Mobility Intelligence and Neurosymbolic Systems

Most of you know our firm from its investments in early-stage AI software startups and as an AI advisor to corporations. Few know about the AI systems we have been developing and how we use them with our corporate customers or in new startups we spin out. Over the past several years we have been working on a class of AI-based mobility intelligence systems that are used for understanding a population’s mobility behavior within a region, such as a neighborhood, a city, or even an entire state. We found that neurosymbolic systems that incorporate generative AI components can be extremely effective in understanding such behaviors and providing their users with mobility intelligence.

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Autonomous Vehicles Employing An End-to-End AI Approach

Robotaxis and autonomoustrucks are the two autonomous vehicle use cases that receive the most attention. AI is a key enabling technology for both. To achieve the determinism required in mobility, #AV software platforms incorporated a combination of statistical and symbolic AI. A new crop of AV startups, led by Wayve and Waabi, received large financing rounds for their “end-to-end” deep neural network approaches similar to those used in generative AI. Could these approaches result in vehicles that are cheaper to produce and operate than those utilizing the approaches used to date, adhere to regulations, and be accepted by autonomous vehicle users?

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