Analysis:
Many machine autonomy solutions rely on Deep Learning, using massive datasets in enormous datacenters to generate autonomy software trained using statistical methods and complicated pattern matching. This approach has a number of drawbacks including technical complexity, cost and difficulty scaling. Opteran Technologies leveraged honeybee research to understand how tiny, real brains deliver complex autonomy. The algorithms and chipsets inspired by this work power Opteran’s vision based autonomy solutions -  small, lightweight, ultra-low power – that are edge only and do not rely large datasets or even training. Opteran’s solution, which they broadly deem “natural intelligence”, provides for efficient, robust, and scalable machine autonomy for a number of common autonomy tasks. – Dan Kara

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