Paypal, Inc.

Lin Song

Chun Kiat Ho

Kai Xie

Kim Dung Bui

Yuehao Wu

Edwin Boaz Soenaryo

Rey Neo

Fei Li

Srinivasan Manoharan

Vinesh Chirakkil

Karl Anton Hennig

Thomas Anthony Doran

Junhua Zhao

Meng Zang

Premila Viswanathan

Xiaoying Han

Jun Zhang

Jun Yang

Xiaohan Yun

Zhenyin Yang

Pengshan Zhang

Quin Zuo

Jyothish Kozhipurath

Vipul Jain

Nilotpal Paul

Ke Zheng

Anurag Singh

Wen Lu

Jie How Ko

Huynh Phi Long

RaviKumar PhoolChand Vishwakarma

Anu Kumari

Atul Kumar Agrawal

Jerry Tso

Jintao Guo

Chinmayee Rathi

Mihir Sirohi

Methods and systems are presented for providing a container orchestration framework for facilitating development and deployment of software applications across different operating environments within an enterprise system. Upon receiving a service request for processing a set of data is received, the container orchestration framework determines one or more machines that store the set of data. Instead of processing the set of data remotely, the container orchestration framework deploys a container that encapsulates an application on the one or more machines. Each application instance running on the one or more machines are executed to process a corresponding subset of data stored on the machine locally. The container orchestration framework obtains the output data from executing the applications on each of the one or more machines, and present the output data as a response to the service request.

Container orchestration framework

A computer system receives a set of user-defined rules are that useable by a computer service to automate a decision flow. The computer system generates a graph model from the user-defined rules. From the graph model, the computer system determines an input dependency model that is indicative of a set of inputs referred to in the graph model. The input dependency model is useable by an orchestrator to coordinate accesses to the one or more data stores in which the set of inputs is stored. The computer system receives the set of inputs and determines one or more automated decisions by applying the set of inputs to the graph model.

Automated decision platform

Methods and systems for content distribution and management are presented. A transaction flow for conducting different stages of a transaction is determined in response to a request for the transaction from an application executable at a user device. The transaction flow includes a sequence of content pages to be displayed within a graphical user interface (GUI) of the application over the different stages of the transaction. The content associated with a tagged UI element of at least one content page is identified. The content is validated for the tagged UI element of the at least one content page, based on a software and hardware configuration of the user device. The validated content is provided via a network to the application at the user device to be displayable with the tagged UI element on the at least one content page of the transaction flow during a corresponding stage of the transaction.

Artificial intelligence (AI) engine for dynamic content distribution and management

Techniques are disclosed relating to using machine learning techniques to predict storage configurations for historical data. In some embodiments, a computer system stores representations of historical data according to a current set of storage parameters. The representations may include snapshots of historical data in a data repository at different points in time. The computer system may receive queries for historical data specifying points in time from which to retrieve the historical data. In some embodiments, the computer system responds to the queries using the stored representations and determines performance metrics for the responses. In some embodiments, the computer system trains a machine learning model using the performance metrics. Based on output of the trained model, the computer system updates the current set of storage parameters. The updating may affect subsequent storage of representations in the data repository, which may advantageously improve query response times and decrease repository storage size.

Alteration of historical data representations using data repository performance metrics

Techniques are disclosed relating to data validation using encode values. In various embodiments, a data monitoring system may retrieve a plurality of datasets from a live database at a non-production datacenter. The data monitoring system may perform encoding operations on one or more of the plurality of datasets to generate encode values that correspond to the plurality of datasets. The data monitoring system may then retrieve an updated dataset, for example from an experimental database at the non-production datacenter, and perform validation operations to validate one or more characteristics of the updated dataset. For example, in some embodiments, the data monitoring system may retrieve the encode values corresponding to the plurality of datasets and use the encode values to validate the updated dataset. The data monitoring system may then generate a validation output indicative of a result of the validation operations.

Data validation using encode values

Aspects of the present disclosure involve systems, methods, devices, and the like for generating highly scalable temporal graph databases. In one embodiment, a novel architecture is presented that enables the identification of mutation or changes in graphs. For the identification a combination of graph-based modeling and journal entry is used. Events occurring are consumed and changes are ingested, transformed for use by a graph simulation system. The changes are journaled using a vertex centric temporal journaling schema.

System and method for generating highly scalable temporal graph database

Techniques are disclosed relating to detecting matching datasets using encode values. In various embodiments, a data monitoring system may perform encoding operations on a first dataset to generate a first encode value that corresponds to a particular one of one or more fields included in the first dataset. The data monitoring system may then determine whether the first dataset matches a previously analyzed dataset. For example, in some embodiments, data monitoring system may compare the first encode value to a previous encode value that corresponds to a second field of the previously analyzed dataset. Based on this comparison, the data monitoring system may generate an output value that is indicative of a similarity between the first encode value and the previous encode value. The data monitoring system may then determine whether the first dataset matches the previously analyzed dataset based on this output value.

Detection of matching datasets using encode values

Techniques are disclosed relating to data versioning in a multi-datacenter topology. In various embodiments, a computer system at a first datacenter may execute a query at a first point in time against a particular dataset that is maintained at the first datacenter. The particular dataset includes a first data record with a corresponding version number, where the version number is associated with a value of the first data record at the first point in time. In response to the first query, the computer system may receive a first results dataset that includes the first data record with its corresponding version number. The computer system may then store information indicative of the results dataset that is usable to retrieve, at a subsequent time from a historical version of the particular dataset at a second datacenter, the first data record with the same value as at the first point in time.

Data versioning in a multi-datacenter topology

Aspects of the present disclosure involve systems, methods, devices, and the like for an end-to-end solution to auto-identifying features. In one embodiment, a novel architecture is presented that enables the identification of optimal features and feature processes for use by a machine learning model. The novel architecture introduces a feature orchestrator for managing, routing, and retrieving the data and features associated with analytical job request. The novel architecture also introduces a feature store designed to identify, rank, and store the features and data used in the analysis. To aid in identifying the optimal features and feature processes, a training system may also be included in the solution which can perform some of the training and scoring of the features.

Solution to end-to-end feature engineering automation

Systems and methods for regulating service behavior include a system provider device where a policy is registered. The policy defines a modified service behavior for a service running one or more remote servers. In some embodiments, the registered policy is transmitted to a first satellite agent located at a first remote server. By way of example, and after transmitting the registered policy to the first satellite agent, data is received from the first satellite agent corresponding to the service having the modified service behavior running on the first remote server. Thereafter, the system provider may verify that the service having the modified service behavior running on the first remote server satisfies a metric. In various embodiments, and in response to the verifying, the registered policy is transmitted to a second satellite agent located at a second remote server.

Systems and methods for regulating service behavior

Techniques are disclosed relating to coordinating processing data transmissions between computing systems over a network. In various embodiments, a system includes a coordinator that receives information about an expected batch transmission between a data publishing application at a first computing system and a data processing application at a second computing system. Based on the received information, the coordinator determines a time when the data publishing application is expected to publish the batch transmission to the data processing application and causes the second computing system to initiate execution of the data processing application in conjunction with the determined time to receive and process the batch transmission from the data publishing application.

Coordination of batch transmissions and processing between transmitting and receiving computing systems

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Singapore, Singapore

Lin Song