Abstract: A cloud platform may include a model interface that receives from a client and at an interface for accessing a large language model, a prompt for a response from the large language model, and the client is associated with a set of configuration parameters via a cloud platform that supports the interface. The cloud platform may modify, in accordance with the set of configuration parameters, the prompt that results in a modified prompt and transmit, to the large language model, the modified prompt. The cloud platform may receive the response generated by the large language model and provide the response to a model that determines one or more probabilities that the response contains content from one or more content categories. The cloud platform may transmit the response or the one or more probabilities to the client.

Abstract: A method identifies relevant data sources in a data visualization user interface. The process constructs an interaction matrix X whose rows correspond to users and whose columns correspond to data sources. Each entry measures the extent to which a user interacts with a data source according to user interactions with data visualizations generated from the data source. The method factors X into a product of a user matrix U times a source matrix ST using iterative refinement to minimize the least squares difference between X and U·ST. A user connects to a data server. The method computes affinity scores between the user and data sources. Each affinity score is a dot product of a row of U (a user) and a row of S (a data source). The method selects some data sources corresponding to high computed affinity scores and returns the selected data sources to the user.

Abstract: In an AC/DC converter including an autotransformer having a primary winding connected to an AC power supply network and two secondary windings connected to two rectifier circuits operating in parallel to deliver a DC voltage to a load, the two same-polarity outputs of the two rectifier circuits being connected to respective first ends of a first coil and of a second coil whose second ends are connected together to form a first output of the converter, and the two outputs of the two rectifier circuits having the same other polarity being connected respectively to the first ends of a third coil and of a fourth coil whose second ends are connected together to form a second output of the converter, provision is made for the first, second, third, and fourth coils are wound on a common magnetic core. The invention is applicable to converters for use on board aircraft.

Abstract: A method for training a classifier which forms part of a search engine comprises: receiving a document submitted by an end user of the search engine at a server; creating a training set of documents, the training set including the document submitted by the end user; training the classifier using the training set; and paying an incentive to the end user for submitting the document.

Abstract: In an AC/DC converter including an autotransformer having a primary winding connected to an AC power supply network and two secondary windings connected to two rectifier circuits operating in parallel to deliver a DC voltage to a load, the two same-polarity outputs of the two rectifier circuits being connected to respective first ends of a first coil and of a second coil whose second ends are connected together to form a first output of the converter, and the two outputs of the two rectifier circuits having the same other polarity being connected respectively to the first ends of a third coil and of a fourth coil whose second ends are connected together to form a second output of the converter, provision is made for the first, second, third, and fourth coils are wound on a common magnetic core. The invention is applicable to converters for use on board aircraft.

Abstract: According to one aspect of the invention, there is provided a method for training a classifier. The method includes receiving a document submitted by an end user of the classifier at a server. Creating a training set of documents, the training set including the document submitted by the end user. Training the classifier using the training set and paying an incentive to the end user for submitting the document.