Patents by Inventor Madan Mohan Rao Jampani
Madan Mohan Rao Jampani has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 11699093Abstract: Techniques for generating and executing an execution plan for a machine learning (ML) model using one of an edge device and a non-edge device are described. In some examples, a request for the generation of the execution plan includes at least one objective for the execution of the ML model and the execution plan is generated based at least in part on comparative execution information and network latency information.Type: GrantFiled: January 16, 2018Date of Patent: July 11, 2023Assignee: Amazon Technologies, Inc.Inventors: Nagajyothi Nookula, Poorna Chand Srinivas Perumalla, Aashish Jindia, Danjuan Ye, Eduardo Manuel Calleja, Song Ge, Vinay Hanumaiah, Wanqiang Chen, Safeer Mohiuddin, Romi Boimer, Madan Mohan Rao Jampani, Fei Chen
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Patent number: 11443237Abstract: Systems and techniques are disclosed for a centralized platform for enhanced automated machine learning using disparate datasets. An example method includes receiving user specification of one or more data sources to be integrated with the system, the data sources storing datasets to be utilized to train one or more machine learning models by the system, and the datasets reflecting user interaction data. A dataset is imported from the data source, and machine learning models are automatically trained based a particular machine learning model recipe of a plurality of machine learning model recipes. A first trained machine learning model is implemented, with the system being configured to respond to queries based on the implemented machine learning model, and with the responses including personalized recommendations.Type: GrantFiled: November 26, 2019Date of Patent: September 13, 2022Assignee: Amazon Technologies, Inc.Inventors: Hyunjoon Song, Bindu Priya Reddy, Shuyi Zhang, Venkatesh Maralavadi Sreenivas, Madan Mohan Rao Jampani, Stefano Stefani
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Patent number: 11075991Abstract: A data set may be partitioned according to relative differences indicated by a cover tree. A cover tree may be generated for a data set. Items in the data set may be stored at the same or different nodes according to the relative difference between the items indicated in the cover tree. Portions of the cover tree may be assigned to different nodes storing the data set. Access requests for the data set may be performed by sending the access requests to nodes identified according to the assigned portions of the cover tree.Type: GrantFiled: April 3, 2020Date of Patent: July 27, 2021Assignee: Amazon Technologies, Inc.Inventors: Pracheer Gupta, Poorna Chand Srinivas Perumalla, Jia Bi Zhang, Srikanth Kandalam Srinivasa, Madan Mohan Rao Jampani, Stefano Stefani
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Patent number: 11023440Abstract: A computing resource service provider deploys resources to process input data sets on an ongoing basis and provide requestors with queryable data structures generated from the input data sets over determined, rolling periods of time. In one embodiment, the input data sets are processed using one or more nearest neighbor search algorithms, and the outputs therefrom are represented in data structures which are rotated as newer data structures are subsequently generated. The disclosed systems and techniques improve resource utilization, processing efficiency, query latency, and result consistency relative to known controls for large and/or complex data processing tasks, such as those employed in machine learning techniques.Type: GrantFiled: June 27, 2017Date of Patent: June 1, 2021Assignee: Amazon Technologies, Inc.Inventors: Pracheer Gupta, Madan Mohan Rao Jampani, Andrea Olgiati, Poorna Chand Srinivas Perumalla, Stefano Stefani
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Patent number: 10964312Abstract: Features are disclosed for generating predictive personal natural language processing models based on user-specific profile information. The predictive personal models can provide broader coverage of the various terms, named entities, and/or intents of an utterance by the user than a personal model, while providing better accuracy than a general model. Profile information may be obtained from various data sources. Predictions regarding the content or subject of future user utterances may be made from the profile information. Predictive personal models may be generated based on the predictions. Future user utterances may be processed using the predictive personal models.Type: GrantFiled: August 13, 2018Date of Patent: March 30, 2021Assignee: Amazon Technologies, Inc.Inventors: William Folwell Barton, Rohit Prasad, Stephen Frederick Potter, Nikko Strom, Yuzo Watanabe, Madan Mohan Rao Jampani, Ariya Rastrow, Arushan Rajasekaram
