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Instead of using UE, I built my own Vulkan engine for full control over rendering and memory. Features: - Data-driven rendering - Preallocated arenas, no runtime heap - Cascaded shadow maps - Temporal AA Currently building a fully 3D voxel GUI. #cubeworld #vulkan

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Wolfram von Funck

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445,270 Aufrufe • vor 11 Monaten •via X (Twitter)

Wissenschaft & TechnologieGaming#cubeworld#vulkan
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I built my own graphics library and got a whole map of my city onto a device with only 64kb of free RAM using my own rendering method written entirely in C & assembly, and a converter that take GeoJSON files and compresses them - this one went from 5mb to 34kb in my proprietary binary format, uses linedraw vector rendering to keep the entire memory buffer at only 8kb of RAM whilst tiling larger maps In short Screw google, aint no reason maps needs to be gigabytes of RAM to use

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Working on Sparse Volumetric Light-maps. Thanks to CynicatPro🎃 for pointing me at Unreal's version. In a nutshell it's just another sparse voxel data structure. My implementation is, no doubt, different from Epic Games Store's own. I'm using 4x4x4 probe grid with intermediate nodes having very wide branching factor of 64 as well (4x4x4). I liked the parameters that Unreal is using, of limiting both total memory as well as the lowest level of detail, which is common in sparse grid implementations. Here's Bistro scene with just 1Mb limit. This is roughly equivalent to a 512x512 lightmap texture in 2d, except surface light maps require unique UVs and you typically get very little detail out of 512 resolution texture with a lot of light leaking. There is also no directional response. My implementation encodes second-order spherical harmonics for each probe (9 coefficients), encoding RGB channels as RGBE9995 (4 bytes). So far only worked on the structure, actual bake is yet to come. I've been eyeing sparse voxel structures for a while now, and have been studying them roughly since the GigaVoxel paper by Cyril Crassin but never really implemented anything for the GPU before. I was always the BVH-kind of guy. It's a fascinating topic. --- Stats for the scene: --- Total memory usage: 1.000 MB Node count: 609 Unique probe count: 24,025 Probe reuse: 38.36 % Unexpanded nodes: 15,714 --- Again, note that there is no GI going on here, only the structure of the probe tree and the algorithm for building it from a given scene.
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There's so much focus on "how can AI do my work for me?" I think the more important question is "what work can I now do with AI that I would have never attempted before?" Earlier this year I wrote freestiler, a vector tiling engine for R and Python, with the help of Claude and Codex. I knew what the ideal engine looked like and how it would work at a high level. I didn't know how to put it together, and I don't know Rust, the language I wanted under the hood. Previously I would never have attempted this project as the ROI wasn't there. It would have taken me a year or more to learn the internals of a vector tiling engine and enough Rust to implement one. With Opus-level models, I could take it on. freestiler now powers all my vector tiling pipelines, including the map below rendering 143 million jobs from LODES, and it has 114 GitHub stars. Building this way has required a different set of skills. I don't review the code line by line. I set up adversarial agents to do that and write the test suites. What I review is the architecture, the behavior, and the results. Agent teams surface findings and explain their reasoning; I evaluate and critique. My job isn't to stress over code formatting, but instead to focus on questions like whether the engine is designed right, whether the output is correct, and if the UX makes sense. This means that I haven't "replaced my work." I've taken on entirely new work, with the help of agents, that I would have never done otherwise. It has taken some getting used to shipping code I haven't personally typed. In the old way of working, I built understanding through writing that code. Now I build understanding through managing the project - writing a spec, reviewing structure, evaluating UX. And that's helped me think a whole lot bigger in terms of what I can now do.

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fine, i'll build it myself, open source ofc Launching Three-Maps, a rapid blockout editor for building game maps for threejs games: Create a floor plan in 2D, automatically generate 3D levels from it, edit them, export to .glb and use in your games (see end of video) Features: - Floorplan 2D: A 2D canvas to map out the floor - Edit Mode for Objects: Edit Vertices/Edges/Faces, extrude, bevel, fillet and chamfer - Brush Mode: Rapidly build map elements with a RealtimeCSG like experience. Cubes, Stairs, Doors, Arch, Cylinder, Custom polygons. Yes, you can even curve the stairs - Modifiers: Yes, you read that right, slap that array modifier on your pillar and call it a day - Terrain Generator: Perlin, Voronoi, you name it. Oh yes, you can rasterize it and edit every single vertex in edit mode. Keyboard shortcuts are mostly same as blender to activate that muscle memory (G/R/S, axis lock XYZ) Soon: - AI integration. Boot that MCP and directly connect your fav AI agent to build the floorplan, generate 3D maps and more (you will love how this movie ends) It's a little rough and in early, very early alpha so come and join as a contributor instead of calling it slop It's all vibe coded btw, i have no idea what the code does I need this to build my game, as i'm a total blender noob and threejs is great, so why not? Outshipping every CAD and 3D startup just because i want to build a game, that's how you accelerate

