Abstract: A method includes providing an interactive graphical user interface comprising a first menu providing one or more input options, a second menu providing one or more machine learning models, and a third menu providing one or more output formats. The method also includes generating a graph in a portion of the interactive graphical user interface by detecting one or more user selections of an input option, a machine learning model, and an output format, displaying nodes corresponding to the input option, the machine learning model, the output format, and displaying edges connecting the first node to the second node, and the second node to the third node. The method additionally includes applying the machine learning model to an input associated with the input option to generate an output in the output format. The method further includes providing, by the interactive graphical user interface, the output in the output format.

Abstract: Described techniques may be utilized to process transcribed text of a transcription stream using a compression ratio machine learning (ML) model to determine at least two compression ratios. The transcribed text may then be processed by a summarization ML model using the at least two compression ratios to obtain a summary stream that includes first summarized text having a first compression ratio of the at least two compression ratios, relative to a first corresponding portion of the transcribed text, and second summarized text having a second compression ratio of the at least two compression ratios, relative to a second corresponding portion of the transcribed text. The transcribed text may also be summarized by the summarization ML model based on a complexity score determined by a complexity ML model.

Abstract: A tagging system appends supplemental information to an original sequence of items, to produce a supplemented sequence of items. The tagging system includes a transformer-based encoder neural network that maps the supplemented sequence into hidden state information. The tagging system includes a post-processing neural network that transform the hidden state information into a tagged output sequence of items. That is, each item in the tagged output sequence includes a tag that identifies its entity class or some other characteristic. The tagging system can increase the accuracy of the tags it produces by virtue of the inclusion of the supplemental information added to each original sequence. A training system trains the tagging system to perform plural tasks, which further increases the accuracy of the tags it produces. The training system may commence training of the tagging system using a pre-trained model for the encoder neural network.

Abstract: Systems and methods are provided for generating a keyword sequence from an input query. A first text sequence corresponding to an input query may be received and encoded into a source sequence representation using an encoder of a machine learning model. A keyword sentence may then be generated from the source sequence representation using a decoder of the machine learning model. The decoder may generate a modified generation score for a plurality of prediction tokens, wherein the modified generation score is based on the respective prediction token generation score and a maximum generation score for a suffix of each prediction token. The decoder may then select the prediction token of the plurality of prediction tokens based on the modified generation score, and add the selected prediction token to the previously decoded partial hypothesis provided by the decoder.

Abstract: A mosquito trapping device includes a body, a mosquito storage box, a fan, and a lattice cover assembly, where the lattice cover assembly is arranged on an upper end portion of the body and forms a first accommodation space with the body, and the mosquito storage box is mounted on the body; the fan causes air to flow through air inlet portions so as to enter the mosquito box and subsequently flow through the accommodation space and air outlets which together form an air duct used to trap mosquitos in the mosquito storage box.

Abstract: A method can include selecting, from at least a first avatar and a second avatar based on at least one attribute of a calendar event associated with a user, a session avatar, the first avatar being based on a first set of images of a user wearing a first outfit and the second avatar being based on a second set of images of the user wearing a second outfit, and presenting the session avatar during a videoconference, the presentation of the session avatar changing based on audio input received from the user during the videoconference.

Abstract: Described techniques may be utilized to process transcribed text of a transcription stream using a summarization ML model to obtain a summary stream. In this way, a live conversation or other live speech may be provided to a user in real-time, using a display of a head-mounted device (HMD) or other suitable device. A user interface may be provided with a toggle or other stream selector for selecting either or both of the transcription stream or the summary stream at a given point in time. Actionable items may be identified within either or both of the transcription stream or the summary stream, and a scroll bar or other action selector may be provided in the user interface to execute corresponding actions.

Abstract: A system for controlling a head mounted device (HMD). The system includes a processor of a controller of the HMD connected to an Internal Measurement Unit (IMU) and a memory on which are stored machine-readable instructions that when executed by the processor, cause the processor to: receive Internal Measurement Unit (IMU) data generated in response to vibrations produced by voiced nasal consonant vocalizations produced by an HMD user, analyze the IMU data to determine whether the IMU data corresponds to an HMD control command, and responsive to a determination that the IMU data corresponds to the HMD control command, execute the HMD control command.

Abstract: A transformer-based neural network includes at least one mask attention network (MAN). The MAN computes an original attention data structure that expresses influence between pairs of data items in a sequence of data items. The MAN then modifies the original data structure by mask values in a mask data structure, to produce a modified attention data structure. Compared to the original attention data structure, the modified attention data structure better accounts for the influence of neighboring data items in the sequence of data items, given a particular data item under consideration. The mask data structure used by the MAN can have static and/or machine-trained mask values. In one implementation, the transformer-based neural network includes at least one MAN in combination with at least one other attention network that does not use a mask data structure, and at least one feed-forward neural network.

