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Multimodal AI: Images, Audio, Video, And Documents

Explore how AI works with pictures, sound, video and documents.

About This Course

Introduction

Image interpretation and image generation require different capabilities. Speech recognition converts audio into text; speech generation produces audio. 'Multimodal' means working with more than one kind of representation, but we still need to ask which inputs and outputs a particular system supports.

We will look at how media becomes numerical input and how those representations connect. The route covers pixels, patches, visual encoders, contrastive learning, OCR, speech recognition, audio samples, video frames, diffusion, latent representations, provenance, and evaluation. Each term comes with a problem it helps explain. Extracting, understanding, and generating content remain different tasks.

Review tokens, embeddings, attention, and generation in Foundation Models: Tokens, Attention, And Generation, and source meaning and lineage in Data: From Business Records To Model Inputs. Begin with images and documents, then audio and video, then generation and product design. Your project is a multimodal workflow with a test packet that checks whether the outputs actually do the job.

Planned Lessons

  1. Pixels, Samples, Frames, And TokensCompare how computers represent a picture, a sound recording, a video and a sentence.
  2. Classification, Detection, Segmentation, And GenerationDistinguish AI that recognises something, finds it in an image or creates new media.
  3. Visual Encoders, Convolution, And PatchesSee how a model turns image details into information it can use.
  4. Aligning Images And LanguageExplore how AI connects pictures with the words used to describe them.
  5. OCR And Document UnderstandingFollow how AI reads text and layout from a document or scanned page.
  6. Charts, Diagrams, And Spatial ReasoningSee why reading a chart or a diagram requires understanding positions and relationships.
  7. Audio Representation And PreprocessingExplore how recorded sound is prepared before an AI model processes it.
  8. Speech Recognition, Diarization, And Transcription ErrorsSpot errors in automatic transcripts, including mistakes about who said what.
  9. Speech Synthesis And Speech-To-Speech SystemsCompare turning written text into speech with generating a reply from spoken input.
  10. Video: Time, Motion, And SamplingSee how choosing which video frames to inspect affects what an AI system understands.
  11. Diffusion: Learning To Reverse A Noise ProcessExplore how an AI image model learns to build a picture by removing noise step by step.
  12. Latent Generation, Guidance, And EditingSee how an image request and editing instructions guide the media a model creates.
  13. Multimodal Evaluation And Failure IsolationFind which step caused an error in a tool that works with images, audio or video.
  14. Provenance, Rights, And Authentic CommunicationCheck the sources, permissions and disclosures needed when sharing AI-created media.
  15. Architecture And Economics Of A Multimodal WorkflowMap the steps and costs of an app that combines several kinds of media.
  16. A Checked Workflow For Your Beginner VideosPlan a video from script to narration and final checks, using AI tools where they help.