Abstract: With the increasing demand for creating large-scale 3D virtual worlds in many industries, there is an immense need for diverse and high-quality 3D content. Machine learning is existentially enabling this quest. In this talk, I will discuss how looking from the perspective of combining differentiable iso-surfacing with differentiable rendering could enable 3D content creation at scale and make real-world impact. Towards this end, we first introduce a differentiable 3D representation based on a tetrahedral grid to enable high-quality recovery of 3D mesh with arbitrary topology. By incorporating differentiable rendering, we further design a generative model capable of producing 3D shapes with complex textures and materials for mesh generation. Our framework further paves the way for innovative high-quality 3D mesh creation from text prompt leveraging 2D diffusion models, which democratizes 3D content creation for novice users.