Bangor University
Physician Associate, Medicine
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Project: Conversational AI Model Improvement Tasks: Selected and evaluated responses for given prompts, determining which responses were more appropriate, relevant, and accurate. This involved assessing the quality of generated text and ensuring it met specific criteria for coherence and context. Tools Used: Custom annotation tools, internal evaluation platforms Outcome: Improved the accuracy and relevance of the AI model's responses, leading to a more natural and effective conversational experience for users. Human-in-the-Loop Feedback (RHLF) Project: Reinforcement Learning from Human Feedback Tasks: Provided feedback on AI-generated outputs to fine-tune the model. This included ranking responses, identifying errors, and suggesting improvements. The feedback loop helped in training the model to better understand and generate human-like responses. Tools Used: Custom annotation interfaces, feedback aggregation systems Outcome: Enhanced the model’s ability to generate responses that align more closely with human expectations and preferences, resulting in a more user-friendly AI system. Text Classification
Sanaa E. hasn’t added any AI Training or Data Labeling experience to their OpenTrain profile yet.
Physician Associate, Medicine
Neuroscience, Biology
AI Trainer
Automation and AI Developer