Abstract: Systems, apparatuses, and methods are described for generating unique identifiers. Identifiers may be organized or grouped by different topics. Identifiers may be requested, generated, stored as groups, and may be allocated from those groups based on requests for identifiers to improve the efficiency of one or more computing devices or systems. The size of each group of identifiers may be adjusted.

Abstract: A method can include determining, by a head-mounted device mounted on a head of a user, a number of degrees of freedom of an input modality of an auxiliary device; determining an input modality of the head-mounted device based on the number of degrees of freedom of the input modality of the auxiliary device; and presenting the input modality of the head-mounted device to the user.

Abstract: A visual programming platform can leverage a machine learning-based coding system to generate an initial set of programming-language code for further graphical editing by a human user. As an example, the visual programming platform can obtain a natural language description of a task to be performed by a computational pipeline. The visual programming platform can process the natural language description of the task with a machine learning coding system that includes one or more machine-learned models to generate, as an output of the machine learning coding system, a set of pseudocode that describes performance of the task. The platform can process the set of pseudocode that describes performance of the task with a compiler to generate a set of programming-language code that defines the computational pipeline for performing the task. The visual programming platform can generate a graphical visualization of the computational pipeline defined by the set of programming-language code.

Abstract: In described techniques, a depth of an object may be determined with respect to a head-mounted device (HMD). A gaze duration with respect to the object may be determined, relative to a gaze duration threshold. Then, based on the depth and on the gaze duration exceeding the gaze duration threshold, virtual content may be rendered at a virtual depth with respect to the HMD that is different than the depth.

Abstract: Techniques of introducing virtual objects into a physical environment of AR system include displacing vertices of a mesh representing the physical environment based on a live depth map. For example, an AR system generates a mesh template, i.e., an initial mesh with vertices that represents a physical environment and a depth map that indicates a geometry of real objects within the physical environment. The AR system is configured to represent the real objects in the physical environment by displacing the vertices of the mesh based on depth values of the depth map and parameter values of a pinhole camera model. The depth values may be taken from the perspective of an illumination source in the physical environment.

Abstract: A mosquito trapping device includes a body, a mosquito storage box, a fan, and a net cover assembly, where the net cover assembly is arranged on an upper end portion of the body and forms a first accommodation space with the body, and the mosquito storage box is mounted on the body; the net cover assembly includes a first net cover, a second net cover, and a third net cover, where the first net cover is provided with a first air outlet portion in communication with the first accommodation space, and the third net cover is provided with a first air inlet portion matching the fan; the mosquito storage box is provided with a second air inlet portion positioned right below the fan and a third air outlet portion in communication with the first accommodation space.

Abstract: A user can interact with sounds and speech in an environment using an augmented reality device. The augmented reality device can be configured to identify objects in the environment and display messages beside the object that are related to sounds produced by the object. For example, the messages may include sound statistics, transcripts of speech, and/or sound detection events. The disclosed approach enables a user to interact with these messages using a gaze and a gesture.

Abstract: An electroplating device includes a process chamber, a substrate holding device, a first cover body, a second cover body, a gas supply part and an exhaust part. The electroplating solution is contained in the inner chamber of the process chamber and the inner chamber has an opening. The substrate holding device is used for holding a substrate, and the substrate holding device is moved into or out of the inner chamber through the opening. The first cover body is connected to the substrate holding device to close the opening after the substrate holding device is moved into the inner chamber, so that the inner chamber is in a closed state. The second cover body is used for closing the opening after the substrate holding device is moved out of the inner chamber, so that the inner chamber is in the closed state again.

Abstract: Nonlinear peri-codec optimization for image and video coding includes obtaining a source image including pixel values expressed in a first defined image sample space, generating a neuralized image representing the source image, the neuralized image including pixel values that are expressed as neural latent space values, encoding the input image wherein the neural latent space values are used as pixel values in a second defined image sample space and the input image is in an operative image format of the encoder, such that a decoder decodes the encoded image to obtain a reconstructed image in the second defined image sample space, wherein the reconstructed image is a reconstructed neuralized image including reconstructed neural latent space values, such that a deneuralized reconstructed image corresponding to the source image is obtained by a nonlinear post-codec image processor in the first defined image sample space.

Abstract: A method comprises determining, by a head-mounted device, a limitation of a user based on a visual input received from a camera included in the head-mounted device; determining an output communication channel and an input communication channel based on the limitation of the user, sending a notification to the user via the output communication channel; and receiving an input from the user via the input communication channel.

Abstract: Systems and methods are related to tracking an attention of a user with respect to content presented on a virtual screen, detecting a defocus event associated with a first region of the content, and determining a next focus event associated with a second region of the content. The determination can be based at least in part on the defocus event and on the tracked attention of the user. The systems and methods can include generating, based on the determined next focus event, a marker for differentiating the second region of the content from a remainder of the content, and in response to detecting a refocus event associated with the virtual screen, triggering execution of the marker associated with the second region of the content.