Just started experimenting with 2D Cloth Physics Simulation using... #raylib and #cplusplus 🧵🪡 By the way, there's a clear, concise article that's an excellent starting point: #gamedev #physics #simulation #verletintegrationshow more

As a learning test, I ported part of my... 2D Cloth Physics Simulation to the web using #Rust 🦀 🧪 Try the mini demo: Real-time simulation with Verlet integration, touch/mouse interaction, and web delivery. #gamedev #physics #simulation #verletintegrationshow more

Defold user Ivan Lytkin shared an #opensource liquid simulation... experiment inspired by Sebastian Lague videos, and powered by compute shaders in Defold. 💧 Check out the current status of the project: #MadeWithDefold #liquidsimulation #physics #gamedev #indiedevshow more

ChatGPT 5.1 vs. Claude Opus 4.5 vs. DeepSeek-V3.2 (left)... (middle) (right) prompt I used: Create a single HTML file containing a realistic cloth simulation using HTML5 Canvas and JavaScript. The cloth should be a grid of points connected by constraints using Verlet integration. Implement gravity and mouse interaction: the user should be able to click and drag particles to tear the cloth. The physics must remain stable without exploding.show more

There's a lot of speculation about whether OpenAI's video... generation model Sora has a 'physics engine' (bolstered by OAI's own claims about 'world simulation'). Like the debate about world models in LLMs, this question is both genuinely interesting and somewhat ill-defined. 🧵1/show more

NVIDIA GEAR lab is breaking new ground. With just... 1.5M parameters, HOVER proves that mastering complex motor skills doesn’t require huge models. Using NVIDIA simulation suite, which accelerates physics by 10,000x, humanoids can learn a year’s worth of motion in under an hour.show more

Newton 1.0 is now generally available. 🙌 Take robot... learning to the next level with: 🤖 Stable Articulated & Complex Mechanism Simulation – accurate, reliable machine modeling. 🖐️ High-Fidelity Hydroelastic Contact Modeling – realistic soft contact and touch-based interactions. 🧵 Deformable Body Simulation – simulate cables, cloth, rubber, and other elastic materials with VBD. ⚡ Accelerated Robot Learning at Scale – seamless integration with open simulation and learning frameworks, NVIDIA Isaac Sim and Isaac Lab for scalable workflows. Learn how to integrate this open-source physics engine into your workflow: #NVIDIAGTCshow more

Claude Opus 4.7 vs GPT 5.4 (2/7) Testing how... well these models do with cloth physics simulation, and honestly I'm quite disappointed to see how poorly GPT 5.4 performed here. Performance was pretty bad... it added all the functionality (panning, cutting, dragging the curtain) under one mouse event, causing it to glitch out a lot. The scene also looks kinda shit. Opus 4.7 pretty much nailed the prompt. First of all, the angle and scene it picked are really nice, with the lamp just creeping into the frame. The dragging, wind physics, and cutting all worked. I also had to reprompt gpt 1-2 times to properly build and remove a bunch of ugly ui cards it added on top of the 3d scene. prompt: Build a premium Vite + React interactive cloth simulation of a cozy room curtain using real particle/constraint physics, with structural + shear springs, damping, collisions, and stable real-time deformation. Users should be able to drag the curtain, add wind, and cut constraints, while the experience stays polished, visually elegant, and numerically stable.show more

Tonight at the house: An intimate AI x Physics... Dinner with Prof. Steve Hsu from Manifold steve hsu, Alex Morisse, Alex Morisse, PhD, Jasper Jasper, and Jeremy Nixon - Automating AI Research. We started off with Alex casually explaining the science behind his stealth deeptech start-up on physics textbooks. A thread on the important questions in AI X physics.🧵show more

We gave Grok 4.5 and GPT-5.6 Sol the exact... same prompt and compared the outputs side by side. The task: generate a fully interactive HTML5 glass bridge simulation with realistic physics, structural failure, cinematic visuals, polished UI, and smooth animations. The difference is actually visible.show more

With the recent three-mesh-bvh changes you can finally make... a full scene-wide BVH to accelerate physics, raycasting, etc. And at some point Pathtracing 😁 Its just a prototype so far but it "just works" with objects and batched instances in a single structure. #threejs #gamedevshow more

ℵ-Is the Beginning the End? Is the End the... Starting Point? Aleph-0, by Hackatao ♛ and insigħt, is an exploration into the secrets of human emotions. A dance of lines and equations between consciousness and quantum physics The art is alive. Dec 13th - 1pm EST/ 7pm CET-ℵshow more

