Abstract: Aspects of the present invention disclose a method, computer program product, and system for management and usage of shared authentication credentials. The method includes one or more processors updating usage information associated with an authentication credential with a media access control address (MAC address) that corresponds to a computing device that corresponds to using the authentication credential. The method further includes one or more processors receiving a login request that includes the authentication credential from a computing device. The method further includes one or more processors fetching a MAC address of the computing device that sent the login request. The method further includes one or more processors validating the authentication credentials and the MAC address.

Abstract: In one embodiment, a method includes receiving a first input by a user from a client system associated with the user, wherein the first input is in a voice modality, analyzing the first input to generate one or more candidate hypotheses, determining one or more modalities for presenting output generated by the one or more computing systems to the user at the client system, and sending instructions to the client system for presenting one or more suggested auto-completions corresponding to one or more of the candidate hypotheses, respectively, wherein each suggested auto-completion comprises the corresponding candidate hypothesis, and wherein the one or more suggested auto-completions are presented in the one or more determined modalities.

Abstract: A processor may receive a smart contract. The processor may generate an entity policy. The entity policy may provide one or more world-state rules associated with a particular entity. The processor may update, responsive to receiving the smart contract, a world-state database of the particular entity. The one or more world-state rules may affect the world-state database of the particular entity differently than the world-state database of a second entity.

Abstract: Systems and processes for operating an intelligent automated assistant are provided. In accordance with one example, a method includes, at an electronic device with one or more processors and memory, obtaining a first set of data corresponding to one or more interactions between a user and the digital assistant on the electronic device; obtaining a second set of data corresponding to one or more interactions between the user and an application on the electronic device; and storing the first set of data and the second set of data. The method further includes receiving a set of executable instructions; processing, based on the received set of executable instructions, the first set of data and the second set of data to obtain a third set of data; and transmitting the third set of data to a remote electronic device.

Abstract: In one embodiment, a method includes receiving an initial input in a first modality from a first user from a client system associated with the first user, determining one or more intents corresponding to the initial input by an intent-understanding module, generating one or more candidate continuation-inputs based on the one or more intents, where the one or more candidate continuation-inputs are in one or more candidate modalities, respectively, and wherein the candidate modalities are different from the first modality, and sending instructions for presenting one or more suggested inputs corresponding to one or more of the candidate continuation-inputs to the client system.

Abstract: In one embodiment, a method includes detecting a user input comprising an incomplete gesture performed by one or more hands of a first user by a client system associated with the first user; selecting one or more candidate gestures from a plurality of pre-defined gestures by the client system based on a personalized gesture-recognition model, wherein each of the candidate gestures is associated with a confidence score representing a likelihood the first user intended to input the respective candidate gesture, and presenting one or more suggested inputs corresponding to one or more of the candidate gestures at the client system.

Abstract: An aerated beverage composition is described herein. The aerated beverage composition comprises coffee having a weight percentage in a range of 0.1-20% with respect to the aerated beverage composition, at least one structurant having a weight percentage in a range of 10-40% with respect to the aerated beverage composition, at least one sweetener having a weight percentage in a range of 21-60% with respect to the aerated beverage composition, at least one solvent. The viscosity of the aerated beverage composition is in a range of 10,0000-3,40,000 cps. The aerated beverage composition, when reconstituted with water, provides a creamy, frothy, and stable ready-to-drink beverage. The present disclosure also provides a simple and convenient process for preparing the aerated beverage composition.

Abstract: In one embodiment, a method includes receiving an initial input in a first modality from a first user at a client system, determining intents and slots corresponding to the initial input, wherein the slots are conditioned on the intents, generating one or more candidate continuation-inputs based on the intents and slots, where the one or more candidate continuation-inputs are in one or more candidate modalities, respectively, wherein the candidate modalities are different from the first modality, and wherein each of the candidate continuation-inputs references entities represented by the slots, and presenting one or more suggested inputs corresponding to one or more of the candidate continuation-inputs at the client system.

Abstract: An example operation includes one or more of identifying, by an archiving server node, a unique archival policy for each of a plurality of blockchain nodes, executing, by the archiving server node, a consensus mechanism to determine at least one block from a plurality of blocks of the plurality of the blockchain nodes to be archived, and running the unique archival policy to archive the at least one block from the plurality of the blocks.

Abstract: Exemplary embodiments relate to improvements in spoken language understanding (SLU) systems. Conventionally, SLU systems include an automatic speech recognition (ASR) component configured to receive an input of audio data and to generate a textual representation of the audio data. Conventional SLU systems also include a natural language understanding (NLU) component configured to receive a text-based transcript and perform language-based tasks such as domain classification, intent determination, and slot-filling. However, these two components are typically trained separately based on different metrics. In real-world situations, errors in the ASR component propagate to the NLU component, which degrades the performance of the overall system. Exemplary embodiments described herein perform SLU in an end-to-end manner that infers semantic meaning directly from audio features without an intermediate text representation.

Abstract: In one embodiment, a method includes receiving an initial input in a first modality from a first user from a client system associated with the first user, determining one or more intents corresponding to the initial input by an intent-understanding module, generating one or more candidate continuation-inputs based on the one or more intents, where the one or more candidate continuation-inputs are in one or more candidate modalities, respectively, and wherein the candidate modalities are different from the first modality, and sending instructions for presenting one or more suggested inputs corresponding to one or more of the candidate continuation-inputs to the client system.

