The technical architecture of GenSpark.ai is built on a cloud-based infrastructure, providing automatic scalability and high availability. It uses containerization technologies such as Docker and Kubernetes for efficient resource management and deployment. The underlying technology stack includes popular frameworks and libraries like TensorFlow, PyTorch, and scikit-learn for machine learning model development. Security measures include data encryption in transit and at rest, multi-factor authentication, and compliance with industry standards like GDPR and HIPAA. Performance optimization is achieved through distributed computing and real-time monitoring tools that provide insights into system performance and resource utilization.