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Patent number: 10915524Abstract: A computing resource service provider deploys resources to process input data sets on an ongoing basis and provide requestors with queryable data structures generated from the input data sets over determined, rolling periods of time. In one embodiment, the input data sets are processed using one or more nearest neighbor search algorithms, and the outputs therefrom are represented in data structures which are rotated as newer data structures are subsequently generated. The disclosed systems and techniques improve resource utilization, processing efficiency, query latency, and result consistency relative to known controls for large and/or complex data processing tasks, such as those employed in machine learning techniques.Type: GrantFiled: June 27, 2017Date of Patent: February 9, 2021Assignee: Amazon Technologies, Inc.Inventors: Pracheer Gupta, Poorna Chand Srinivas Perumalla, Andrea Olgiati, Madan Mohan Rao Jampani, Stefano Stefani
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Publication number: 20200236171Abstract: A data set may be partitioned according to relative differences indicated by a cover tree. A cover tree may be generated for a data set. Items in the data set may be stored at the same or different nodes according to the relative difference between the items indicated in the cover tree. Portions of the cover tree may be assigned to different nodes storing the data set. Access requests for the data set may be performed by sending the access requests to nodes identified according to the assigned portions of the cover tree.Type: ApplicationFiled: April 3, 2020Publication date: July 23, 2020Applicant: Amazon Technologies, Inc.Inventors: Pracheer Gupta, Poorna Chand Srinivas Perumalla, Jia Bi Zhang, Srikanth Kandalam Srinivasa, Madan Mohan Rao Jampani, Stefano Stefani
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Patent number: 10616338Abstract: A data set may be partitioned according to relative differences indicated by a cover tree. A cover tree may be generated for a data set. Items in the data set may be stored at the same or different nodes according to the relative difference between the items indicated in the cover tree. Portions of the cover tree may be assigned to different nodes storing the data set. Access requests for the data set may be performed by sending the access requests to nodes identified according to the assigned portions of the cover tree.Type: GrantFiled: September 25, 2017Date of Patent: April 7, 2020Assignee: Amazon Technologies, Inc.Inventors: Pracheer Gupta, Poorna Chand Srinivas Perumalla, Jia Bi Zhang, Srikanth Kandalam Srinivasa, Madan Mohan Rao Jampani, Stefano Stefani
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Patent number: 10587632Abstract: A method and system including a neural network configured to detect whether a source of the networks packets is transmitting in accordance with a recognized application protocol. The neural network analyzes a set of network packets to determine a probability that the network pattern corresponds to a network pattern associated with a recognized application protocol. If the probability associated with a first recognized application protocol exceeds a threshold probability value, the transmission of the set of network packets may be classified as being transmitted in accordance with the first recognized application protocol. If the probabilities corresponding to the respective recognized application protocols do not exceed the threshold probability value, the neural network classifies the transmission of the set of network packets as malware.Type: GrantFiled: September 28, 2017Date of Patent: March 10, 2020Assignee: Amazon Technologies, Inc.Inventors: Poorna Chand Srinivas Perumalla, Pracheer Gupta, Madan Mohan Rao Jampani
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Patent number: 10496426Abstract: A cluster formation engine invokes generation of an automatically scalable group (ASG) of virtual machine instances, where the ASG is associated with one or more applications to be run in a cloud computing environment. The cluster formation engine detects a failure to generate a first virtual machine instance to be included in the ASG, and completes the generation of the ASG without including the first virtual machine instance in the ASG.Type: GrantFiled: May 30, 2017Date of Patent: December 3, 2019Assignee: Amazon Technologies, Inc.Inventors: Naveen Mysore Nagendra Swamy, Madan Mohan Rao Jampani, Alexander Johannes Smola, Bhavin Thaker
