Users are excited about Perceptron Egocentric's video annotation system for embodied AI robots because it enables precise 3D spatial modeling of joints and entities while unlocking value from vast unlabeled robotics datasets.
Based on 2 visible X reactions from 4 accounts; directional sample.
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This is potentially incredible how in a three-dimensional space each joint and each part of the entity becomes a numerical point on an X, Y and Z axis and perhaps even a fourth dimension of time. I’m envisioning lidar building the conceptual space with it’s dimensions and distances
@FuturistASI agree, if this really works, it will be massive because we have petabytes of robotics data, but without labels
Early benchmarks show the API outperforming Gemini 3.5 Flash.
Users are excited about Perceptron Egocentric's video annotation system for embodied AI robots because it enables precise 3D spatial modeling of joints and entities while unlocking value from vast unlabeled robotics datasets.
Based on 2 visible X reactions from 4 accounts; directional sample.
Ask a question below.
Published answers will appear here.