones to saints. The architects of the time understood this ascent as the soul's own journey, the dark crypt as the stage of penitence, the staircase as the stage of spiritual progress, and the room at the very top as the final stage: the union of the soul with the divine. That room at the top is the camarín, and its dome is one of the most extraordinary interiors in Spain... Every surface is covered in white and gold plasterwork. There is no empty space anywhere. The Baroque called this horror vacui, the horror of the void: the conviction that a space meant to represent heaven should not contain a single bare patch of stone. Out of that plasterwork emerge angels, flowers, birds, and mirrors. The mirrors are not decoration alone. They catch the light pouring in through the windows of the drum and throw it around the chamber, so that the gold seems to move and the whole room appears to shimmer and breathe. This wonder was built by people who believed that if you wanted to show a human being what heaven might feel like, you did not describe it to them. You built a room, and you let them climb into it... -- -- -- If you enjoyed this, I write a weekly newsletter read by over 50,000 people who love rediscovering the beauty of the past. You can join us here: If you'd like to support my work, a paid subscription is what makes it possible.

James Lucas

69,389 görüntüleme • 2 ay önce

I'll always root for a team that open-sources its best work, and Robbyant just did it properly. Robbyant, Ant Group's embodied-AI company, released LingBot-Vision, a vision foundation model for robots, and the part I love is the data. They trained it on 161M images, filtered down from 2B raw ones and mostly pulled straight from the open web, with no human labels, no edge detectors, no depth sensors anywhere in the loop. It learns the exact edges of objects from raw pixels. That's roughly a tenth of the data DINOv3 saw, and under a third of the training. And it shows in the results. On depth, working out how far away things are, the 1B model edges out a 7B on NYU-Depth. It also powers LingBot-Depth 2.0, which reads the surfaces cameras usually choke on, glass and mirrors, and halves indoor depth error. LingBot-Vision is fully open. Weights from the 1.1B flagship down to a tiny 21M version, code, and the paper. This is the timeline I want more of. Robbyant

I'll always root for a team that open-sources its best work, and Robbyant just did it properly. Robbyant, Ant Group's embodied-AI company, released LingBot-Vision, a vision foundation model for robots, and the part I love is the data. They trained it on 161M images, filtered down from 2B raw ones and mostly pulled straight from the open web, with no human labels, no edge detectors, no depth sensors anywhere in the loop. It learns the exact edges of objects from raw pixels. That's roughly a tenth of the data DINOv3 saw, and under a third of the training. And it shows in the results. On depth, working out how far away things are, the 1B model edges out a 7B on NYU-Depth. It also powers LingBot-Depth 2.0, which reads the surfaces cameras usually choke on, glass and mirrors, and halves indoor depth error. LingBot-Vision is fully open. Weights from the 1.1B flagship down to a tiny 21M version, code, and the paper. This is the timeline I want more of. Robbyant

Chubby♨️

48,249 görüntüleme • 1 ay önce

OpenClaw, but built for normal people. Sim is an open-source platform that lets you build AI agent workflows on a drag-and-drop canvas. Connect them to channels like Telegram and WhatsApp and deploy without writing a single line of code. They also have a built-in Copilot that generates entire workflows from plain English, which you can then tweak and customize in the UI. Key features: - Free and open-source (Apache 2.0) - Vector store integration for RAG-grounded agents - Self-host with one command (`npx simstudio`) - Run fully local with Ollama, no API keys needed - Supports vLLM for production-grade self-hosted inference The thing I really like about Sim is the level of control you get. You can add conditional branching, parallel execution, human-in-the-loop approval gates, and even nest workflows inside other workflows. Everything is visible on the canvas, so you know exactly what your agent is doing at every step. And you can build a workflow in Sim, deploy it as an MCP server, and plug it into any agent, including OpenClaw. I've shared the link to Sim's GitHub repo in the next tweet.

OpenClaw, but built for normal people. Sim is an open-source platform that lets you build AI agent workflows on a drag-and-drop canvas. Connect them to channels like Telegram and WhatsApp and deploy without writing a single line of code. They also have a built-in Copilot that generates entire workflows from plain English, which you can then tweak and customize in the UI. Key features: - Free and open-source (Apache 2.0) - Vector store integration for RAG-grounded agents - Self-host with one command (`npx simstudio`) - Run fully local with Ollama, no API keys needed - Supports vLLM for production-grade self-hosted inference The thing I really like about Sim is the level of control you get. You can add conditional branching, parallel execution, human-in-the-loop approval gates, and even nest workflows inside other workflows. Everything is visible on the canvas, so you know exactly what your agent is doing at every step. And you can build a workflow in Sim, deploy it as an MCP server, and plug it into any agent, including OpenClaw. I've shared the link to Sim's GitHub repo in the next tweet.

Akshay 🚀

52,426 görüntüleme • 5 ay önce

A Closer Look at Alchemist AI v3.5🔎 In v1, one agent handled everything. You’d enter a prompt like “make a snake game” and get a single block of code—one input, one output. v2 introduced multiple agents with specialized roles: prompt refinement, frontend, backend, and review. It brought more structure, but the process was still linear. Each step produced a single output. With v3, a single agent could handle multiple tasks. It generated HTML, CSS, JavaScript, searched for assets, and more—all in one go, while maintaining full context. Now in v3.5, we combine both models. Multiple agents work in parallel, each capable of producing multiple outputs at once. The prompt compiler adapts based on what you're building. A 3D game? It prioritizes game engines, rendering, and mechanics. A website or 2D app? It shifts focus to relevant frameworks and tools. The tool handler can call several services simultaneously, feeding context-aware data into the code generator for real-time execution. From single-output generation to parallel, adaptive workflows. In the next breakdown, we’ll dive into the architecture behind our proprietary engine in v3.5.