Abstract: Techniques for database versioning are described. In one embodiment, an apparatus may comprise a database change management component operative to compare a developer table to a reference table to determine a database change set, wherein both the developer table and the reference table are based on a target table; a database conflict management component operative to compare the database change set to the target table to determine a conflicting change set; and a user interface component operative to display the conflicting change set where the conflicting change set comprises one or more conflicting changes; and indicate a conflict-free change set where the conflicting change set is empty. Other embodiments are described and claimed.

Abstract: A network device includes a memory, a plurality of packet processors, a switch fabric coupling the plurality of processors, and processing circuitry. The processing circuitry is configured to receive a data stream to be transmitted on a switch fabric and determine a plurality of credit counts, each credit count being assigned to a respective subchannel of a plurality of subchannels. The packet processor is further configured to determine per-subchannel occupancy of the memory for the plurality of subchannels, select, based on the plurality of credit counts and the per-subchannel occupancy of the memory, a subchannel of the plurality of subchannels for transmitting a cell of a plurality of cells for the data stream, and output data for the cell to the memory for output by the selected subchannel.

Abstract: An ingress fabric endpoint coupled to a switch fabric within a network device reorders packet flows based on congestion status. In one example, the ingress fabric endpoint receives packet flows for switching across the switch fabric. The ingress fabric endpoint assigns each packet for each packet flow to a fast path or a slow path for packet switching. The ingress fabric endpoint processes, to generate a stream of cells for switching across the switch fabric, packets from the fast path and the slow path to maintain a first-in-first-out ordering of the packets within each packet flow. The ingress fabric endpoint switches a packet of a first packet flow after switching a packet of a second packet flow despite receiving the packet of the first packet flow before the packet of the second packet flow.

Abstract: In one embodiment, a method includes receiving a user input comprising a natural-language utterance by an assistant xbot from a client system associated with a user, determining a semantic representation of the user input based on a structural ontology defining a labeling syntax for parsing the natural-language utterance to semantic units comprising actions, objects, and attributes, wherein the semantic representation embeds at least one object within at least one action and declares at least one attribute of the embedded object to be acted upon, sending a request based on the semantic representation to an agent for executing a task corresponding to the user input, receiving results of the executed task mapped to a structure determined by the structural ontology from the agent, and sending from the assistant xbot to the client system instructions for presenting a response based on the results of the executed task.

Abstract: In one embodiment, a method includes receiving, by a first client system, from one or more remote servers, a current version of a global neural network model including multiple federated model parameters, accessing, from a local data store, multiple examples and a local personalization model including multiple local model parameters, wherein each of the examples includes one or more features and one or more labels, training the global neural network model and the local personalization model together on the examples to generate multiple updated federated model parameters and multiple updated local model parameters, storing, in the local data store, the trained local personalization model including the updated local model parameters, and sending, to one or more of the remote servers, the trained global neural network model including the updated federated model parameters.

Abstract: In one embodiment, a method includes receiving a user request for a summarization of a particular type of content objects from a client system associated with a first user, determining one or more modalities associated with the user request, selecting a plurality of content objects of the particular type based on a user profile of the first user, wherein the user profile comprises one or more confidence scores associated with one or more subjects associated with the first user, respectively, and wherein the plurality of content objects are selected based on the one or more confidence scores, generating a summary of each content object based on the user profile and the determined modalities, and sending, to the client system in response to the user request, instructions for presenting the summaries of the plurality of content objects, wherein the summaries are presented via one or more of the determined modalities.

Abstract: An ingress fabric endpoint coupled to a switch fabric within a network device reorders packet flows based on congestion status. In one example, the ingress fabric endpoint receives packet flows for switching across the switch fabric. The ingress fabric endpoint assigns each packet for each packet flow to a fast path or a slow path for packet switching. The ingress fabric endpoint processes, to generate a stream of cells for switching across the switch fabric, packets from the fast path and the slow path to maintain a first-in-first-out ordering of the packets within each packet flow. The ingress fabric endpoint switches a packet of a first packet flow after switching a packet of a second packet flow despite receiving the packet of the first packet flow before the packet of the second packet flow.

Abstract: In one embodiment, a method includes receiving a query from a user from a client system associated with the user, determining one or more initial memory slots based on the query, accessing a memory graph associated with the user which comprises a plurality of nodes and a plurality of edges connecting the nodes, and wherein one or more of the nodes correspond to one or more episodic memories of the user, respectively, and wherein each edge corresponds to a relationship between the connected nodes, selecting one or more candidate nodes from the memory graph by one or more machine-learning models based on the initial memory slots, generating a response based on the initial memory slots and episodic memories corresponding to the selected candidate nodes, and sending instructions for presenting the response to the client system in response to the query.

Abstract: A user interacts with a virtual digital assistant with the intent that it provides assistance with a task. The user sends messages to the virtual digital assistant that include content obtained via user input at a client device. An intent determination model is applied to the content to identify the user's intent. The virtual digital assistant identifies agents that are capable of servicing the intent are identified and retrieves contextual data relating to the message from a data store. An intent arbitration model is used to select one of the agents which is activated to provide assistance with the task. The contextual information may include global metrics of agent performance and/or information regarding the user's preferences.