公开(公告)号：US20230281276A1

公开(公告)日：2023-09-07

申请号：US18171244

申请日：2023-02-17

Applicant: Amazon Technologies, Inc.

Inventor： Owen Thomas ,  Kenneth O Henderson, JR. ,  Sumit Thakur ,  Glenn Danthi ,  Hugh Payton Staub ,  Thomas Albert Faulhaber ,  Vladimir Zhukov

IPC: G06F18/214 ,  G06N20/20 ,  G06F9/54 ,  G06F16/14 ,  G06F16/16 ,  G06F9/48 ,  G06F9/451 ,  G06F8/71 ,  G06N20/00 ,  G06F18/2113

CPC classification number: G06F18/2148 ,  G06N20/20 ,  G06F9/54 ,  G06F16/144 ,  G06F16/164 ,  G06F9/485 ,  G06F9/451 ,  G06F8/71 ,  G06N20/00 ,  G06F18/2113 ,  G06F18/2155

Abstract: Artifacts, including parameters are data sets, associated with experiment tasks are stored at an experiment management service. A query specifying a particular value of a parameter and a particular data set is received, and an indication of an experiment result associated with the particular data set and the particular parameter value is provided.

公开(公告)号：US11586847B1

公开(公告)日：2023-02-21

申请号：US16894707

申请日：2020-06-05

Applicant: Amazon Technologies, Inc.

Inventor： Owen Thomas ,  Kenneth O Henderson, Jr. ,  Sumit Thakur ,  Glenn Danthi ,  Hugh Payton Staub ,  Thomas Albert Faulhaber ,  Vladimir Zhukov

IPC: G06N20/00 ,  G06K9/62 ,  G06N20/20 ,  G06F9/54 ,  G06F16/14 ,  G06F16/16 ,  G06F9/48 ,  G06F9/451 ,  G06F8/71

Abstract: Artifacts, including parameters are data sets, associated with experiment tasks are stored at an experiment management service. A query specifying a particular value of a parameter and a particular data set is received, and an indication of an experiment result associated with the particular data set and the particular parameter value is provided.

公开(公告)号：US11449798B2

公开(公告)日：2022-09-20

申请号：US16588952

申请日：2019-09-30

Applicant: Amazon Technologies, Inc.

Inventor： Andrea Olgiati ,  Maximiliano Maccanti ,  Arun Babu Nagarajan ,  Lakshmi Naarayanan Ramakrishnan ,  Urvashi Chowdhary ,  Gowda Dayananda Anjaneyapura Range ,  Zohar Karnin ,  Laurence Louis Eric Rouesnel ,  Stefano Stefani ,  Vladimir Zhukov

IPC: G06F11/00 ,  G06N20/00 ,  G06F11/07

Abstract: Methods, systems, and computer-readable media for automated problem detection for machine learning models are disclosed. A machine learning analysis system receives data associated with use of a machine learning model. The data was collected by a machine learning inference system and comprises input to the model or a plurality of inferences representing output of the machine learning model. The machine learning analysis system performs analysis of the data associated with the use of the machine learning model. The machine learning analysis system detects one or more problems associated with the use of the machine learning model based at least in part on the analysis. The machine learning analysis system initiates one or more remedial actions associated with the one or more problems associated with the use of the machine learning model.

公开(公告)号：US12008390B1

公开(公告)日：2024-06-11

申请号：US16699488

申请日：2019-11-29

Applicant: Amazon Technologies, Inc.

Inventor： Thomas Albert Faulhaber ,  Jonathan Esterhazy ,  Vladimir Zhukov ,  Stefano Stefani

IPC: G06F9/455 ,  G06F9/54

CPC classification number: G06F9/45558 ,  G06F9/54 ,  G06F2009/45562 ,  G06F2009/45591

Abstract: Methods and apparatus for providing persistent execution environments for computation systems including but not limited to interactive computation systems. A service is provided that extends the notion of static containers to dynamically changing execution environments into which users can install code, add files, etc. The execution environments are monitored, and changes to an execution environment are automatically persisted to environment versions(s) so that code run in the execution environment can be run later or elsewhere simply by referring to the environment. There is no explicit build step for the user. Instead, incremental changes are added to environment versions which are stored and are ready to be used to instantiate respective execution environments on other compute instances.

公开(公告)号：US20210132986A1

公开(公告)日：2021-05-06

申请号：US17145133

申请日：2021-01-08

Applicant: Amazon Technologies, Inc.

Inventor： Vikram Sathyanarayana Anbazhagan ,  Swaminathan Sivasubramanian ,  Stefano Stefani ,  Vladimir Zhukov

IPC: G06F9/48 ,  G06F40/35

Abstract: A determination is made as to whether a value of a first parameter of a first application is to be obtained using a natural language interaction. Based on received input, a first service of a plurality of services is identified. The first service is to be used to perform a first task associated with the first parameter. Portions of the first application to determine the value of the first parameter and to invoke the first service are generated.

公开(公告)号：US20210097433A1

公开(公告)日：2021-04-01

申请号：US16588952

申请日：2019-09-30

Applicant: Amazon Technologies, Inc.

Inventor： Andrea Olgiati ,  Maximiliano Maccanti ,  Arun Babu Nagarajan ,  Lakshmi Naarayanan Ramakrishnan ,  Urvashi Chowdhary ,  Gowda Dayananda Anjaneyapura Range ,  Zohar Karnin ,  Laurence Louis Eric Rouesnel ,  Stefano Stefani ,  Vladimir Zhukov

IPC: G06N20/00 ,  G06F11/07

Abstract: Methods, systems, and computer-readable media for automated problem detection for machine learning models are disclosed. A machine learning analysis system receives data associated with use of a machine learning model. The data was collected by a machine learning inference system and comprises input to the model or a plurality of inferences representing output of the machine learning model. The machine learning analysis system performs analysis of the data associated with the use of the machine learning model. The machine learning analysis system detects one or more problems associated with the use of the machine learning model based at least in part on the analysis. The machine learning analysis system initiates one or more remedial actions associated with the one or more problems associated with the use of the machine learning model.

公开(公告)号：US20210097431A1

公开(公告)日：2021-04-01

申请号：US16588913

申请日：2019-09-30

Applicant: Amazon Technologies, Inc.

Inventor： Andrea Olgiati ,  Lakshmi Naarayanan Ramakrishnan ,  Jeffrey John Geevarghese ,  Denis Davydenko ,  Vikas Kumar ,  Rahul Raghavendra Huilgol ,  Amol Ashok Lele ,  Stefano Stefani ,  Vladimir Zhukov

IPC: G06N20/00 ,  G06N5/04

Abstract: Methods, systems, and computer-readable media for debugging and profiling of machine learning model training are disclosed. A machine learning analysis system receives data associated with training of a machine learning model. The data was collected by a machine learning training cluster. The machine learning analysis system performs analysis of the data associated with the training of the machine learning model. The machine learning analysis system detects one or more conditions associated with the training of the machine learning model based at least in part on the analysis. The machine learning analysis system generates one or more alarms describing the one or more conditions associated with the training of the machine learning model.