A Closer Look at Alchemist AI v3.5🔎 In v1, one agent handled everything. You’d enter a prompt like “make a snake game” and get a single block of code—one input, one output. v2 introduced multiple agents with specialized roles: prompt refinement, frontend, backend, and review. It brought more structure, but the process was still linear. Each step produced a single output. With v3, a single agent could handle multiple tasks. It generated HTML, CSS, JavaScript, searched for assets, and more—all in one go, while maintaining full context. Now in v3.5, we combine both models. Multiple agents work in parallel, each capable of producing multiple outputs at once. The prompt compiler adapts based on what you're building. A 3D game? It prioritizes game engines, rendering, and mechanics. A website or 2D app? It shifts focus to relevant frameworks and tools. The tool handler can call several services simultaneously, feeding context-aware data into the code generator for real-time execution. From single-output generation to parallel, adaptive workflows. In the next breakdown, we’ll dive into the architecture behind our proprietary engine in v3.5.

ALCHEMIST AI 🔮

12,689 görüntüleme • 1 yıl önce

$Face card never declines. 🖤 Grok Imagine { “subject”: { “description”: “A hyper-realistic, raw 8k medium-shot selfie of a stunningly attractive woman with a voluptuous hourglass figure, captured from the waist up.”, “body”: { “physique”: “She has a striking and sexy physique with a narrow waist and prominently large, firm, and upright breasts that create a deep, natural cleavage. Her figure is full and curvy, emphasized by the tight-fitting top.”, “pose”: “A waist-up selfie pose, holding the phone naturally. Her body is slightly angled, while her head is turned to look back over her shoulder with a sultry and confident gaze.”, “features”: “Long, dark, slightly messy hair with realistic flyaways and visible texture. Extreme facial detail: natural skin pores, tiny freckles, a small beauty mark on her chest, and a realistic oily sheen on the T-zone. Her lips are full, glossy, and show natural lip lines. Eyes have wet, crystalline reflections.” } }, “wardrobe”: { “outfit”: “A tight-fitting, black ribbed cotton V-neck top. The fabric is stretched across her large bust, showing the realistic tension of the ribbed weave and micro-fibers.”, “accessories”: “A small, realistic silver septum ring with a metallic glint. No necklace is worn.” }, “pose_action”: “Taking a spontaneous, high-detail selfie in a private indoor setting, looking back over the shoulder to highlight her silhouette and curves.”, “scene”: { “environment”: “A dimly lit, realistic bedroom or dressing room background with natural depth.”, “elements”: “Soft-focus (bokeh) background showing a messy bed or a door frame, typical of a real home photo. The focus is exclusively sharp on her skin, eyes, and the texture of her top.”, “composition”: “Vertical medium shot, framing the subject from the top of her head down to her waistline.” }, “lighting”: { “setup”: “Soft, directional ambient light from a nearby window or lamp.”, “details”: “The light creates realistic highlights on the curve of her breasts and shoulders. Subtle micro-shadows are visible in the folds of the ribbed fabric and under her chin.” }, “camera”: { “technical”: “Raw smartphone photography style, f/1.8 aperture for natural optical blur. Zero post-processing look. High ISO detail with minimal noise, capturing microscopic skin and fabric textures. Sharp focus on the pupils.”, “aspect_ratio”: “2:3”, “constraints”: [ “CRITICAL: The woman must have large, firm, and upright breasts shown clearly in a medium shot (waist-up).”, “CRITICAL: Ultra-photorealistic skin texture with pores and natural imperfections.”, “No necklace.”, “Individuality in facial features, natural dark hair with septum ring.”, ] } }$

Face card never declines. 🖤 Grok Imagine { “subject”: { “description”: “A hyper-realistic, raw 8k medium-shot selfie of a stunningly attractive woman with a voluptuous hourglass figure, captured from the waist up.”, “body”: { “physique”: “She has a striking and sexy physique with a narrow waist and prominently large, firm, and upright breasts that create a deep, natural cleavage. Her figure is full and curvy, emphasized by the tight-fitting top.”, “pose”: “A waist-up selfie pose, holding the phone naturally. Her body is slightly angled, while her head is turned to look back over her shoulder with a sultry and confident gaze.”, “features”: “Long, dark, slightly messy hair with realistic flyaways and visible texture. Extreme facial detail: natural skin pores, tiny freckles, a small beauty mark on her chest, and a realistic oily sheen on the T-zone. Her lips are full, glossy, and show natural lip lines. Eyes have wet, crystalline reflections.” } }, “wardrobe”: { “outfit”: “A tight-fitting, black ribbed cotton V-neck top. The fabric is stretched across her large bust, showing the realistic tension of the ribbed weave and micro-fibers.”, “accessories”: “A small, realistic silver septum ring with a metallic glint. No necklace is worn.” }, “pose_action”: “Taking a spontaneous, high-detail selfie in a private indoor setting, looking back over the shoulder to highlight her silhouette and curves.”, “scene”: { “environment”: “A dimly lit, realistic bedroom or dressing room background with natural depth.”, “elements”: “Soft-focus (bokeh) background showing a messy bed or a door frame, typical of a real home photo. The focus is exclusively sharp on her skin, eyes, and the texture of her top.”, “composition”: “Vertical medium shot, framing the subject from the top of her head down to her waistline.” }, “lighting”: { “setup”: “Soft, directional ambient light from a nearby window or lamp.”, “details”: “The light creates realistic highlights on the curve of her breasts and shoulders. Subtle micro-shadows are visible in the folds of the ribbed fabric and under her chin.” }, “camera”: { “technical”: “Raw smartphone photography style, f/1.8 aperture for natural optical blur. Zero post-processing look. High ISO detail with minimal noise, capturing microscopic skin and fabric textures. Sharp focus on the pupils.”, “aspect_ratio”: “2:3”, “constraints”: [ “CRITICAL: The woman must have large, firm, and upright breasts shown clearly in a medium shot (waist-up).”, “CRITICAL: Ultra-photorealistic skin texture with pores and natural imperfections.”, “No necklace.”, “Individuality in facial features, natural dark hair with septum ring.”, ] } }