Robora Sim: A PyBullet-Powered Environment for Learning Robotic Physical... Intelligence We are currently building our Robora simulation environment setup for our sim based learning, leveraging PyBullet, an industry-standard physics engine widely used in AI-driven robotics research and development. The environment is optimized with GPU-accelerated learning algorithms, enabling high-speed imitation learning and reinforcement learning within a safe and controlled virtual setup before shipping out to real world. This simulation platform allows our models to learn, adapt, and generalize across different robot morphologies, terrain types and task objectives - all before deployment to the real world. At it's core, the system combines a VLA-powered high-level planner with low-level motion control algorithms, working cohesively to produce emergent, physically intelligent behaviors. This synergy between simulation, learning, and real-world transfer marks a major step forward in our pursuit of adaptive and intelligent robotic systems. Through advanced domain randomization and synthetic data generation, the Robora Simulation Environment ensures that policies trained in simulation transfer effectively to real-world robots, minimizing the sim-to-real gap. Moreover, users will be able to test and integrate their own hardware kits within selected simulation environments in the Robora Dapp, ensuring seamless compatibility and safer real-world implementation.show more

The Google Gemini can transform your questions and complex... topics into custom and interactive visualizations — directly within your chat. Whether you’re rotating a molecule or simulating a complex physics system, you create 3D simulations with just one prompt in Gemini. Try starting your prompt with “show me...,” to get your interactive visualization. For the best results, try using Gemini’s Flash model.show more

Always wanted to try combining my paper with NCA,... and turns out this approach is a perfect starting point It decouples grid with rules from rendering by using SIREN as a decoder, so I just replaced it with SAD Same rules, different way to render them in higher resolutionshow more

For years Yann LeCun has argued that generative video... models can't truly learn physics. DeepMind's Physics-IQ benchmark proved him right, reporting "a striking lack of physical understanding in current generative video models". The best one scored just 29.5%. This CVPR 2026 paper finds the fix in LeCun's own playbook. "Inference-time Physics Alignment" doesn't retrain the generator. It steers a video model's denoising at inference using a reward from VJEPA-2, LeCun's Joint Embedding Predictive Architecture. - Won first place in the ICCV 2025 PhysicsIQ Challenge with a 62.64% score, beating the previous state of the art by 7.42%. - Repurpose VJEPA-2's "surprise" score as a reward, then search and rank multiple candidate denoising trajectories at test time. - Why it matters: It's a neat vindication of LeCun's thesis. The pixel-prediction generator alone doesn't get physics, but the JEPA world model approach he champions supplies the physics the video model lacks.show more

One warrior. One impossible battle. Only one survives. Created... with Seadance 2.0 on Lart AI Here is the link to try: Prompt: A cinematic, hyper-realistic 12-second action sequence in a ruined modern city at sunset. A fearless female warrior in realistic tactical combat armor faces a towering 40-foot monster with rough stone-like skin and glowing eyes. The monster charges with immense weight, causing the ground to crack, dust to erupt, and nearby vehicles to shake realistically. The woman sprints, slides under a massive punch, and uses momentum to leap from a collapsed concrete slab, delivering a powerful strike with an energy-infused sword. The monster staggers backward with believable body mechanics, destroying a building facade as debris falls naturally under gravity. She performs one final spinning aerial attack, slicing through the monster's glowing core. The giant collapses with realistic physics, creating a massive dust cloud, flying rubble, shockwave, and ground vibration. The woman lands in a controlled three-point stance, breathing heavily as the dust settles and sunlight shines through the smoke. Ultra-photorealistic, Hollywood blockbuster quality, handheld cinematic camera, dynamic tracking shots, physically accurate motion, realistic muscle movement, cloth simulation, debris, lighting, shadows, HDR, volumetric smoke, motion blur, 4K, 60fps, dramatic sound design, seamless action, no cartoon style, no exaggerated superhero physics, every movement follows real-world momentum and gravity.show more

