Results for “neural-network-architecture”

Enforces system design, project structure, dependency management, error handling, testing, and documentation standards at principal-engineer level.

Estructura aplicaciones Flutter en módulos independientes y reutilizables con flutter_modular, incluyendo diseño de paquetes, dependencias y configuración de Melos.

Compare tradeoffs and recommend architectural patterns — dependency injection, service-oriented architecture, repository, domain events, circuit breaker, and anti-corruption layer. Use when choosing between design patterns, planning microservices boundaries, evaluating system design alternatives, or asking 'which pattern should I use' for a specific coupling or resilience problem.

NestJS architecture including modules, dependency injection, guards, interceptors, and microservices patterns.

Eng manager-mode plan review. (gstack)

Multiplayer game development principles. Architecture, networking, synchronization.

Application architecture patterns and code organization — clean architecture, hexagonal architecture, feature-based structure, dependency inversion, module boundaries, SOLID principles at module scale. Activate on "clean architecture", "hexagonal architecture", "feature-based structure", "dependency inversion", "module boundaries", "architecture pattern", "folder structure", "fat controller", "circular dependency", "IoC container". NOT for microservice decomposition (use microservices-patterns) or database schema design (use database-design-patterns).

Applies SOLID principles, clean architecture layers, dependency injection, and patterns like CQRS and event sourcing to design scalable, maintainable systems.

SONA self-optimizing neural architecture with ReasoningBank trajectory learning, EWC++ anti-forgetting, and reinforcement learning feedback loops.

Provides guidance for interpreting and manipulating neural network internals using nnsight with optional NDIF remote execution. Use when needing to run interpretability experiments on massive models (70B+) without local GPU resources, or when working with any PyTorch architecture.

Create publication-quality scientific diagrams using Nano Banana Pro AI with smart iterative refinement. Uses Gemini 3 Pro for quality review. Only regenerates if quality is below threshold for your document type. Specialized in neural network architectures, system diagrams, flowcharts, biological pathways, and complex scientific visualizations.