Noira

24,873 görüntüleme • 5 ay önce

Get ready for an epic 2024: GameSwift Modular Blockchain will propel web3 gaming to the next level. GameSwift AI 🎮 has a modular architecture designed to provide flexibility and scalability, tailor-made for the dynamic world of gaming. Forget monolithic limitations. GameSwift's modular magic allows you to customize and optimize your blockchain experience like never before. Think of it like a Lego set for your dApps, where you slot in the perfect pieces to create the ultimate gaming experience. 🧱 The GameSwift Modular Blockchain has it all: • Adaptability: Need a super fast chain for ultrafast transactions? zkEVM handles the heavy lifting while the modular design keeps everything optimized. • Flexibility: As technology evolves, the GameSwift ecosystem can adapt. Upgrade modules, integrate new features and stay cutting edge. GameSwift's modularity lets you mix and match capabilities to craft the perfect platform for your game. • Scalability: GameSwift's modular design effortlessly adapts to demand, ensuring smooth gameplay for all, even as your game explodes in popularity. CoinGecko includes GameSwift in Modular Blockchain category One important milestone has been crypto data platform CoinGecko recognizing GameSwift by including it in their "Top Modular Blockchain Coins by Market Cap" category. This emphasizes GameSwift's credibility, potential and hard work in the wider crypto marketplace. Notably, of the 3 projects in this category, GameSwift has the lowest market cap - making it a true gem for the next BTC halving and bull run. 🔥 The Success of Modular Blockchains As we all know, Celestia is a modular blockchain that has also seen great achievements, showing the power and potential of modular designs. With GameSwift being another highly innovative modular blockchain and its 2024 roadmap, we can be certain this project will continue to surge. And with its low market cap, GSWIFT token is undoubtedly the gem of modular blockchains in crypto. But wait, there's more! GameSwift's modularity also opens up a world of new possibilities for developers: • Optimize efficiency - focus on creating incredible playability without worrying about exorbitant fees. Speed up contract execution and build games that are fun and financially sustainable. • Focus on what matters - Forget security worries, GameSwift's ZK Shared Security system keeps your game safe while you concentrate on crafting the best possible experience. • Use cross-chains - seamlessly connect with other blockchains, expanding your reach and unlocking new opportunities for your game. And for $GSWIFT holders? Get ready for some sweet sidechain action! Stake your tokens to earn rewards from the games built on GameSwift's modular ecosystem. This is a win-win situation: developers get the tools they need to build amazing games and you get rewarded for being part of the GameSwift ecosystem. In conclusion, the GameSwift modular blockchain is the key to unlocking a world of possibilities, where developers can create without limits and players can experience games like never before. With GameSwift, the future of Web3 gaming is modular, adaptable, and limitless. 🚀

Get ready for an epic 2024: GameSwift Modular Blockchain will propel web3 gaming to the next level. GameSwift AI 🎮 has a modular architecture designed to provide flexibility and scalability, tailor-made for the dynamic world of gaming. Forget monolithic limitations. GameSwift's modular magic allows you to customize and optimize your blockchain experience like never before. Think of it like a Lego set for your dApps, where you slot in the perfect pieces to create the ultimate gaming experience. 🧱 The GameSwift Modular Blockchain has it all: • Adaptability: Need a super fast chain for ultrafast transactions? zkEVM handles the heavy lifting while the modular design keeps everything optimized. • Flexibility: As technology evolves, the GameSwift ecosystem can adapt. Upgrade modules, integrate new features and stay cutting edge. GameSwift's modularity lets you mix and match capabilities to craft the perfect platform for your game. • Scalability: GameSwift's modular design effortlessly adapts to demand, ensuring smooth gameplay for all, even as your game explodes in popularity. CoinGecko includes GameSwift in Modular Blockchain category One important milestone has been crypto data platform CoinGecko recognizing GameSwift by including it in their "Top Modular Blockchain Coins by Market Cap" category. This emphasizes GameSwift's credibility, potential and hard work in the wider crypto marketplace. Notably, of the 3 projects in this category, GameSwift has the lowest market cap - making it a true gem for the next BTC halving and bull run. 🔥 The Success of Modular Blockchains As we all know, Celestia is a modular blockchain that has also seen great achievements, showing the power and potential of modular designs. With GameSwift being another highly innovative modular blockchain and its 2024 roadmap, we can be certain this project will continue to surge. And with its low market cap, GSWIFT token is undoubtedly the gem of modular blockchains in crypto. But wait, there's more! GameSwift's modularity also opens up a world of new possibilities for developers: • Optimize efficiency - focus on creating incredible playability without worrying about exorbitant fees. Speed up contract execution and build games that are fun and financially sustainable. • Focus on what matters - Forget security worries, GameSwift's ZK Shared Security system keeps your game safe while you concentrate on crafting the best possible experience. • Use cross-chains - seamlessly connect with other blockchains, expanding your reach and unlocking new opportunities for your game. And for $GSWIFT holders? Get ready for some sweet sidechain action! Stake your tokens to earn rewards from the games built on GameSwift's modular ecosystem. This is a win-win situation: developers get the tools they need to build amazing games and you get rewarded for being part of the GameSwift ecosystem. In conclusion, the GameSwift modular blockchain is the key to unlocking a world of possibilities, where developers can create without limits and players can experience games like never before. With GameSwift, the future of Web3 gaming is modular, adaptable, and limitless. 🚀

