International Business Machines Corporation

Clarissa Ho

Jacob Thomas Covell

Robert Huntington Grant

Zachary A Silverstein

Clement Decrop

Pranav Chunduri

Nicholas Bokun

Spencer Sturton

A computer-implemented method and a computer program product for optimizing groupings in a breakout session in a virtual classroom. A computer retrieves profiles of students in the virtual classroom, where the profiles of the students include data of academic performances of the students. The computer retrieves a known correspondents archive which includes historic data of productivities correlated to interactions among the students. In response to initialization of the breakout session in the virtual classroom, the computer determines optimal groups that yield most productive results, based on the profiles of the students, the known correspondents archive, and requirements of group settings given by an instructor, using a machine learning model. The computer provides the instructor with the optimal groups. In another embodiment, the computer analyzes context of customized assignments for the breakout session and determines the optimal groups further based on the context to the customized assignments.

Using a machine learning model to optimize groupings in a breakout session in a virtual classroom

A computer-implemented method, a computer program product, and a computer system for dynamically adjusting zoom settings in a multiple user environment. A server determines whether the multiple user environment is an environment of co-located users or an environment of distributed users. In response to determining the environment of the co-located users, the server determines an aggregated preference, determines an optimal zoom setting for a singular display based on the aggregated preference, and adjusts the singular display based on the optimal zoom setting for the singular display. In response to determining the environment of the distributed users, the server determines optimal zoom settings for respective ones of the multiple displays, based on preferences of respective ones of the distributed users, and the server adjusts the respective ones of the multiple displays, based on the optimal zoom settings for the respective ones of the multiple displays.

Dynamically adjusting zoom settings by a server in multiple user environments

A method, system, and computer program product for generating personalized security testing simulations is provided. The method identifies a user of a communications system. The user is associated with a user profile. The method generates a simulated attack communication based on the user, the user profile, and an attack personalization model. The simulated attack communication is transmitted to the user via the communications system. The method identifies a user response to the simulated attack communication and modifies the attack personalization model based on the user response.

Personalized security testing communication simulations

An approach is provided for generating an interface. Using natural language processing and natural language understanding, ingredients are derived from audio data from a customer's spoken order of ingredients of a food item. Locations of the ingredients in a preparation area are identified. A location of an employee is determined. Distances of the ingredient locations to the employee location are calculated. A sequence of selecting the ingredients is determined so that the employee selecting the ingredients in the sequence optimizes a speed at which the food item is prepared. An overlay to an interface for viewing in an augmented reality (AR) headset worn by the employee is generated and displayed. The overlay includes indicators overlaying an image of the preparation area. The indicators mark the ingredients, mark the sequence of selecting the ingredients, and distinguish the ingredients from other ingredients in the preparation area.

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New York, NY, United States of America

Clarissa Ho