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公开(公告)号：US11436524B2
公开(公告)日：2022-09-06
申请号：US16146331
申请日：2018-09-28
Applicant: Amazon Technologies, Inc.
Inventor： Nikhil Kandoi , Ganesh Kumar Gella , Rama Krishna Sandeep Pokkunuri , Sudhakar Rao Puvvadi , Stefano Stefani , Kalpesh N. Sutaria , Enrico Sartorello , Tania Khattar
IPC: G06N20/00 , G06N5/04 , G06F9/50 , H04L67/1001
Abstract: Techniques for hosting machine learning models are described. In some instances, a method of receiving a request to perform an inference using a particular machine learning model; determining a group of hosts to route the request to, the group of hosts to host a plurality of machine learning models including the particular machine learning model; determining a path to the determined group of hosts; determining a particular host of the group of hosts to perform an analysis of the request based on the determined path, the particular host having the particular machine learning model in memory; routing the request to the particular host of the group of hosts; performing inference on the request using the particular host; and providing a result of the inference to a requester is performed.
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公开(公告)号：US11341339B1
公开(公告)日：2022-05-24
申请号：US16874582
申请日：2020-05-14
Applicant: Amazon Technologies, Inc.
Inventor： Shang-Wen Daniel Li , Meghana Puvvadi , Trevor Andrew Morse , Roger Scott Jenke , Yi Zhang , Rama Krishna Sandeep Pokkunuri
Abstract: Techniques for creating and calibrating natural-language understanding (NLU) machine learning models are described. In certain embodiments, a training service tunes parameters of a function, taking the output from an NLU machine learning model as an input of the function, to calibrate the NLU machine learning model's output to optimize the interpretability of the resulting output, e.g., confidence score(s). Embodiments herein include generating, by the NLU machine learning model, an output based at least in part on an input (e.g., utterance) from a user, and applying a tuned, output modifying function to the output from the NLU machine learning model to generate a modified output. An inference may be generated based at least in part on the modified output.
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公开(公告)号：US11258725B2
公开(公告)日：2022-02-22
申请号：US16880740
申请日：2020-05-21
Applicant: Amazon Technologies, Inc.
Inventor： Parikshit Shivajirao Pol , Subramanian Sankara Subramanian , Rajaprabhu Thiruchi Loganathan , Rama Krishna Sandeep Pokkunuri , Gopinath Duddi , Akshat Vig , Safeer Mohiuddin , Sudarshan Narasimhan
IPC: G06F16/30 , H04L47/70 , G06F16/13 , G06F16/901 , G06F16/2455 , G06F9/50 , G06F11/34 , G06F16/23 , H04L43/065 , G06F11/30
Abstract: Information describing changes to a collection of items maintained by a database may be stored in a log file. The information in the log file may be converted into a stream of records describing the changes. The records may be directed to a computing node selected for performing a trigger function in response to the change, based on applying a hash function to a portion of the record, identifying a hash space associated with a value output by the hash function, and mapping from the hash space to the selected computing node.
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公开(公告)号：US11252149B1
公开(公告)日：2022-02-15
申请号：US17039920
申请日：2020-09-30
Applicant: Amazon Technologies, Inc.
Inventor： Jin Hoon Bang , Kartik Rustagi , John Baker , Swapandeep Singh , Rama Krishna Sandeep Pokkunuri , Omkar Prakash Kurode
Abstract: A resource of a dialog-driven management service is allocated for a first set of requests based on determining that a population of capacity indicators in a throttling data structure exceeds a threshold. One or more capacity indicator deduction iterations associated with the resource are conducted during a time interval for which the resource remains allocated for the first set of requests. In a given iteration, a number of capacity indicators is deducted from the throttling data structure based on a resource throttling setting. A second set of requests is rejected based on the population of the throttling data structure.
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公开(公告)号：US20210064476A1
公开(公告)日：2021-03-04
申请号：US17019072
申请日：2020-09-11
Applicant: Amazon Technologies, Inc.
Inventor： Maximiliano Maccanti , Timothy Andrew Rath , Rama Krishna Sandeep Pokkunuri , Akshat Vig , Clarence Wing Yin NG , Srivaths Badrinath Copparam , Rajaprabhu Thiruchi Loganathan , Wei Xiao , William Alexander Stevenson
IPC: G06F11/14
Abstract: A system that implements a data storage service may store data for a database table in multiple replicated partitions on respective storage nodes. In response to a request to back up a table, the service may back up individual partitions of the table to a remote storage system independently and (in some cases) in parallel, and may update (or create) and store metadata about the table and its partitions on storage nodes of the data storage service and/or in the remote storage system. Backing up each partition may include exporting it from the database in which the table is stored, packaging and compressing the exported partition for upload, and uploading the exported, packaged, and compressed partition to the remote storage system. The remote storage system may be a key-value durable storage system in which each backed-up partition is accessible using its partition identifier as the key.