ETHachi Uchiha | Crypto DEGENius

10,982 görüntüleme • 2 yıl önce

Any attack on the President is an attack on the millions of Zimbabweans who entrusted him with the responsibility to lead our nation in accordance with the Constitution of Zimbabwe. Leadership in a democracy is derived from the will of the people, and President Emmerson Dambudzo Mnangagwa was elected to serve and advance the interests of the nation. Those of us who believe in peace, stability, national unity, and progressive development will continue to stand firmly behind him. As Zimbabweans, we have a collective responsibility to support initiatives that promote economic growth, infrastructure development, investment, job creation, and the overall prosperity of our country. I will continue to stand with our Commander-in-Chief of the Zimbabwe Defence Forces, First Secretary of ZANU-PF, and President of the Republic of Zimbabwe, Emmerson Dambudzo Mnangagwa. My support is rooted in my belief that Zimbabwe's future is built through unity, hard work, constructive engagement, and a shared commitment to national development. Zimbabwe belongs to all of us, and it is our duty to work together in building a stronger, more prosperous, and more united nation for future generations. #NyikaInovakwaNeVeneVayo 🇿🇼

Any attack on the President is an attack on the millions of Zimbabweans who entrusted him with the responsibility to lead our nation in accordance with the Constitution of Zimbabwe. Leadership in a democracy is derived from the will of the people, and President Emmerson Dambudzo Mnangagwa was elected to serve and advance the interests of the nation. Those of us who believe in peace, stability, national unity, and progressive development will continue to stand firmly behind him. As Zimbabweans, we have a collective responsibility to support initiatives that promote economic growth, infrastructure development, investment, job creation, and the overall prosperity of our country. I will continue to stand with our Commander-in-Chief of the Zimbabwe Defence Forces, First Secretary of ZANU-PF, and President of the Republic of Zimbabwe, Emmerson Dambudzo Mnangagwa. My support is rooted in my belief that Zimbabwe's future is built through unity, hard work, constructive engagement, and a shared commitment to national development. Zimbabwe belongs to all of us, and it is our duty to work together in building a stronger, more prosperous, and more united nation for future generations. #NyikaInovakwaNeVeneVayo 🇿🇼

BaShona.

11,780 görüntüleme • 2 ay önce

The A's continue to stack up on young left-handed pitching, selecting Mason Edwards (2nd round, pick 47). Edwards wields a 91-94 mph four-seam averaging ~21 iVB, although the pitch plays below its raw carry from a very high 6.6 ft. release height. Likely needs to be 93-95 for big league success, swing-and-miss somewhat lacked. The secondaries and their potential make Edwards the prospect he is. From the over-the-top release, his 80 mph curveball generates strong two-plane movement (-10/11) at a very steep approach. Strong command of the offering, ability to use at high frequency. While he didn't use it too often, Edwards' changeup has massive promise, also on a very steep plane from his heavily vertical release. Showed velocity and movement separation from his four-seam, projects as a great weapon vs. RHH. Boasted an elite whiff rate >50%. Needs more consistent feel and usage. The southpaw's slider is also a work in progress and was non-existent in many outings this year, but it will be a critical bridge pitch in his arsenal. 80-82 mph with inconsistent shape. With such a large vertical distinction between his four-seam and curveball, Edwards needs a hard, tight slider to sit between the pair and make swing decisions tougher. Hopefully, the A's can find a mid-80s pitch in gyro territory. The largest area for growth with Edwards is his command, as he posted a walk rate >10% in each of his three collegiate seasons (11.9% junior year). In my opinion, it seemed like he was always pitching for punchouts and around the edges of the plate. I think more strikes should come with more in-zone emphasis in early counts, and he has the stuff to never worry about being over the plate. With some velocity progression and refinement of his changeup and slider, I find it very likely Mason Edwards becomes at least of middle of the rotation starting pitcher. A's have a stellar crop of young southpaws.

The A's continue to stack up on young left-handed pitching, selecting Mason Edwards (2nd round, pick 47). Edwards wields a 91-94 mph four-seam averaging ~21 iVB, although the pitch plays below its raw carry from a very high 6.6 ft. release height. Likely needs to be 93-95 for big league success, swing-and-miss somewhat lacked. The secondaries and their potential make Edwards the prospect he is. From the over-the-top release, his 80 mph curveball generates strong two-plane movement (-10/11) at a very steep approach. Strong command of the offering, ability to use at high frequency. While he didn't use it too often, Edwards' changeup has massive promise, also on a very steep plane from his heavily vertical release. Showed velocity and movement separation from his four-seam, projects as a great weapon vs. RHH. Boasted an elite whiff rate >50%. Needs more consistent feel and usage. The southpaw's slider is also a work in progress and was non-existent in many outings this year, but it will be a critical bridge pitch in his arsenal. 80-82 mph with inconsistent shape. With such a large vertical distinction between his four-seam and curveball, Edwards needs a hard, tight slider to sit between the pair and make swing decisions tougher. Hopefully, the A's can find a mid-80s pitch in gyro territory. The largest area for growth with Edwards is his command, as he posted a walk rate >10% in each of his three collegiate seasons (11.9% junior year). In my opinion, it seemed like he was always pitching for punchouts and around the edges of the plate. I think more strikes should come with more in-zone emphasis in early counts, and he has the stuff to never worry about being over the plate. With some velocity progression and refinement of his changeup and slider, I find it very likely Mason Edwards becomes at least of middle of the rotation starting pitcher. A's have a stellar crop of young southpaws.

