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Combining insights from generative probabilistic models and systems neuroscience

Combining insights from generative probabilistic models and systems neuroscience

We are building a unified algorithmic architecture to achieve human-level intelligence in vision, language, and motor control. Currently, we are focusing on visual object recognition and segmentation. We are interested in general solutions that work well across multiple sensory domains and tasks. Using inductive biases drawn from neuroscience, our system requires orders of magnitude less training data than traditional machine learning techniques. Our underlying framework combines advantages of deep architectures and generative probabilistic models. We use modern software engineering practices, and we strive to maintain a codebase and a culture that are a joy to work in.
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Computer Vision Researcher

Dev/Ops Engineer - Cloud Infrastructure

Software Engineer - Camera/Imaging

Machine Learning Researcher

Senior Cloud Software Engineer

Integration Engineer

Senior Frontend Engineer

Roboticist (Control)

Founder Vicarious FPC Inc
Total raised

$122M

Funded over

6 rounds

Latest round

Series C (Jul 2017)