Train AURA AI Model Studio
Fine-tune AURA AI's spatial generation neural engine by feeding diverse memory data, tracking epoch metrics, and improving 360° environment fidelity over time.
Epoch Increments & Loss Curve
Metrics automatically improve as new multimodal memory datasets are fed into AURA AI.
Before vs After AURA Fine-Tuning Benchmark
Visual comparison of base spatial model vs fine-tuned AURA AI output on patient data.
Generic 360 Panorama
Blurry personal belongings, missing spatial lighting, default stock furniture, flat audio background.
Photorealistic 360 Memory World
Exact mahogany coffee table, vintage Zenith TV, grandfather clock chime, warm fireplace shadows, interactive avatar.
Feed Training Dataset
Supply new pairs of memory images, 3D scans, and descriptions to improve AURA AI.
Active Training Datasets (4)
Contains flowerbeds, fountains, benches, chirping birds, wind audio.
Leather couches, grandfather clocks, fireplaces, classic TVs, ceiling fans.
Wooden rocking chairs, wind chimes, twilight street lamps.
Cobblestones, café tables, street lights, acoustic reverberations.