Abstract: A method includes: receiving a user query; generating first embedding data for the user query via a language agnostic machine learning embedding model; and predicting a first intent of the user query based on the first embedding data.

Abstract: Systems and methods disclosed herein provide a geo-targeted online reservation system that ensures authenticity of customer devices requesting reservations by generating reservations only if threshold authentication conditions are satisfied. For example, a computing device registered with a server system receives inputs for requesting a reservation of a limited release product and for configuring the product. To authenticate the computing device, the server device transmits an electronic message to the computing device requesting the computing device to respond. A response to the message is one threshold authentication condition for generating the reservation. Upon determining that one or more threshold authentication conditions are satisfied, the server device generates a reservation for the product.

Abstract: Systems and methods disclosed herein provide a geo-targeted online reservation system that ensures authenticity of customer devices requesting reservations by generating reservations only if threshold authentication conditions are satisfied. For example, a computing device registered with a server system receives inputs for requesting a reservation of a limited release product and for configuring the product. To authenticate the computing device, the server device transmits an electronic message to the computing device requesting the computing device to respond. A response to the message is one threshold authentication condition for generating the reservation. Upon determining that one or more threshold authentication conditions are satisfied, the server device generates a reservation for the product.

Abstract: A method includes: receiving a user query; generating first embedding data for the user query via a language agnostic machine learning embedding model; and predicting a first intent of the user query based on the first embedding data.

Abstract: Methods and systems for training an intent classifier. For example, a question-intent tuple dataset comprising data samples is received. Each data sample has a question, an intent, and a task. A pre-trained language model is also received and fine-tuned by adjusting values of learnable parameters. Parameter adjustment is performed by generating a plurality of neural network models. Each neural network model is trained to predict at least one intent of the respective question having a same task value of the tasks of the question-intent tuple dataset. Each task represents a source of the question and the respective intent. The fine-tuned language model generates embeddings for training input data, the training input data comprising a plurality of data samples having questions and intents. Further, feature vectors for the data samples of the training input data are generated and used to train an intent classification model for predicting intents.

Abstract: Systems and method are disclosed for processing unrecognized user queries. A received user query is classified via a first machine learning model. A first classification determination is made for the user query. In response to the first classification determination, features of the user query are identified via a second machine learning model. The user query is grouped into a cluster based on the features of the user query. Information about the cluster is displayed for prompting a user action. The user action may include identification of an intent for the user query.

Abstract: Systems and methods for generating training questions are disclosed. The method includes identifying a structure for generating an input; formulating the input according to the structure; providing the input to a first machine learning model; receiving an output from the first machine learning model based on the input; and training a second machine learning model based on the output. The first machine learning model may be a pre-trained generative language model.

Abstract: Methods and systems for generating and using a conversation summary model. The method comprises receiving at least one training dataset. The at least one training dataset comprises data samples, each data sample comprising a text comprising text segments. The text is labelled with a conversation summary comprising any of the text segments which summarize the text. The at least one training dataset includes a dataset from a specific source. Using the at least one training dataset and the pre-trained model, the method further comprises generating the conversation summary model by fine-tuning the pre-trained model. The generated conversation summary model may be used to generate conversation summaries for chat conversations.

Abstract: Systems and methods disclosed herein provide a geo-targeted online reservation system that ensures authenticity of customer devices requesting reservations by generating reservations only if threshold authentication conditions are satisfied. For example, a computing device registered with a server system receives inputs for requesting a reservation of a limited release product and for configuring the product. To authenticate the computing device, the server device transmits an electronic message to the computing device requesting the computing device to respond. A response to the message is one threshold authentication condition for generating the reservation. Upon determining that one or more threshold authentication conditions are satisfied, the server device generates a reservation for the product.

Abstract: Methods and systems for training an intent classifier. For example, a question-intent tuple dataset comprising data samples is received. Each data sample has a question, an intent, and a task. A pre-trained language model is also received and fine-tuned by adjusting values of learnable parameters. Parameter adjustment is performed by generating a plurality of neural network models. Each neural network model is trained to predict at least one intent of the respective question having a same task value of the tasks of the question-intent tuple dataset. Each task represents a source of the question and the respective intent. The fine-tuned language model generates embeddings for training input data, the training input data comprising a plurality of data samples having questions and intents. Further, feature vectors for the data samples of the training input data are generated and used to train an intent classification model for predicting intents.