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Patent Agency Ranking
公开(公告)号：US10423493B1
公开(公告)日：2019-09-24
申请号：US14977472
申请日：2015-12-21
Applicant: Amazon Technologies, Inc.
Inventor： Akshat Vig , Parikshit Shivajirao Pol , Subramanian Sankara Subramanian , Rama Krishna Sandeep Pokkunuri , Rajaprabhu Thiruchi Loganathan , Harini Chandrasekharan
Abstract: In response to determining that continuous data protection is to be enabled for a particular table of a database service, a service component verifies that automated transmission of change records of the table to a log-structured journal has been configured. A given change record comprises a before-image and an after-image associated with a committed database write, and is assigned a unique sequence number. In response to a determination to restore the table as of a specified point in time, a restore record set is identified from the journal with respect to a selected snapshot of the table. The restore record set includes change records which are not represented in the snapshot and are to be represented in the restored table. A restore result table is created using the selected snapshot and the restore record set.
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公开(公告)号：US12143343B1
公开(公告)日：2024-11-12
申请号：US17532958
申请日：2021-11-22
Applicant: Amazon Technologies, Inc.
Inventor： Swaminathan Sivasubramanian , Vasanth Philomin , Ganesh Kumar Gella , Santosh Kumar Ameti , Meghana Puvvadi , Manikya Pavan Kiran Pothukuchi , Harshal Pimpalkhute , Rama Krishna Sandeep Pokkunuri , Yahor Pushkin , Roger Scott Jenke , Yaser Al-Onaizan , Yi Zhang , Saab Mansour , Salvatore Romeo
Abstract: A system receives one or more transcripts of communications between entities. The system identifies a requested action in the communications based at least in part on a mapping between the requested action and an application programming interface. The system identifies one or more statements eliciting information, based on parameters to the application programming interface. The system generates a definition of an artificial agent based, at least in part, on the requested action and the one more statements eliciting information.
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公开(公告)号：US11769019B1
公开(公告)日：2023-09-26
申请号：US16953205
申请日：2020-11-19
Applicant: Amazon Technologies, Inc.
Inventor： Prashant Mathur , Georgiana Dinu , Anna Currey , Eric J. Nowell , Aakash Upadhyay , Haiyu Yao , Marcello Federico , Yaser Al-Onaizan , Rama Krishna Sandeep Pokkunuri , Jian Wang , Xianglong Huang
Abstract: A translation system receives examples of translations between a first language and a second language. In response to receiving request to translate a source text from the first language to the second language, the system ranks the examples based on the example's applicability to one or more portions of the source text. The system performs additional training of a neural network that was pre-trained to translate from the first language to the second language, where the additional training is based on one or more top-ranking examples. The system translates the source text to the second language using the additionally trained neural network.
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公开(公告)号：US11588755B2
公开(公告)日：2023-02-21
申请号：US17589643
申请日：2022-01-31
Applicant: Amazon Technologies, Inc.
Inventor： Parikshit Shivajirao Pol , Subramanian Sankara Subramanian , Rajaprabhu Thiruchi Loganathan , Rama Krishna Sandeep Pokkunuri , Gopinath Duddi , Akshat Vig , Safeer Mohiuddin , Sudarshan Narasimhan
IPC: G06F16/30 , H04L47/70 , G06F16/13 , G06F16/901 , G06F16/2455 , G06F9/50 , G06F11/34 , G06F16/23 , H04L43/065 , G06F11/30
Abstract: Information describing changes to a collection of items maintained by a database may be stored in a log file. The information in the log file may be converted into a stream of records describing the changes. The records may be directed to a computing node selected for performing a trigger function in response to the change, based on applying a hash function to a portion of the record, identifying a hash space associated with a value output by the hash function, and mapping from the hash space to the selected computing node.
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公开(公告)号：US20220158953A1
公开(公告)日：2022-05-19
申请号：US17589643
申请日：2022-01-31
Applicant: Amazon Technologies, Inc.
Inventor： Parikshit Shivajirao Pol , Subramanian Sankara Subramanian , Rajaprabhu Thiruchi Loganathan , Rama Krishna Sandeep Pokkunuri , Gopinath Duddi , Akshat Vig , Safeer Mohiuddin , Sudarshan Narasimhan
IPC: H04L47/70 , G06F16/13 , G06F16/901 , G06F16/2455 , G06F9/50 , G06F11/34 , G06F16/23 , H04L43/065
Abstract: Information describing changes to a collection of items maintained by a database may be stored in a log file. The information in the log file may be converted into a stream of records describing the changes. The records may be directed to a computing node selected for performing a trigger function in response to the change, based on applying a hash function to a portion of the record, identifying a hash space associated with a value output by the hash function, and mapping from the hash space to the selected computing node.
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