Matthew Knauer

14,992 görüntüleme • 1 ay önce

Here’s a look at my AR keychain prototype !! 🥹🩷 You can swap out icons (for now only the ones i’ve animated… and u know there's is a lot!!), scan it trough filters (for now) and my animation shows up I actually started with a card format at first, but i wanted to spend more time on the designs, so i went with keychains for the first release, i didn’t want to make regular keychains either, and bringing AR together with my animations lets people actually "hold" them instead of them just living on my pc, it makes them feel alive and interactive, something i’ve wanted to try ever since the Nintendo 3ds AR cards 🥹 This is my 4th prototype gulp, and my 5th is already done Will be 3D, look and feel better, will be thinner, doesn’t need the rotating system anymore etc.. (i'm choosing between wood or acrylic for the final version) And in the future, i’m planning to design and make my own app (alrdy started :D) so it doesn’t rely on tiktok/instagram/snap filters, and the animations will be interactive too !! :D i’m also designing custom borders so you can use your keychain without a league border if u don't wanna look like a full on nerd, and i’m working on more AR formats beyond keychains :D More soon, i’m really excited 🥹🩷

Here’s a look at my AR keychain prototype !! 🥹🩷 You can swap out icons (for now only the ones i’ve animated… and u know there's is a lot!!), scan it trough filters (for now) and my animation shows up I actually started with a card format at first, but i wanted to spend more time on the designs, so i went with keychains for the first release, i didn’t want to make regular keychains either, and bringing AR together with my animations lets people actually "hold" them instead of them just living on my pc, it makes them feel alive and interactive, something i’ve wanted to try ever since the Nintendo 3ds AR cards 🥹 This is my 4th prototype gulp, and my 5th is already done Will be 3D, look and feel better, will be thinner, doesn’t need the rotating system anymore etc.. (i'm choosing between wood or acrylic for the final version) And in the future, i’m planning to design and make my own app (alrdy started :D) so it doesn’t rely on tiktok/instagram/snap filters, and the animations will be interactive too !! :D i’m also designing custom borders so you can use your keychain without a league border if u don't wanna look like a full on nerd, and i’m working on more AR formats beyond keychains :D More soon, i’m really excited 🥹🩷

Nayra 🎐┃twitch.tv/lxst_nayra

89,030 görüntüleme • 9 ay önce

$We have released Seedance 2.0. Due to the 2500-character limit, please translate the following prompts into Chinese before use. [Technical Specs] Generate a 10-second, 16:9, 720p cinematic video. Smooth continuous camera motion with no cuts. The overall pacing is fast and tightly compressed, with rapid escalation from start to finish. Audio evolves quickly from a high-performance engine idle into intricate mechanical shifting and clicks, culminating in a soft electronic chime and the distinct sound of a "mwah" blowing kiss. [Global Constraints] Only the evolving mechanical character appears; no other humans or characters. All transformations must follow physical logic and maintain structural continuity. No object should pass through or intersect with other solid objects. Every robotic component must originate from visible parts of the Porsche 911 (doors, hood, wheels, chassis) through unfolding, splitting, or reconfiguration. [Scene Setup — 0:00–0:01] A sleek, metallic silver Porsche 911 sits on a rain-slicked futuristic city street at night, neon lights reflecting off its polished surface. The camera starts at a low-angle front-quarter view and begins a fast, smooth tracking-arc towards the side. [Rapid Transformation Initiation — 0:01–0:03] Transformation triggers instantly. The car’s suspension drops, and the frame begins to fracture into a complex grid of panels. The doors swing open and begin to segment into articulated arm structures. The front hood splits down the center, folding inward to reveal a glowing internal core. The headlights flicker and start to reorient as the "eyes." [Accelerated Feminine Reconfiguration — 0:03–0:07] The mechanical action is dense, overlapping, and fluid, emphasizing graceful but powerful motion. Lower Body: The rear wheels and wheel arches split and rotate downward, reassembling into slender, high-heeled mechanical legs. Torso: The roof and rear engine cover slide and compress, forming a sleek, curvaceous hourglass torso that retains the car’s aerodynamic lines. Arms & Hands: The side mirrors and door panels unfold into delicate but strong hands and fingers. Head: The front bumper and emblem area segment and rise, folding into a feminine-shaped head with a sleek metallic "helmet" visor. [Logical Transformation Constraints — No Spontaneous Appearance] The robot’s "skin" is composed of the car's outer silver panels. The internal frame and wiring emerge from the engine and undercarriage. No parts appear out of thin air; every joint is a reconfigured automotive component. [Transformation Completion — 0:07–0:08.5] The robot stands tall and elegant. The silver panels lock into place with a satisfying "click," revealing glowing blue LED accents in the seams. The silhouette is clearly feminine, humanoid, and sophisticated, reflecting the premium design of the original vehicle. [Final Hero Ending — 0:08.5–0:10] As the robot stabilizes, the camera performs a rapid, smooth zoom-in (Dolly-In) directly to her face. The robot tilts its head slightly, and the optic sensors (eyes) brighten. It brings its mechanical hand to its metallic lips and performs a graceful blowing kiss (fly-kiss) gesture toward the camera. The video ends with a close-up of the face, capturing the reflection of neon lights in its visor just as the kiss is released. [Cinematography Notes] Continuous Motion: No cuts or fades; the camera must transition from the car-tracking shot to the face-zoom seamlessly. Material Consistency: The robot must maintain the exact metallic silver paint, texture, and reflections of the Porsche. Energy: The transformation should feel high-energy and "force-driven," while the final gesture is soft and charismatic.$

