Abstract: Embodiments of a system and a method for classifying blocks of text at varying, possibly simultaneous, and possibly interacting levels of scope (e.g., sentence, paragraph, section, document) are disclosed. A system includes a processor coupled to: a data reader to receive an input comprising of a data stream, and convert the data stream into one or more logical data blocks of varying scopes. The system includes a dependency tree generator to create a dependency tree to define the scope and dependencies of each of a plurality of natural language processors (NL Processors) with respect to each other such that the dependency tree identifies when an input of a NL Processor (depender) depends on an output of another NL Processor (dependee). Each NL Processor is configured based on a type of at least one logical data block of the one or more logical blocks to which it applies.

Abstract: Disclosed herein are techniques for using a generative adversarial network (GAN) to train a semantic parser of a dialog system. A method described herein involves accessing seed data that includes seed tuples. Each seed tuple includes a respective seed utterance and a respective seed logical form corresponding to the respective seed utterance. The method further includes training a semantic parser and a discriminator in a GAN. The semantic parser learns to map utterances to logical forms based on output from the discriminator, and the discriminator learns to recognize authentic logical forms based on output from the semantic parser. The semantic parser may then be integrated into a dialog system.

Abstract: A method includes accessing document including sentences, document being associated with configuration flag indicating whether ABSA, SLSA, or both are to be performed; inputting the document into language model that generates chunks of token embeddings for the document; and, based on the configuration flag, performing at least one from among the ABSA and the SLSA by inputting the chunks of token embeddings into a multi-task model. When performing the SLSA, a part of token embeddings in each of the chunks is masked, and the masked token embeddings do not belong to a particular sentence on which the SLSA is performed.

Abstract: Systems, methods, articles of manufacture, and computer program products to: train a prediction model using a machine learning process, the prediction model configured to estimate whether further application of a hyperparameter tuning technique will cause an improvement in at least one of the hyperparameters; select the hyperparameters using the tuning technique; apply the prediction model to determine if further adjustment of the hyperparameters is likely to improve the success metric; and terminate the tuning technique when: accuracy of the prediction model in predicting improvement in a hyperparameter is above a predetermined accuracy threshold, and the prediction model predicts that further application of the tuning technique will not result in an improvement to the hyperparameter; or the accuracy of the prediction model in predicting improvement in the parameter is below the predetermined accuracy threshold, and an accuracy of hyperparameter adjustment is determined to be below a predetermined adjustment

Abstract: The various implementations described herein include a video camera assembly that includes: (1) a housing; (2) an image sensor positioned within the housing and having a field of view corresponding to a scene in the smart home environment; and (3) a concave-shaped front face positioned in front of the image sensor such that light from the scene passes through the front face prior to entering the image sensor; where the front face includes: (a) an inner section corresponding to the image sensor; and (b) an outer section between the housing and the inner section, the outer section having a concave shape that extends from an outer periphery of the outer section to an inner periphery of the outer section; and where the concave shape extends around an entirety of the outer periphery.

Abstract: Techniques for using enhanced logit values for classifying utterances and messages input to chatbot systems in natural language processing. A method can include a chatbot system receiving an utterance generated by a user interacting with the chatbot system and inputting the utterance into a machine-learning model including a series of network layers. A final network layer of the series of network layers can include a logit function. The machine-learning model can map a first probability for a resolvable class to a first logit value using the logit function. The machine-learning model can map a second probability for a unresolvable class to an enhanced logit value. The method can also include the chatbot system classifying the utterance as the resolvable class or the unresolvable class based on the first logit value and the enhanced logit value.

Abstract: Techniques for noise data augmentation for training chatbot systems in natural language processing. In one particular aspect, a method is provided that includes receiving a training set of utterances for training an intent classifier to identify one or more intents for one or more utterances; augmenting the training set of utterances with noise text to generate an augmented training set of utterances; and training the intent classifier using the augmented training set of utterances. The augmenting includes: obtaining the noise text from a list of words, a text corpus, a publication, a dictionary, or any combination thereof irrelevant of original text within the utterances of the training set of utterances, and incorporating the noise text within the utterances relative to the original text in the utterances of the training set of utterances at a predefined augmentation ratio to generate augmented utterances.

Abstract: The present invention provides methods of treating a S. aureus bloodstream infection (bacteremia) to a patient in need thereof, the method comprising administering ceftobiprole as ceftobiprole miedocaril to the patient at a dosage corresponding to 500 mg of ceffobiprole every 6 hours on days 1 to 8 and 500 mg every 8 hours on days 9 onwards.

Abstract: Apparatuses, systems, and methods comprising acoustically absorptive air ducts comprising an internally positioned structure component as an endoskeleton and an air impervious inner layer, and an acoustically absorptive foam outer layer, environmental control systems comprising such air ducts, and vehicles incorporating such environmental control systems are disclosed with methods for manufacture and installations are disclosed.

