# Multimodal Models

> Joint text, image, audio, and video representations, encoders, projectors, fusion, generation, and cross-modal evaluation.

Canonical: https://learn.significanthobbies.com/curriculum/concepts/multimodal-models

Joint text, image, audio, and video representations, encoders, projectors, fusion, generation, and cross-modal evaluation.

- Difficulty: core
- Tracks: Multimodal & Spatial Computing

## Mental model

Multimodal models align different signal spaces through shared or connected representations. Data alignment, modality-specific encoders, fusion, and cross-modal evals are central.



## Primary sources

- [CLIP: Learning Transferable Visual Models From Natural Language Supervision](https://arxiv.org/abs/2103.00020) (paper)

## Practice

### Design exercise: Multimodal Models

Joint text, image, audio, and video representations, encoders, projectors, fusion, generation, and cross-modal evaluation. Implement designOutline() returning non-empty values for: modalityEncoders, fusion, crossModalEval. Each value must name a concrete mechanism or decision.

**Expected evidence:** A design outline with modalityEncoders, fusion, crossModalEval plus an explicit failure mode or trade-off.

## Review prompts

- What does a projector do in a vision-language model, and why is aligned data the bottleneck?

## Build evidence

- **Synthesize: AI Models & Training** — Move from transformer foundations through pre-training, fine-tuning, post-training, compression, and evaluation. Produce one working system, benchmark, or evidence-backed design that integrates the path.
- **Synthesize: Multimodal & Spatial Computing** — Connect vision, audio, generation, on-device intelligence, robotics, spatial interfaces, and HCI. Produce one working system, benchmark, or evidence-backed design that integrates the path.

## Prerequisites

- [Vision Models](https://learn.significanthobbies.com/curriculum/concepts/vision-models)
- [Voice & Audio Systems](https://learn.significanthobbies.com/curriculum/concepts/voice-audio-systems)

## Related concepts

- [Model Quantization](https://learn.significanthobbies.com/curriculum/concepts/model-quantization)
- [Vision Models](https://learn.significanthobbies.com/curriculum/concepts/vision-models)

## Learning paths

- [12-Week AI Models & Training](https://learn.significanthobbies.com/curriculum/roadmaps/ai-models-training-12w)
- [12-Week Multimodal & Spatial Computing](https://learn.significanthobbies.com/curriculum/roadmaps/multimodal-spatial-12w)