We have released Seedance 2.0. Due to the 2500-character limit, please translate the following prompts into Chinese before use. [Technical Specs] Generate a 10-second, 16:9, 720p cinematic video. Smooth continuous camera motion with no cuts. The overall pacing is fast and tightly compressed, with rapid escalation from start to finish. Audio evolves quickly from a high-performance engine idle into intricate mechanical shifting and clicks, culminating in a soft electronic chime and the distinct sound of a "mwah" blowing kiss. [Global Constraints] Only the evolving mechanical character appears; no other humans or characters. All transformations must follow physical logic and maintain structural continuity. No object should pass through or intersect with other solid objects. Every robotic component must originate from visible parts of the Porsche 911 (doors, hood, wheels, chassis) through unfolding, splitting, or reconfiguration. [Scene Setup — 0:00–0:01] A sleek, metallic silver Porsche 911 sits on a rain-slicked futuristic city street at night, neon lights reflecting off its polished surface. The camera starts at a low-angle front-quarter view and begins a fast, smooth tracking-arc towards the side. [Rapid Transformation Initiation — 0:01–0:03] Transformation triggers instantly. The car’s suspension drops, and the frame begins to fracture into a complex grid of panels. The doors swing open and begin to segment into articulated arm structures. The front hood splits down the center, folding inward to reveal a glowing internal core. The headlights flicker and start to reorient as the "eyes." [Accelerated Feminine Reconfiguration — 0:03–0:07] The mechanical action is dense, overlapping, and fluid, emphasizing graceful but powerful motion. Lower Body: The rear wheels and wheel arches split and rotate downward, reassembling into slender, high-heeled mechanical legs. Torso: The roof and rear engine cover slide and compress, forming a sleek, curvaceous hourglass torso that retains the car’s aerodynamic lines. Arms & Hands: The side mirrors and door panels unfold into delicate but strong hands and fingers. Head: The front bumper and emblem area segment and rise, folding into a feminine-shaped head with a sleek metallic "helmet" visor. [Logical Transformation Constraints — No Spontaneous Appearance] The robot’s "skin" is composed of the car's outer silver panels. The internal frame and wiring emerge from the engine and undercarriage. No parts appear out of thin air; every joint is a reconfigured automotive component. [Transformation Completion — 0:07–0:08.5] The robot stands tall and elegant. The silver panels lock into place with a satisfying "click," revealing glowing blue LED accents in the seams. The silhouette is clearly feminine, humanoid, and sophisticated, reflecting the premium design of the original vehicle. [Final Hero Ending — 0:08.5–0:10] As the robot stabilizes, the camera performs a rapid, smooth zoom-in (Dolly-In) directly to her face. The robot tilts its head slightly, and the optic sensors (eyes) brighten. It brings its mechanical hand to its metallic lips and performs a graceful blowing kiss (fly-kiss) gesture toward the camera. The video ends with a close-up of the face, capturing the reflection of neon lights in its visor just as the kiss is released. [Cinematography Notes] Continuous Motion: No cuts or fades; the camera must transition from the car-tracking shot to the face-zoom seamlessly. Material Consistency: The robot must maintain the exact metallic silver paint, texture, and reflections of the Porsche. Energy: The transformation should feel high-energy and "force-driven," while the final gesture is soft and charismatic.

underwood

19,462 görüntüleme • 4 ay önce

Dagknight technical progress As would be mentioned in a still unshared post by Michael Sutton, the dagknight effort is split into v0 devnet, v1 testnet and v2 mainnet candidate. I’ve been testing the current v0-based implementation in a small devnet with the help of some testers who run nodes and miners with me. The DK work can be thought of as split into two parts: (1) implementing the actual protocol and (2) wiring it up and using it. The testing and development over the last month has been focused on (2). Obviously, DK is a consensus change for selecting parents. What’s not so obvious is that such a change affects DAA, coinbase, IBD, pruning and a lot more. Each of these areas is very sensitive and requires proper understanding to wire correctly. An important consideration and difference from GD is that DK does not focus on maximizing a property like blue work. So to maintain topological properties of blue work, an independent (free) GD implementation is kept running specifically for maintaining blue work. This allows us to keep using the property for topology. Coloring and blue score use the megachain induced by DK. The wiring around DK as of this posting is in a working state, but still needs to be reviewed. Next efforts will be focused on protocol specific components, particularly Tie-Breaking and incremental UMC. Attached are some captures from the internal devnet. The dense DAG image is what happens when things related to DAA or other similar consensus parameter causes a node to insist on their POV. The video is a recent snippet of the KGI running on the devnet showing (perhaps not obviously) DK at work. The current “dagknight” branch is now posted on the main repo. A topic in the Public R&D has been opened for Dagknight development.

Dagknight technical progress As would be mentioned in a still unshared post by Michael Sutton, the dagknight effort is split into v0 devnet, v1 testnet and v2 mainnet candidate. I’ve been testing the current v0-based implementation in a small devnet with the help of some testers who run nodes and miners with me. The DK work can be thought of as split into two parts: (1) implementing the actual protocol and (2) wiring it up and using it. The testing and development over the last month has been focused on (2). Obviously, DK is a consensus change for selecting parents. What’s not so obvious is that such a change affects DAA, coinbase, IBD, pruning and a lot more. Each of these areas is very sensitive and requires proper understanding to wire correctly. An important consideration and difference from GD is that DK does not focus on maximizing a property like blue work. So to maintain topological properties of blue work, an independent (free) GD implementation is kept running specifically for maintaining blue work. This allows us to keep using the property for topology. Coloring and blue score use the megachain induced by DK. The wiring around DK as of this posting is in a working state, but still needs to be reviewed. Next efforts will be focused on protocol specific components, particularly Tie-Breaking and incremental UMC. Attached are some captures from the internal devnet. The dense DAG image is what happens when things related to DAA or other similar consensus parameter causes a node to insist on their POV. The video is a recent snippet of the KGI running on the devnet showing (perhaps not obviously) DK at work. The current “dagknight” branch is now posted on the main repo. A topic in the Public R&D has been opened for Dagknight development.

coderofstuff

52,857 görüntüleme • 5 ay önce

Realistic footage with Seedance 2.0 👇 Prompt: This is handheld documentary footage recorded on an early-2000s consumer DV camcorder at the construction site of the Great Pyramid of Giza. The footage feels like real, imperfect documentation of one of the largest building projects in history. The recording shows hundreds of workers moving massive stone blocks on a large construction ramp. Teams of men are pulling ropes attached to sledges with heavy limestone blocks. Overseers with sticks walk along the lines giving orders. Dust fills the air. In the background, the partially built pyramid rises against the sky. The work is extremely physical and organized. The camera moves along one of the work gangs, following a team of workers as they pull a large block up the ramp. It occasionally tilts up to show the height of the structure. There are natural cuts between different groups of workers and close views of the ropes straining and the stone moving slowly. The movement of the camera feels like someone walking among the workers documenting the labor. The handheld camera shows constant shake, drifting framing, autofocus hunting in the bright sunlight and dust, exposure changes, motion blur, and the typical look of filming heavy physical work with an old DV camcorder. The person filming is clearly moving through the active construction site. Natural sound only: the sound of hundreds of men shouting and grunting in rhythm, ropes creaking under tension, stones scraping on the ground, and general noise of a massive construction site. No music. The result must feel like authentic, raw footage of the construction of the Great Pyramid, captured on an old camcorder.

