Kepler V2
Providing a prompt that introduces a mathematics topic from high school to undergraduate level, then allowing the AI to answer, and then we verify the answer with general characteristics such as truthfulness, vocabulary, etc.
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Experienced in AI training and data annotation, specializing in refining machine learning models through structured datasets. Skilled in evaluating AI responses, labeling data with precision, and optimizing models to enhance accuracy and coherence. Proficient in crafting and curating question-answer datasets, aligning AI behavior with specific guidelines, and adapting responses based on diverse personality frameworks. Strong ability to analyze linguistic patterns, improve contextual understanding, and ensure high-quality AI interactions.
Providing a prompt that introduces a mathematics topic from high school to undergraduate level, then allowing the AI to answer, and then we verify the answer with general characteristics such as truthfulness, vocabulary, etc.
As an AI Trainer at Alignerrr, I worked closely with Omni, an AI model that required fine-tuning based on specific criteria. My role involved curating and annotating question-answer datasets to enhance its conversational abilities and decision-making processes. This experience sharpened my expertise in data labeling, prompt evaluation, and AI alignment. Additionally, I had to adapt Omni’s responses based on various AI personalities, ensuring consistency across different tones and behavioral frameworks. This required a deep understanding of linguistic nuances, user intent, and model optimization techniques to refine its interactions. My work contributed to improving the model’s coherence, contextual awareness, and adaptability.
Preparatory Class (Second Year), Second-year Preparatory Class
Preparatory Class (First Year), Mathematics, Physics & Computer Science
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