robot 2.0

106,304 Aufrufe • vor 4 Monaten

DIGITAL TWIN UPDATE: The Unreal Engine digital twin project is CANCELLED! WE ARE OPEN SOURCING THE WORK!!!!!!! Instead, I'm building an end-to-end land management platform I'm calling Mazzap because it's an app and it's a map and also I'm Mr. Mazza. I'm also not calling a digital twin anymore; I'm calling it a V.E.I.L. which stands for Virtually Embodied Intelligent Land which serves the dual purpose of sounding way cooler and also conveys the long-term aims of the prject way better. With Mazzap anyone can easily generate a veil with nothing but publicly available data (and some photogrammetry objects if you so choose). Everything is perfectly georefrenced and you can right-click anywhere on your veil to get coordinates you can plug into google maps yourself. The next step for this is going to be building a survey companion mobile app so you can get field data yourself complete with attribute tables to drop in to get even HIGHER fidelity data than USGS. My stretch goal is using something like SAM 3D (but better) to generate georefrenced 3d tree assets based on the real trees on your land (which will eventually lead to growth and fruiting simulators based on your soil and hydrology data). Then again maybe that's not the next step; maybe the next step is plumbing in IoT devices so you can view assets in real time on your land. GPS trackers on the sheep, or maybe data from your solar controller. Or maybe it's up to you, because it's completely open source and it has an agents markdown file ready for your own coding agent to read and adapt for your purposes (did I mention this is vibecloded slop? sowwyyyy) Watch demo below and see how you can go from zero to beautifully rendered 3d map of your property in less than 15 minutes! If you're coming in cold to all this, below in the QT is a nested thread of reverse chronological tweets of my work on this (in unreal) so far.
5:21

DIGITAL TWIN UPDATE: The Unreal Engine digital twin project is CANCELLED! WE ARE OPEN SOURCING THE WORK!!!!!!! Instead, I'm building an end-to-end land management platform I'm calling Mazzap because it's an app and it's a map and also I'm Mr. Mazza. I'm also not calling a digital twin anymore; I'm calling it a V.E.I.L. which stands for Virtually Embodied Intelligent Land which serves the dual purpose of sounding way cooler and also conveys the long-term aims of the prject way better. With Mazzap anyone can easily generate a veil with nothing but publicly available data (and some photogrammetry objects if you so choose). Everything is perfectly georefrenced and you can right-click anywhere on your veil to get coordinates you can plug into google maps yourself. The next step for this is going to be building a survey companion mobile app so you can get field data yourself complete with attribute tables to drop in to get even HIGHER fidelity data than USGS. My stretch goal is using something like SAM 3D (but better) to generate georefrenced 3d tree assets based on the real trees on your land (which will eventually lead to growth and fruiting simulators based on your soil and hydrology data). Then again maybe that's not the next step; maybe the next step is plumbing in IoT devices so you can view assets in real time on your land. GPS trackers on the sheep, or maybe data from your solar controller. Or maybe it's up to you, because it's completely open source and it has an agents markdown file ready for your own coding agent to read and adapt for your purposes (did I mention this is vibecloded slop? sowwyyyy) Watch demo below and see how you can go from zero to beautifully rendered 3d map of your property in less than 15 minutes! If you're coming in cold to all this, below in the QT is a nested thread of reverse chronological tweets of my work on this (in unreal) so far.

