Foundry: Distilling 3D Foundation Models for the Edge

1. 1Pre-train large-scale 3D foundation models using self-supervised learning
2. 2Apply knowledge distillation techniques to compress models while preserving general-purpose feature extraction capabilities
3. 3Evaluate and fine-tune compressed models for specific edge AI applications
4. 4Deploy compressed models on edge devices, such as robots and AR/VR headsets

Machine learning researchers and engineers working on edge AI applications, such as robotics and AR/VR, can benefit from Foundry to deploy efficient and effective models on resource-constrained devices

💡 Foundry enables efficient deployment of general-purpose 3D foundation models on edge devices without sacrificing downstream-agnostic capabilities

💡 Distill 3D foundation models for edge AI with Foundry!