公开(公告)号：US20230409983A1

公开(公告)日：2023-12-21

申请号：US17843264

申请日：2022-06-17

Applicant: Cisco Technology, Inc.

Inventor： Srinivas Siva Kumar Aradhyula ,  Eugenia Kim ,  Myungjin Lee ,  Ali Payani

IPC: G06N20/20 ,  H04L67/10 ,  H04L67/52

CPC classification number: G06N20/20 ,  H04L67/10 ,  H04L67/52

Abstract: In one embodiment, a controller for a federated learning system identifies a first dataset and a second dataset available to a particular node of the federated learning system. The first dataset comprises features that are common to all nodes of the federated learning system. The second dataset comprises features that are common only to a subset of nodes of the federated learning system. The controller configures the particular node to train a first model using the first dataset. The controller causes formation of a global model in the federated learning system that aggregates the first model from the particular node with models from all other nodes of the federated learning system. The controller configures the particular node to train a second model using the second dataset.

公开(公告)号：US20250147956A1

公开(公告)日：2025-05-08

申请号：US18387278

申请日：2023-11-06

Applicant: Cisco Technology, Inc.

Inventor： Ali Payani ,  Ramana Rao V.R. Kompella

IPC: G06F16/2452 ,  G06F16/242

Abstract: In one embodiment, a method herein comprises: inputting, by a device, an input prompt to a first large language model to generate an output; computing, by the device, a reward metric in part by using a solver to process the output; tuning, by the device and based on the reward metric, a second large language model configured to correct errors of the first large language model using reinforcement learning; and using, by the device, the second large language model to correct an error of the first large language model.

公开(公告)号：US20230132213A1

公开(公告)日：2023-04-27

申请号：US17508241

申请日：2021-10-22

Applicant: Cisco Technology, Inc.

Inventor： Myungjin Lee ,  Ali Payani ,  Ramana Rao V.R. Kompella

IPC: G06N20/20

Abstract: In one embodiment, a device receives, from a plurality of training nodes that train a set of machine learning models using local training datasets, bias metrics associated with those machine learning models for each feature of the local training datasets. The device generates aggregated machine learning models over time that aggregate the machine learning models trained by the plurality of training nodes. The device constructs, based on the bias metrics, bias lineages for the aggregated machine learning models. The device provides, based on the bias lineages, a bias lineage for a particular one of the aggregated machine learning models for display.

公开(公告)号：US20250077562A1

公开(公告)日：2025-03-06

申请号：US18242933

申请日：2023-09-06

Applicant: Cisco Technology, Inc.

Inventor： Jayanth Srinivasa ,  Ali Payani ,  Ramana Rao V. R. Kompella

IPC: G06F16/34 ,  G06F16/338 ,  G06F40/106 ,  G06F40/289

Abstract: In one implementation, a device receives relevancy parameters from a user interface indicative of how relevant different portions of a text document are to a user. The device segments the text document into segments based on the relevancy parameters. The device generates a summary of the text document using the segments. The device provides, to the user interface, the summary of the text document and an indication of how much each of the segments contributed to the summary.

公开(公告)号：US20230281426A1

公开(公告)日：2023-09-07

申请号：US17684635

申请日：2022-03-02

Applicant: Cisco Technology, Inc.

Inventor： Ali Payani ,  Ramana Rao V. R. KOMPELLA

IPC: G06N3/04 ,  G06N3/08

CPC classification number: G06N3/0427 ,  G06N3/08

Abstract: In one embodiment, a device makes an inference regarding input data using an artificial intelligence model. The device captures one or more feature vectors used by the artificial intelligence model to make the inference. The device selects, based on the one or more feature vectors, a representative sample from a training dataset used to train the artificial intelligence model. The device provides the representative sample for display in conjunction with the inference.

公开(公告)号：US20230169962A1

公开(公告)日：2023-06-01

申请号：US17538148

申请日：2021-11-30

Applicant: Cisco Technology, Inc.

Inventor： Hugo Latapie ,  Ozkan Kilic ,  Adam James Lawrence ,  Gaowen Liu ,  Ramana Rao V. R. Kompella ,  Ali Payani

IPC: G10L15/18 ,  G10L15/06 ,  G10L25/48 ,  G10L15/24

CPC classification number: G10L15/1815 ,  G10L15/063 ,  G10L25/48 ,  G10L15/24

Abstract: In one embodiment, a device identifies, using a semantic reasoning engine, activities in a location, based on sensor data obtained from a plurality of sensors deployed to the location. The device associates the activities with areas of the location in which they occurred. The device makes, using the semantic reasoning engine, an inference about a particular activity, based in part on where that activity occurred. The device raises, based on the inference, an alert regarding the particular activity.

公开(公告)号：US20230058385A1

公开(公告)日：2023-02-23

申请号：US17720078

申请日：2022-04-13

Applicant: Cisco Technology, Inc.

Inventor： Pallavi Kalapatapu ,  Ali Payani

IPC: G06F21/60

Abstract: This disclosure describes techniques for protecting privacy of a user with respect to emotion detection via a computer network. The techniques may include receiving sensed data associated with a user. A privacy policy of the user may be used with processing of the sensed data. For example, based at least in part on the privacy policy, a private subset of the sensed data may be filtered from remaining sensed data. The remaining sensed data may be used to determine an emotion classification result. The emotion classification result may indicate a sharable emotion of the user, for instance.