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AI Lesson & Submodule

Transformer Failure Modes

Diagnose gradient explosion, representation collapse, and VRAM leaks.

Why This Matters

Large scale models suffer from training instabilities and KV Cache memory leaks in production.

What You Will Learn

  • •Diagnose gradient blowups
  • •Mitigate training collapse
  • •Track KV cache VRAM

Concepts Covered

Gradient explosionsRepresentation collapse metricsKV Cache memory logs

Mapped Foundation Project: Mini Transformer Block Explainer

Visual deconstruction of a standard decoder block, outlining normalizations, skip links, and output projections.

Architecture Preview

Block-by-block diagram tracking vector changes as inputs pass through decoder normalizations and linear mappings.

Input TokensLayer Norm Layer 1Multi-Head Attention Block
Tech Stack Planned
ReactTypeScriptFramer Motion
GitHub: Coming SoonLive Demo: Coming Soon
Coming Soon

Technical Interview Value

  • ?What is a KV Cache, and how does it optimize generation speed at the cost of VRAM memory?
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