AI Library of Alexandria

Complete AI Study โ€” 48 Documents

A unified, cross-referenced knowledge base covering the entire AI stack โ€” from mathematical foundations and deep learning through LLMs, agents, RAG, enterprise deployment, multimodal AI, safety, interpretability, and the future roadmap. Auto-enriched every 12 hours.

48
Documents
54,665
Total Lines
12
Categories
46
AI Topics
๐Ÿ“

Foundations

10 docs ยท 10,334 lines

ML, Deep Learning, Training, Data Engineering, RL, GNNs, Math, Federated, Causal

๐Ÿง 

LLMs

5 docs ยท 7,897 lines

Transformer, Model Families, Tokenization, Quantization, NLP

๐Ÿค–

Agents

5 docs ยท 8,090 lines

Agent Architectures, Multi-Agent, Frameworks, MCP/ACP, Tools

๐Ÿ”

RAG

3 docs ยท 8,182 lines

RAG Architectures, Advanced RAG, Vector Databases

๐Ÿญ

Enterprise

3 docs ยท 4,493 lines

AI Deployment, Fine-Tuning, Infrastructure

โšก

Advanced

10 docs ยท 10,163 lines

Multimodal, Diffusion, Evaluation, Prompt Engineering, Interpretability, RecSys, TS, Adv, UX, AutoML

๐Ÿ”ฌ

Emerging

3 docs ยท 1,332 lines

Research Frontiers, AI Safety, AI Governance

๐Ÿ“š

Reference

3 docs ยท 1,617 lines

Glossary, Future Roadmap, SOUL.md/SKILL.md

๐Ÿ”„

Evolution

1 docs ยท 221 lines

7-Stage AI Adoption Timeline: ChatGPT to AI Economy

๐Ÿ“„

Papers

1 docs ยท 516 lines

50+ Foundational AI Papers with Summaries

๐Ÿข

Industry

3 docs ยท 826 lines

Industry Applications, AI Economics, Robotics

โšก

Hermes

1 docs ยท 994 lines

Full Reference: CLI, Slash Commands, Config, Providers, Toolsets

๐Ÿงญ Study Pathways

Choose your learning path based on your role:

๐Ÿง 
ML Engineer: Math โ†’ ML Foundations โ†’ Deep Learning โ†’ Training Methodologies โ†’ LLM Models. Start โ†’
๐Ÿ”ง
LLM Engineer: Transformer Architecture โ†’ Model Families โ†’ Tokenization โ†’ Quantization โ†’ Prompt Engineering โ†’ Evaluation. Start โ†’
๐Ÿค–
Agent Developer: Agent Architectures โ†’ MCP/ACP โ†’ Multi-Agent Systems โ†’ Agentic Frameworks โ†’ Tool Comparisons โ†’ SOUL/SKILL. Start โ†’
๐Ÿ“š
RAG Specialist: RAG Architectures โ†’ Advanced RAG โ†’ Vector Databases. Start โ†’
๐Ÿญ
Enterprise Architect: Enterprise Deployment โ†’ Fine-Tuning โ†’ AI Infrastructure โ†’ Evaluation. Start โ†’
๐Ÿš€
AI Researcher: Diffusion Models โ†’ Multimodal AI โ†’ Interpretability โ†’ Safety โ†’ Emerging Research โ†’ Papers. Start โ†’
๐Ÿ›ก๏ธ
Safety Practitioner: AI Safety โ†’ Interpretability โ†’ Governance โ†’ Adversarial ML โ†’ Federated Learning. Start โ†’

๐Ÿ“Š Library Statistics

CategoryDocsLinesKey Topics
๐Ÿ“ Foundations1010,334ML, Deep Learning, Training, Data Engineering, RL, GNNs, Math, Federated, Causal
๐Ÿง  LLMs57,897Transformer, Model Families, Tokenization, Quantization, NLP
๐Ÿค– Agents58,090Agent Architectures, Multi-Agent, Frameworks, MCP/ACP, Tools
๐Ÿ” RAG38,182RAG Architectures, Advanced RAG, Vector Databases
๐Ÿญ Enterprise34,493AI Deployment, Fine-Tuning, Infrastructure
โšก Advanced1010,163Multimodal, Diffusion, Evaluation, Prompt Engineering, Interpretability, RecSys, TS, Adv, UX, AutoML
๐Ÿ”ฌ Emerging31,332Research Frontiers, AI Safety, AI Governance
๐Ÿ“š Reference31,617Glossary, Future Roadmap, SOUL.md/SKILL.md
๐Ÿ”„ Evolution12217-Stage AI Adoption Timeline: ChatGPT to AI Economy
๐Ÿ“„ Papers151650+ Foundational AI Papers with Summaries
๐Ÿข Industry3826Industry Applications, AI Economics, Robotics
โšก Hermes1994Full Reference: CLI, Slash Commands, Config, Providers, Toolsets
Total4854,6652.1 MB

AI Library of Alexandria โ€” Complete AI Study Reference

C:\Workspace\AiBaseKnowledge\ ยท 48 Documents ยท 54,665 Lines

June 2026 ยท Auto-enriching every 12 hours