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A really impressive set of Three.js graphics experiments just got open sourced, and these are much more than little visual demos. They are basically reusable procedural systems for oceans, vegetation, fluids and even whole planets. 🔹 Poseidon A real-time FFT ocean running on WebGPU. It simulates large swells, smaller...

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Token Gremlin

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34,448 просмотров • 1 месяц назад •via X (Twitter)

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Комментарии: 5

Фото профиля Mr Pixel | Driftania 🏝
Mr Pixel | Driftania 🏝1 месяц назад

Building an entire planet from tectonic plates down to surface biomes in pure browser code is the kind of overkill I respect. In my own terrain work the erosion step is always where things get spicy.

Фото профиля Camaleón Raro
Camaleón Raro1 месяц назад

rendering procedural simulations via automated agent pipelines removes the need for manual shader tweaking during 3D asset generation. when we batch multi-agent rendering workers, caching intermediate geometry states cut memory overhead by ~60%. are you running rendering workers locally via headless runners or orchestrating through cloud pipelines?

Фото профиля Klark_Max
Klark_Max1 месяц назад

It's funny that as soon as I have tried vibecoding with ThreeJS, I tried generating the world too. It's almost as fun as trying to make a game

Фото профиля Benjamin Springer
Benjamin Springer1 месяц назад

great demos! Thank you! 🙏

Фото профиля kitze 🛠️ tinkerer.club
kitze 🛠️ tinkerer.club1 месяц назад

Jfc

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Fable 5 built this real-time ocean scene directly in the browser using Three.js, WebGPU and TSL, with no engine and no baked assets. The interesting part is not just that the water looks good. The whole system is being simulated: wave spectrum, GPU FFT, foam generation and refracted-ray caustics, all running live. This is exactly where frontier models start becoming genuinely useful for technical graphics work. Not by replacing years of rendering research, but by compressing the path from complex math to a working interactive result. A small, focused scene, but technically very serious. Cc: Adem Vessell
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Fable 5 built this real-time ocean scene directly in the browser using Three.js, WebGPU and TSL, with no engine and no baked assets. The interesting part is not just that the water looks good. The whole system is being simulated: wave spectrum, GPU FFT, foam generation and refracted-ray caustics, all running live. This is exactly where frontier models start becoming genuinely useful for technical graphics work. Not by replacing years of rendering research, but by compressing the path from complex math to a working interactive result. A small, focused scene, but technically very serious. Cc: Adem Vessell

Token Gremlin

21,731 просмотров • 2 месяцев назад

I’ve officially open-sourced SYLVA. 🌲 SYLVA is a fully procedural cinematic forest that runs directly in the browser. Terrain, trees, roots, grass, water, sky, clouds, fog, and weather are generated at runtime using Three.js, WebGL2, and GLSL, without downloaded tree models, textures, HDRIs, or terrain heightmaps. Trees are procedurally grown, terrain is generated mathematically, and the world includes dynamic water, atmosphere, vegetation LODs, rain, lightning, wind, storms, fireflies, birds, and a cinematic camera system. The demo is also interactive. Open the EDITOR to change the environment, visual presets, quality, weather states, wind and storms, move through different times of day, or simply walk around and explore the forest yourself. The project is still actively being developed, and there’s a ridiculous amount left to improve, optimize, and experiment with. But that’s also why I wanted to open it now. SYLVA is MIT-licensed, so you can explore the code, learn from it, modify it, fork it, optimize it, or use it as the foundation for something completely different. Source code: Live demo: Feedback, contributions, experiments, and forks are all welcome. 🌲 (This project is being updated RIGHT NOW.)
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I’ve officially open-sourced SYLVA. 🌲 SYLVA is a fully procedural cinematic forest that runs directly in the browser. Terrain, trees, roots, grass, water, sky, clouds, fog, and weather are generated at runtime using Three.js, WebGL2, and GLSL, without downloaded tree models, textures, HDRIs, or terrain heightmaps. Trees are procedurally grown, terrain is generated mathematically, and the world includes dynamic water, atmosphere, vegetation LODs, rain, lightning, wind, storms, fireflies, birds, and a cinematic camera system. The demo is also interactive. Open the EDITOR to change the environment, visual presets, quality, weather states, wind and storms, move through different times of day, or simply walk around and explore the forest yourself. The project is still actively being developed, and there’s a ridiculous amount left to improve, optimize, and experiment with. But that’s also why I wanted to open it now. SYLVA is MIT-licensed, so you can explore the code, learn from it, modify it, fork it, optimize it, or use it as the foundation for something completely different. Source code: Live demo: Feedback, contributions, experiments, and forks are all welcome. 🌲 (This project is being updated RIGHT NOW.)

