Tech Study Guide

Multimodal ML

Multimodal ML with vision, audio, speech-to-text, text-to-speech, vision-language models, image embeddings, OCR pipelines, multimodal RAG, and video model basics.

machine-learning multimodal vision audio

Multimodal ML

Multimodal systems combine text, images, audio, video, documents, or structured data. They add preprocessing, alignment, storage, privacy, and evaluation problems beyond text-only LLMs.

Modality Map

Modality Common Tasks Operational Risk
Vision Classification, detection, segmentation, OCR. Image quality, resolution, privacy, bias.
Audio Speech recognition, diarization, classification. Noise, accents, latency, consent.
Text-to-speech Voice generation. Misuse, consent, watermarking.
Vision-language Captioning, document QA, UI understanding. Hallucinated visual details.
Video Temporal understanding and generation. Cost, storage, frame sampling.

Multimodal RAG

Multimodal RAG retrieves evidence from text, images, tables, diagrams, and OCR. The system needs source metadata, page/region coordinates, image hashes, and citation rendering that users can inspect.

OCR Pipeline

flowchart LR
  PDF[PDF or image] --> Render[Render pages]
  Render --> OCR[OCR text]
  Render --> Vision[Image embeddings]
  OCR --> Chunks[Text chunks]
  Vision --> Index[Image/vector index]
  Chunks --> Index
  Index --> Answer[Grounded answer]

Practical Lab: Document QA Evidence

question: "What is the invoice due date?"
evidence:
  page: 2
  bounding_box: [120, 310, 260, 340]
  extracted_text: "Due: 2026-06-15"
answer_policy:
  cite page and field
  abstain if OCR confidence is low

Study Cards

Question

Why is multimodal RAG harder than text RAG?

Answer

Evidence can live in images, coordinates, OCR text, tables, or temporal segments that need different indexing and citation.

Question

What should document QA cite?

Answer

The source document plus page, region, or extracted field that supports the answer.

Question

Why does audio ML need privacy review?

Answer

Audio can contain voices, identity, background speech, and sensitive context.

References