#real-time inference

WaveGrad is a high-fidelity vocoder based on Denoising Diffusion Models that enables 6-iteration rapid convergence. Supports GPU training, real-time inference, and customizable setups. Provides pretrained models and generated samples for advanced audio synthesis.

The Dynamic Sparse Voxel Transformer (DSVT) efficiently analyzes large-scale point clouds in autonomous driving. Excelling with state-of-the-art performance in the Waymo Open Dataset, it achieves real-time 3D object detection through unique rotated set partitioning. With minimal dependencies, DSVT optimizes performance in both single-sweep and multi-sweep configurations. Highlighted at CVPR2023 and integrated into the OpenPCDet framework, DSVT represents significant advancements in 3D perception without overstating its capabilities.

The framework provides a versatile and real-time approach to constructing vectorized HD maps, essential for autonomous vehicle systems. Through a unified modeling strategy, it precisely captures intricate map elements, supporting consistent learning outcomes. Its hierarchical embedding system adds flexibility in handling structured map details, while additional matching and supervision methods enhance convergence speed. Proven on datasets like nuScenes and Argoverse2, it delivers high accuracy and robustness in complex driving scenarios, supporting various BEV encoders for detailed environmental mapping.

Chronon enhances AI/ML data management by simplifying feature definitions from raw data and enabling efficient batch and stream processing. It supports low-latency serving and maintains consistency and observability, allowing organizations to utilize extensive data sets efficiently. The platform features integrated orchestration, scalable backfills, and innovative APIs to ensure the accuracy of both real-time and historical data. Designed for models requiring real-time data handling, Chronon addresses infrastructure challenges, focusing on model development over data operations.