Abstract: An artificial intelligence (AI) interaction method, system, and computer program product include selecting an artificial intelligence model to respond to a query to generating a response to the query using the selected artificial intelligence model, and receiving the response to the query from the selected artificial intelligence model.

Abstract: An apparatus includes a first plate, a second plate, a third plate, a ferroelectric dielectric, and a paraelectric dielectric. The ferroelectric dielectric is between the first plate and the second plate such that the first plate, the ferroelectric dielectric, and the second plate form a first capacitor. The paraelectric dielectric is between the second plate and the third plate such that the second plate, the paraelectric dielectric, and the third plate form a second capacitor.

Abstract: A computing system, computer program product, and computer-implemented method for quantitative comment summarization are provided. The method includes receiving a collection of comments, identifying a set of candidate key points corresponding to the collection of comments, and selecting a subset of key points from the set of candidate key points, wherein the selected subset of key points includes key points that are most salient in the collection of comments. The method also includes automatically mapping each comment within the collection of comments to any corresponding key points within the subset of key points based on a match score between each comment and key point pair, as well as generating a summary including the subset of key points and an absolute number or percentage of the comments mapped to each key point.

Abstract: Systems, computer-implemented methods, and computer program products to facilitate sparse depth completion with semantic mesh deformation optimization in an augmented reality environment are provided. According to an embodiment, a system can comprise a processor that executes computer executable components stored in memory. The computer executable components comprise a depth completion component that generates a first depth map from an image and sparse depth samples. The computer executable components further comprise a semantic mesh deformation component that performs a semantic mesh deformation process, using the sparse depth samples, to generate a second depth map comprising a defined image accuracy.

Abstract: Systems and methods for utilizing a mnemonic to communicate sensitive data to an agent are disclosed. In aspects, a computer-implemented method comprises: establishing a telephone connection between a caller and an agent; entering an encryption key received from the agent into a mnemonic application of the computer device to permute an algorithm of the mnemonic application; receiving sensitive data in the form of one or more alphabetic, numeric or alpha-numeric sequence; initiating the mnemonic application to generate a mnemonic of the sensitive data using the encryption key, wherein the mnemonic is a sequence of words representing the sensitive data; displaying the mnemonic to the caller; and conveying audio communication of the mnemonic to the agent through the telephone connection to enable remote decoding of the mnemonic back into the at least one sensitive number sequence.

Abstract: A system may include a memory and a processor in communication with the memory. The processor may be configured to perform operations that include generating a key pair and encrypting a data credential with a public key to make a data credential secret. The operations may further include storing the data credential secret in a cluster on a host and deploying a workload on the cluster. The operations may also include establishing an empty bundle in the host and generating a pod trusted execution environment.

Abstract: Techniques regarding tiling a CR gate configuration to one or more lattices characterizing quantum circuit topologies are provided. For example, one or more embodiments described herein can comprise a system, which can comprise a memory that can store computer executable components. The system can also comprise a processor, operably coupled to the memory, and that can execute the computer executable components stored in the memory. The computer executable components can comprise a tiling component that can generate a cross-resonance gate configuration that delineates a control qubit assignment and a target qubit assignment in conjunction with a frequency allocation onto a lattice characterizing a quantum circuit topology.

Abstract: One or more systems, devices, computer program products and/or computer-implemented methods provided herein relate to data drift detection in an edge device. A system can comprise a memory configured to store computer executable components; and a processor configured to execute the computer executable components stored in the memory, wherein the computer executable components can comprise a verification component that can verify accuracy of a first model and accuracy of a second model to detect data drift associated with an edge device that is deployed without network connectivity; a computation component that can compute at least a first ratio based on the accuracy of the first model and the accuracy of the second model; and an analysis component that can use the at least the first ratio to determine whether performance degradation of at least one of the first model or the second model is a function of the data drift.

Abstract: A technique for generating a performance prediction of a machine learning model with uncertainty intervals includes obtaining a first model configured to perform a task and a production dataset. At least one metric predicting a performance of the first model at performing the task on the production dataset is generated using a second model. The second model is a meta-model associated with the first model. At least one value predicting an uncertainty of the at least one metric predicting the performance of the first model at performing the task on the production dataset is generated using a third model. The third model is a meta-meta-model associated with the second model. An indication of the at least one metric and the at least one value is provided.

Abstract: Semiconductor devices and methods of forming the same include recessing sacrificial layers in a stack of alternating sacrificial layers and channel layers using a first etch to form curved recesses at sidewalls of each sacrificial layer in the stack, with tails of sacrificial material being present at a top and bottom of each curved recess. Dielectric plugs are formed that each partially fill a respective curved recess, leaving exposed at least a portion of each tail of sacrificial material. The tails of sacrificial material are etched back using a second etch to expand the recesses. Inner spacers are formed in the expanded recesses.