Abstract: Systems and methods disclosed herein provide a geo-targeted online reservation system that ensures authenticity of customer devices requesting reservations by generating reservations only if threshold authentication conditions are satisfied. For example, a computing device registered with a server system receives inputs for requesting a reservation of a limited release product and for configuring the product. To authenticate the computing device, the server device transmits an electronic message to the computing device requesting the computing device to respond. A response to the message is one threshold authentication condition for generating the reservation. Upon determining that one or more threshold authentication conditions are satisfied, the server device generates a reservation for the product.

Abstract: Systems and methods disclosed herein provide a geo-targeted online reservation system that ensures authenticity of customer devices requesting reservations by generating reservations only if threshold authentication conditions are satisfied. For example, a computing device registered with a server system receives inputs for requesting a reservation of a limited release product and for configuring the product. To authenticate the computing device, the server device transmits an electronic message to the computing device requesting the computing device to respond. A response to the message is one threshold authentication condition for generating the reservation. Upon determining that one or more threshold authentication conditions are satisfied, the server device generates a reservation for the product.

Abstract: Systems and methods disclosed herein provide a geo-targeted online reservation system that ensures authenticity of customer devices requesting reservations by generating reservations only if threshold authentication conditions are satisfied. For example, a computing device registered with a server system receives inputs for requesting a reservation of a limited release product and for configuring the product. To authenticate the computing device, the server device transmits an electronic message to the computing device requesting the computing device to respond. A response to the message is one threshold authentication condition for generating the reservation. Upon determining that one or more threshold authentication conditions are satisfied, the server device generates a reservation for the product.

Abstract: Systems and methods disclosed herein provide a geo-targeted online reservation system that ensures authenticity of customer devices requesting reservations by generating reservations only if threshold authentication conditions are satisfied. For example, a computing device registered with a server system receives inputs for requesting a reservation of a limited release product and for configuring the product. To authenticate the computing device, the server device transmits an electronic message to the computing device requesting the computing device to respond. A response to the message is one threshold authentication condition for generating the reservation. Upon determining that one or more threshold authentication conditions are satisfied, the server device generates a reservation for the product.

Abstract: Systems and methods disclosed herein provide a geo-targeted online reservation system that ensures authenticity of customer devices requesting reservations by generating reservations only if threshold authentication conditions are satisfied. For example, a computing device registered with a server system receives inputs for requesting a reservation of a limited release product and for configuring the product. To authenticate the computing device, the server device transmits an electronic message to the computing device requesting the computing device to respond. A response to the message is one threshold authentication condition for generating the reservation. Upon determining that one or more threshold authentication conditions are satisfied, the server device generates a reservation for the product.

Abstract: Systems and methods disclosed herein provide a geo-targeted online reservation system that ensures authenticity of customer devices requesting reservations by generating reservations only if threshold authentication conditions are satisfied. For example, a computing device registered with a server system receives inputs for requesting a reservation of a limited release product and for configuring the product. To authenticate the computing device, the server device transmits an electronic message to the computing device requesting the computing device to respond. A response to the message is one threshold authentication condition for generating the reservation. Upon determining that one or more threshold authentication conditions are satisfied, the server device generates a reservation for the product.

Abstract: A system for use in material testing which can be used on non-planar shapes and which is simple and inexpensive in construction. The system includes a layer of piezoelectric material sandwiched between and connected to a unified electrode and a plurality of excitable electrodes; and a structure, such as a Faraday structure-like unit which prevents electric or static fields from getting into or out of the structure and controls voltage potentials contained therein to be uniform, enclosing the ultrasonic transducer unit, and functions by maintaining a voltage potential on the electrodes and the piezoelectric material then pulling to the reference potential selected electrodes to generate a signal which excites the piezoelectric material so it generates a corresponding signal and then measuring the return signal generated by the piezoelectric material in response to a return signal from material being tested in response to the signal generated by the piezoelectric material.

Abstract: In a nondestructive testing system, a preamplifier is connected to a piezoelectric element and is tuned to optimize the amplitude of a signal input to the piezoelectric element and the shape of a response signal. A receiver amplifier couples the signal received from the piezoelectric element to an ultrasound system.