Token Gremlin

14,608 просмотров • 1 месяц назад

GPT-6 Astra can already plan, code, and build. The more interesting question is what happens when it can call a dedicated 3D tool at the exact moment a project needs an asset. So we connected Hyper3D Rodin MCP and asked Astra to build an interactive Solar System Explorer. Astra handled the app logic and integration. When it needed 3D models, it called Hyper3D Rodin directly. Hyper3D Rodin generated the required assets, and Astra brought them back into the project and continued building from there. That is where the workflow gets useful. Instead of stopping to search for assets or creating them manually, Astra can keep moving while Hyper3D handles the specialized 3D generation, with more control over the output and assets that are easier to integrate into the final project. The result is a browser-based solar system where the generated 3D models are part of the actual experience, not just outputs sitting in a model viewer.
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GPT-6 Astra can already plan, code, and build. The more interesting question is what happens when it can call a dedicated 3D tool at the exact moment a project needs an asset. So we connected Hyper3D Rodin MCP and asked Astra to build an interactive Solar System Explorer. Astra handled the app logic and integration. When it needed 3D models, it called Hyper3D Rodin directly. Hyper3D Rodin generated the required assets, and Astra brought them back into the project and continued building from there. That is where the workflow gets useful. Instead of stopping to search for assets or creating them manually, Astra can keep moving while Hyper3D handles the specialized 3D generation, with more control over the output and assets that are easier to integrate into the final project. The result is a browser-based solar system where the generated 3D models are part of the actual experience, not just outputs sitting in a model viewer.

GitHub Projects Community

11,097 просмотров • 25 дней назад

At Avalon we are building "Real-time creating" - the ability to generate gameplay ready persistent worlds prompted from text. While others are building real-time video world models, Avalon is building real-time world generation inside a fully playable, persistent multiplayer engine. Internally running at 3840×2180 at 60 FPS. Built on Unreal Engine. Multiplayer by default. Persistent by default. Gameplay-ready by default. This is not a video latent replay. Not a simulation of interaction. It is a real 3D world with physics, logic, and authoritative multiplayer state. Avalon is trained on proprietary Avalon interaction data and powered by a hybrid system that combines language understanding, 3D model generation, procedural systems, and structured gameplay logic synthesis. Players can walk through a live world and generate environments, assets, mechanics, and entirely new gameplay modes using natural language. We accomplish this through a combination of 3D model generation, game logic generation based on our proprietary systems, and AI driven world creation. While other players are inside it. Changes persist instantly. State is synchronized in real time. Creation happens inside the world, not outside of it. Describe a biome. Spawn a civilization. Create a survival mode. Build a dungeon crawler. Launch a new game inside the world. Avalon interprets intent and integrates it directly into the live multiplayer environment. This is not a world model predicting video. This is a gameplay engine that understands language. If you can describe it, you can build it. And others can walk into it instantly.
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At Avalon we are building "Real-time creating" - the ability to generate gameplay ready persistent worlds prompted from text. While others are building real-time video world models, Avalon is building real-time world generation inside a fully playable, persistent multiplayer engine. Internally running at 3840×2180 at 60 FPS. Built on Unreal Engine. Multiplayer by default. Persistent by default. Gameplay-ready by default. This is not a video latent replay. Not a simulation of interaction. It is a real 3D world with physics, logic, and authoritative multiplayer state. Avalon is trained on proprietary Avalon interaction data and powered by a hybrid system that combines language understanding, 3D model generation, procedural systems, and structured gameplay logic synthesis. Players can walk through a live world and generate environments, assets, mechanics, and entirely new gameplay modes using natural language. We accomplish this through a combination of 3D model generation, game logic generation based on our proprietary systems, and AI driven world creation. While other players are inside it. Changes persist instantly. State is synchronized in real time. Creation happens inside the world, not outside of it. Describe a biome. Spawn a civilization. Create a survival mode. Build a dungeon crawler. Launch a new game inside the world. Avalon interprets intent and integrates it directly into the live multiplayer environment. This is not a world model predicting video. This is a gameplay engine that understands language. If you can describe it, you can build it. And others can walk into it instantly.

AVALON

65,913 просмотров • 7 месяцев назад

A guy named Vladimir Romanyuk literally simulated the entire universe on a consumer PC. It is called SpaceEngine. Open it and you can leave Earth, pass the Moon, cross the Solar System, exit the Milky Way, and reach a galaxy billions of light-years away. The entire journey is seamless. You can explore: > Known planets and exoplanets > Black holes with glowing disks > Nebulae and star clusters > Asteroids and comets > Billions of unknown galaxies > Trillions of planetary systems Real objects are placed using data from astronomical catalogs. Where humanity’s maps end, SpaceEngine uses science-based procedural generation to create stars, planets, atmospheres, oceans, and entire galaxies that could exist. You can land on almost any planet or moon and explore its alien landscape. You can accelerate time and watch planets complete their orbits in seconds. You can even pilot spacecraft, enter black holes, explore the universe in VR, or build your own solar systems. Most games create a few worlds and call them enormous. Vladimir built something so large that Earth becomes nearly impossible to find once you leave it.
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A guy named Vladimir Romanyuk literally simulated the entire universe on a consumer PC. It is called SpaceEngine. Open it and you can leave Earth, pass the Moon, cross the Solar System, exit the Milky Way, and reach a galaxy billions of light-years away. The entire journey is seamless. You can explore: > Known planets and exoplanets > Black holes with glowing disks > Nebulae and star clusters > Asteroids and comets > Billions of unknown galaxies > Trillions of planetary systems Real objects are placed using data from astronomical catalogs. Where humanity’s maps end, SpaceEngine uses science-based procedural generation to create stars, planets, atmospheres, oceans, and entire galaxies that could exist. You can land on almost any planet or moon and explore its alien landscape. You can accelerate time and watch planets complete their orbits in seconds. You can even pilot spacecraft, enter black holes, explore the universe in VR, or build your own solar systems. Most games create a few worlds and call them enormous. Vladimir built something so large that Earth becomes nearly impossible to find once you leave it.