Abstract: An example of an apparatus to transport utility-scale lithium-ion batteries in a racked and operational state. The apparatus includes a base and an isolation platform. In addition, the apparatus includes an isolator mounted on the base to support the isolation platform. The isolator is to dampen forces exerted on the isolation platform from the base. Furthermore, the apparatus includes a rack mounted onto the isolation platform. The rack is to secure a plurality of lithium-ion batteries to store energy at a utility-scale to be provided to a power distribution network. The plurality of lithium-ion batteries is racked in an operational state during transportation.

Abstract: A computer-implemented method includes: accessing a plurality of datasets, where each dataset of the plurality of datasets includes training examples; selecting datasets that include the training examples in a source language and a target language; and sampling, based on a sampling weight that is determined for each of the selected datasets, the training examples from the selected datasets to generate the training batches; training an ML model for performing at least a first task using the training examples of the training batches, by interleavingly inputting the training batches to the ML model; and outputting the trained ML model configured to perform the at least the first task on input utterances provided in at least one among the source language and the target language. The sampling weight is determined for each of the selected datasets based on one or more attributes common to the training examples of the selected dataset.

Abstract: The present disclosure is related to techniques for converting a natural language utterance to a logical form query and deriving a natural language interpretation of the logical form query. The techniques include accessing a Meaning Resource Language (MRL) query and converting the MRL query into a MRL structure including logical form statements. The converting includes extracting operations and associated attributes from the MRL query and generating the logical form statements from the operations and associated attributes. The techniques further include translating each of the logical form statements into a natural language expression based on a grammar data structure that includes a set of rules for translating logical form statements into corresponding natural language expressions, combining the natural language expressions into a single natural language expression, and providing the single natural language expression as an interpretation of the natural language utterance.

Abstract: An approach for facilitating mechanical and electrical connection of electric machines and electrical components in an electrical system using connectors with quick connect/disconnect electrical connectors is disclosed. Each quick connect/disconnect electrical connector can be placed on the end of an electrical power distribution cable that connects with an electric machine or electrical component. The electric machines and electrical components and the electrical power distribution cables can have hollow coolant passages formed therein to receive cooling fluid from a cooling device for direct cooling of the electric machines, electrical components and the electrical power distribution cables.

Abstract: The present disclosure relates to systems, methods, and computer-readable media for identifying a variety of events that occur within a gaming session and generating event reports based on the identified events. For example, a gaming service (e.g., a cloud gaming server) can leverage content analysis and event recognizer services on a cloud computing system to detect one or more in-game events based on gaming content (e.g., video content, audio content, controller inputs) that is delivered to a client system. Systems described herein can train and implement event recognizers trained to track various in-game events across multiple gaming applications. Based on the tracked events, the systems described herein can generate event reports for events, individual users, and groups of users of the cloud computing system.

Abstract: Techniques are disclosed herein for integrating document question answering in an artificial intelligence-based platform, such as a chatbot system. The techniques include receiving a query from a user, rewriting the query to include one or more specific descriptors, computing an embedding vector for the rewritten query, retrieving one or more textual passages from a document store utilizing the embedding vector for the rewritten query, determining one or more answers to the rewritten query within the one or more textual passages, and returning the one or more answers.

Abstract: Techniques for using logit values for classifying utterances and messages input to chatbot systems in natural language processing. A method can include a chatbot system receiving an utterance generated by a user interacting with the chatbot system. The chatbot system can input the utterance into a machine-learning model including a set of binary classifiers. Each binary classifier of the set of binary classifiers can be associated with a modified logit function. The method can also include the machine-learning model using the modified logit function to generate a set of distance-based logit values for the utterance. The method can also include the machine-learning model applying an enhanced activation function to the set of distance-based logit values to generate a predicted output. The method can also include the chatbot system classifying, based on the predicted output, the utterance as being associated with the particular class.

Abstract: A composite scaffold having a highly porous interior with increased surface area and void volume is surrounded by a flexible support structure that substantially maintains its three-dimensional shape under tension and provides mechanical reinforcement during repair or reconstruction of soft tissue while simultaneously facilitating regeneration of functional tissue.

Abstract: Methods and systems for using machine learning models to organize and select modular components for user interface templates. For example, the methods and systems may use machine learning and/or artificial intelligence to generate user interfaces with a preferred number of user input fields and/or pages, in which the preferred number both satisfies any requirements for the user interface (e.g., information, categories of information, etc.), and ensures that all privacy concerns are met.

Abstract: Systems, method and computer readable medium are provided for automated storage and retrieval. User authentication information is received via a user interface for a dynamic storage and retrieval device. The user identity is verified based upon the authentication information and previously stored authentication data. Order information is retrieved for an order associated with the user following the verifying of user identity, the order information indicating one or more locations for items associated with the order. Instructions are transmitted to initiate a physical opening of at least one of the dynamic storage and retrieval device and at least one static storage location to enable the user to retrieve at least one item of the order, the static storage location including a controller controlling a locking mechanism and communicatively coupled to the dynamic storage and retrieval device.

Abstract: The present invention comprises conjugates comprising a glucagon-like peptide 1 (GLP-1) fusion peptide coupled to a cyclic PYY peptide. The invention also relates to pharmaceutical compositions and methods for use thereof. The novel conjugates are useful for preventing, treating or ameliorating diseases and disorders disclosed herein.