The performance gains from Nvidia's Hopper to Blackwell GPUs come from increased size and power, not efficiency. This signals a potential scaling limit, creating an opportunity for radically new hardware primitives and neural network architectures beyond today's matrix-multiplication-centric models.

Unlike video models that generate frame-by-frame, Marble natively outputs Gaussian splats—tiny, semi-transparent particles. This data structure enables real-time rendering, interactive editing, and precise camera control on client devices like mobile phones, a fundamental architectural advantage for interactive 3D experiences.

Born from 20 years of agency work, Rive aims to solve the inefficient, error-prone process of translating static designs into code. It does this by providing a single graphics format that designers create with and that ships directly in the final product, removing the translation step entirely.

Instead of building on existing web standards, Rive created its own specification and renderer. This freedom from legacy constraints allowed them to build a format optimized for real-time, interactive performance, which existing standards could not support.

Traditional video models process an entire clip at once, causing delays. Descartes' Mirage model is autoregressive, predicting only the next frame based on the input stream and previously generated frames. This LLM-like approach is what enables its real-time, low-latency performance.

Instead of using high-level compilers like Triton, elite programmers design algorithms based on specific hardware properties (e.g., AMD's MI300X). This bottom-up approach ensures the code fully exploits the hardware's strengths, a level of control often lost through abstractions like Triton.

Rive intentionally doesn't support importing from other design tools. Its high-performance rendering features (like vector feathering) differ from standard effects. Forcing creation within Rive's editor guarantees the design-time preview perfectly matches the final runtime output, eliminating mismatches.

The primary performance bottleneck for LLMs is memory bandwidth (moving large weights), making them memory-bound. In contrast, diffusion-based video models are compute-bound, as they saturate the GPU's processing power by simultaneously denoising tens of thousands of tokens. This represents a fundamental difference in optimization strategy.

Rive is often miscategorized as just a motion tool. Its true vision is to create a new, real-time graphics format for building entire interactive experiences, where motion is a fundamental requirement, not the end goal.