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Continuous Self-learning through Feedback Loop in AI Systems
AI systems utilize a feedback loop where the agent, co-pilot, and analyst work in harmony to continuously improve each other's knowledge. The AI agent hands over unanswered questions to the human team with the AI co-pilot, and the subsequent answer teaches the AI agent for the future. This seamless system requires all components to be integrated within the same platform to avoid data formatting and compatibility issues that could arise from merging legacy systems with AI technology. The self-improvement nature of AI systems lies in the ability for the system to internally build knowledge and learn from interactions, making it a powerful tool for organizations.