Foundation · 2021– · one space, many senses
Multimodal Architecture
Encoders for different modalities — vision, language, audio — connected through shared representation spaces or a shared decoder.
ModLensFoundation
Interactive Diagram
Focus the lens
Click any component to read what it does. Signal direction follows the edges.
inputVision Encoder. Images become tokens via a visual transformer.
Core idea
Meaning is modality-independent. Project images, text and audio into a common space where a single architecture can reason across them.
Why it exists
Real tasks mix modalities: documents contain layout and text, videos contain frames and speech; single-modality models cannot see the whole input.
Data Flow
What moves through the system
- 01Modality encoders produce token streams.
- 02Projection layers align them into a shared space.
- 03A transformer reasons over the fused sequence.
- 04Outputs may be text, boxes, or other modalities.
Strengths
- + Cross-modal reasoning and search
- + One backbone for many input types
Limitations
- − Alignment quality is the hard part
- − Evaluation across modalities is immature
Applications
- · Document intelligence
- · Visual QA
- · Multimodal search
- · Video understanding