Abstract: Embodiments of the invention are directed to data replication in an active-active databases having a source site and a target site. Aspects include creating a subscription activation message in a capture address space, the subscription activation message having a timestamp after a latest committed timestamp of the active-active databases and transmitting the subscription activation message to a subscription activation module of the target site of the active-active databases. Based on a determination that one or more tables associated with the subscription activation message are inactive, aspects also include repairing the one or more tables. Based on a determination that all tables associated with the subscription activation message are active, aspects include initiate replication of the capture address space from the source site to the target site with a timestamp of the latest committed timestamp.

Abstract: The present disclosure relates to methods and apparatuses related to the deposition of a protective layer selective to an interlayer dielectric layer so that the protective layer is formed onto a top portion associated with the interlayer dielectric layer. In some embodiments, a method comprises: forming an interlayer dielectric layer on a substrate; covering a trench region with a metal liner, wherein the trench region is situated above the substrate and formed within the interlayer dielectric layer; and depositing a protective layer selective to the interlayer dielectric layer so that the protective layer is formed onto a top portion associated with the interlayer dielectric layer. In various embodiments, the depositing the protective layer comprises: repeatedly depositing the protective layer via a multi-deposition sequence; or depositing a self-assembled monolayer onto the top portion.

Abstract: Methods, computer program products, and/or systems are provided that perform the following operations: identifying an application marker for a source application; mapping the application marker to a set of micro-patterns provided in a micro-pattern repository, wherein a micro-pattern defines a set of actions to be performed to modernize a source application component for a target platform; generating a set of potential modernization pathways for the source application, wherein a potential modernization pathway is based, at least in part, on an aggregation of one or more micro-patterns included in the set of micro-patterns mapped to the application marker; determining a recommended modernization pathway from the set of potential modernization pathways based, at least in part, on micro-pattern optimization; and providing the recommended modernization pathway for source application modernization execution, wherein the source application modernization execution includes executing each micro-pattern included in th

Abstract: Semiconductor devices and methods of forming the same include forming a stack of alternating first and second sacrificial layers. The first sacrificial layers are recessed relative to the second sacrificial layers. Replacement channel layers are grown from sidewalls of the first sacrificial layers. A first source/drain region is grown from the replacement channel layer. The recessed first sacrificial layers are etched away. A second source/drain region is grown from the replacement channel layer. The second sacrificial layers are etched away. A gate stack is formed between and around the replacement channel layers.

Abstract: Aspects of the invention include systems and methods to obtain meta features of a dataset for training in a deep learning application. A method includes selecting an initial search space that defines a type of deep learning architecture representation that specifies hyperparameters for two or more neural network architectures. The method also includes applying a search strategy to the initial search space. One of the two or more neural network architectures are selected based on a result of an evaluation according to the search strategy. A new search space is generated with new hyperparameters using an evolutionary algorithm and a mutation type that defines one or more changes in the hyperparameters specified by the initial search space, and, based on the mutation type, the new hyperparameters are applied to the one of the two or more neural networks or the search strategy is applied to the new search space.

Abstract: A mechanism is provided in a data processing system for displaying cyber threat data in a narrative format. The mechanism receives a cyber threat information file that comprises cyber threat data in a serialized format. The mechanism generates a tree data structure representing relationships between objects in the cyber threat data and generates a user interface presenting the cyber threat data in a narrative format based on the tree data structure. The mechanism presents the user interface to an analyst.

Abstract: Machine teaching in an embodiment can include receiving a user annotated concept for a given image in given context. The given image can be broken into parts and classified. Relationships can be determined associated with the parts. The created relationships can be stored along with the user annotated concept in a knowledge base. One or more similar images can be annotated using the parts and relationships. A second image associated the given context can be retrieved, decomposed into parts. The parts can be classified. Relationships can be determined associated with the second image's parts. Classifications and relationships associated with the second image's parts can be compared with classifications and relationships associated with the given image's parts. Based on comparing, the second image can be annotated with the user annotated concept for the given image.

Abstract: Aspects include receiving a document and classifying at least a subset of the document as having a first type of data. Features are extracted from the document. The extracting includes initiating processing of the at least a subset of the document by a first processing engine that was previously trained to extract features from the first type of data. The extracting also includes initiating processing of a remaining portion of the document not included in the at least a subset of the document by a second processing engine that was previously trained to extract features from a second type of data. The first type of data is different than the second type of data. Features are received from one or both of the first processing engine and the second processing engine. The received features are stored as features of the document.

Abstract: A network architecture may receive situational data. The network architecture may acquire participant data associated with a participant. The network architecture may accept object data associated with an object. The network architecture may generate likelihood of infectiousness of the object based on the participant data and the object data. The network architecture may display the likelihood of infectiousness to one or more users.

Abstract: A mechanism is provided for implement a discrepancy detection mechanism for detecting discrepancies between clinical notes and administrative records. Clinical concepts are extracted from the clinical notes and the administrative records in a patient's electronic medical records (EMRs). The extracted clinical concepts are filtered based on semantic type information to identify concepts that reference diseases or syndromes while also removing negated instances. Utilizing the positive mentions of diseases in clinical notes, the positive mentions of diseases or syndromes in the clinical notes are compared against each positive entry in the administrative records. A discrepancy summary is then generated for diseases or syndromes that failed to translate correctly from clinical notes to the administrative records in the patient's EMRs.