This model just built a fully functional ray-tracing engine inside a web browser using simple prompts.
I was absolutely floored when I saw the sheer variety of complex applications being generated by the latest iteration of Google’s model. I just watched a fascinating breakdown from an AI professional who pushed Gemini 3 to its absolute limits to see what it could code. The expert demonstrated how this model can generate complex, interactive applications ranging from voxel art creators to economic simulators, all without heavy-handed manual coding.
It is clear that we are moving past the era where LLMs simply write text or basic code snippets. The creator showed that this model can now handle “state,” physics logic, and multimodal inputs to build functional software that feels like it took weeks to develop by hand. The ability to simply ask for a simulator and get a working product with Newtonian physics or frame-by-frame video analysis is a massive leap forward.
💎 Insight 1: High-Fidelity Visuals and Physics Engines
The most visually striking part of this demonstration was the expert’s exploration of 3D rendering and physics. He started by showing off a Voxel Art Generator that didn’t just create static images, it created interactive 3D models. The author prompted the system to build a “procedurally generated robot” tool. What was incredible was the interactivity, as users could click a “scrap” button, and the model programmed a physics simulation where the robot shatters into pieces on the ground. It wasn’t a pre-rendered video, it was live code handling gravity and collision detection. You could then reassemble the pieces into a completely new random robot or even specific objects like a retro Polaroid camera.
But the visuals didn’t stop there. The industry pro then asked the model to build a ray-tracing demo. For context, ray tracing is computationally expensive and usually reserved for high-end gaming, but the model managed to code a “house of mirrors” directly in the browser. You could see a voxel man reflecting in the mirrors, with light bouncing off floating metallic shapes. While the creator noted there were some small visual artifacts, the fact that the model understood how to program light reflection and surface textures from a simple text description is wild. They also showed off an image-to-voxel tool where you could upload a flat 2D photo, like a picture of Muhammad Ali or a cat, and the AI converted it into a rotating 3D voxel asset.
📉 Insight 2: Deep Analysis and Multimodal Logic
Beyond just making things look cool, the original poster demonstrated the model’s ability to ingest data and videos for complex analysis. One of the standout examples was a Golf Swing Analyzer. The creator uploaded a video of a golf swing, and because Gemini 3 is natively multimodal, it ingested the footage frame-by-frame. It didn’t just describe the video, it performed a segmentation analysis, calculating shoulder rotation, hip rotation, and tempo ratios. It even compared the user’s swing style to professional golfers like John Rahm. This shows that the model can build apps that “see” and interpret physical motion to give coaching feedback.
The expert also touched on financial modeling with an “AI Bubble Simulator.” This wasn’t just a chart; it was a fully interactive strategy game. The user plays as a startup founder, managing capital, hiring staff, and acquiring companies while trying to avoid the “bubble pop.” The tool pulled in real historical data, comparing current AI hype cycles to the dot-com crash, specifically comparing Nvidia to Cisco. It displayed graphs showing the gap between capital expenditure and revenue, providing a verdict on whether the industry is in a speculative bubble or a productive realignment. It’s amazing to see an AI build a tool that teaches macroeconomic concepts through gameplay.
🪐 Insight 3: Complex Simulation and Gamification
The final set of demonstrations proved that the model can handle complex logic and rulesets. The talented creator showed off a Gravity Simulator where users could place planets, stars, and black holes onto a canvas. The code automatically calculated the Newtonian physics, meaning if you placed a massive star near a planet, the planet’s orbit would shift realistically. You could even throw in a black hole and watch it suck the entire solar system into a void. The system handled the math for mass, velocity, and trajectory in real-time.
To top it off, the author shared a custom Monopoly Board Generator. This wasn’t a generic board, he asked for a Donkey Kong theme, and the AI generated the board, the property prices, and the pieces, like a Donkey Kong Sky Rail train. But the really impressive part was the logic: you can actually play the game against AI opponents. The creator explained that you can negotiate trades with these AI players via chat, meaning the model is managing the game rules, the visual board state, and the personality of the opponents simultaneously. From a “Power of 10” zoom animation that scales from the universe down to a subatomic particle, to a fluid dynamics sim that tracks your hand movements via webcam, the range of logic this model can implement is astounding.
If you want to see these simulations in action and grab the links to try them yourself, you need to check out the full video breakdown below.