rbyte

rbyte

Simplified dataset configuration for large, multimodal models from more than 50 popular spatial intelligence datasets. Features: • ROS2/MCAP support • Inter-modality alignment • Dataframes with pola.rs • Visualization with rerun.io

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Tron

Train spatial intelligence leveraging our cutting-edge research on large, multimodal foundation models. Features: • Episode construction and model configuration with hydra • Built with PyTorch Lightining • Pre-trained models and notebooks • Model tracking with wandb.ai • Inference visualization with rerun.io

compose intelligence

  • 001

    Align Modalities

    Camera. Radar. Lidar. Audio. Controls. Easily align your multimodal data. rbyte supports conversion to mcap; a flexible format for all things spatial intelligence.

  • 002

    Encode modalities

    Chose from pre-trained modality encoders, or train modality encoders from scratch. Take inspiration from our research, and that of the wider AI community.

  • 003

    Construct episodes

    Easily construct training episodes from aligned, multimodal data through hydra.

  • 004

    Train spatial intelligence

    Leverage our cutting-edge research to train spatial intelligence foundation models.

Products ↓

Nutron

Multimodal dataset search

Vektor

Scenario understanding

OPEN-SOURCE ↓

Open Scenario Map

Unseen scenarios at scale

Dev Tools

Open spatial intelligence

Developer preview

Join the rbyte and Tron developer preview, and help us build spatial intelligence in the open.

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