AIGC 3D technology reached a significant milestone in 2023, advancing from its nascent stage. It leverages AI to process dimensions as digital matrices for generation and inference. Capabilities include text-to-3D (Dream Fusion, Tripo3D) and image-to-3D (Point-E, Shap-E, Wonder3D, Zero123/Zero123++, DreamGaussian). NeRF and Gaussian Splatting are key reconstruction techniques, with the latter offering faster, training-free precision. The Model Context Protocol (MCP) allows AI to directly control 3D applications like Blender, revolutionizing software interaction. Applications are expanding into VR/AR and design.
Despite progress, limitations persist. There's a critical need for algorithm optimization, enhanced computing power, and more high-quality 3D training data. Generating complex 3D models can still be slow. The design industry requires highly detailed, workable models, which AIGC currently struggles to fully provide, often focusing on clear mesh surfaces. Stable Diffusion also exhibits spatial inconsistency in 3D rendering. Overall, while advancing rapidly, AIGC 3D still needs improvements in speed and model quality.

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