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Publication number: 20190220783Abstract: Techniques for generating and executing an execution plan for a machine learning (ML) model using one of an edge device and a non-edge device are described. In some examples, a request for the generation of the execution plan includes at least one objective for the execution of the ML model and the execution plan is generated based at least in part on comparative execution information and network latency information.Type: ApplicationFiled: January 16, 2018Publication date: July 18, 2019Inventors: Nagajyothi NOOKULA, Poorna Chand Srinivas PERUMALLA, Aashish JINDIA, Danjuan YE, Eduardo Manuel CALLEJA, Song GE, Vinay HANUMAIAH, Wanqiang CHEN, Safeer MOHIUDDIN, Romi BOIMER, Madan Mohan Rao JAMPANI, Fei CHEN
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Publication number: 20190180736Abstract: Features are disclosed for generating predictive personal natural language processing models based on user-specific profile information. The predictive personal models can provide broader coverage of the various terms, named entities, and/or intents of an utterance by the user than a personal model, while providing better accuracy than a general model. Profile information may be obtained from various data sources. Predictions regarding the content or subject of future user utterances may be made from the profile information. Predictive personal models may be generated based on the predictions. Future user utterances may be processed using the predictive personal models.Type: ApplicationFiled: August 13, 2018Publication date: June 13, 2019Inventors: William Folwell Barton, Rohit Prasad, Stephen Frederick Potter, Nikko Strom, Yuzo Watanabe, Madan Mohan Rao Jampani, Ariya Rastrow, Arushan Rajasekaram
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Patent number: 10109273Abstract: Features are disclosed for maintaining data that can be used to personalize spoken language understanding models, such as speech recognition or natural language understanding models. The personalization data can be used to update the models based on some or all of the data. The data may be obtained from various data sources, such as applications or services used by the user. Personalized spoken language understanding models may be generated or updated based on updates to the personalization data or some other portion of the stored personalization data. Generation of personalized spoken language understanding models may be prioritized such that the generation process accommodates multiple users.Type: GrantFiled: August 29, 2013Date of Patent: October 23, 2018Assignee: Amazon Technologies, Inc.Inventors: Arushan Rajasekaram, Nikko Strom, Madan Mohan Rao Jampani
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Patent number: 10049656Abstract: Features are disclosed for generating predictive personal natural language processing models based on user-specific profile information. The predictive personal models can provide broader coverage of the various terms, named entities, and/or intents of an utterance by the user than a personal model, while providing better accuracy than a general model. Profile information may be obtained from various data sources. Predictions regarding the content or subject of future user utterances may be made from the profile information. Predictive personal models may be generated based on the predictions. Future user utterances may be processed using the predictive personal models.Type: GrantFiled: September 20, 2013Date of Patent: August 14, 2018Assignee: Amazon Technologies, Inc.Inventors: William Folwell Barton, Rohit Prasad, Stephen Frederick Potter, Nikko Strom, Yuzo Watanabe, Madan Mohan Rao Jampani, Ariya Rastrow, Arushan Rajasekaram
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Patent number: 9361289Abstract: Features are disclosed for maintaining data that can be used to personalize spoken language processing, such as automatic speech recognition (“ASR”), natural language understanding (“NLU”), natural language processing (“NLP”), etc. The data may be obtained from various data sources, such as applications or services used by the user. User-specific data maintained by the data sources can be retrieved and stored for use in generating personal models. Updates to data at the data sources may be reflected by separate data sets in the personalization data, such that other processes can obtain the update data sets separate from other data.Type: GrantFiled: August 30, 2013Date of Patent: June 7, 2016Assignee: Amazon Technologies, Inc.Inventors: Madan Mohan Rao Jampani, Arushan Rajasekaram, Nikko Strom, Yuzo Watanabe, Stan Weidner Salvador