Ihtesham Ali

30,438 просмотров • 2 месяцев назад

New Sci-Fi FPS from the developer of Escape from Tarkov "COR3" announced 🔹Set on Mars in the year 2251 🔹You are a private investigator for “History Unfolded", a mysterious company with no identity 🔹They call you an "Executor" who is tasked with investigating the possibility of uncovering files related to experiments that started in year 2170 🔹Managed by a "Handler" named Aurora Strogova, not allowed to contact the "Hirer" or you'll be harmed 🔹Can hire additional help to assist you with the job 🔹There are major factions and companies in the game...SOYUZ, CORE, Terra Mater, Cult of Mars, Astrocorp, United Solar, etc 🔹Fossil Fuels replaced by NIC batteries, which in early days caused incidents and explosions equivalent to 1 ton of TNT - which was abused by radical terrorists 🔹Investigate events like a lost cargo freighter in deep space with bodies on it, weapons experiments, agricultural stations with advanced facilities, and a Sky Lift that detached from a planet 🔹New access terminal called CORIE players can access right now that provides a ton of information, daily decoding tasks, and also has restricted areas
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New Sci-Fi FPS from the developer of Escape from Tarkov "COR3" announced 🔹Set on Mars in the year 2251 🔹You are a private investigator for “History Unfolded", a mysterious company with no identity 🔹They call you an "Executor" who is tasked with investigating the possibility of uncovering files related to experiments that started in year 2170 🔹Managed by a "Handler" named Aurora Strogova, not allowed to contact the "Hirer" or you'll be harmed 🔹Can hire additional help to assist you with the job 🔹There are major factions and companies in the game...SOYUZ, CORE, Terra Mater, Cult of Mars, Astrocorp, United Solar, etc 🔹Fossil Fuels replaced by NIC batteries, which in early days caused incidents and explosions equivalent to 1 ton of TNT - which was abused by radical terrorists 🔹Investigate events like a lost cargo freighter in deep space with bodies on it, weapons experiments, agricultural stations with advanced facilities, and a Sky Lift that detached from a planet 🔹New access terminal called CORIE players can access right now that provides a ton of information, daily decoding tasks, and also has restricted areas

Game Hunter 🔜 TGS

404,289 просмотров • 8 месяцев назад

I built a Three.js rendering study inspired by Tiny Glade’s painterly aesthetic, and got it running at 120fps in the browser. Over the past few weeks, I’ve been studying how stylized games achieve that soft, handcrafted look in real time. Tiny Glade was a huge inspiration, and I wanted to use the browser as a constraint: no compute shaders, no native GPU access, and single-threaded JavaScript. As part of this study, I implemented: - GPU-driven instanced brick walls with procedural noise jitter and elastic build animations - Tree, bush, and flower rendering with billboard card expansion, wind sway, and grow animations - Procedural grass with terrain conformance and interactive push deformation - Animated water with layered noise, interactive ripples, and Fresnel-based reflections - Procedural terrain with slope-aware triplanar materials, dirt paths, and rocks - A 7-pass post-processing stack with TAA, bloom, depth of field, painterly filtering, ACES tonemapping, 3D LUT color grading, and film grain The hardest part wasn’t writing any single shader. It was making all of these systems work together at high frame rates inside WebGL, where every millisecond counts and performance problems compound quickly across animation, materials, post-processing, and scene management. Some techniques in this study were inspired by analyzing Tiny Glade’s rendering approach, while others were original implementations built from scratch from visual reference. That contrast taught me a lot: recreating an effect is one challenge, but designing your own shaders and systems to achieve a similar feel is a very different one. This is a private educational rendering study. Some temporary placeholder content is being used during the research phase, and any public or production version would use original or properly licensed assets. Huge credit to Pounce Light for the incredible art direction and rendering work in Tiny Glade: Three.js #gamedev #webgl #threejs #rendering #graphics #realtimerendering #shaderdev
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I built a Three.js rendering study inspired by Tiny Glade’s painterly aesthetic, and got it running at 120fps in the browser. Over the past few weeks, I’ve been studying how stylized games achieve that soft, handcrafted look in real time. Tiny Glade was a huge inspiration, and I wanted to use the browser as a constraint: no compute shaders, no native GPU access, and single-threaded JavaScript. As part of this study, I implemented: - GPU-driven instanced brick walls with procedural noise jitter and elastic build animations - Tree, bush, and flower rendering with billboard card expansion, wind sway, and grow animations - Procedural grass with terrain conformance and interactive push deformation - Animated water with layered noise, interactive ripples, and Fresnel-based reflections - Procedural terrain with slope-aware triplanar materials, dirt paths, and rocks - A 7-pass post-processing stack with TAA, bloom, depth of field, painterly filtering, ACES tonemapping, 3D LUT color grading, and film grain The hardest part wasn’t writing any single shader. It was making all of these systems work together at high frame rates inside WebGL, where every millisecond counts and performance problems compound quickly across animation, materials, post-processing, and scene management. Some techniques in this study were inspired by analyzing Tiny Glade’s rendering approach, while others were original implementations built from scratch from visual reference. That contrast taught me a lot: recreating an effect is one challenge, but designing your own shaders and systems to achieve a similar feel is a very different one. This is a private educational rendering study. Some temporary placeholder content is being used during the research phase, and any public or production version would use original or properly licensed assets. Huge credit to Pounce Light for the incredible art direction and rendering work in Tiny Glade: Three.js #gamedev #webgl #threejs #rendering #graphics #realtimerendering #shaderdev