Zy

54,025 Aufrufe • vor 4 Monaten

"Both are tools that can accomplish the same task but one is smaller and easier for anyone to own and both require a human’s creative touch to truly shine." -- This is how I feel about Suno. My whole job is working with creators & musicians, and I get to watch how they use this tool to make their own music and ideas shine. I get to see people release new EPs and albums using Suno. People are cutting up stems in Suno, using their own productions & voice notes and getting to have full creative control, but Suno makes it easier, more affordable for them to make the music they love -- as the iPhone did. Suno Studio was built as a complement for DAWs and a way to solve pain points we've heard from musicians over and over again -- how do I get clean stems, how do I edit specific stems, how do I extract stems back to my DAW? Musicians are spending hours and hours still making songs that they feel proud of on Suno. I don't know that you can discount the creativity involved in their process without watching them at work.
1:57

"Both are tools that can accomplish the same task but one is smaller and easier for anyone to own and both require a human’s creative touch to truly shine." -- This is how I feel about Suno. My whole job is working with creators & musicians, and I get to watch how they use this tool to make their own music and ideas shine. I get to see people release new EPs and albums using Suno. People are cutting up stems in Suno, using their own productions & voice notes and getting to have full creative control, but Suno makes it easier, more affordable for them to make the music they love -- as the iPhone did. Suno Studio was built as a complement for DAWs and a way to solve pain points we've heard from musicians over and over again -- how do I get clean stems, how do I edit specific stems, how do I extract stems back to my DAW? Musicians are spending hours and hours still making songs that they feel proud of on Suno. I don't know that you can discount the creativity involved in their process without watching them at work.

eat soup

129,494 Aufrufe • vor 7 Monaten

It's PS5 RDNA 1.5 all over again, and reading responses, like a certain fandom never gets tired of being let down or uninformed. There's reasons PS5 often outperforms Xbox Series X despite the latter having 44% more compute than PS5 and being "full RDNA 2", which Digital Foundry did a video on. As I said at the start of the gen, most RDNA2 features Xbox/PC fans claim PS5 is missing, it was unlikely to use as they're Microsoft DirectX RDNA tie in features, and PS5 doesn't use DX but instead its own proprietary custom API called AGC. Why would PlayStation push for Microsoft DirectX RDNA features, when they don't use DirectX? Any AGC API specific graphics features PS5 uses (that Xbox wouldn't have) are not widely publicly advertised, as PlayStation don't need to advertise them the way Microsoft does due to their PC DirectX market. Thus every customisation PS5 has (which Kepler seemingly glosses over or doesn't recognise), from its faster clockspeeds, cache scrubbers, I/O set up, CPU alleviating decompression, DMA controllers and processors, geometry engine etc, will have been specifically designed around AGC or vice versa, NOT DirectX RDNA2 features. PS6 will be no different. There may be DirectX RDNA5 features they do not need or use, but there will inevitably be other unique customisations of their own and for their OWN proprietary API instead, no doubt bolstered by Amethyst custom features from their partnership with AMD. If history is any indicator, PlayStation is right to prioritise their own API and modifications, as these tend to have greater cost to perfomance results for the hardware vs the competition. The RDNA2 DirectX image below is taken directly from AMD's website, and again, PlayStation doesn't use Microsoft's DirectX. #PS6
2:53

It's PS5 RDNA 1.5 all over again, and reading responses, like a certain fandom never gets tired of being let down or uninformed. There's reasons PS5 often outperforms Xbox Series X despite the latter having 44% more compute than PS5 and being "full RDNA 2", which Digital Foundry did a video on. As I said at the start of the gen, most RDNA2 features Xbox/PC fans claim PS5 is missing, it was unlikely to use as they're Microsoft DirectX RDNA tie in features, and PS5 doesn't use DX but instead its own proprietary custom API called AGC. Why would PlayStation push for Microsoft DirectX RDNA features, when they don't use DirectX? Any AGC API specific graphics features PS5 uses (that Xbox wouldn't have) are not widely publicly advertised, as PlayStation don't need to advertise them the way Microsoft does due to their PC DirectX market. Thus every customisation PS5 has (which Kepler seemingly glosses over or doesn't recognise), from its faster clockspeeds, cache scrubbers, I/O set up, CPU alleviating decompression, DMA controllers and processors, geometry engine etc, will have been specifically designed around AGC or vice versa, NOT DirectX RDNA2 features. PS6 will be no different. There may be DirectX RDNA5 features they do not need or use, but there will inevitably be other unique customisations of their own and for their OWN proprietary API instead, no doubt bolstered by Amethyst custom features from their partnership with AMD. If history is any indicator, PlayStation is right to prioritise their own API and modifications, as these tend to have greater cost to perfomance results for the hardware vs the competition. The RDNA2 DirectX image below is taken directly from AMD's website, and again, PlayStation doesn't use Microsoft's DirectX. #PS6

