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🔬Deep Dive
Math Foundations
Neural Networks
Transformer Architecture
Scaling
LLM Pre-training
Alignment Techniques
Reasoning Internals
Interpretability
Model Architectures
Hardware & Compute
Fine-tuning & Adaptation
Research Skills
AI Economics & Impact
🔬Deep Dive
Math Foundations
Neural Networks
Transformer Architecture
Scaling
LLM Pre-training
Alignment Techniques
Reasoning Internals
Interpretability
Model Architectures
Hardware & Compute
Fine-tuning & Adaptation
Research Skills
AI Economics & Impact
Deep DiveScaling

Scaling

The laws governing how model capability grows with compute, data, and parameters — and what happens at the frontier.

In This Section

Scaling Laws — Compute, Data, Parameters

Kaplan et al. power laws, FLOP budgeting, and predicting performance before training.

Chinchilla & Optimal Training

Compute-optimal training, the 20 tokens/parameter rule, and deliberate overtraining.

Emergent Abilities & Phase Transitions

Capabilities that appear suddenly at scale and why they are hard to predict.

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