Abstract: A device includes one or more processors configured to detect single-stream data and generate multi-stream augmented data that includes one or more modified versions of the single-stream data. The one or more processors are configured to process the multi-stream augmented data to generate multiple output channels. The one or more processors are also configured to reduce the multiple output channels to produce single-stream output data.

Abstract: An online system receives user data for users of the online system and assigns the users to one or more user cohorts based on the user data. The online system generates a prompt for content to be included in a landing page presented to each user cohort, in which the prompt includes a template for the landing page and information describing the user cohorts. The online system then provides the prompt to a generative artificial intelligence model to obtain an output and extracts, from the output, a set of content to be included in the landing page for each user cohort. The online system generates variants of the landing page for each user cohort based on the extracted set of content.

Abstract: An online system receives information describing an order placed by a user of the online system and a set of contextual features associated with servicing the order. The online system also retrieves a set of user features associated with the user. The online system accesses a machine learning model trained to predict a tip amount the user is likely to provide for servicing the order and applies the machine learning model to a set of inputs, in which the set of inputs includes the information describing the order, the set of user features, and the set of contextual features. The online system then determines a suggested tip amount for servicing the order based on the predicted tip amount.

Abstract: An online system receives information describing an order placed by a user of the online system and a set of contextual features associated with servicing the order. The online system also retrieves a set of user features associated with the user. The online system accesses a machine learning model trained to predict a tip amount the user is likely to provide for servicing the order and applies the machine learning model to a set of inputs, in which the set of inputs includes the information describing the order, the set of user features, and the set of contextual features. The online system then determines a suggested tip amount for servicing the order based on the predicted tip amount.

Abstract: The present invention relates to thermostable quick-dissolving thin films comprising a biological moiety and an excipient mix which are suitable for the formulation of biological moieties such as viral vaccines, to methods for manufacturing such thermostable quick-dissolving thin films, and to their use in therapy. The excipient mix comprises one or more water-soluble polymer(s), a sugar selected from sucrose, trehalose and a combination thereof, a metal ion, a carboxylate, and a buffering agent.

Abstract: A method of providing vehicle diagnostics may include receiving a first communication from a user, processing the first communication using a natural language processing (NLP) model to produce NLP model output including a sequence of words, extracting one or more keywords from the sequence of words, and instructing a data acquisition and transfer device (DAT) connected to an OBD port of a vehicle to perform a selected function based on the one or more keywords. The method may further include receiving diagnostic data from the DAT, the diagnostic data having been retrieved from the vehicle by the DAT in accordance with the selected function, and determining a diagnostic condition of the vehicle based on the diagnostic data.

Abstract: A method of providing vehicle diagnostics may include receiving a first communication from a user, processing the first communication using a natural language processing (NLP) model to produce NLP model output including a sequence of words, extracting one or more keywords from the sequence of words, and instructing a data acquisition and transfer device (DAT) connected to an OBD port of a vehicle to perform a selected function based on the one or more keywords. The method may further include receiving diagnostic data from the DAT, the diagnostic data having been retrieved from the vehicle by the DAT in accordance with the selected function, and determining a diagnostic condition of the vehicle based on the diagnostic data.

Abstract: An apparatus includes a memory and processor. The memory stores document categories, text generated from an image a physical document page, and a machine learning algorithm. The machine learning algorithm is configured to extract features associated with natural language processing and features associated with the text. The machine learning algorithm is also configured to generate a feature vector that includes the first and second pluralities of features, and to generate, based on the feature vector, a set of probabilities, each of which is associated with a document category and indicates a probability that the physical document from which the text was generated belongs to that document category. The processor applies the machine learning algorithm to the text, to generate the set of probabilities, identifies a largest probability, and assigns the image to the associated document category.

Abstract: The disclosure is directed to compounds of formula (I), and pharmaceutically acceptable salts thereof. Pharmaceutical compositions comprising compounds of formula (I), as well as methods of their use and preparation, are also described.

Abstract: A method of providing vehicle diagnostics may include receiving a first communication from a user, processing the first communication using a natural language processing (NLP) model to produce NLP model output including a sequence of words, extracting one or more keywords from the sequence of words, and instructing a data acquisition and transfer device (DAT) connected to an OBD port of a vehicle to perform a selected function based on the one or more keywords. The method may further include receiving diagnostic data from the DAT, the diagnostic data having been retrieved from the vehicle by the DAT in accordance with the selected function, and determining a diagnostic condition of the vehicle based on the diagnostic data.

Abstract: An apparatus includes a memory and processor. The memory stores document categories, text generated from an image a physical document page, and a machine learning algorithm. The machine learning algorithm is configured to extract features associated with natural language processing and features associated with the text. The machine learning algorithm is also configured to generate a feature vector that includes the first and second pluralities of features, and to generate, based on the feature vector, a set of probabilities, each of which is associated with a document category and indicates a probability that the physical document from which the text was generated belongs to that document category. The processor applies the machine learning algorithm to the text, to generate the set of probabilities, identifies a largest probability, and assigns the image to the associated document category.

