By Mugi
Mugi updates her project by moving from a single-camera setup to a dual-camera solution, improving motion capture accuracy and overall system reliability.
More from the Lab
Eman demos a website that reads grid-based inputs and game elements, helping AI reliably understand board game layouts, mechanics, and rules.
Mugi shares early SignMate experiments capturing ASL motion, testing MediaPipe, RPM, and ASL Mocap datasets to evaluate gesture accuracy and complexity.
Mugi updates SignMate's motion generation system by adding face tracking and fingerspelling to improve ASL accuracy, expressiveness, and realism.
Sometimes our AI just stopped responding. Mugi shows how we fixed silent failures and made Yield reliable.
Research-backed principles that make AI interviews feel more natural and trustworthy.
40 seconds per turn was too slow. Eman parallelized agents, fixed caching, and cut latency by 12%. Here's how.