Realistic footage with Seedance 2.0 👇 Prompt: This is handheld documentary footage recorded on an early-2000s consumer DV camcorder at the construction site of the Great Pyramid of Giza. The footage feels like real, imperfect documentation of one of the largest building projects in history. The recording shows hundreds of workers moving massive stone blocks on a large construction ramp. Teams of men are pulling ropes attached to sledges with heavy limestone blocks. Overseers with sticks walk along the lines giving orders. Dust fills the air. In the background, the partially built pyramid rises against the sky. The work is extremely physical and organized. The camera moves along one of the work gangs, following a team of workers as they pull a large block up the ramp. It occasionally tilts up to show the height of the structure. There are natural cuts between different groups of workers and close views of the ropes straining and the stone moving slowly. The movement of the camera feels like someone walking among the workers documenting the labor. The handheld camera shows constant shake, drifting framing, autofocus hunting in the bright sunlight and dust, exposure changes, motion blur, and the typical look of filming heavy physical work with an old DV camcorder. The person filming is clearly moving through the active construction site. Natural sound only: the sound of hundreds of men shouting and grunting in rhythm, ropes creaking under tension, stones scraping on the ground, and general noise of a massive construction site. No music. The result must feel like authentic, raw footage of the construction of the Great Pyramid, captured on an old camcorder.

TechHalla

69,173 görüntüleme • 1 ay önce

Colmap 4.0 was very recently released, so it inspired me to do some work to better understand it and its new capabilities with Rerun. I want to really understand how Colmap, and in particular, pycolmap, works outside of just calling it via the CLI. So my goal is to use the low-level pycolmap API to log every part of the pipeline. The explicit goal is to have an alternative to the SQLite database that I can utilize. Instead of SQLite, I want to try logging everything directly to rerun and use RRD. This means I can have deep inspectability and still save the features/matches/2D view geometry, but be able to view it directly in rerun. I think this is one of the superpowers that rerun provides; data and visualizations are deeply integrated. As I'm often working with sequential data (videos), I'm going to specifically focus on four things: 1. Monocular Video Simple: Calls high-level APIs such as pycolmap.extract_features, pycolmap.match_sequential, pycolmap.incremental_mapping. These are basically identical to the CLI options and provide a good baseline. 2. Monocular Video Streamed: Take the above high-level APIs and break them down to their iterator version, logging each component in a streamed manner. This way, I can stream the intermediate features to rerun while the extraction/matching/mapping is happening. 3. Rig with unknown calibration: <- WHAT THE VIDEO SHOWS This is probably the most interesting version and the first one I've been working on. It allows one to set a rig between known sensors, such as in VR/AR devices, leading to much better reconstructions with multiple cameras. This is the case where we don't know the calibration a priori, so we have to run a reconstruction twice: once as a normal Colmap reconstruction with no rig constraints, use this to generate the constraints, and then do it again with the newly found rig. 4. Rig with known calibration: This is the RoboCap example, where we have a pre-calibrated set of sensors, so we don't need to run the two reconstructions and also gain better matching between cameras, both spatially and temporally. Again, this leads to a much better reconstruction! Along with all this, GLOMAP has become a first-class global mapper, making it super easy to use directly within pycolmap! I'm excited to do more with this and compare it to things like pycuvslam, vipe, and other alternatives.

Colmap 4.0 was very recently released, so it inspired me to do some work to better understand it and its new capabilities with Rerun. I want to really understand how Colmap, and in particular, pycolmap, works outside of just calling it via the CLI. So my goal is to use the low-level pycolmap API to log every part of the pipeline. The explicit goal is to have an alternative to the SQLite database that I can utilize. Instead of SQLite, I want to try logging everything directly to rerun and use RRD. This means I can have deep inspectability and still save the features/matches/2D view geometry, but be able to view it directly in rerun. I think this is one of the superpowers that rerun provides; data and visualizations are deeply integrated. As I'm often working with sequential data (videos), I'm going to specifically focus on four things: 1. Monocular Video Simple: Calls high-level APIs such as pycolmap.extract_features, pycolmap.match_sequential, pycolmap.incremental_mapping. These are basically identical to the CLI options and provide a good baseline. 2. Monocular Video Streamed: Take the above high-level APIs and break them down to their iterator version, logging each component in a streamed manner. This way, I can stream the intermediate features to rerun while the extraction/matching/mapping is happening. 3. Rig with unknown calibration: <- WHAT THE VIDEO SHOWS This is probably the most interesting version and the first one I've been working on. It allows one to set a rig between known sensors, such as in VR/AR devices, leading to much better reconstructions with multiple cameras. This is the case where we don't know the calibration a priori, so we have to run a reconstruction twice: once as a normal Colmap reconstruction with no rig constraints, use this to generate the constraints, and then do it again with the newly found rig. 4. Rig with known calibration: This is the RoboCap example, where we have a pre-calibrated set of sensors, so we don't need to run the two reconstructions and also gain better matching between cameras, both spatially and temporally. Again, this leads to a much better reconstruction! Along with all this, GLOMAP has become a first-class global mapper, making it super easy to use directly within pycolmap! I'm excited to do more with this and compare it to things like pycuvslam, vipe, and other alternatives.

