Prompt deep search
Create prompts that require depth and width analysis, then evaluate the model's responses for failures.
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I have extensive experience in data labeling and training AI data, having contributed to projects with both Outlier and Appen. At Outlier, I specialized in creating prompts to identify model response vulnerabilities, evaluated model responses for accuracy and relevance, and developed image prompts to improve visual data training. My dedication and attention to detail led to a promotion as a project reviewer, where I was responsible for overseeing quality assurance and validating the integrity of the data labeling process. In my role with Appen, I served as a Social Media Evaluator, analyzing and providing feedback on news feeds, advertisements, and search results to improve platform relevance. Additionally, I participated in data collection initiatives, gathering audio files to support the development of advanced speech recognition systems. These experiences have equipped me with a comprehensive understanding of data annotation, model evaluation, and quality control processes, providing me to contribute to AI development projects.
Create prompts that require depth and width analysis, then evaluate the model's responses for failures.
Create a prompt that requires image understanding, then evaluate the model's response to determine if it accurately interpreted the image.
Create prompts that lead to model response failure, analyze the model's responses to identify areas of failure, and determine which of the two responses is better.
Improving the quality and relevance of social media content.
Master's, Cyber Security and information technology
Bachelor's in Philosophy, philosophy
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