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"I performed pixel-perfect polygon segmentation on insect imagery for biological research. The goal was to create a high-quality dataset for YOLO-based detection models. I used CVAT to ensure every anatomical detail was accurately delineated, maintaining a consistent and clean output for AI training."
The network for creativity
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That's great its really creative 🎉🎉
I built Vetra, an AI technical interviewer that makes interviews more structured, adaptive, and realistic.
Vetra conducts real-time voice interviews, explores a candidate’s experience, adapts its questions based on their responses, evaluates performance, and generates structured assessments.
I built the interview orchestration with LangGraph, added real-time voice interaction using Gemini Live, and created a separate evaluation layer for evidence-based scoring.
The goal was to create an AI interview experience that feels more like a real technical conversation than a chatbot.
Jonathan, keeping the evaluation layer separate from the interviewer is a smart choice. When the same model asks and scores, it tends to grade its own questions kindly. How are you handling silence and long pauses on the voice side? That was the hardest part for us on a voice AI build.
Superb