NIB

48,001 Aufrufe • vor 5 Monaten

NVIDIA just handed every solo creator and freelancer an unfair advantage. Jensen Huang walked on stage and announced RTX Spark. An ARM-based laptop chip that nobody saw coming. They called it the most power efficient PC chip ever built. 20 cores. Blackwell graphics. 6144 CUDA cores. Up to 128GB of LPDDR5X memory. But forget the spec sheet for a second. Here is what actually matters. RTX Spark is built to run AI models locally. No cloud subscription. No API costs. No waiting on a server somewhere. Everything runs directly on the laptop at full speed. That changes the math completely for anyone using AI to make money. The guy generating 3D assets in Blender with Claude his renders now take minutes instead of hours. More projects per day. More income per week. The girl producing AI kids content for YouTube local rendering means no upload wait times, no generation limits, no monthly fees eating into her margins. The freelancer building websites and automating outreach every AI tool in his stack now runs faster and cheaper than before. 30 laptops from Asus, Dell, Lenovo, MSI and others. Available this fall. For years the barrier was hardware. You needed an expensive setup to run serious AI workflows locally. NVIDIA just put that power inside a thin laptop anyone can carry anywhere. The people who already figured out how to monetize AI are about to move twice as fast. The people who haven’t started yet just ran out of excuses. Save this.
0:45

NVIDIA just handed every solo creator and freelancer an unfair advantage. Jensen Huang walked on stage and announced RTX Spark. An ARM-based laptop chip that nobody saw coming. They called it the most power efficient PC chip ever built. 20 cores. Blackwell graphics. 6144 CUDA cores. Up to 128GB of LPDDR5X memory. But forget the spec sheet for a second. Here is what actually matters. RTX Spark is built to run AI models locally. No cloud subscription. No API costs. No waiting on a server somewhere. Everything runs directly on the laptop at full speed. That changes the math completely for anyone using AI to make money. The guy generating 3D assets in Blender with Claude his renders now take minutes instead of hours. More projects per day. More income per week. The girl producing AI kids content for YouTube local rendering means no upload wait times, no generation limits, no monthly fees eating into her margins. The freelancer building websites and automating outreach every AI tool in his stack now runs faster and cheaper than before. 30 laptops from Asus, Dell, Lenovo, MSI and others. Available this fall. For years the barrier was hardware. You needed an expensive setup to run serious AI workflows locally. NVIDIA just put that power inside a thin laptop anyone can carry anywhere. The people who already figured out how to monetize AI are about to move twice as fast. The people who haven’t started yet just ran out of excuses. Save this.

Shelpid.WI3M

27,732 Aufrufe • vor 1 Monat

I'm now building Executor full time as a startup! The state of tool calling is a mess: - Everyone is using different agents - You have no idea what actions are going to run - Destructive actions are treated the same as normal Executor lets you set up everything once & use it with any agent. You're able to control what tools can be called, require approval on destructive actions, and invite your team to all use them. Under the hood, it's built on codemode to let you add thousands of tools with 0 context bloat. I've been using it for a month so far and it has completely changed how I interact with agents. There's so much to be built here, immediately next up on the roadmap is workspaces, skills, workflows, and generative ui. Everything is being built open source over at there's a lot more coming on an SDK to embed it into your own agents, a self hostable cloud app, and plugins There's an early beta version over at It's very early on - if you hit any bugs let me know and I'll get them fixed up, excited to share more as I build it!
0:36

I'm now building Executor full time as a startup! The state of tool calling is a mess: - Everyone is using different agents - You have no idea what actions are going to run - Destructive actions are treated the same as normal Executor lets you set up everything once & use it with any agent. You're able to control what tools can be called, require approval on destructive actions, and invite your team to all use them. Under the hood, it's built on codemode to let you add thousands of tools with 0 context bloat. I've been using it for a month so far and it has completely changed how I interact with agents. There's so much to be built here, immediately next up on the roadmap is workspaces, skills, workflows, and generative ui. Everything is being built open source over at there's a lot more coming on an SDK to embed it into your own agents, a self hostable cloud app, and plugins There's an early beta version over at It's very early on - if you hit any bugs let me know and I'll get them fixed up, excited to share more as I build it!