Ibrahim Boona

58,625 просмотров • 6 месяцев назад

There is a major concern about Data Centers that are using closed loop cooling systems that’s not being talked about There are a lot of chemicals being put into the water used in these systems. That water has to be flushed out every couple years Whistleblowers say that chemical water is being pushed into our streams and waterways and may have extremely limited cleaning requirements depending on state “I'm getting whistleblowers on the inside saying that they're taking all that waste and they're just running it down into the sewers. They're wanting to go to more closed cooling systems, and in those closed cooling systems, you still are gonna be using chemicals. There's no regulations about every 2 years when you have to clean out a cooling closed system, where are you gonna throw all of those chemicals?” “Taking polluted water and running it through system and dumping it into a river and it flows downstream, that will have a natural dilution, would resolve the issue, and it's not. Even if it's a closed cooling system, that water that's recycling in there, eventually they have to clean those systems. They have to release that water. And are there any regulations to look at what chemicals aren't in that water before we release it into the environment and just create another pollution issue?” “Right now it's a free-for-all out there.” It’s not a complete free for all, it depends on the states and general federal regulations. Discharges from cleaning, blowdown or maintenance are subject to environmental rules There should be compliance reporting but whistleblowers are saying none of this is being followed, they’re saying it’s a “free for all” and the data centers are just planning on the chemicals being diluted as they flow down our waterways We need investigations
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There is a major concern about Data Centers that are using closed loop cooling systems that’s not being talked about There are a lot of chemicals being put into the water used in these systems. That water has to be flushed out every couple years Whistleblowers say that chemical water is being pushed into our streams and waterways and may have extremely limited cleaning requirements depending on state “I'm getting whistleblowers on the inside saying that they're taking all that waste and they're just running it down into the sewers. They're wanting to go to more closed cooling systems, and in those closed cooling systems, you still are gonna be using chemicals. There's no regulations about every 2 years when you have to clean out a cooling closed system, where are you gonna throw all of those chemicals?” “Taking polluted water and running it through system and dumping it into a river and it flows downstream, that will have a natural dilution, would resolve the issue, and it's not. Even if it's a closed cooling system, that water that's recycling in there, eventually they have to clean those systems. They have to release that water. And are there any regulations to look at what chemicals aren't in that water before we release it into the environment and just create another pollution issue?” “Right now it's a free-for-all out there.” It’s not a complete free for all, it depends on the states and general federal regulations. Discharges from cleaning, blowdown or maintenance are subject to environmental rules There should be compliance reporting but whistleblowers are saying none of this is being followed, they’re saying it’s a “free for all” and the data centers are just planning on the chemicals being diluted as they flow down our waterways We need investigations

Wall Street Apes

70,044 просмотров • 2 месяцев назад

Tom Campbell: "The planets and the universe only render themselves when people are looking at them. It's like the video game 'No Man's Sky'. We are living in a simulation." Our reality computes on the fly whatever a player sees. Land on a planet and you get animals, shrubs, lakes and land features. Look away and it is no longer computed. Nothing is saved in memory. Only a set of values that can be regenerated if someone looks again. "It only computed what the person saw. As soon as you looked away, it wasn't computed anymore." "There is no tree. There is no forest. If nobody is there and it is not being observed, it is not being rendered." Stars are just little dots of light. They do not have to come from a sun 20 light years away. When the sun comes up or you go to sleep they stop being rendered for you. We are living in a simulation computed by consciousness.
3:40

Tom Campbell: "The planets and the universe only render themselves when people are looking at them. It's like the video game 'No Man's Sky'. We are living in a simulation." Our reality computes on the fly whatever a player sees. Land on a planet and you get animals, shrubs, lakes and land features. Look away and it is no longer computed. Nothing is saved in memory. Only a set of values that can be regenerated if someone looks again. "It only computed what the person saw. As soon as you looked away, it wasn't computed anymore." "There is no tree. There is no forest. If nobody is there and it is not being observed, it is not being rendered." Stars are just little dots of light. They do not have to come from a sun 20 light years away. When the sun comes up or you go to sleep they stop being rendered for you. We are living in a simulation computed by consciousness.

Interstellar

12,507 просмотров • 1 месяц назад

Astra can create beautiful three.js UIs entirely in code. You don't need an assets library or MCP to create detailed 3D models. These are all code and are easy to customize for your agent. Give Astra a video, URL, or code reference, then ask it to keep comparing the result against the reference and fixing mistakes. Liquid Glass, shaders, motion design, procedural three.js models, and full environments. All from a few prompts. Some prompts I used: "Recreate this in a single HTML file with three.js. Keep comparing it against the reference and fix any differences." "Add Liquid Glass buttons. On hover, animate the lighting around the borders and make the background gradients move slightly with the pointer. Add subtle particles." "Improve the lighting, edges, and modeling. Give the keys more depth and verify the result against the real MacBook." Too many projects I could open-source. Let me know which one should I release.
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Astra can create beautiful three.js UIs entirely in code. You don't need an assets library or MCP to create detailed 3D models. These are all code and are easy to customize for your agent. Give Astra a video, URL, or code reference, then ask it to keep comparing the result against the reference and fixing mistakes. Liquid Glass, shaders, motion design, procedural three.js models, and full environments. All from a few prompts. Some prompts I used: "Recreate this in a single HTML file with three.js. Keep comparing it against the reference and fix any differences." "Add Liquid Glass buttons. On hover, animate the lighting around the borders and make the background gradients move slightly with the pointer. Add subtle particles." "Improve the lighting, edges, and modeling. Give the keys more depth and verify the result against the real MacBook." Too many projects I could open-source. Let me know which one should I release.

