Research Knowledge Base: AI × Networks
Deep research at the intersection of AI/ML and network systems. Structured as a 3D knowledge graph with mental models, mathematical rigor, and systematic validation.
Knowledge Domains
Networks
Pure networking concepts: ORAN architecture, 5G NR, RAN scheduling, beamforming, latency budgets, network slicing.
Explore Networks →AI / ML
Pure AI/ML concepts: Transformers, attention, KV cache, RL policy gradients, LLM serving, diffusion models, GNNs.
Explore AI →AI × Networks
The intersection: ML for RAN, RL for resource allocation, edge inference, LLM for config, traffic prediction, federated learning.
Explore Intersection →Papers
Research paper analyses across all 4 rounds: core claims, methodology, limitations, AI×Networks connections.
View Papers →Resources & Downloads
Reference handbooks that underpin the Networks and AI×Networks domains — full PDFs for deep systems study and interview prep. Click to download.
System Design Handbook
End-to-end system design reference — scaling, load balancing, caching, data partitioning, consistency models, and trade-off analysis. PDF · 47 MB
↓ Download PDFArchitecture Patterns Playbook
Software & distributed-systems architecture patterns — layered, event-driven, microservices, CQRS, and resilience playbooks. PDF · 34 MB
↓ Download PDFHow This Works
Every topic goes through 4 research rounds before completion:
| Round | Focus | Output |
|---|---|---|
| Round 1 | Mental model + intuition | Plain-language understanding, spatial metaphor, why it exists |
| Round 2 | Internal mechanics + math | Key equations, derivations, algorithmic steps, complexity analysis |
| Round 3 | Where it breaks + debates | Failure modes, edge cases, open problems, expert arguments |
| Round 4 | AI × Networks connection | Intersection links, cross-links to ≥2 existing KB nodes |
Current Backlog
See BACKLOG.md for the full topic queue, prioritized by intersection research value.
Last updated: June 2026