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Topic: pytorch

64 skills in this topic.

V3 Performance Optimization Achieve aggressive v3 performance targets: 2.49x-7.47x Flash Attention speedup, 150x-12,500x search improvements, 50-75% memory reduction. Comprehensive benchmarking and optimization suite.
diegopacheco/ai-playground 15
V3 Swarm Coordination 15-agent hierarchical mesh coordination for v3 implementation. Orchestrates parallel execution across security, core, and integration domains following 10 ADRs with 14-week timeline.
diegopacheco/ai-playground 15
Verification & Quality Assurance Comprehensive truth scoring, code quality verification, and automatic rollback system with 0.95 accuracy threshold for ensuring high-quality agent outputs and codebase reliability.
diegopacheco/ai-playground 15
github-multi-repo Multi-repository coordination, synchronization, and architecture management with AI swarm orchestration
diegopacheco/ai-playground 15
deployer-workflow Full-stack development workflow that orchestrates deployer agents (backend, frontend, database, testing, review) in a phased pipeline. Asks which backend language (Java/Go/Rust) then runs all agents.
diegopacheco/ai-playground 15
deployer-workflow Full-stack development workflow that orchestrates deployer agents (backend, frontend, database, testing, review) in a phased pipeline. Asks which backend language (Java/Go/Rust) then runs all agents.
diegopacheco/ai-playground 15
deployer-workflow Full-stack development workflow that orchestrates deployer agents (backend, frontend, database, testing, review) in a phased pipeline. Asks which backend language (Java/Go/Rust) then runs all agents.
diegopacheco/ai-playground 15
vsdd Verified Spec-Driven Development (VSDD) workflow. Fuses SDD + TDD + VDD into a single AI-orchestrated pipeline. Enforces: Spec Crystallization -> Test-First Implementation -> Adversarial Refinement -> Formal Hardening -> Convergence. Use when user invokes /vsdd.
diegopacheco/ai-playground 15
runbook-generator Reads the full codebase, detects service architecture and dependencies, then generates operational runbooks for common failure modes into runbook.md.
diegopacheco/ai-playground 15
autobench
diegopacheco/ai-playground 15
deployer-workflow Full-stack development workflow that orchestrates deployer agents (backend, frontend, database, testing, review) in a phased pipeline. Asks which backend language (Java/Go/Rust) then runs all agents.
diegopacheco/ai-playground 15
deployer-workflow Full-stack development workflow that orchestrates deployer agents (backend, frontend, database, testing, review) in a phased pipeline. Asks which backend language (Java/Go/Rust) then runs all agents.
diegopacheco/ai-playground 15
deployer-workflow Full-stack development workflow that orchestrates deployer agents (backend, frontend, database, testing, review) in a phased pipeline. Asks which backend language (Java/Go/Rust) then runs all agents.
diegopacheco/ai-playground 15
deployer-workflow Full-stack development workflow that orchestrates deployer agents (backend, frontend, database, testing, review) in a phased pipeline. Asks which backend language (Java/Go/Rust) then runs all agents.
diegopacheco/ai-playground 15
deployer-workflow Full-stack development workflow that orchestrates all deployer agents (backend, frontend, database, testing, review, documentation) in a phased pipeline. Asks which backend language (Java/Go/Rust) then runs all agents.
diegopacheco/ai-playground 15
AgentDB Advanced Features Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.
diegopacheco/ai-playground 15
AgentDB Learning Plugins Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through experience.
diegopacheco/ai-playground 15
AgentDB Memory Patterns Implement persistent memory patterns for AI agents using AgentDB. Includes session memory, long-term storage, pattern learning, and context management. Use when building stateful agents, chat systems, or intelligent assistants.
diegopacheco/ai-playground 15
AgentDB Performance Optimization Optimize AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations. Use when optimizing memory usage, improving search speed, or scaling to millions of vectors.
diegopacheco/ai-playground 15
AgentDB Vector Search Implement semantic vector search with AgentDB for intelligent document retrieval, similarity matching, and context-aware querying. Use when building RAG systems, semantic search engines, or intelligent knowledge bases.
diegopacheco/ai-playground 15
browser Web browser automation with AI-optimized snapshots for claude-flow agents
diegopacheco/ai-playground 15
github-code-review Comprehensive GitHub code review with AI-powered swarm coordination
diegopacheco/ai-playground 15
github-project-management Comprehensive GitHub project management with swarm-coordinated issue tracking, project board automation, and sprint planning
diegopacheco/ai-playground 15
json-formatter Validate, format, and minify JSON files when users request JSON validation, formatting, or ask to validate their JSONs
diegopacheco/ai-playground 15