Rhys

220,043 Aufrufe • vor 2 Monaten

God's eye view 24-hour replay of Operation Epic Fury. The Iran strikes kicked off and I set an AI agent swarm loose to record every OSINT signal I could find before the caches cleared. Built a full 4D reconstruction in WorldView. I can scrub through minute by minute and watch the whole thing unfold on a 3D globe: > Airspace clearing over Tehran > Ground strike coordinates locking in > Severe GPS interference blinding the region > EO and SAR satellites making passes over the strike zone > No-fly zones locking down 9 countries > Shipping fleets scrambling at the Strait of Hormuz It's pretty amazing how complete of a picture you can build without "proprietary data fusion" -- one dev with public signals and a love for computer graphics and geospatial intelligence. Thank you for all the love on my last post. Dropping WorldView in April. This my friends is just the beginning.
0:52

God's eye view 24-hour replay of Operation Epic Fury. The Iran strikes kicked off and I set an AI agent swarm loose to record every OSINT signal I could find before the caches cleared. Built a full 4D reconstruction in WorldView. I can scrub through minute by minute and watch the whole thing unfold on a 3D globe: > Airspace clearing over Tehran > Ground strike coordinates locking in > Severe GPS interference blinding the region > EO and SAR satellites making passes over the strike zone > No-fly zones locking down 9 countries > Shipping fleets scrambling at the Strait of Hormuz It's pretty amazing how complete of a picture you can build without "proprietary data fusion" -- one dev with public signals and a love for computer graphics and geospatial intelligence. Thank you for all the love on my last post. Dropping WorldView in April. This my friends is just the beginning.

Bilawal Sidhu

3,999,288 Aufrufe • vor 4 Monaten

Two data points dropped in the last few months that should terrify every software company that thinks its codebase is a moat. First, one engineer at Cloudflare, working with Claude via AI agents, rebuilt 94% of Next.js, one of the most widely used frontend frameworks on the internet, built over 10 years by a large engineering team in a single week. Total cost was $1,100 in API tokens. The result, called Vinext, is a drop-in replacement that builds production apps up to 4x faster and produces client bundles 57% smaller and customers are already running it in production. Second is Cursor CEO Michael Truell deployed a swarm of hundreds of GPT-5.2 agents that ran uninterrupted for an entire week and built a fully functional web browser from scratch called FastRender. 3 million lines of code, thousands of files and a custom Rust rendering engine with HTML parsing, CSS layout, text shaping, and a custom JavaScript VM. Total cost was roughly $30,000. For context, Google has spent billions of dollars and decades of engineering building Chrome. And the benchmarks say by next year, you will be able to one-shot prompt anything. The moat that software companies spent decades building, the complexity of their codebase, the years it would take a competitor to replicate it, the switching costs that moat assumed humans were the unit of production. AI does not care how long it took you to build it, it only cares how long it takes to rebuild it. And right now, the answer is one week.
1:05

Two data points dropped in the last few months that should terrify every software company that thinks its codebase is a moat. First, one engineer at Cloudflare, working with Claude via AI agents, rebuilt 94% of Next.js, one of the most widely used frontend frameworks on the internet, built over 10 years by a large engineering team in a single week. Total cost was $1,100 in API tokens. The result, called Vinext, is a drop-in replacement that builds production apps up to 4x faster and produces client bundles 57% smaller and customers are already running it in production. Second is Cursor CEO Michael Truell deployed a swarm of hundreds of GPT-5.2 agents that ran uninterrupted for an entire week and built a fully functional web browser from scratch called FastRender. 3 million lines of code, thousands of files and a custom Rust rendering engine with HTML parsing, CSS layout, text shaping, and a custom JavaScript VM. Total cost was roughly $30,000. For context, Google has spent billions of dollars and decades of engineering building Chrome. And the benchmarks say by next year, you will be able to one-shot prompt anything. The moat that software companies spent decades building, the complexity of their codebase, the years it would take a competitor to replicate it, the switching costs that moat assumed humans were the unit of production. AI does not care how long it took you to build it, it only cares how long it takes to rebuild it. And right now, the answer is one week.

Milk Road AI

16,781 Aufrufe • vor 2 Monaten