公开(公告)号：US20250094771A1

公开(公告)日：2025-03-20

申请号：US18471048

申请日：2023-09-20

Applicant: AT&T Intellectual Property I, L.P.

Inventor： Deven Panchal ,  Dan Musgrove ,  David H. Lu ,  Isilay Baran

IPC: G06N3/045 ,  G06N3/08

Abstract: Aspects of the subject disclosure may include, for example, combining a plurality of machine learning (ML) models to form a composite model, the plurality of ML models including a first ML model trained on first local data received at a first network location and added models including a second ML model through an nth ML model, respective added models of the added models each being respectively trained on respective training data at a respective network location remote from the first network location; receiving input data at the first network location; providing the input data to the composite model; receiving, from the composite model, a conclusion about a status of the input data; receiving an indication to update one or more models of the plurality of ML models; and updating the one or more models according to the indication. Other embodiments are disclosed.

公开(公告)号：US20250139429A1

公开(公告)日：2025-05-01

申请号：US18498605

申请日：2023-10-31

Applicant: AT&T Intellectual Property I, L.P.

Inventor： Sudharani Parvangada ,  Mercy Chan ,  Muralidhar Siddabathula ,  Isilay Baran

IPC: G06N3/08 ,  G06N3/0455

Abstract: Aspects of the subject disclosure may include, for example, a device having a processing system including a processor; and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations of: receiving, from a user interface, a sample input format specification and output format specification for transforming data; searching a repository for a tag and associated data; merging or updating the sample input format specification and the output format specification with the associated data responsive to finding the tag in the repository, thereby creating updated data; providing the updated data as a prompt to a large language model; receiving a response to the prompt from the large language model; verifying that the response is satisfactory; and storing a context comprising the tag, the updated data and the response in the repository. Other embodiments are disclosed.