Autodesk, Inc.

Nvidia Corporation

Justin Frank Matejka

George William Fitzmaurice

Tovi Samuel Grossman

Gord Kurtenbach

Fraser Anderson

Azam Khan

Igor Mordatch

Wei Li

Marsha Leverock

Paul D Vaters

Xiaojun Bi

Michael Glueck

Thomas White

Stelian Coros

Benjamin LaFreniere

Ruta P Desai

Jo Karel Vermeulen

Anderson Nogueira

Ryan Michael Schmidt

William C Sabram

Ara Danielyan

Michael Chen

Ruslana Steininger

Damien Paul Andre Masson

Alexandra R Bergin

Jaime A Perkins

Adam L Menter

Howard R Swearer

Gordon P Kurtenbach

Danil Nagy

Evan Patrick Atherton

Heather Kerrick

David Thomasson

Maurice Ugo Conti

Erin Marie Bradner

Ali Baradaran Hashemi

Benjamin Lafreniere

Barrett Ens

Frederik Brudy

Arthur Harsuvanakit

Kendra Ann Wannamaker

Anirban Ghosh

Nick Beirne

Barret Ens

Gordon Paul Kurtenbauch

Steven Li

Nikhita Joshi

George Frank Fitzmaurice

Raimund Dachselt

Patrick Reipschläger

Christian Smitherman

Warren Karl Schrey

Michael L Mcmanus

Gord Kurenbach

Ji In Shin

Jiin Shin

Michael L McManus

Michael D Ekstrand

Jessica Lo

One embodiment of a computer-implemented method for executing software application commands on practice data comprises identifying a command demonstration that is stored in a database based on a current command being interacted with in a graphical user interface, wherein the command demonstration is associated with sample application data; receiving a selection of whether to execute the command demonstration on the sample application data or current application data; causing the command demonstration to be executed on either the sample application data or a copy of current application data to generate modified data; and causing the modified data to be output within the graphical user interface.

Techniques for trial-and-error learning in complex application environments

One embodiment of a computer-implemented method for analyzing human motion data includes receiving a set of motion data that indicates one or more movements of a first person within a real-world environment; generating a virtual avatar corresponding to the first person based on the set of motion data; determining a position of the virtual avatar within an extended reality (ER) scene based on the one or more movements; and displaying the virtual avatar in the ER scene according to the determined position.

Immersive analysis environment for human motion data

A command map GUI that illustrates command usage patterns of one or more entities. A server receives and stores command usage data from a plurality of users/clients, each user/client executing a software application having a set of commands. A current user/client displays, via a GUI, graphical representations of the command usage data received from the server. The server receives new command usage data from a user/client included in the one or more entities. In response, the server automatically updates command usage data for the one or more entities, pushes the updated command usage data to the current user/client, and causes the GUI to display graphical representations of the updated command usage data. Thus, the command usage data of the one or more entities is automatically updated and displayed in the GUI in real-time or near real-time as new commands are continually invoked by users in the one or more entities.

Techniques for analyzing the proficiency of users of software applications in real-time

A command map GUI that illustrates command usage patterns of a first entity and/or a comparison between the first entity and a second entity. A server receives and stores command usage data from a plurality of clients, each client executing a software application that enables a set of commands. A client displays the GUI based on command usage data received from the server. The GUI displays a circle chart comprising a plurality of segments representing various command categories, each segment including a wedge that represents the amount of usage of the corresponding command category. The GUI also displays a plurality of data points, each data point representing a command, wherein the distance from the center of the circle chart represents the amount of usage of the corresponding command. The GUI may display a certification and/or an unused command recommended for a user based on command usage patterns of the user.

Techniques for analyzing the proficiency of users of software applications

A feedback mechanism that reports software issues between users of software applications and the developers of the software applications. The feedback mechanism generates feedback logs that capture moments of user frustration at the moment a user encounters issues with using a particular software application executing on a client device. The feedback mechanism is triggered to generate a feedback log by the user via a predetermined set of user inputs. Once generated, the feedback log captures an associated importance level, a user description, and/or context information (such as application and command activity information) for the particular software application and one or more other software applications that interacted with the particular software application executing on the client device. The feedback log can also capture multimedia content such as audio, images, and videos. The feedback log is then transmitted to a server of a developer of the particular software application.

