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Jason Okorie@jasonokorie
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1 year of experience
About me
I'm here to learn and make an impact. I'm relentlessly working towards being a leader in innovation, technology and my community. My interests in artificial intelligence, embedded systems and bioinformatic tracking for wearables shape my core competencies. My goal is to merge my passion for robotics and automation with computational biotechnology, contributing to groundbreaking advancements in medical technologies.
is under improvement
🤝 Top Collaborators
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🤓 Latest Submissions
GoferAI - Semantic VLA RAG Layer
Gofer AI is a human-to-robot learning platform that transforms everyday demonstration videos into robot-executable intelligence. Instead of manually programming robotic behavior through conventional reinforcement learning, users can record a task using a phone or GoPro. Our system extracts keyframes using OpenCV, identifies task phases, objects, and human motion patterns using multimodal Gemini models, and converts demonstrations into structured semantic memory through a Video RAG architecture. These demonstrations are embedded, tagged, and stored for retrieval, allowing the system to reason over prior tasks and reuse knowledge. The extracted trajectories are converted into canonical action representations, then replayed and augmented in simulation using Isaac Lab and Real2Render2Real for scalable data generation. This pipeline enables behavior cloning, demo-initialized reinforcement learning, and diffusion-based policy training. The result is a robot-ready policy capable of sim-to-real transfer. Gofer AI bridges the gap between human intent and autonomous execution—turning video into intelligence.
15 Feb 2026