𝗣𝗼𝗽𝘂𝗹𝗮𝗿 𝗼𝗽𝗶𝗻𝗶𝗼𝗻: "𝗝𝘂𝘀𝘁 𝗴𝗲𝗻𝗲𝗿𝗮𝘁𝗲 𝗺𝗼𝗿𝗲 𝘀𝗶𝗺𝘂𝗹𝗮𝘁𝗶𝗼𝗻 𝗱𝗮𝘁𝗮." After working... with many 𝗿𝗼𝗯𝗼𝘁 𝗺𝗮𝗻𝗶𝗽𝘂𝗹𝗮𝘁𝗶𝗼𝗻 teams who've fallen into the simulation trap, here's what I've learned: Simulation teaches your robot to be really, really good at simulation. Unlike blind locomotion policies that can get away with sim-to-real transfer because they rely mainly on proprioception and contact forces, 𝘃𝗶𝘀𝗶𝗼𝗻-𝗴𝘂𝗶𝗱𝗲𝗱 𝗺𝗮𝗻𝗶𝗽𝘂𝗹𝗮𝘁𝗶𝗼𝗻 𝗶𝘀 𝗲𝘅𝘁𝗿𝗲𝗺𝗲𝗹𝘆 𝘀𝗲𝗻𝘀𝗶𝘁𝗶𝘃𝗲 𝘁𝗼 𝘃𝗶𝘀𝘂𝗮𝗹 𝗱𝗼𝗺𝗮𝗶𝗻 𝗴𝗮𝗽. The subtle differences accumulate: - Simulated friction vs real surface textures - Perfect lighting vs shadows, reflections, glare - Ideal object geometries vs manufacturing tolerances - Instantaneous sensor readings vs real-world noise and latency - Clean backgrounds vs cluttered, dynamic environments 𝗧𝗵𝗲 𝗰𝗹𝗮𝘀𝘀𝗶𝗰 𝗽𝗿𝗼𝗴𝗿𝗲𝘀𝘀𝗶𝗼𝗻: Week 1: "Our model works perfectly in sim!" Week 2: "Let's collect some real data to fine-tune." Week 3: "The real data completely contradicts what the sim taught..." Week 4: "Okay, let's collect way more real data." Month 2: "We basically need to retrain from scratch." 𝗧𝗵𝗲 𝗽𝗮𝗶𝗻𝗳𝘂𝗹 𝘁𝗿𝘂𝘁𝗵: There's no shortcut to real-world data collection for vision-based manipulation. Simulation is amazing for debugging, prototyping, safety testing, and of course to supplement your real data. But it's not a substitute for understanding how your robot actually behaves in the actual environment. 𝗪𝗵𝗮𝘁 𝘄𝗼𝗿𝗸𝘀: Use simulation strategically - for exploring edge cases, testing safety boundaries, and rapid iteration. But build your production models on real data from real environments. The teams that succeed treat simulation as a powerful tool, not a magic solution. This is why Neuracore focuses on making real-world data collection so much easier and faster. Because the physics of your actual environment can't be simulated away. 𝗪𝗼𝗿𝗹𝗱 𝗺𝗼𝗱𝗲𝗹𝘀, 𝘆𝗼𝘂 𝘀𝗮𝘆? 𝗪𝗲𝗹𝗹, 𝗽𝗲𝗿𝗵𝗮𝗽𝘀 𝗺𝗼𝗿𝗲 𝗼𝗻 𝘁𝗵𝗮𝘁 𝗶𝗻 𝗮𝗻𝗼𝘁𝗵𝗲𝗿 𝗽𝗼𝘀𝘁! 𝗪𝗵𝗮𝘁'𝘀 𝗯𝗲𝗲𝗻 𝘆𝗼𝘂𝗿 𝗲𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 𝘄𝗶𝘁𝗵 𝘀𝗶𝗺-𝘁𝗼-𝗿𝗲𝗮𝗹 𝘁𝗿𝗮𝗻𝘀𝗳𝗲𝗿? 𝗛𝗮𝘀 𝗶𝘁 𝘄𝗼𝗿𝗸𝗲𝗱 𝗮𝘀 𝘄𝗲𝗹𝗹 𝗮𝘀 𝗲𝘅𝗽𝗲𝗰𝘁𝗲𝗱?show more

PAUSE AT 0:07 AS SHE REACHES HER HAND DIRECTLY... INTO THE LENS. A patio clip of a girl in a plunge halter gown showing off her outfit. Yet it clears 3 generative video bottlenecks: ▫️ Dynamic ruched drape & slit physics: gathered pleats and high leg slit maintain physical cloth simulation during a 360 spin at 0:05 without mesh tearing ▫️ Near-field lens occlusion: hand reaching directly toward the camera at 0:07 with jewelry and manicured fingers resolving with zero digit fusion ▫️ Multi-subject identity introduction: rapid transition at 0:09 introducing a second person with independent facial geometry and zero identity bleed Not a real girl. Not a real dress. Pure compute. Replay twice. Spot the single frame where the render breaks.show more

In a masterclass at Sequoia Capital AI Ascent, Jim... Fan laid out the "Great Parallel": how robotics is speedrunning the LLM playbook. 🔹 VLA → WAM: Moving from language-heavy models to "World Action Models" that dream in physics. 🔹 Teleop → EgoScale: Replacing manual data with human egocentric video. 🔹 Simulation 2.0: Using neural simulators like DreamDojo to turn compute into environments. "Our generation was born too late to explore the earth and too early to explore the stars. But we are born just in time to solve robotics." He believes that robots will pass the Physical Turing Test in the coming 2–3 years.show more

If you are using an if statement inside a... for loop, did you know there's a better way of doing this is Swift? I'm talking about the where clause. Using the where clause in a for loop can provide several benefits over using an if statement inside a for loop: Readability: It explicitly states the condition that must be met for an element to be processed, making the purpose of the loop clearer to anyone reading the code. Efficiency: When using a where clause, the filtering of elements is done at the level of the sequence, which can be more efficient than filtering within the loop with an if statement. Brevity: Using a where clause often results in more concise code, as it eliminates the need for an if statement and associated braces. This can make the code more manageable and easier to maintain.show more