Walmart Apollo, LLC

Airwatch LLC

Honeywell International Inc.

Vmware, Inc.

International Business Machines Corporation

Saurabh Agrawal

Ramani Panchapakesan

Kannan Achan

Sushant Kumar

Evren Korpeoglu

Soumya Wadhwa

Deena Dayalan Kothandaraman

Venugopal Mani

Behzad Shahrasbi

Durga Deepthi Singh Sharma

Renju Chandrasekhara Panicker

Gangadhar Nittala

Ian Ragsdale

Arjun Kochhar

Akshay Laxminarayan

Sushilvas Vasavan

Kamiya Motwani

Suja Ramachandran

Ilanchezhian Kuppusamy

Dinesh C Verma

Mathews Thomas

Ashish Kumar Agrawal

Sagar Tayal

Utpal Mangla

Mridul Jain

Shouvik Das

Pawan Kumar Gupta

Gajendra Alias Nishad Kamat

Ruben Nieves

Santhosh Chandrashekarappa Irani

Nikhil Jere

Santhosh Chandrashekarappa

Kartik Patel

Ramakrishna Rao Pavanje Vishwanatha

A computer-implemented method for grouping devices in a massive multiple-input and multiple-output (MIMO)-based cellular network, in accordance with one embodiment, includes determining movement states of end devices in a cell of the massive MIMO-based cellular network, estimating payload requirements of the end devices, and grouping the end devices in a group based on the determined movement states and the estimated payload requirements.

Dynamic massive MIMO end device pairing based on predicted and real time connection state

Systems herein include a managed content application that can place markers for conversations within secure documents. A separate social application can serve as the platform for the conversations, allowing for efficient conversations that can occur in real time. The markers can be stored with the documents and identify the conversation, allowing users to retrieve historical conversations that occurred on the social application from within the document. This can allow users to quickly come up to speed without having to rehash the conversations with the original participants. Document security can also be maintained without sacrificing conversation efficiency of the social application.

Containerized contextual conversation system

A privacy system includes a computing device configured to obtain user transactional data characterizing at least one transaction of a user on an ecommerce marketplace and to determine a privacy vulnerability score of the user by comparing the transactional data to a user vulnerability distribution. The computing device is also configured to send the privacy vulnerability score to a personalization engine.

Methods and apparatuses for identifying privacy-sensitive users in recommender systems

A recommender system can include a defender computing device that is configured to obtain customer interaction data characterizing customer interactions with an ecommerce marketplace. The defender computing device can also be configured to determine an item recommendation based on the customer interaction data using a trained differentially private recommendation model and send the item recommendation to the customer. The trained differentially private recommendation model is more likely to determine the same item recommendation after poisoned data is injected into the customer interaction data than a recommendation model that is not privately trained.

Methods and apparatuses for defending against data poisoning attacks in recommender systems

This application relates to apparatus and methods for automatically detecting attacks to advertisement systems. In some examples, a computing device trains a machine learning process based on a training dataset. The training dataset may be an identified portion of a website session dataset that includes a lower percentage of malicious data caused by attacks than other portions, or may include no malicious data. Once trained, the computing device generates features from a website session dataset for a customer, and applies the trained machine learning process to the generated features to detect malicious data within the website session dataset for the customer. Further, the computing device may filter the website session data to remove the detected malicious data, and may store the filtered website session data within a data repository. The computing device may provide the filtered website session data to a recommendation system to generate item recommendations for the customer.

Methods and apparatus for automatically detecting data attacks using machine learning processes

Examples described herein include systems and methods for providing push notifications to a third-party application executing on a client device. An example can include encrypting user credentials, generating a callback Uniform Resource Locator ('URL') with at least a portion of the encrypted credentials embedded into the URL, and requesting notifications from an email service to be provided at the callback URL. Upon receiving a notification at the callback URL, a system component can decrypt the credentials within the URL using a private key and log into the email account using those decrypted credentials. The system component can then generate a push notification based on any changes found in the email account and cause the notification to be delivered to the third-party application on the client device.

Email notification system

An apparatus for winding coils onto a spherical body includes a frame, a feeder spool, a first hemispherical bobbin, a second hemispherical bobbin, a first spring-loaded pin, a second spring-loaded pin, and a motor arrangement. The feeder spool is rotationally mounted on the frame, has first and second wires wound thereon, and is configured to rotate about a first rotational axis. The first and second hemispherical bobbins are rotationally mounted on the frame and configured to rotate about a second rotational axis that is parallel to the first rotational axis. The bobbins are spaced apart from each other to define a wire-feeder gap through which the first and second wires may be fed. The motor arrangement is coupled to the first and second hemispherical bobbins and is configured to cause the first and second hemispherical bobbins to rotate in opposite directions about the second rotational axis.

Spherical coil winding machine

Systems and methods of real-time modeling pipeline inferencing are disclosed. At least one model configured to calculate at least one metric from one or more features is deployed. A model inferencing pipeline configured to extract the one or more features from a customer-specific data pipeline is implemented for the at least one mode. The model inferencing pipeline is generated using a training data set extracted from a cross-customer data pipeline. The at least one metric is calculated using the one or more features extracted from the customer-specific data pipeline.

System and method for real-time modeling inference pipeline

A spherical brushless direct current (BLDC) machine includes a first stator, a second stator, and a spherical rotor. The first stator is symmetrically disposed about a first axis and includes a first multi-pole stator core having a first multi-phase winding wound thereon. The second stator is symmetrically disposed about a second axis and includes a second multi-pole stator core having a second multi-phase winding wound thereon. The second stator core is coupled to the first stator core, and the second axis intersects the first axis. The spherical rotor is disposed adjacent to, and is moveable relative to, the first and second stators. The spherical rotor includes a plurality of magnets that emanate a magnetic field, and each magnet has at least one of its magnetic poles facing the first and second stators.

Spherical brushless direct current machine

Disclosed are various examples for threat detection and security for edge devices in communication with Internet-of-Things (IoT) devices. In one example, a profile is associated with a virtual machine of a gateway device. The profile includes an expected behavior for the virtual machine. The virtual machine is executed by a hypervisor of the gateway device. An actual behavior for the virtual machine is determined. A remedial action is performed. The remedial action is based on an anomaly between the expected behavior and the actual behavior.

Encrypted log aggregation

A spherical resolver system includes a spherical body, an outer body, a first sensor coil, a second sensor coil, a third sensor coil, a first primary coil, and a circuit. The spherical body has a first axis of symmetry, a second axis of symmetry, and a third axis of symmetry, and the first, second, and third axes of symmetry are disposed perpendicular to each other. The circuit is coupled to the first primary coil and is operable to supply a first alternating current (AC) reference signal (V) to the first primary coil, whereby a first sensor signal (V) is selectively induced in the first sensor coil, second sensor signal (V) is selectively induced in the second sensor coil, and a third sensor signal (V) is selectively induced in the third sensor coil, and supplies one or more signals representative of the sensor position.

Spherical voice coil based resolver system

Examples of the present disclosure relate to providing policy-protected file access. Some examples involve a configuration profile that includes a credential. The credential permits access to a policy-protected file. Once installed, the configuration profile causes the second credential to be accessible by a file management application of the client device, but inaccessible by a user of the client device. A file management application provides access to the policy-protected file based on the second credential.

Policy protected file access

Examples of the present disclosure relate to protecting files with an information rights policy. Files can be protected as specified by a content policy associated with the file. The content policy can specify whether the file should be protected while at rest on a device as well as when the file is shared with another user of an enterprise.

Applying rights management policies to protected files

Growing community of inventors

Bengaluru, India

Saurabh Agrawal