7419results about "Details involving graphical user interface" patented technology

A graphical, hierarchical document stream browser and environment for semantic (e.g. framing) and performance data analysis and interactive visualization integrates three scales: entities (competitive), entity (diachronic), and document (linguistic). The document level includes annotation and computational linguistics facilities; the entity level has calendrical and time-series focus. All levels emphasize deep linkage and network (i.e. connective / relational space) view of objects, with user-configurable connectivity. Large language model (LLM) integrations provide synthetic advisories, public opinions, reports, plot insights, comparisons; traditional natural language processing techniques and neural models are also employed. A smart plot system includes a “plot cart” and interpreter with an analysis snippet library. Graph structure may arise via adjustable blending or perceptual optimization of canned attribute-related distance functions or via link-induction query language with deep “semantic stored procedure” subexpressions, or feed into graph neural network-style inference for predictions. Most non-LLM ongoing computational load is client-side, using precomputed hierarchical summary files.

In some embodiments, a computer system changes a visual prominence of a respective virtual object in response to detecting a threshold amount of overlap between a first virtual object and a second virtual object. In some embodiments, a computer system changes a visual prominence of a respective virtual object based on a change in spatial location of a first virtual object with respect to a second virtual object. In some embodiments, a computer system applies visual effects to representations of physical objects, virtual environments, and / or physical environments. In some embodiments, a computer system changes a visual prominence of a virtual object relative to a three-dimensional environment based on display of overlapping objects of different types in the three-dimensional environment. In some embodiments, a computer system changes a level of opacity of a first virtual object overlapping a second virtual object in response to movement of the first virtual object.

An example operation may include one or more of storing a generative artificial intelligence (GenAI) model configured to create images, displaying a plurality of prompts on a user interface of a software application, receiving an identifier of a goal of the user and attributes of the goal via the plurality of prompts on the user interface, executing the GenAI model on the identifier of the goal of the user and the attributes of the goal to generate a custom image of the goal for the user, and displaying the custom image of the goal via the user interface of the software application.

Techniques and systems for the dynamic generation of a map interface include generating temporal activity models by representing individual social media postings as having respective density distributions in time. Each posting's temporal density distribution spans multiple sequential time windows centered on the posting's timestamp, with density contributions decreasing in value for time windows further from the timestamp. The temporal models may be combined with spatial density distributions to generate comprehensive geo-temporal representations of social media activity. A graphical user interface displays an interactive map with overlay elements determined based on calculated activity attributes, including detected temporal patterns and anomalies identified by comparing current activity models against historical baselines. The modeling approach enables improved visualization of activity patterns while providing inherent privacy protection through probabilistic representation of individual posts.

Systems, devices, and methods for presenting audio associated with events associated with spatialized audio effects or non-spatialized audio effects in three-dimensional environments are disclosed. The spatialized and / or non-spatialized audio effects correspond with displaying, via a display generation component, a three-dimensional environment from a viewpoint of a user. While displaying the three-dimensional environment from the viewpoint of the user, the computer system detects an event. When the computer system detects an event which corresponds to a spatialized sound effect, the computer system presents the sound effect as emanating from a location in the three-dimensional environment associated with the event. When the computer system detects an event which corresponds to a non-spatialized sound effect, the computer system presents the sound effect as emanating from a predetermined location for audio in the three-dimensional environment that has a predetermined spatial relationship relative to the viewpoint of the user

A computer system displays representations of second computer systems included in a communication session and / or content in an environment in some embodiments. For example, the computer system displays the representations of the second computer systems in a first region while content is not shared in the communication session and displays the representations of the second computer systems in a second region different from the first region concurrently with content that is shared in the communication session. In some embodiments, the computer system displays the representations of the second computer system (e.g., a representation of a shared content item) such that it partially occludes a representation of the one or more participants of the video communication session when the representation of the one or more participants is a non-spatial representation.

An example operation may include one or more of establishing a network connection between a computing system and one or more external sources over a computer network, receiving a request from a user via a software application on a user device, collecting data about the user from the one or more external sources via the established network connection, executing a machine learning model on the collected data about the user to determine a goal of the user, and displaying an image of the goal via a user interface of the software application.

An example operation may include one or more of generating a unique image based on execution of an image generating model and displaying the unique image via a user interface of a software application, assigning a segment of the unique image to a goal at a first point in time based on user inputs via a user interface of the software application, monitoring account activity of a user within the software application, determining, at a second point in time, that the user is closer to the goal based on the monitored account activity of the user within the software application, and in response to the determination, increasing a size of the segment of the unique image assigned to the goal of the user.

A system and method for creating complex, immersive, and interactive digital content is disclosed. The system integrates advanced artificial intelligence, multi-modal input processing, cloud-based shared environments, and immersive hardware to generate, optimize, and deliver rich interactive experiences. The platform supports content mashups, custom scenario generation, and adaptive AI behaviors, enabling the creation of unique and engaging digital environments across various media formats.

