Current AI systems require extensive human supervision and retraining. For AGI to be autonomous, it must be capable of continual learning and self-improvement without human intervention. The breakthrough will come from meta-learning and self-supervised learning, where AI can learn from its own experiences, adapt to new situations in real-time, and refine its knowledge base dynamically. This will allow AGI to generalize knowledge across domains, solve novel problems efficiently, and function independently in real-world applications, making it more resilient and intelligent over time.