公开(公告)号：US11863844B2

公开(公告)日：2024-01-02

申请号：US16833582

申请日：2020-03-28

Applicant: Intel Corporation

Inventor： Ravishankar Iyer ,  Nilesh Kumar Jain ,  Rameshkumar Illikkal ,  Carl S. Marshall ,  Selvakumar Panneer ,  Rajesh Poornachandran

IPC: H04N21/234 ,  H04N21/81 ,  H04N21/647 ,  H04N21/235

CPC classification number: H04N21/812 ,  H04N21/235 ,  H04N21/23418 ,  H04N21/23424 ,  H04N21/64715

Abstract: Various embodiments for dynamically generating an advertisement in a video stream are disclosed. In one embodiment, video stream content associated with a video stream for a user device is received. Video analytics data is obtained for the video stream content, which indicates a scene recognized in the video stream content. An advertisement to be generated and inserted into the video stream content is then selected based on the scene recognized in the video stream content, and an advertisement template for generating the selected advertisement is obtained. Video advertisement content corresponding to the advertisement is then generated based on the advertisement template and the video analytics data. The video advertisement content is then inserted into the video stream content, and the modified video stream content is transmitted to the user device.

公开(公告)号：US20200250003A1

公开(公告)日：2020-08-06

申请号：US16652038

申请日：2018-06-29

Applicant: Intel Corporation

Inventor： Shao-Wen Yang ,  Yen-Kuang Chen ,  Ragaad Mohammed Irsehid Altarawneh ,  Juan Pablo Munoz Chiabrando ,  Siew Wen Chin ,  Kushal Datta ,  Subramanya R. Dulloor ,  Julio C. Zamora Esquivel ,  Omar Ulises Florez Choque ,  Vishakha Gupta ,  Scott D. Hahn ,  Rameshkumar Illikkal ,  Nilesh Kumar Jain ,  Siti Khairuni Amalina Kamarol ,  Anil S. Keshavamurthy ,  Heng Kar Lau ,  Jonathan A. Lefman ,  Yiting Liao ,  Michael G. Millsap ,  Ibrahima J. Ndiour ,  Luis Carlos Maria Remis ,  Addicam V. Sanjay ,  Usman Sarwar ,  Eve M. Schooler ,  Ned M. Smith ,  Vallabhajosyula S. Somayazulu ,  Christina R. Strong ,  Omesh Tickoo ,  Srenivas Varadarajan ,  Jesús A. Cruz Vargas ,  Hassnaa Moustafa ,  Arun Raghunath ,  Katalin Klara Bartfai-Walcott ,  Maruti Gupta Hyde ,  Deepak S. Vembar ,  Jessica McCarthy

IPC: G06F9/50 ,  G06K9/00 ,  G06N3/04 ,  G06N3/063

Abstract: In one embodiment, an apparatus comprises a processor to: identify a workload comprising a plurality of tasks; generate a workload graph based on the workload, wherein the workload graph comprises information associated with the plurality of tasks; identify a device connectivity graph, wherein the device connectivity graph comprises device connectivity information associated with a plurality of processing devices; identify a privacy policy associated with the workload; identify privacy level information associated with the plurality of processing devices; identify a privacy constraint based on the privacy policy and the privacy level information; and determine a workload schedule, wherein the workload schedule comprises a mapping of the workload onto the plurality of processing devices, and wherein the workload schedule is determined based on the privacy constraint, the workload graph, and the device connectivity graph. The apparatus further comprises a communication interface to send the workload schedule to the plurality of processing devices.

公开(公告)号：US20240013099A1

公开(公告)日：2024-01-11

申请号：US18471128

申请日：2023-09-20

Applicant: Intel Corporation

Inventor： Rohit Verma ,  Arun Raghunath ,  Juan Pablo Munoz ,  Nilesh Kumar Jain

IPC: G06N20/00

CPC classification number: G06N20/00

Abstract: Methods, apparatus and articles of manufacture to implement frameworks for training of federated learning models are disclosed. Example apparatus disclosed herein are to cause transmission of a first query to a first worker node of a plurality of worker nodes, the first query based on constraints to train a machine learning model. Disclosed example apparatus are also to cause transmission of a second query to a second worker node of the plurality of worker nodes, the second query based on the constraints. Disclosed example apparatus are further to cause transmission of a third query to the first worker node based on comparison of a first score from the first worker node to a second score from the second worker node, the third query instructing the first worker node to train the machine learning model.

公开(公告)号：US20250061317A1

公开(公告)日：2025-02-20

申请号：US18935223

申请日：2024-11-01

Applicant: INTEL CORPORATION

Inventor： Juan Pablo Munoz Chiabrando ,  Jinjie Yuan ,  Nilesh Kumar Jain

IPC: G06N3/0495

Abstract: An example apparatus includes interface circuitry, machine-readable instructions, and at least one processor circuit to be programmed by the machine-readable instructions to sparsify a base model of a foundation model to generate a sparse base model, apply a neural low-rank adapter search to the sparse base model, and output a fine-tuned base model based on application of the neural low-rank adapter search to the sparse base model.