Meng To

105,156 просмотров • 29 дней назад

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Introducing Rocket 1.0. A single platform where business thinking, competitive intelligence, and production-grade building share one workspace and one memory. Every decision is informed. Every build starts from the full picture. Nothing is lost between steps, tools, or teams. 🔹If you are a founder, you validate before you commit. 🔹If you lead a product team, strategy and execution live in the same place for the first time. 🔹If you lead sales, you walk into every room knowing exactly what the other side is facing. 🔹If you lead marketing, the competitive signal reaches you before the campaign, not after it. 🔹If you run a business, every decision starts from a real answer instead of a best guess. This is Vibe Solutioning. Not just better planning but also faster execution. A better starting point for everything your business builds, decides, and acts on.

Rocket

409,605 просмотров • 6 месяцев назад

🚀 Announcing Echo — our new frontier model for 3D world generation. Echo turns a simple text prompt or image into a fully explorable, 3D-consistent world. Instead of disconnected views, the result is a single, coherent spatial representation you can move through freely. This is part of a bigger shift in AI: from generating pixels and tokens to generating spaces. Echo predicts a geometry-grounded 3D scene at metric scale, meaning every novel view, depth map, and interaction comes from the same underlying world — not independent hallucinations. Once generated, the world is interactive in real time. You control the camera, explore from any angle, and render instantly — even on low-end hardware, directly in the browser. High-quality 3D world exploration is no longer gated by expensive equipment. Under the hood, Echo infers a physically grounded 3D representation and converts it into a renderable format. For our web demo, we use 3D Gaussian Splatting (3DGS) for fast, GPU-friendly rendering — but the representation itself is flexible and can be easily adapted. Why this matters: consistent 3D worlds unlock real workflows — digital twins, 3D design, game environments, robotics simulation, and more. From a single photo or a line of text, Echo builds worlds that are reliable, editable, and spatially faithful. Echo also enables scene editing and restyling. Change materials, remove or add objects, explore design variations — all while preserving global 3D consistency. Editing no longer breaks the world. This is only the beginning. Echo is the foundation for future world models with dynamics, physical reasoning, and richer interaction — environments that don’t just look right, but behave right. Explore the generated worlds on our website and sign up for the closed beta. The era of spatial intelligence starts here. 🌍 #Echo #WorldModels #SpatialAI #3DFoundationModels Check it out:
1:07

🚀 Announcing Echo — our new frontier model for 3D world generation. Echo turns a simple text prompt or image into a fully explorable, 3D-consistent world. Instead of disconnected views, the result is a single, coherent spatial representation you can move through freely. This is part of a bigger shift in AI: from generating pixels and tokens to generating spaces. Echo predicts a geometry-grounded 3D scene at metric scale, meaning every novel view, depth map, and interaction comes from the same underlying world — not independent hallucinations. Once generated, the world is interactive in real time. You control the camera, explore from any angle, and render instantly — even on low-end hardware, directly in the browser. High-quality 3D world exploration is no longer gated by expensive equipment. Under the hood, Echo infers a physically grounded 3D representation and converts it into a renderable format. For our web demo, we use 3D Gaussian Splatting (3DGS) for fast, GPU-friendly rendering — but the representation itself is flexible and can be easily adapted. Why this matters: consistent 3D worlds unlock real workflows — digital twins, 3D design, game environments, robotics simulation, and more. From a single photo or a line of text, Echo builds worlds that are reliable, editable, and spatially faithful. Echo also enables scene editing and restyling. Change materials, remove or add objects, explore design variations — all while preserving global 3D consistency. Editing no longer breaks the world. This is only the beginning. Echo is the foundation for future world models with dynamics, physical reasoning, and richer interaction — environments that don’t just look right, but behave right. Explore the generated worlds on our website and sign up for the closed beta. The era of spatial intelligence starts here. 🌍 #Echo #WorldModels #SpatialAI #3DFoundationModels Check it out:

SpAItial AI

177,073 просмотров • 9 месяцев назад

I built an app in Softr for the HVAC industry to solve some crucial problems. The problem is that those in the HVAC industry and similar industries like construction, plumbing, and electrical do not have one source of truth where: 1. Their clients can request for thier services. 2. Clients can be onboarded after they make a payment. 3. They store the information and bio data of their technicians. 4. They assign tasks to their technicians. 5. Technicians can track onsite jobs with pictures in real time of when working. 6. Clients see the progress of their projects. 7. Invoices and quotations from paid clients can be tracked. 8. Technicians borrow assets from the company, and they can be tracked. 9. There is a database where every individual, from technicians to admin and clients, are all stored. 10. Login details from every individual are secured and they can only see things that are their business without seeing that of another person, be ita technician or a client. These and many more are what people in these industries face as a challenge. I came up with a solution that addresses all these problems. I built a workflow that also auto-populated the users table in the database with technicians and clients when the records are filled in the technician and client tables, respectively. There is also a workflow that sends an email to the admin when a client makes a request from the portal. Taking advantage of the database, workflow, and portal gave a full-blown application for the HVAC industry. If you are in the construction, plumbing, electrical, or HVAC industry and you need a similar build, reach out, and I will be more than happy to replicate this for you or something similar in Softr.
14:08

