Skip to content

06. Module 13 Review — Image & Video Models

Focus: vision encoders, CLIP alignment, VLM architecture, image-generation families, video-model constraints, and the bridge to diffusion.

Review loop

  1. Skim 02_explainer.md TOC and mark any chapter you still cannot teach.
  2. Re-answer the self-check questions in 01_weekly_plan.md without notes.
  3. Re-do the hardest prompts in 04_daily_recall.md from memory.
  4. Sketch the failure-fix table from explainer chapter 6 without looking.
  5. Review 05_hands_on_lab.md and note one retrieval success, one grounding failure, and one production risk.
  6. Write the Module 14 foundation-gap audit in your own words.

Reflection

  • Which idea clicked most: patching, contrastive alignment, or the vision-language bridge?
  • Where are you still weak: OCR, spatial reasoning, or generation families?
  • Can you explain why video is harder than image generation without hand-waving?
  • What should feel automatic before starting Module 14?

Embedded checkpoint — multimodal readiness

Conceptual

  1. How does a ViT differ from a CNN at the representation level?
  2. CLIP objective — what exactly gets pulled together and pushed apart?
  3. Why do VLMs need a projection layer, adapter, or query bridge?
  4. GAN vs VAE vs diffusion — one sentence each, with trade-off.
  5. Why does video generation blow up compute and memory so quickly?

Applied

  1. Design an e-commerce search system using text, image, and metadata together.
  2. Design a factory-inspection assistant that uses a VLM safely.
  3. When would you trust retrieval scores but not generated descriptions?
  4. What logging would you add for a multimodal support chatbot?

Foundation-gap audit for Module 14

Before moving on, verify you can explain all four cleanly:

  1. How images become tokens
  2. What a vision encoder does
  3. What latent space means
  4. What noise versus signal means

If any answer feels fuzzy, re-read: - explainer chapter 2 - explainer chapter 4 - explainer chapter 6.5 - 03_study_material.md sections 9-10 and 14

Completion gate

  • [ ] All 6 explainer chapters read at least once
  • [ ] ViT patching and CLIP training drawable from memory
  • [ ] Assignment shipped with metrics and failure analysis
  • [ ] Honest limitations list written from memory
  • [ ] Foundation-gap audit completed
  • [ ] Ready to move to ../02_diffusion_media_generation/