An example operation may include one or more of training a generative artificial intelligence (GenAI) model to generate images based on user data using a dataset of images, executing the GenAI model based on input data from a user interface of a software application to generate an image corresponding to the input data, and displaying the image via a user interface of a software application, receiving feedback about the image via the user interface; andretraining the GenAI model based on the generated image and the received feedback about the image via the user interface.

An example operation may include one or more of generating a unique image comprising a plurality of image segments via an image generating model and displaying the unique image via a user interface of a software application, installing a smart contract associated with the unique image on a blockchain ledger, detecting a command to move an image segment from among the plurality of image segments based on user inputs via the user interface of the software application, removing the image segment from the unique image and adding the image segment to a different image based on the detected command, and transmitting the different image to a user account of the software application.

Some examples of the disclosure are directed to systems and methods for communicating image sensor data to a computer system using one or more media links that allow for image sensor data to be displayed within a three-dimensional environment. In some examples, while presenting a three-dimensional environment that includes an electronic device that is communicatively coupled to an image sensor (e.g., a camera, or some other imaging device) within the three-dimensional environment, the electronic device utilizes a visual code displayed on the electronic device to establish a communication link with the image sensor receiving an indication to display image sensor data from the image sensor that is communicatively coupled to the electronic device. In some examples, while presenting a three-dimensional environment that includes a first pre-defined location within the three-dimensional environment, the electronic device facilitates the user to choose an image sensor to display at the pre-defined location.

An example operation may include one or more of storing user data in a storage device, receiving inputs via prompts displayed on a user interface of a software application, identifying a plurality of goals within the received inputs and generating a plurality of data structures corresponding to the plurality of goals, respectively, executing a generative artificial intelligence (GenAI) model on the plurality of goals and the stored user data to generate a plurality of custom images of the plurality of goals, and displaying a plurality of identifiers of the plurality of data structures corresponding to the plurality of goals on a user interface, and simultaneously display the plurality of custom images next to the plurality goals, respectively.

In some embodiments, a computer system changes a visual prominence of a respective virtual object in response to detecting a threshold amount of overlap between a first virtual object and a second virtual object. In some embodiments, a computer system changes a visual prominence of a respective virtual object based on a change in spatial location of a first virtual object with respect to a second virtual object. In some embodiments, a computer system applies visual effects to representations of physical objects, virtual environments, and / or physical environments. In some embodiments, a computer system changes a visual prominence of a virtual object relative to a three-dimensional environment based on display of overlapping objects of different types in the three-dimensional environment. In some embodiments, a computer system changes a level of opacity of a first virtual object overlapping a second virtual object in response to movement of the first virtual object.

An example operation may include one or more of establishing a network connection between the computing system and a data source, iteratively performing a sequence of steps comprising collecting user data from the data source, executing a generative artificial intelligence (GenAI) model on the collected user data to generate a different image segment, and filling in a different subset of pixels of an image with the generated image segment and display the partially-filled in image on a user interface.

In some embodiments, an electronic device generates virtual lighting effects while presenting a content item. In some embodiments, an electronic device enhances navigation to a respective playback position of a content item. In some embodiments, an electronic device displays media content in a three-dimensional environment. In some embodiments, an electronic device presents media content in different modes of presentation.

An example operation includes one or more of logging user actions with respect to placement of objects of content on a user interface including respective content types of the objects of content, training an artificial intelligence (AI) model to learn location preferences for a content type on the user interface based on the logged user actions including the respective content types, receiving a request to open an object on the user interface with the content type, determining a display location on the user interface for the object based on execution of the AI model on the content type, and displaying the object at the determined display location on the user interface.

Methods for displaying and organizing user interfaces in a computer-generated environment provide for an efficient and intuitive user experience. In some embodiments, user interfaces can be grouped together into a container. In some embodiments, user interfaces can be added to a container, removed from a container, or moved from one location in the container to another location. In some embodiments, a visual indication is displayed before a user interface is added to a container. In some embodiments, a user interface can replace an existing user interface in a container. In some embodiments, when moving a user interface in a computer-generated environment, the transparency of a user interface that is obscured can be modified.

Methods for counter-scaling windows and rearranging objects within those counter-scaled windows in a 3D computer-generated environment is disclosed. The windows can be counter-scaled in accordance with changes to their depth within the 3D computer-generated environment. Objects within the window can be presented at their actual size and with their correct scale relative to each other and with respect to the 3D computer-generated environment, and can maintain their actual size and scale relative to each other and the environment regardless of the depth of the window in the environment. Some embodiments of the disclosure rearrange the layout of the objects to present more or fewer objects in the window as the size of the window changes due to counter-scaling. Depth-dependent window resizing and object rearrangement while preserving actual object size and scale within the 3D computer-generated environment can provide a more authentic viewing experience and can encourage increased user interaction.