I built an app in Softr for the HVAC industry to solve some crucial problems. The problem is that those in the HVAC industry and similar industries like construction, plumbing, and electrical do not have one source of truth where: 1. Their clients can request for thier services. 2. Clients can be onboarded after they make a payment. 3. They store the information and bio data of their technicians. 4. They assign tasks to their technicians. 5. Technicians can track onsite jobs with pictures in real time of when working. 6. Clients see the progress of their projects. 7. Invoices and quotations from paid clients can be tracked. 8. Technicians borrow assets from the company, and they can be tracked. 9. There is a database where every individual, from technicians to admin and clients, are all stored. 10. Login details from every individual are secured and they can only see things that are their business without seeing that of another person, be ita technician or a client. These and many more are what people in these industries face as a challenge. I came up with a solution that addresses all these problems. I built a workflow that also auto-populated the users table in the database with technicians and clients when the records are filled in the technician and client tables, respectively. There is also a workflow that sends an email to the admin when a client makes a request from the portal. Taking advantage of the database, workflow, and portal gave a full-blown application for the HVAC industry. If you are in the construction, plumbing, electrical, or HVAC industry and you need a similar build, reach out, and I will be more than happy to replicate this for you or something similar in Softr.

Ada || Airtable, Zapier & Make.com

28,843 просмотров • 10 месяцев назад

How many of you actually know how "what you eat" grows? 🤔 I never learned crop science in school. I learned it by walking around our farm with my father, who showed me different crops and explained how they grow. But not everyone has access to a farm, so I built a 3D Crop Science application in Three.js using Claude Opus 5 to make that learning experience more visual and interactive. It is an exploration of different types of seeds where each seed has three different stages. The first stage shows the whole seed. The second stage is a cross section that shows what is inside the seed and how it grows. The third stage shows the germination phase through a 3D model. There are 24 models in total. The original models were 1,349.6 MB, which Claude optimized down to just 11.6 MB in total. All of the 3D models were generated using Tripo. Claude also created visual information for each seed showing details like seed type, storage tissue and germination phase. Each seed also has a YouTube video that shows how it actually grows in the real world. There is also a section showing where each seed is commonly grown using both a 3D globe and a flat map. You can explore different regions and click on specific areas to see more information about where that seed is grown. The entire experience is fully responsive and also includes quizzes that you can take in both normal and 3D formats. I strongly believe education becomes much more effective when you can see, interact, watch and explore instead of relying only on textbooks. Live: Code:
1:14

How many of you actually know how "what you eat" grows? 🤔 I never learned crop science in school. I learned it by walking around our farm with my father, who showed me different crops and explained how they grow. But not everyone has access to a farm, so I built a 3D Crop Science application in Three.js using Claude Opus 5 to make that learning experience more visual and interactive. It is an exploration of different types of seeds where each seed has three different stages. The first stage shows the whole seed. The second stage is a cross section that shows what is inside the seed and how it grows. The third stage shows the germination phase through a 3D model. There are 24 models in total. The original models were 1,349.6 MB, which Claude optimized down to just 11.6 MB in total. All of the 3D models were generated using Tripo. Claude also created visual information for each seed showing details like seed type, storage tissue and germination phase. Each seed also has a YouTube video that shows how it actually grows in the real world. There is also a section showing where each seed is commonly grown using both a 3D globe and a flat map. You can explore different regions and click on specific areas to see more information about where that seed is grown. The entire experience is fully responsive and also includes quizzes that you can take in both normal and 3D formats. I strongly believe education becomes much more effective when you can see, interact, watch and explore instead of relying only on textbooks. Live: Code:

The Bugged Dev

45,652 просмотров • 1 месяц назад

✨ I've been using #Unity3D for 12 years. ✨ I'm using Blender's GeoNodes for a procedural mesh that's realtime-animated with a custom shader in Unity. ---(reminiscing, reflection follows)-- At some point, you realize it's 'all' states, relationships, and data/information. What is, isn't, and how they relate, subject to laws, principles. 🌌 Define some latent space -> atomics, data -> simulation/form -> information. Like a grid-texture of pixels that are to mean something, represent something. And they are processed/simulated in some way by some measure. So that you get some transformed, meaningful result. What is possible, here? -- in that space. (by the parameters, and features *defined*). 🧊 Likewise, a 3D field-volume in which things exist, being and not being. It may sound mystical, but I mean it literally: the definition of what things are, and are not, and what that means as a relationship (to something[s]). Take, for example a sphere, or box collider primitive. 🪩 Sphere's and circles are the most simple colliders, involving only a point (where they are) and radius (distance from that point, as a center) to define. 💥 The equations to calculate collisions against and between spheres is also relatively straightforward. Implementation of that is a part of building primitive relationships and definitions for simulations. 🎇 It follows, that for a particle system, the data structure of a single element/particle is (about) some point that simulates in some way. Boids and fluid sims have this in common. It seems this year (so far) has been ~about realizing that (with greater lucidity, at least), and learning it all relates to the nature of the universe. Involving simulations, and data flow-control... Ultimately, all these things are objective to us, in that we learned and were taught about how things work. And all the same, *I'm* still learning, too. 👀 #blender #b3d #geometrynodes #gamedev
0:41

