Abstract: Techniques for augmenting training data include accessing training data comprising a plurality of training examples comprising a first training example comprising a first natural language utterance and a first logical form for the first natural language utterance. A second natural language utterance is generated by adding or replacing one or more values in the first natural language utterance. A logical form for the second natural language utterance is generated. A second training example is generated, comprising the second natural language utterance and the logical form for the second natural language utterance. The training data is augmented by adding the second training example to the plurality of training examples to generate an augmented training data set. A machine learning model is trained to generate logical forms for utterances using the augmented training data set.

Abstract: This disclosure generally relates to USB TYPE-C, and, in particular, DISPLAYPORT Alternate Mode communication in a USB TYPE-C environment. In one embodiment, a device determines a DISPLAYPORT mode and determines an orientation of a USB TYPE-C connector plug. A multiplexer multiplexes a DISPLAYPORT transmission based in part on the determined orientation of the USB TYPE-C connector plug.

Abstract: Systems and methods for secure database schema migration are described. In an illustrative, non-limiting embodiment, an Information Handling System (IHS) may include: a processor and a memory, the memory having program instructions that cause the processor to: calculate a first hash of schema objects for a database; compare the calculated first hash of the schema objects with an expected second hash of the schema objects for the database; determine that the schema objects comprise a previous version of the database; and execute scripts to upgrade the schema objects for the database. The program instructions can also cause the processor to: determine that the calculated first hash of the schema objects does not compare with the expected second hash of the schema objects, and determine that the calculated first hash of the schema objects compares with a third hash of the schema objects corresponding to the previous version of the database.

Abstract: The invention relates to engineered immune cells comprising a chimeric antigen receptor or a T cell receptor, wherein said CAR or TCR comprises an antigen binding domain capable of specific binding to one or more epitopes associated with neutrophil extracellular traps.

Abstract: An apparatus and method for coating a substrate includes preheating a first portion of the substrate to a first temperature. The method includes ejecting a first material from a material applicator so that the first material is applied to the preheated first portion of the substrate. The first material includes a first solvent component and a first coating component. The first temperature is greater than an ambient temperature and less than a boiling point of the first coating component.

Abstract: The present invention relates to N-substituted-dioxocyclobutenylamino-3-hydroxy-picolinamide compounds of Formulae (IA and 1B) or a pharmaceutically acceptable salt or hydrate thereof, that inhibit CC chemokine receptor 6 (CCR6), pharmaceutical compositions containing these compounds, and the use of these compounds for treating or preventing diseases, conditions, or disorders ameliorated by inhibition of CCR6.

Abstract: Methods and apparatus for partitioned private interconnects to provider networks are described. At least a portion of available bandwidth of a private physical interconnect between a provider network and a connectivity intermediary's network is designated as the bandwidth limit of an interconnect partition set up on behalf of a customer at the request of the intermediary. The intermediary's network comprises one or more devices to which at least one of the customer's devices is connected. Access to one or more resources of the provider network via the interconnect is enabled. Traffic monitoring results associated with the interconnect are used to enforce the designated bandwidth limit of the partition.

Abstract: Techniques are disclosed herein for improving model robustness on operators and triggering keywords in natural language to a meaning representation language system. The techniques include augmenting an original set of training data for a target robustness bucket by leveraging a combination of two training data generation techniques: (1) modification of existing training examples and (2) synthetic template-based example generation. The resulting set of augmented data examples from the two training data generation techniques are appended to the original set of training data to generate an augmented training data set and the augmented training data set is used to train a machine learning model to generate logical forms for utterances.

Abstract: Techniques for extracting key information from a document using machine-learning models in a chatbot system is disclosed herein. In one particular aspect, a method is provided that includes receiving a set of data, which includes key fields, within a document at a data processing system that includes a table detection module, a key information extraction module, and a table extraction module. Text information and corresponding location data are extracted via optical character recognition. The table detection module detects whether one or more tables are present in the document and, if applicable, a location of each of the tables. The key information extraction module extracts text from the key fields. The table extraction module extracts each of the tables based on input from the optical character recognition and the table detection module. Extraction results include the text from the key fields and each of the tables can be output.

Abstract: A method for forming a diamond product. Diamond material is provided and a damage layer comprising sp2 bonded carbon is formed in the material. The presence of the damage layer defines a first diamond layer above and in contact with the damage layer and a second diamond layer below and in contact with the damage layer. The damage layer is electrochemically etched to separate it from the first layer, wherein the electrochemical etching is performed in a solution containing ions, the solution having an electrical conductivity of at least 500 ?S cm?1, and wherein the ions are capable of forming radicals during electrolysis. The diamond product is also described.

