Abstract: A control circuit for a multi-output converter. The control circuit includes a first feedback pin and a second feedback pin. The first feedback pin is coupled to a first output terminal of the multi-output converter and receives a first feedback signal indicative of a first output signal. The second feedback pin is coupled to a second output terminal of the multi-output converter and receives a second feedback signal indicative of a second output signal. The control circuit controls a first secondary switch coupled to the first output terminal and a second secondary switch coupled to the second output terminal based on the first feedback signal and the second feedback signal. Where during a first switching cycle of multiple switching cycles, the control circuit is configured to turn on the first secondary switch and the second secondary switch in a time-multiplexed manner.

Abstract: Methods, systems, and apparatus, including computer-readable media, for managing interactions with multiple artificial intelligence chatbots. In some implementations, a text input from a user is received. The system identifies multiple chatbots that the user is authorized to access, and the system selects a subset of the multiple chatbots based on the text input from the user. The system provides the text input from the user to each of the chatbots in the subset to generate a response to the text input from each of the chatbots in the subset. The system provides an output response to the text input from the user for presentation at the user device, where the response is based on one or more of the responses generated the chatbots in the subset.

Abstract: Disclosed herein are systems and methods for intelligent generation and display of insights using information in a data repository. For example, disclosed herein are methods for generating and displaying insights using initial data from a data repository, and intelligently/automatically proposing, generating, and displaying further insights using previously-generated insights.

Abstract: A multi-label object detection method based on an object detection network includes: selecting an image of an object to be detected as an input image; based on a trained object detection network, obtaining a class of the object to be detected, coordinates of a center of the object to be detected, and a length and a width of a detection rectangular box according to the input image; and outputting the class of the object to be detected, the coordinates of the center of the object to be detected, and the length and the width of the detection rectangular box. The method of the present invention can perform real-time and accurate object detection on different classes of objects with improved detection speed and accuracy, and can solve the problem of object overlapping and occlusion during the object detection.