✨ I've been using #Unity3D for 12 years. ✨ I'm using Blender's GeoNodes for a procedural mesh that's realtime-animated with a custom shader in Unity. ---(reminiscing, reflection follows)-- At some point, you realize it's 'all' states, relationships, and data/information. What is, isn't, and how they relate, subject to laws, principles. 🌌 Define some latent space -> atomics, data -> simulation/form -> information. Like a grid-texture of pixels that are to mean something, represent something. And they are processed/simulated in some way by some measure. So that you get some transformed, meaningful result. What is possible, here? -- in that space. (by the parameters, and features *defined*). 🧊 Likewise, a 3D field-volume in which things exist, being and not being. It may sound mystical, but I mean it literally: the definition of what things are, and are not, and what that means as a relationship (to something[s]). Take, for example a sphere, or box collider primitive. 🪩 Sphere's and circles are the most simple colliders, involving only a point (where they are) and radius (distance from that point, as a center) to define. 💥 The equations to calculate collisions against and between spheres is also relatively straightforward. Implementation of that is a part of building primitive relationships and definitions for simulations. 🎇 It follows, that for a particle system, the data structure of a single element/particle is (about) some point that simulates in some way. Boids and fluid sims have this in common. It seems this year (so far) has been ~about realizing that (with greater lucidity, at least), and learning it all relates to the nature of the universe. Involving simulations, and data flow-control... Ultimately, all these things are objective to us, in that we learned and were taught about how things work. And all the same, *I'm* still learning, too. 👀 #blender #b3d #geometrynodes #gamedev

Mirza Beig

105,248 просмотров • 10 месяцев назад

I've been working on web projects with Three.js more and more lately — 2D, 3D, XR — and the one thing I've noticed is the lack of tools compared to game engines. That's why I decided to start building on the side a library of 3D assets that are actually little programs, AI-native, and fully customizable. I called this @polyfork_ , and it's already being used by dozens of people that have an AI centric workflow, since the website can be fully understood and used by agents. Assets are being built each day, at a rate of 100+ a week, and I'm planning to make it the biggest programmatic-3D library on the internet. Almost half of the models are free, and I opened slots for "founding" members, who can make a one-time payment for lifetime access, with access to all current models and kits, plus everything built from now on. Get one before they run out.
0:29

I've been working on web projects with Three.js more and more lately — 2D, 3D, XR — and the one thing I've noticed is the lack of tools compared to game engines. That's why I decided to start building on the side a library of 3D assets that are actually little programs, AI-native, and fully customizable. I called this @polyfork_ , and it's already being used by dozens of people that have an AI centric workflow, since the website can be fully understood and used by agents. Assets are being built each day, at a rate of 100+ a week, and I'm planning to make it the biggest programmatic-3D library on the internet. Almost half of the models are free, and I opened slots for "founding" members, who can make a one-time payment for lifetime access, with access to all current models and kits, plus everything built from now on. Get one before they run out.

Lucas Martinic

40,621 просмотров • 2 месяцев назад

I think a lot of people are missing what GPT-6 can really do because they're using it out of the box. Give it the right free MCPs and skills, and it starts to feel like magic. Start with Blender MCP. In my tests, it works faster and uses fewer tokens than computer use. If you want to have fun with procedural modeling, go for it. For more detailed models, I use 3D generators and let GPT handle the processing, rigging and animation. You don't need to burn tokens making it build every detail from scratch. I've spent the last six months putting this setup together. These are the tools I actually use for Blender, Unity, Godot and Unreal, including my 3D generation tools. Full breakdown:
0:56

I think a lot of people are missing what GPT-6 can really do because they're using it out of the box. Give it the right free MCPs and skills, and it starts to feel like magic. Start with Blender MCP. In my tests, it works faster and uses fewer tokens than computer use. If you want to have fun with procedural modeling, go for it. For more detailed models, I use 3D generators and let GPT handle the processing, rigging and animation. You don't need to burn tokens making it build every detail from scratch. I've spent the last six months putting this setup together. These are the tools I actually use for Blender, Unity, Godot and Unreal, including my 3D generation tools. Full breakdown:

