Educating AI: Review and analyze AI-generated outputs, providing structured feedback to improve the model’s understanding and ability to apply knowledge to real-world situations. Help refine the AI’s decision-making process and problem-solving capabilities.
Problem Solving: Break down complex problems into clear, step-by-step solutions. Guide the AI through these problems to teach it how to reason and solve them effectively and logically.
Red Teaming: Assess the AI's knowledge base for biases, inaccuracies, and gaps. Design and execute tests that push the model’s boundaries, ensuring it produces reliable and accurate outputs that meet real-world expectations.
Continuous Improvement: Work collaboratively with AI developers and researchers to integrate feedback, contributing to the ongoing refinement and evolution of the AI system.
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