The present disclosure generally describes user interfaces related to time. In accordance with embodiments, user interfaces for displaying and enabling an adjustment of a displayed time zone are described. In accordance with embodiments, user interfaces for initiating a measurement of time are described. In accordance with embodiments, user interfaces for enabling and displaying a user interface using a character are described. In accordance with embodiments, user interfaces for enabling and displaying a user interface that includes an indication of a current time are described. In accordance with embodiments, user interfaces for enabling configuration of a background for a user interface are described. In accordance with embodiments, user interfaces for enabling configuration of displayed applications on a user interface are described.

The technology relates to systems and methods for generating context-aware, dynamic visualizations. In an example, a method includes extracting a dynamic context signal; based on the dynamic context signal, retrieving a first visualization; causing a display of the first visualization as part of an application user interface; at an expiration of a refresh period, extracting an updated dynamic context signal; based on the updated dynamic context signal, retrieving a second visualization; and replacing the first visualization with the second visualization as part of an application user interface.

Systems and methods are described for inputting text input to a trained machine learning model; generating, using the trained machine learning model and based on the text input, a single-layer image comprising a plurality of objects; segmenting the single-layer image to generate a plurality of images, each image of the plurality of images comprising a depiction of a respective object of the plurality of objects of the single-layer image; extracting, from the text input, a portion of the text input describing a background portion of the single-layer image; generating, using the trained machine learning model and based on the extracted portion of the text input, a background image; and generating the multi-layer image based on the plurality of images and the background image.

An example operation may include at least one of receiving, via a user interface of a device, an activation input from a user to initiate a session, capturing, by a camera of the device, a scan of a body of the user, wherein the capturing comprises recording at least one image and / or at least one video of the user, processing the at least one image and / or video to generate a three- dimensional model of the user comprising measurements and contours of the body, retrieving, from a database, at least one clothing item associated with the user, the at least one clothing item comprising dimensional attributes and texture attributes, rendering, by a graphics processing unit, the at least one clothing item onto the three-dimensional model to generate a visual representation, wherein the rendering simulates draping behavior, movement, and light interaction of the at least one clothing item relative to the three-dimensional model, and displaying, on the user interface, an interactive visualization comprising the visual representation of the three-dimensional model with the at least one clothing item from multiple viewing angles.

The present disclosure relates to systems, methods, and non-transitory computer-readable media that edit digital images using combinations of speech input and gesture interactions. For instance, in some embodiments, the disclosed systems receive speech input from a client device displaying a digital image within a graphical user interface, the digital image portraying an object. Additionally, the disclosed systems detect, via the graphical user interface, one or more gesture interactions with respect to the object of the digital image. Based on the speech input, the disclosed systems determine an edit for the object of the digital image indicated by the one or more gesture interactions. Further, the disclosed systems modify the object within the digital image using the edit indicated by the one or more gesture interactions.

A graphical, hierarchical document stream browser and environment for semantic (e.g. framing) and performance data analysis and interactive visualization integrates three scales: entities (competitive), entity (diachronic), and document (linguistic). The document level includes annotation and computational linguistics facilities; the entity level has calendrical and time-series focus. All levels emphasize deep linkage and network (i.e. connective / relational space) view of objects, with user-configurable connectivity. Large language model (LLM) integrations provide synthetic advisories, public opinions, reports, plot insights, comparisons; traditional natural language processing techniques and neural models are also employed. A smart plot system includes a “plot cart” and interpreter with an analysis snippet library. Graph structure may arise via adjustable blending or perceptual optimization of canned attribute-related distance functions or via link-induction query language with deep “semantic stored procedure” subexpressions, or feed into graph neural network-style inference for predictions. Most non-LLM ongoing computational load is client-side, using precomputed hierarchical summary files.

In implementation of techniques for three-dimensional reconstructions based on Gaussian primitives, a computing device implements a reconstruction system to receive a first digital image depicting an object from a first angle and a second digital image depicting the object from a second angle. The reconstruction system segments the first digital image and the second digital image into patches. The reconstruction system then generates, using a machine learning model, three-dimensional Gaussian primitives that predict parameters of points of the object in a three-dimensional space that correspond on a per-pixel basis to pixels of the patches. The reconstruction system then forms a three-dimensional reconstruction of the object for display in a user interface by merging the three-dimensional Gaussian primitives.

Systems and methods for generating custom art fonts with consistent style include receiving user input that identifies a base font style for a custom font and includes descriptive text that defies one or more text effects to use for the custom font. Depth maps are selected for characters to be included in the custom font. The depth maps are preprocessed to add noise to the depth maps. A generative model generates custom font images conditioned with the text prompt and the depth maps. The custom font images are then used to render text on a display screen of a computing device.

Certain aspects of the present disclosure provide techniques for generating an output image based on a text prompt. A method may include receiving the text prompt; providing a user interface comprising one or more input elements associated with one or more words of the text prompt; receiving input corresponding to at least one of the one or more input elements, the input indicating a semantic importance for each of at least one of the one or more words associated with the at least one of the one or more input elements; and generating the output image based on the text prompt and the input.