Stefan 3D AI

26,513 просмотров • 25 дней назад

From Eric Vishria on how the top AI founders are building products completely opposite of the SaaS era: "One of the things that is really different in the AI world versus the SaaS world, is that in the SaaS world, over and over again, you had people who really understood the customer. And the problem. And then they understood a domain. They understood what the technology was more or less capable of. But it wasn't a real question of if you could build something or not. For example, take Salesforce, Workday, and ServiceNow. CRM existed before Salesforce. HR management existed before Workday. Same thing with ServiceNow. So in every case, Salesforce followed Siebel. Workday followed Peoplesoft. ServiceNow followed Peregrine and Remedy, and others. So they were just kind of, cloud SaaS versions of the prior generation product. They just understood the customers. They understood the problem. And they were just like, here's a better version. And that evolved a little bit over time in SaaS land. But that's what it is. And so product development in that way was done by people who really understood the customer and the problems. And then just took advantage of the next wave. And this is almost diametrically opposite of product development in the AI era. When I look at the teams that are having the most success today, they have intimate knowledge of the models. They are right on the frontier of understanding which models are better at what, and why, and when. And what they're going to be good at and what they're not going to be good at. And what they're spending their time on, is figuring out how do I apply this capability of this model to this domain or to this user. So they're actually working inside out or technology out, versus customer problem in. And of course, they understand the customer problem. And a lot of times they have firsthand knowledge of it. But they're really close to the metal and capability, and they're applying it. And I think this is a really different way to develop products than in SaaS. I started my career as a product manager a long time ago, and it's almost the complete opposite of everything you learned. "Listen to the customer, understand it, then bring it back to the engineering and product teams." If you did that right now, ask a bunch of customers what they want out of AI, and you brought it back, for the most part, it may not be possible today with today's technology. Whereas the teams that are winning right now really understand the technology and are applying it out. And so I think this reversal matters. I think it's a big difference in terms of how companies are getting built. And maybe even the types of entrepreneurs that will be successful. I'm not sure. You're seeing some real change there. Look at the Bret Taylor's at Sierra. That's a super, super technical founder who really gets it. Brett and Clay really get it. You look at Michael and his co-founders at Cursor. They're super technical founders and they get it. They all really understand what these things can and can't do. And that's a pretty different dynamic relative to the way the best SaaS companies got built." Link in bio for the full conversation going deep on the current class of startups going from zero to $100m+ in ARR within 12 months.
5:13

From Eric Vishria on how the top AI founders are building products completely opposite of the SaaS era: "One of the things that is really different in the AI world versus the SaaS world, is that in the SaaS world, over and over again, you had people who really understood the customer. And the problem. And then they understood a domain. They understood what the technology was more or less capable of. But it wasn't a real question of if you could build something or not. For example, take Salesforce, Workday, and ServiceNow. CRM existed before Salesforce. HR management existed before Workday. Same thing with ServiceNow. So in every case, Salesforce followed Siebel. Workday followed Peoplesoft. ServiceNow followed Peregrine and Remedy, and others. So they were just kind of, cloud SaaS versions of the prior generation product. They just understood the customers. They understood the problem. And they were just like, here's a better version. And that evolved a little bit over time in SaaS land. But that's what it is. And so product development in that way was done by people who really understood the customer and the problems. And then just took advantage of the next wave. And this is almost diametrically opposite of product development in the AI era. When I look at the teams that are having the most success today, they have intimate knowledge of the models. They are right on the frontier of understanding which models are better at what, and why, and when. And what they're going to be good at and what they're not going to be good at. And what they're spending their time on, is figuring out how do I apply this capability of this model to this domain or to this user. So they're actually working inside out or technology out, versus customer problem in. And of course, they understand the customer problem. And a lot of times they have firsthand knowledge of it. But they're really close to the metal and capability, and they're applying it. And I think this is a really different way to develop products than in SaaS. I started my career as a product manager a long time ago, and it's almost the complete opposite of everything you learned. "Listen to the customer, understand it, then bring it back to the engineering and product teams." If you did that right now, ask a bunch of customers what they want out of AI, and you brought it back, for the most part, it may not be possible today with today's technology. Whereas the teams that are winning right now really understand the technology and are applying it out. And so I think this reversal matters. I think it's a big difference in terms of how companies are getting built. And maybe even the types of entrepreneurs that will be successful. I'm not sure. You're seeing some real change there. Look at the Bret Taylor's at Sierra. That's a super, super technical founder who really gets it. Brett and Clay really get it. You look at Michael and his co-founders at Cursor. They're super technical founders and they get it. They all really understand what these things can and can't do. And that's a pretty different dynamic relative to the way the best SaaS companies got built." Link in bio for the full conversation going deep on the current class of startups going from zero to $100m+ in ARR within 12 months.

The Peel

209,752 просмотров • 1 год назад

Inferact CEO Simon Mo says open and closed models are converging. The moat is environment: "What really differentiates open-weight models from closed-weight models? In the end, there's not much differentiation. It's more about the distribution strategy and go-to-market strategy. Capability-wise, I don't really see a big gap, not even today." "One of the most important parts is just the data. It's about who gets what data, and then what are the environments you are building to let the model improve on itself." "For Moonshot, they have built some of the best environments for front-end coding... the ability for this model to code and then see what the rendered code is, and then continue looping in this iterative process." "Now, this is about their environment to improve the model. It's not about just source data. It's not about where they get the data from. Rather, it's who can build the best environment and who can make the most optimization and algorithmic choices to leverage all this learning from this environment." "The next year is all gonna be about that: how open-weight model labs are differentiating and really getting the model to meet the real world." Simon Mo
2:06

Inferact CEO Simon Mo says open and closed models are converging. The moat is environment: "What really differentiates open-weight models from closed-weight models? In the end, there's not much differentiation. It's more about the distribution strategy and go-to-market strategy. Capability-wise, I don't really see a big gap, not even today." "One of the most important parts is just the data. It's about who gets what data, and then what are the environments you are building to let the model improve on itself." "For Moonshot, they have built some of the best environments for front-end coding... the ability for this model to code and then see what the rendered code is, and then continue looping in this iterative process." "Now, this is about their environment to improve the model. It's not about just source data. It's not about where they get the data from. Rather, it's who can build the best environment and who can make the most optimization and algorithmic choices to leverage all this learning from this environment." "The next year is all gonna be about that: how open-weight model labs are differentiating and really getting the model to meet the real world." Simon Mo

a16z

39,424 просмотров • 1 месяц назад