Parallax: The Community-Trained Vision Model

Parallax is a high-performance VLM (Vision Language Model) that evolves through crowdsourced training and decentralized fine-tuning. Inspired by a hybrid of Vision Transformers (ViT), CLIP, and SAM-like attention mechanisms, Parallax is optimized for real-time spatial reasoning and contextual understanding.

The model roadmap includes multimodal capabilities, incorporating image, text, and geospatial metadata to support next-generation agents and robotics.

Core applications:

• Autonomous Vehicles: Lane detection, object recognition, behavior prediction

• Robotics: Depth estimation, pose tracking, environment mapping

• Surveillance & Smart Cities: Anomaly detection, crowd analytics, access control

• AR/VR & IoT: Real-time image parsing, spatial reasoning, edge vision

Parallax is modular, updatable, and trainable across verticals using contributed real-world data.