Multimodal machine-learned models for synchronized explanatory outputs
Multimodal machine-learned models generate synchronized action and explanation outputs, addressing the challenge of verifying accuracy in machine-learned models by enabling quick validation and reducing computational costs through synchronized explanatory outputs.
Patent Information
- Authority / Receiving Office
- WO · WO
- Patent Type
- Applications
- Current Assignee / Owner
- GDM HOLDING LLC
- Filing Date
- 2026-01-13
- Publication Date
- 2026-07-16
AI Technical Summary
Existing machine-learned models often generate outputs with errors or erroneous information, making it difficult to verify their accuracy, especially in critical tasks, and this verification process can be slower and more costly than manual generation.
Implement multimodal machine-learned models that generate synchronized action and explanation outputs, allowing for concurrent delivery of actions and explanations in different modalities, enabling early verification of output correctness and reducing computational costs.
Enables effective delivery of explanatory outputs synchronized with action performance, allowing for quick validation of output accuracy and reducing computational resources by enabling early exit if incorrect, thus improving efficiency and reducing costs.
Smart Images
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