Pablo Vela

30,070 görüntüleme • 4 ay önce

The Airbus A350 is, without question, the most beautiful airliner gracing the skies today. A masterpiece of modern engineering and design, it combines elegance with efficiency. From every angle, the A350 is perfectly proportioned. Its long, graceful fuselage flows seamlessly into a set of gently curved wings that flex in flight like a bird in motion—an iconic silhouette that instantly sets it apart. The wingtips, with their signature upturned ‘sharklets,’ don’t just look stunning—they whisper of aerodynamic excellence and fuel-saving innovation. Its nose profile is distinctive yet refined, with a gentle curvature and a cockpit visor that gives the aircraft a futuristic, almost predatory presence. And unlike many other widebodies, the A350’s fuselage length is in perfect harmony with its wing span and tail height—there’s a visual symmetry that makes it appear poised, balanced, and utterly graceful, whether taxiing on the tarmac or soaring above the clouds. But it’s not just a pretty face. The A350 is a triumph of technology—built from over 50% carbon-fibre-reinforced composite, powered by next-generation Rolls-Royce Trent XWB engines, and brimming with advanced systems that make it one of the most efficient and capable long-haul aircraft ever built. In an age where function often overrides form, the A350 is a rare exception—a true flying work of art that proves beauty and brains can coexist. 📸 by ig/captainchris Not an ad

aircraftmaintenancengineer

30,458 görüntüleme • 1 yıl önce

Code Interpreter in ChatGPT is incredible! Took me 5 mins to make this game. You can make your own game assets with any AI generator and then ask GPT-4 with Code Interpreter to write code. If you have any problems you can ask it to fix the errors. 1. Write this prompt: "write p5.js code for Asteroids where you control a spaceship with the mouse and shoot asteroids with the left click of the mouse. If your spaceship collides with an asteroid, you lose. If you shoot down all asteroids, you win! I want to use my own textures for the spaceship and for asteroids." 2. Go to Openprocessing website create and save sketch (you'll need to save it before uploading any texture files). Copy paste code from GPT-4 3. Generate texture files and remove backgrounds, for example in Clip Drop 4. Replace names of files with your filenames 5. Run the program 6. If something doesn't work ask GPT-4 to fix it (you can copy an error and paste in GPT-4) like you would ask a human programmer 7. To learn a bit of programming write these prompts to GPT-4: "Act as my programming teacher. Tell me an algorithm of Asteroids game in detail and make names of functions and explain what each of these functions will do. Don't write the code just yet." and then " Can you describe the algorithm overall for a 10-year-old child"

Code Interpreter in ChatGPT is incredible! Took me 5 mins to make this game. You can make your own game assets with any AI generator and then ask GPT-4 with Code Interpreter to write code. If you have any problems you can ask it to fix the errors. 1. Write this prompt: "write p5.js code for Asteroids where you control a spaceship with the mouse and shoot asteroids with the left click of the mouse. If your spaceship collides with an asteroid, you lose. If you shoot down all asteroids, you win! I want to use my own textures for the spaceship and for asteroids." 2. Go to Openprocessing website create and save sketch (you'll need to save it before uploading any texture files). Copy paste code from GPT-4 3. Generate texture files and remove backgrounds, for example in Clip Drop 4. Replace names of files with your filenames 5. Run the program 6. If something doesn't work ask GPT-4 to fix it (you can copy an error and paste in GPT-4) like you would ask a human programmer 7. To learn a bit of programming write these prompts to GPT-4: "Act as my programming teacher. Tell me an algorithm of Asteroids game in detail and make names of functions and explain what each of these functions will do. Don't write the code just yet." and then " Can you describe the algorithm overall for a 10-year-old child"

Kris Kashtanova

1,674,909 görüntüleme • 3 yıl önce

Some insider info regarding Deadlock PvE. The PvE mode features 4 game variants and 7 different stages* (*?). Heroes have a progression system and personal Artifacts (currently one of the testing options). You kill monsters and get a chest containing an item. In one of the variants, chests drop from bosses. In another, they are rewarded for completing challange (potentially along the lines of: "kill 100 monsters using the 1st skill, get upgrades beneficial for the 1st skill"). Items can stack and be upgraded (similarly to Streetbrawl, but like you'll get 4 items, but each duplicate will affect the damage percentage, radius, etc.) The number of items and possible upgrades is limited. There are also legendary items from Streetbrawl, as well as a new type of item (artifacts) that have a separate inventory slot. Bosses can disable your stamina and items, and affect both you and the monsters in general. The final objectives differ for each mode, but exact descriptions are not available yet. --- In reality, this is the exact same thing that happened with StreetBrawl 6 - Valve threw in a wide variety of ideas and is currently testing them. (For those who don't remember, there were initially many different rumors about how StreetBrawl worked, but the final 4v4 system, random items, and round-based combat remained). Information from an anonymous source who previously discussed the mod-split in the Ranked update and the item changes in the Minor Update (prior to the Ranked update)

Some insider info regarding Deadlock PvE. The PvE mode features 4 game variants and 7 different stages* (*?). Heroes have a progression system and personal Artifacts (currently one of the testing options). You kill monsters and get a chest containing an item. In one of the variants, chests drop from bosses. In another, they are rewarded for completing challange (potentially along the lines of: "kill 100 monsters using the 1st skill, get upgrades beneficial for the 1st skill"). Items can stack and be upgraded (similarly to Streetbrawl, but like you'll get 4 items, but each duplicate will affect the damage percentage, radius, etc.) The number of items and possible upgrades is limited. There are also legendary items from Streetbrawl, as well as a new type of item (artifacts) that have a separate inventory slot. Bosses can disable your stamina and items, and affect both you and the monsters in general. The final objectives differ for each mode, but exact descriptions are not available yet. --- In reality, this is the exact same thing that happened with StreetBrawl 6 - Valve threw in a wide variety of ideas and is currently testing them. (For those who don't remember, there were initially many different rumors about how StreetBrawl worked, but the final 4v4 system, random items, and round-based combat remained). Information from an anonymous source who previously discussed the mod-split in the Ranked update and the item changes in the Minor Update (prior to the Ranked update)

DEADLOCK PROJECT 8

204,074 görüntüleme • 2 gün önce