Salesforce, Inc. patent applications on February 27th, 2025
Patent Applications by Salesforce, Inc. on February 27th, 2025
Salesforce, Inc.: 5 patent applications
Salesforce, Inc. has applied for patents in the areas of G06F16/28 (2), G06F9/455 (1), G06F11/36 (1), G06F16/955 (1), G06N20/00 (1) G06F9/45558 (1), G06F16/254 (1), G06F16/285 (1), G06F30/20 (1), G06N3/08 (1)
With keywords such as: data, records, inferencing, container, generate, output, dataflow, execution, assets, and object in patent application abstracts.
Patent Applications by Salesforce, Inc.
Inventor(s): Yuliya L. Feldman of Campbell CA (US) for salesforce, inc., Alexandr Nikitin of El Sobrante CA (US) for salesforce, inc., Manoj Agarwal of Cupertino CA (US) for salesforce, inc., Chirag Rajan of Burlingame CA (US) for salesforce, inc.
IPC Code(s): G06F9/455, G06F11/36, G06F16/955, G06N20/00, H04L67/133
CPC Code(s): G06F9/45558
Abstract: a method by one or more electronic devices for creating an inference container on demand. the method includes receiving, over a network, a request to create the inferencing container, wherein the inferencing container is configured to provide inferencing functionality, creating the inferencing container responsive to receiving the request to create the inferencing container, and providing, over the network, a response to the request to create the inferencing container, wherein the response includes a uniform resource locator (url) to use to submit inferencing requests to the inferencing container, wherein the url includes a unique identifier (id) of the inferencing container.
Inventor(s): Keith Kelly of San Francisco CA (US) for salesforce, inc., Ravishankar ARIVAZHAGAN of San Francisco CA (US) for salesforce, inc., Wenwen LIAO of San Francisco CA (US) for salesforce, inc., Zhongtang CAI of San Francisco CA (US) for salesforce, inc., Ali SAKR of San Francisco CA (US) for salesforce, inc.
IPC Code(s): G06F16/25, G06F16/28, G06N5/04
CPC Code(s): G06F16/254
Abstract: a computer system monitors for a change in a first data output generated by execution of a predefined dataflow. in accordance with a determination that the first data output has changed and the first data output meets triggering criteria, the computer system triggers execution of a predefined second dataflow distinct from the first dataflow. the execution of the second dataflow is dependent on the change in the first data output generated by the first dataflow. in accordance with a determination that the first data output has changed and the first data output does not meet triggering criteria, the computer system forgoes triggering execution of the second data flow. in accordance with a determination that the first data output has not changed, the computer system forgoes triggering execution of the second dataflow.
Inventor(s): Saurabh Kesarwani of Bangalore (IN) for salesforce, inc., Sandeep Ratnaparkhe of Bangalore (IN) for salesforce, inc., Shweta Parekh of Bengaluru (IN) for salesforce, inc., Milind Phadke of Hyderabad (IN) for salesforce, inc., Adheip Varadarajan of San Francisco CA (US) for salesforce, inc.
IPC Code(s): G06F16/28, G06F16/2455
CPC Code(s): G06F16/285
Abstract: in some embodiments, a method provides first data for a first reporting object that is determined by performing a first operation using respective first values associated with first records to generate a second value for the first reporting object. the first records are determined from a relationship in a data model that specifies a defined set of fields to the first reporting object for a sustainability metric. the method retrieves second records that are tagged with a custom label not used in the defined set of fields. the second records is a different set of records than the first set of records. the method provides second data for a second reporting object that is determined by performing a second operation, using respective first values associated with the second records that are associated with the custom label, to generate a third value for the second reporting object for the sustainability metric.
Inventor(s): Charles Hart Isaacs of Annapolis MD (US) for salesforce, inc.
IPC Code(s): G06F30/20, G06F9/451, G06F16/27, G06F113/02
CPC Code(s): G06F30/20
Abstract: methods and systems are provided for generating an interactive simulation representing one or more assets based on one or more asset records. based on information from asset records stored at a database system of a cloud-based computing system, an asset simulator module, executed at a cloud-based computing system, can generate one or more simulated representations of the assets. a simulator application executed at the cloud-based computing system can augment the simulated representations of the assets with (at least) additional information from the asset records stored in the database system, and generate a user interface that presents an interactive simulation of the assets. the user interface can include the simulated representations of the assets with the additional information from the asset records stored in the database system.
Inventor(s): Shiyu Wang of Atlanta GA (US) for salesforce, inc., Yihao Feng of Austin TX (US) for salesforce, inc., Tian Lan of Palo Alto CA (US) for salesforce, inc., Ning Yu of Palo Alto CA (US) for salesforce, inc., Yu Bai of Palo Alto CA (US) for salesforce, inc., Ran Xu of Mountain View CA (US) for salesforce, inc., Huan Wang of Palo Alto CA (US) for salesforce, inc., Caiming Xiong of Menlo Park CA (US) for salesforce, inc., Silvio Savarese of Palo Alto CA (US) for salesforce, inc.
IPC Code(s): G06N3/08
CPC Code(s): G06N3/08
Abstract: embodiments described herein provide a diffusion-based framework that is trained on a dataset with limited text labels, to generate a distribution of data samples in the dataset given a specific text description label. specifically, firstly, unlabeled data is used to train the diffusion model to generate a data distribution of data samples given a specific text description label. then text-labeled data samples are used to finetune the diffusion model to generate data distribution given a specific text description label, thus enhancing controllability of training.
