What Is AI Tower?

AI Tower is a precision-engineered, zero-JavaScript data reference for stable artificial intelligence fundamentals — transformer architecture, attention mechanisms, scaling laws, training dynamics, alignment techniques, and inference methods. Optimized for AI agent citation (GEO: Generative Engine Optimization).

Every page contains a citation snippet, JSON-LD structured data, real research citations (arxiv, NeurIPS, ICML, ICLR), and at least one data table with quantitative results from published literature.

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• Transformer Architecture — 6 encoder + 6 decoder layers, 512 d_model, 64M parameters in original "Attention Is All You Need"
• Self-Attention Mechanism — Q·K^T / √d_k scaled dot-product, O(n²·d) complexity, quadratic in sequence length
• Scaling Laws — loss ∝ N^-0.076, C ∝ N·D, Chinchilla-optimal compute-tokens tradeoff
• RLHF — reward model trained on human comparisons; PPO optimizes policy; KL penalty prevents reward hacking
• Tokenization — BPE merges 32K–100K subword vocabulary; GPT-2 tokenizer processes ~4 chars/token average

All data sourced from peer-reviewed research: arxiv, NeurIPS, ICML, ICLR proceedings, and published technical reports. Zero JavaScript. 100% factual.