IT Services Circle
Jun 13, 2026 · Artificial Intelligence
What Interviewers Expect: Understanding Transformers Beyond Codex and AI Code Generation
The article explains why modern interviewers ask about Transformer fundamentals, breaks down its core components such as self‑attention, multi‑head attention, feed‑forward networks, residual connections and positional encodings, and demonstrates a complete PyTorch toy model that predicts the sum‑mod‑10 of integer sequences while visualizing loss curves, attention heatmaps, embedding PCA and early‑stage gradient norms.
Gradient AnalysisModel VisualizationMulti-Head Attention
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