Abstract: A device includes a memory configured to store instructions and one or more processors configured to execute the instructions. The one or more processors are configured to execute the instructions to receive audio data including a first audio frame corresponding to a first output of a first microphone and a second audio frame corresponding to a second output of a second microphone. The one or more processors are also configured to execute the instructions to provide the audio data to a first noise-suppression network and a second noise-suppression network. The first noise-suppression network is configured to generate a first noise-suppressed audio frame and the second noise-suppression network is configured to generate a second noise-suppressed audio frame. The one or more processors are further configured to execute the instructions to provide the noise-suppressed audio frames to an attention-pooling network. The attention-pooling network is configured to generate an output noise-suppressed audio frame.

Abstract: An apparatus includes a memory and processor. The memory stores document categories, text generated from an image a physical document page, and a machine learning algorithm. The text includes errors associated with noise in the image. The machine learning algorithm is configured to extract features associated with natural language processing and features associated with the errors from the text. The machine learning algorithm is also configured to generate a feature vector that includes the first and second pluralities of features, and to generate, based on the feature vector, a set of probabilities, each of which is associated with a document category and indicates a probability that the physical document from which the text was generated belongs to that document category. The processor applies the machine learning algorithm to the text, to generate the set of probabilities, identifies a largest probability, and assigns the image to the associated document category.

Abstract: A system defining a visual sensing pipeline architecture flexibly allows application developers to dynamically adapt the spatial resolution and update rate of different “rhythmic pixel encoding regions” in a scene. The system ingests pixel streams with raster-scan pixel read-out patterns, but only encodes relevant pixels prior to storing them in memory. The system includes streaming hardware to decode the stored rhythmic pixel encoding region stream into traditional frame-based representations to feed into standard computer vision algorithms.

Abstract: An apparatus includes a memory and processor. The memory stores OCR and NLP algorithms. The processor receives an image of a physical document page and executes the OCR algorithm to convert the image into text. The processor identifies errors in the text, which are associated with noise in the image. The processor generates a feature vector that includes features obtained by executing the NLP algorithm on the text, and features associated with the identified errors in the text. The processor uses the feature vector to assign the image to a document category. Documents assigned to the document category share one or more characteristics, and the feature vector is associated with a probability greater than a threshold that the physical document associated with the image includes those characteristics. The processor then stores the image in a database as a page of an electronic document belonging to the assigned document category.

Abstract: A device includes a memory configured to store instructions and one or more processors configured to execute the instructions. The one or more processors are configured to execute the instructions to receive audio data including a first audio frame corresponding to a first output of a first microphone and a second audio frame corresponding to a second output of a second microphone. The one or more processors are also configured to execute the instructions to provide the audio data to a first noise-suppression network and a second noise-suppression network. The first noise-suppression network is configured to generate a first noise-suppressed audio frame and the second noise-suppression network is configured to generate a second noise-suppressed audio frame. The one or more processors are further configured to execute the instructions to provide the noise-suppressed audio frames to an attention-pooling network. The attention-pooling network is configured to generate an output noise-suppressed audio frame.

Abstract: An apparatus includes a memory and processor. The memory stores OCR and NLP algorithms. The processor receives an image of a physical document page and executes the OCR algorithm to convert the image into text. The processor identifies errors in the text, which are associated with noise in the image. The processor generates a feature vector that includes features obtained by executing the NLP algorithm on the text, and features associated with the identified errors in the text. The processor uses the feature vector to assign the image to a document category. Documents assigned to the document category share one or more characteristics, and the feature vector is associated with a probability greater than a threshold that the physical document associated with the image includes those characteristics. The processor then stores the image in a database as a page of an electronic document belonging to the assigned document category.

Abstract: An apparatus includes a memory and processor. The memory stores document categories, text generated from an image a physical document page, and a machine learning algorithm. The text includes errors associated with noise in the image. The machine learning algorithm is configured to extract features associated with natural language processing and features associated with the errors from the text. The machine learning algorithm is also configured to generate a feature vector that includes the first and second pluralities of features, and to generate, based on the feature vector, a set of probabilities, each of which is associated with a document category and indicates a probability that the physical document from which the text was generated belongs to that document category. The processor applies the machine learning algorithm to the text, to generate the set of probabilities, identifies a largest probability, and assigns the image to the associated document category.

Abstract: The present invention relates to thermostable quick-dissolving thin films comprising a biological moiety and an excipient mix which are suitable for the formulation of biological moieties such as viral vaccines, to methods for manufacturing such thermostable quick-dissolving thin films, and to their use in therapy. The excipient mix comprises one or more water-soluble polymer(s), a sugar selected from sucrose, trehalose and a combination thereof, a metal ion, a carboxylate, and a buffering agent.

Abstract: A system for manufacturing a string of pocketed coil springs comprising: a coil-forming subsystem that produces two coil springs; a spring transporter subsystem that receives the two coil springs at a first position and conveys the two coil springs to a second position; a spring compressor subsystem that compresses the two coil springs; a fabric-folding subsystem that receives a piece of fabric and folds the fabric to create an open side; a spring inserter subsystem that receives the two compressed coil springs and inserts the two compressed coil springs between top and bottom surfaces of a folded piece of fabric; two welder subsystems that form first and second welds between top and bottom surfaces of the folded piece of fabric, the first welds and the second welds forming a plurality of pockets in the fabric, each of the plurality of pockets comprising a compressed coil spring.