Q-Aware Labs is dedicated to advancing the quality, safety, and reliability of artificial intelligence systems through rigorous testing, ethical safeguards, and data quality improvements. My main mission is to help organizations build more robust, reliable, and responsible AI solutions.
I am in the way to develop frameworks, tools, and methodologies for comprehensive AI system testing, focusing on:
- Performance validation across diverse scenarios
- Robustness testing against edge cases
- Consistency evaluation across model versions
- Behavioral testing for expected outputs
Committed to developing and implementing safeguards that ensure AI systems operate within ethical boundaries:
- Bias detection and mitigation strategies
- Fairness metrics and monitoring
- Transparency and explainability tools
- Safety evaluation frameworks
I research and develop best practices for prompt engineering:
- Systematic prompt testing methodologies
- Prompt optimization techniques
- Reliability enhancement through prompt design
- Version control and management for prompts
My testing automation initiatives focus on:
- Automated test case generation
- Continuous integration for AI systems
- Regression testing frameworks
- Performance monitoring tools
Help organizations maintain high-quality training data through:
- Data validation frameworks
- Dataset bias analysis
- Data cleaning and preprocessing tools
- Quality metrics and monitoring systems
Explore my repositories to find tools and resources for:
- AI testing frameworks
- Prompt engineering utilities
- Data quality assessment tools
- Ethical AI evaluation suites
- Documentation and guides
- Email: antony.garcia@qawarelabs.com
All projects under Q-Aware Labs are licensed under the MIT License unless otherwise specified.
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