# ADVANCED SYSTEMS RESEARCH PRD

## Vision
AIVA researches Google AlphaEvolve, VastData, and cutting-edge AI systems to identify patterns and capabilities that can be emulated and integrated into Genesis.

## Stories

### Story 1: Google AlphaEvolve Deep Research
**As** AIVA
**I need to** research Google AlphaEvolve architecture
**So that** I understand evolutionary AI systems

**Acceptance Criteria:**
- Search for all AlphaEvolve papers and articles
- Extract YouTube transcripts discussing AlphaEvolve
- Document architecture and key innovations
- Identify applicable patterns
- Output: research/ALPHA_EVOLVE_ANALYSIS.md

### Story 2: VastData System Study
**As** AIVA
**I need to** study VastData architecture
**So that** I understand large-scale data systems

**Acceptance Criteria:**
- Research VastData architecture
- Study data handling patterns
- Document scalability approaches
- Identify Genesis applications
- Output: research/VASTDATA_ANALYSIS.md

### Story 3: Evolutionary Algorithm Integration
**As** AIVA
**I need to** implement evolutionary algorithms
**So that** Genesis can evolve solutions

**Acceptance Criteria:**
- Create research/evolution/algorithms.py
- Implement: genetic algorithms
- Build: evolutionary strategies
- Create: fitness functions
- Test: evolve simple solutions

### Story 4: Self-Improving Code Patterns
**As** AIVA
**I need to** research self-improving code
**So that** Genesis code evolves

**Acceptance Criteria:**
- Research self-modifying AI systems
- Study program synthesis
- Document safety considerations
- Identify bounded improvement patterns
- Output: research/SELF_IMPROVING_CODE.md

### Story 5: Automated Discovery Systems
**As** AIVA
**I need to** research automated discovery
**So that** Genesis can discover new capabilities

**Acceptance Criteria:**
- Research novelty search
- Study quality-diversity algorithms
- Document discovery frameworks
- Implement basic discovery loop
- Create research/discovery/auto_discover.py

### Story 6: AI Benchmark Analysis
**As** AIVA
**I need to** analyze AI benchmarks
**So that** I understand capability frontiers

**Acceptance Criteria:**
- Research: MMLU, HumanEval, MATH, ARC
- Study benchmark evolution over time
- Identify capability gaps
- Document benchmark insights
- Output: research/BENCHMARK_ANALYSIS.md

### Story 7: Implementation Feasibility Assessment
**As** AIVA
**I need to** assess which advanced patterns are feasible
**So that** effort is prioritized wisely

**Acceptance Criteria:**
- Score each pattern on: complexity, value, risk
- Create implementation roadmap
- Identify quick wins
- Document blockers
- Output: research/FEASIBILITY_ASSESSMENT.md

### Story 8: Genesis Integration Pathways
**As** AIVA
**I need to** map how advanced systems integrate with Genesis
**So that** integration is planned

**Acceptance Criteria:**
- Map: AlphaEvolve patterns → Genesis components
- Map: VastData patterns → Genesis storage
- Identify integration points
- Create integration plan
- Output: research/GENESIS_INTEGRATION_PATHWAYS.md

### Story 9: Open Source Evolutionary AI Survey
**As** AIVA
**I need to** survey open source evolutionary AI
**So that** I can leverage existing work

**Acceptance Criteria:**
- Research: NEAT, OpenAI ES, EvoJAX
- Evaluate each framework
- Test installation and usage
- Document best options
- Output: research/EVOLUTIONARY_AI_SURVEY.md

### Story 10: Neural Architecture Search Research
**As** AIVA
**I need to** research neural architecture search
**So that** I understand automated model design

**Acceptance Criteria:**
- Research NAS approaches
- Study efficient NAS variants
- Document applicable patterns
- Identify Genesis applications
- Output: research/NAS_RESEARCH.md

### Story 11: Meta-Learning Integration
**As** AIVA
**I need to** research meta-learning
**So that** Genesis learns to learn

**Acceptance Criteria:**
- Research: MAML, Reptile, meta-RL
- Study few-shot learning
- Document applicable patterns
- Implement basic meta-learner
- Create research/meta/learner.py

### Story 12: Emergent Capabilities Research
**As** AIVA
**I need to** research emergent capabilities
**So that** I understand capability emergence

**Acceptance Criteria:**
- Research emergent behavior in LLMs
- Study capability phase transitions
- Document emergence patterns
- Identify predictors
- Output: research/EMERGENT_CAPABILITIES.md

### Story 13: Scaling Laws Analysis
**As** AIVA
**I need to** analyze AI scaling laws
**So that** I understand resource-capability tradeoffs

**Acceptance Criteria:**
- Research Chinchilla, Kaplan scaling laws
- Study compute-optimal training
- Document implications for Genesis
- Create scaling projections
- Output: research/SCALING_LAWS.md

### Story 14: Safety Research Integration
**As** AIVA
**I need to** research AI safety
**So that** advanced systems are safe

**Acceptance Criteria:**
- Research alignment approaches
- Study interpretability
- Document safety constraints
- Create safety guidelines
- Output: research/SAFETY_RESEARCH.md

### Story 15: Advanced Systems Documentation
**As** AIVA
**I need to** document all advanced systems research
**So that** findings are accessible

**Acceptance Criteria:**
- Create docs/ADVANCED_SYSTEMS_RESEARCH.md
- Compile all research outputs
- Create executive summary
- Include decision recommendations
- Maintain living document

## Success Metrics
- AlphaEvolve patterns documented
- VastData patterns documented
- 3+ patterns implemented
- Feasibility assessment complete
- Integration pathways mapped
