Multimodal AI
multimodal-ai refers to artificial intelligence models capable of ingesting and/or generating data across various Data-Modalities.
Key Concepts
- Modality: A specific data type or format used as input or output.
- Common Modalities: Includes Text, Images, Audio, Lidar, and Thermal-Imaging.
- Processing Capabilities: Models increasingly bridge the gap between digital perception and physical action, enabling complex Robotics applications.
Recent Developments & Integrations
- Physical AI & Robotics: Significant strides are being made in integrating multimodal models into physical agents. Google DeepMind is actively deploying Gemini AI to create adaptable, general-purpose robots capable of navigating unstructured environments.
- Open-Source & Specialized Models: The landscape includes open-weights models like Inkling, vision-only Computer Use Agents like Microsoft Fara 1.5-27B, and structured decision models like Cloudflare’s Clef 27B.
- Document Comprehension: Advanced RAG techniques now support complex document understanding via screenshot-based retrieval.