Abstract: The present disclosure relates to techniques for identifying out-of-domain utterances.

Abstract: Techniques are described for developing and using applications and skills with autonomous vehicles. In some embodiments, a development platform is provided that enables access to a developer console for developing software modules for use with autonomous vehicles. For example, a developer can specify instructions for causing an autonomous vehicle to perform one or more operations. To control the behavior of an autonomous vehicle, the instructions can cause an executing computer system at the autonomous vehicle to generate calls to an application programming interface (API) associated with an autonomous navigation system of autonomous vehicle. Such calls to the API can be configured to adjust parameters of a behavioral objective associated with a trajectory generation process performed by the autonomous navigation system that controls the behavior of the autonomous vehicle. The instructions specified by the developer can be packaged as a software module that can be deployed for use at autonomous vehicle.

Abstract: A method includes receiving a training set of utterances for training a machine-learning model to identify one or more intents for one or more utterances, and augmenting the training set of utterances with out-of-domain (OOD) examples. The augmenting includes: generating a data set of OOD examples, filtering out OOD examples from the data set of OOD examples, determining a difficulty value for each OOD example remaining within the filtered data set of the OOD examples, and generating augmented batches of utterances including utterances from the training set of utterances and utterances from the filtered data set of the OOD based on the difficulty value for each OOD. Thereafter, the machine-learning model is trained using the augmented batches of utterances in accordance with a curriculum training protocol.

Abstract: A method, computer system, and computer program product are provided for deploying software using a versioning schema. An n-dimensional string is obtained that describes a version of a component, wherein a value for each dimension describes a particular feature of the component. The n-dimensional string is analyzed using a template to determine each feature of the component. It is determined whether to deploy the version of the component based on the analyzing and based on criteria related to one or more features of the component.

Abstract: A pipe insulation is formed from multiple discrete sheets of fiberglass that are wetted with a binder composition. The sheets are spiral wound around a mandrel in a partially overlapping fashion. The wound sheets are further processed to interface with one another and form a unitary elongated cylinder. The binder in the elongated cylinder is then cured to form the pipe insulation.

Abstract: The present invention provides pharmaceutically active pyrrolo[2,3-d]pyrimidinyl and pyrrolo[2,3-d]pyridinyl acrylamides and analogues thereof. Such compounds are useful for inhibiting Janus Kinase (JAK). This invention also is directed to compositions comprising methods for making such compounds, and methods for treating and preventing conditions mediated by JAK.

Abstract: The invention relates to compounds of Formula (I) and pharmaceutically acceptable salts thereof, wherein A, L, X, Y and p are as defined in the description; to their use in medicine; to compositions containing them; to processes for their preparation; and to intermediates used in such processes. The compounds of Formula (I) may modulate the activity of antigens of interest and may be useful in inducing or enhancing an immune response against diseases, disorders and conditions mediated by antigens of interest.

Abstract: A method for 3D object perception is described. The method includes extracting features from each image of a synthetic stereo pair of images. The method also includes generating a low-resolution disparity image based on the features extracted from each image of the synthetic stereo pair images. The method further includes predicting, by a trained neural network, a feature map based on the low-resolution disparity image and one of the synthetic stereo pair of images. The method also includes generating, by a perception prediction head, a perception prediction of a detected 3D object based on the feature map predicted by the trained neural network.

Abstract: A method of forming a part includes 3D printing a photopolymerizable resin and forming a preformed part and subsequently post-curing the preformed part with electron beams. The preformed part may be cured via UV curing. A section of the preformed part post-cured with electron beams may have a thickness of at least 1.0 centimeter, for example, at least 2.0 centimeters or at least 3.0 centimeters. An electron beam dosage to post-cure the preformed part may be between 10 kilogray (kGy) and 100 kGy. The preformed part may be 3D printed using stereolithography (SLA), digital light processing (DLP) or material jetting (MJ) and the photopolymerizable resin may include at least one of an acrylate functional polymer and a methacrylate functional polymer. In the alternative, or in addition to, the photopolymerizable resin may include at least one of a urethane, a polyester, and a polyether.

Abstract: Techniques are disclosed herein for focused training of language models and end-to-end hypertuning of the framework. In one aspect, a method is provided that includes obtaining a machine learning model pre-trained for language modeling, and post-training the machine learning model for various tasks to generate a focused machine learning model. The post-training includes: (i) training the machine learning model on an unlabeled set of training data pertaining to a task that the machine learning model was pre-trained for as part of the language modeling, and the unlabeled set of training data is obtained with respect to a target domain, a target task, or a target language, and (ii) training the machine learning model on a labeled set of training data that pertains to another task that is an auxiliary task related to a downstream task to be performed using the machine learning model or output from the machine learning model.