Lyft had ten patents in artificial intelligence during Q2 2024. Lyft Inc has filed patents for an improved transportation matching system that identifies low engagement providers and optimally matches them with scheduled transportation requests. The system also includes a directional filter to provide a transportation match probability indicator based on user manipulation. Additionally, the patents cover intelligent restrictions on transportation changes based on signals in a dynamic transportation matching system to ensure safety and efficiency. GlobalData’s report on Lyft gives a 360-degree view of the company including its patenting strategy. Buy the report here.
Lyft had no grants in artificial intelligence as a theme in Q2 2024.
Recent Patents
Application: Optimizing engagement of transportation providers (Patent ID: US20240185147A1)
The patent application from Lyft Inc. describes an enhanced transportation matching system that identifies low engagement transportation providers by analyzing their activity and generates engagement scores. The system then selects a low engagement provider to fulfill a transportation request based on rankings generated from attributes associated with the providers and the request, excluding high engagement providers. The selected provider is then notified of the request through a graphical user interface. The method also involves monitoring interactions with the mobile application, generating engagement scores using models or neural networks, identifying reasons for low engagement, and predicting probabilities of service.
Additionally, the patent application includes claims for a computer-readable storage medium and a system implementing the described method. These claims detail instructions for monitoring mobile application activity, generating engagement scores, selecting low engagement providers based on rankings, and providing notifications. The system also includes instructions for monitoring interactions with the mobile application, utilizing engagement level generator models or neural networks, identifying reasons for low engagement, and predicting probabilities of service. Furthermore, the system can handle offline providers by receiving requests to switch to online mode when notified of a transportation request.
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