Vmware, Inc.

Adobe, Inc.

Gaurav Verma

Suchit Shivashankar

Balaji Vasan Srinivasan

Karthikeyan Palanisamy

Manjunath Subramani

Don Joy

Vishwa Vinay

Anandhavelu Natarajan

Bakhtiyar Hussain Syed

Sopan Khosla

Sanket Vaibhav Mehta

Sahith Thallapally

Niyati Himanshu Chhaya

Shiv Kumar Saini

Aman Mishra

Keerti Harpavat

Suryateja B V

Pranav Goel

Trikay Nalamada

Mitansh Jain

Siddharth Sahay

Samagra Sharma

Sneha Chowdary Vinjam

Described herein are example methods and systems for enrolling a user device with an unified endpoint management system ('UEMS') directly from another user device. The examples describe a first user device that is already enrolled with the UEMS and a second user device that is seeking to be enrolled. The two user devices can establish a direct connection with each other. The second user device can be authenticated by a user inputting the same migration password or pin at both user device. The first user device can generate and send a migration data file to the second user device. The migration data file can include settings, policies, software packages, and files managed by the UEMS. The second user device can copy settings, policies, and files, and install the applications from the migration data file. The second user device can notify an UEMS server of the device migration.

Device to device migration in a unified endpoint management system

Examples herein describe systems and methods for application-specific compliance enforcement. An example method can include receiving, at a user device, profiles containing application-specific restrictions. When a first application is opened, a management agent compares the corresponding application-specific restrictions with current device settings. This can be done with a checksum comparison where the checksums are created based on a hash with an application- or profile-specific identifier. If they differ, the management agent stores the current device settings and prompts for, or automatically changes, the device settings to new compliant values before allowing the first application to operate in the foreground of the user device screen. If the first application is closed or minimized, the stored device settings can be restored. The management agent can compare those against application-specific restrictions of the second application before allowing the second application to run in the foreground.

Dynamic application-level compliance enforcement

Rewriting text in the writing style of a target author is described. A stylistic rewriting system receives input text and an indication of the target author. The system trains a language model to understand the target author's writing style using a corpus of text associated with the target author. The language model may be transformer-based, and is first trained on a different corpus of text associated with a range of different authors to understand linguistic nuances of a particular language. Copies of the language model are then cascaded into an encoder-decoder framework, which is further trained using a masked language modeling objective and a noisy version of the target author corpus. After training, the encoder-decoder framework of the trained language model automatically rewrites input text in the writing style of the target author and outputs the rewritten text as stylized text.

Stylistic text rewriting for a target author

A sound association system identifies one or more aurally active words in digital text. Aurally active words refer to words that denote particular sounds. Context-based sounds corresponding to the one or more aurally active words are also identified. Each context-based sound is anchored to or associated with the corresponding one or more aurally active words and is played back when the digital text is played back or read, providing context-based background sounds associated with the one or more aurally active words. For example, a context-based sound can be played back at a higher volume when the one or more aurally active words are played back or read, and at a lower volume when other words of the digital text are played back or read.

Automatically associating context-based sounds with text

Disclosed are various examples for enforcing network access permissions on applications that are installed on a client device. A network whitelist or network blacklist can be deployed by a management service onto a managed client device. A management component can facilitate enforcement of the whitelist and/or blacklist to enforce network access rules on installed applications.

Network access by applications in an enterprise managed device system

A method for personalized playback of a video as performed by a video platform includes parsing a video into segments based on visual and audio content of the video. The platform creates multimodal fragments that represent underlying segments of the video, and then orders the multimodal fragments based on a preference of a target user. The platform thus enables nonlinear playback of the segmented video in accordance with the multimodal fragments.

Personalizing videos with nonlinear playback

Disclosed are various examples for client device migration to utilize management platform features. In some examples, the client device is identified as compatible with a management platform. A migration of the client device to utilize a management platform feature is accepted through a user interface. A management platform account is created with a management platform service. A management profile is installed on the client device. The profile is compatible with the management platform. The management platform feature is enabled on the client device.

Migration of managed devices to utilize management platform features

Disclosed are various examples for facilitating enrollment of a client device into more than one management framework. A client device can be enrolled with a management service as a fully managed device. The client device can also be enrolled with the management service as a personal or bring-your-own-device (BYOD), which causes a workspace to be created on the device that is segregated from the rest of the client device. Both enrollments can be managed by a remotely executed management service.

Linking multiple enrollments on a client device

Content fragments aligned to content criteria enable rich sets of multimodal content to be generated based on specified content criteria, such as content needs pertaining to various content delivery platforms and scenarios. For instance, the described techniques take a set of content (e.g., text, images, etc.) along with a specified content criteria (e.g., business/user need) and creates content fragment variants that are tailored to the content criteria with respect to both the information presented as well as the style of the content presented.

Content fragments aligned to content criteria

A method for generating stylistic feature prescriptions to align a body of text with one or more target goals includes receiving, at a stylistic feature model, a body of text, where the body of text is selected by a user via a graphical user interface (GUI). The stylistic feature model identifies stylistic features from the body of text and populates a stylistic feature vector with the stylistic features. A trained de-confounded prediction model receives the stylistic feature vector. The trained de-confounded prediction model using the stylistic feature vector generates a prediction value for each of one or more target goals, compares the prediction value for each of the one or more target goals to a target value for each of the one or more target goals and outputs, for display on the GUI, one or more stylistic feature prescriptions to the body of text based on results of the comparing.

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Bengaluru, India

Gaurav Verma