User feedback mechanism for software applications

Techniques for analyzing command usage of software applications

One embodiment of a computer-implemented method for automatically generating command recommendations for a software workflow comprises identifying a plurality of command sequences stored in a database based on a current command being interacted with in a graphical user interface; computing a score for each command sequence included in the plurality of command sequences based on one or more commands included in the command sequence and one or more commands included in a command history; determining at least one command sequence included in the plurality of command sequences to output based on the scores; and outputting the at least one command sequence for display.

One embodiment of the invention disclosed herein provides a system that includes a mirror apparatus with a first surface to which a half-silvered mirror film is applied, where the mirror apparatus transmits a transmitted image from a second surface to the first surface. The system further includes a servo-controlled dimmer that adjusts a level of ambient light associated with the mirror apparatus. The system further includes a motion sensing device that tracks positions of a plurality of points associated with an object; wherein the object is situated on the half-silvered mirror film side of the mirror apparatus. The system further includes a computing device including a memory that stores instructions that, when executed by a processor included in the computing device, cause the processor to control the servo-controlled dimmer to adjust the ambient light such that both the transmitted image and a reflected image is visible on the first surface.

Reflection-based target selection on large displays with zero latency feedback

An automated robot design pipeline facilitates the overall process of designing robots that perform various desired behaviors. The disclosed pipeline includes four stages. In the first stage, a generative engine samples a design space to generate a large number of robot designs. In the second stage, a metric engine generates behavioral metrics indicating a degree to which each robot design performs the desired behaviors. In the third stage, a mapping engine generates a behavior predictor that can predict the behavioral metrics for any given robot design. In the fourth stage, a design engine generates a graphical user interface (GUI) that guides the user in performing behavior-driven design of a robot. One advantage of the disclosed approach is that the user need not have specialized skills in either graphic design or programming to generate designs for robots that perform specific behaviors or express various emotions.

Generative design techniques for robot behavior

In various embodiments, a mentor application automatically obtains assistance with software applications. The mentor application generates a computer-generated help request associated with a first user of a software application. Based on the computer-generated help request and a set of user contexts associated with a set of users, the mentor application computes match scores. Each match score predicts how suitable a particular user is for servicing the computer-generated help request. Based on the match scores, the mentor application transmits at least one help request notification to at least one user included in the set of users to determine a second user to service the computer-generated help request. The mentor application then establishes a computer connection between the first user and the second user through which an interactive help session between the first user and the second user is held.

Computer-based techniques for obtaining personalized assistance with software applications

In various embodiments, a ranking application automatically ranks designs included in a design space based on user preference(s). The ranking application determines that a first design included in the design space is a first positive example of user preference(s). The ranking application then computes a score associated with a second design that is also included in the design space based on a first attribute value and a second attribute value. The first attribute value is associated with both the first design and an attribute and the second value is associated with both the second design and the attribute. Subsequently, the ranking application orders the designs based on the first score and a second score associated with the second design to generate a ranked list of designs. The ranking application then displays the ranked list of designs via a graphical user interface to facilitate exploration of the design space.

Example-based ranking techniques for exploring design spaces

In various embodiments, a dataset generation application generates a new dataset based on an original dataset. The dataset generation engine perturbs a first data item included in the original dataset to generate a second data item. The dataset generation application then generates a test dataset based on the original dataset and the second data item. The test dataset includes the second data item instead of the first data item. Subsequently, the dataset generation application determines that the test dataset is characterized by a first property value that is substantially similar to a second property value that characterizes the original dataset. The first property value and the second property value are associated with the same property. Finally, the dataset generation application generates a new dataset based on the test dataset. The new dataset conveys aspect(s) of the original dataset without revealing the first data item.

Perturbation-based techniques for anonymizing datasets

A design application is configured to visualize and explore large-scale generative design datasets. The design explorer includes a graphical user interface (GUI) engine that generates a design explorer, a composite explorer, and a tradeoff explorer. The design explorer displays a visualization of a multitude of design options included in a design space. The design explorer allows a user to filter the design space based on input parameters that influence a generative design process as well as various design characteristics associated with the different design options. The composite explorer displays a fully interactive composite of multiple different design options. The composite explorer exposes various tools that allow the user to filter the design space via interactions with the composite. The tradeoff explorer displays a tradeoff space based on different rankings of design options. The different rankings potentially correspond to competing design characteristics specified by different designers.

Techniques for visualizing and exploring large-scale generative design datasets

Growing community of inventors

Newmarket, Canada

Justin Frank Matejka