Abstract: Disclosed is a method for improving performance of a streaming media session between a plurality of communicating entities. Observation reports are collected from a plurality of monitoring entities. Each observation report comprises information pertaining to events observed and recorded at a corresponding monitoring entity. A size of at least one window to be used for analyzing the observation reports is determined. The observation reports are analyzed using the at least one window of the determined size, to determine a correlation between the events across the observation reports. A problem encountered during the streaming media session is identified, based upon the correlation between the events. A notification is sent to at least one of the monitoring entities, based upon the problem. The notification is sent during the streaming media session.

Abstract: A system includes a processor and a memory set coupled to the processor. The system also includes a repair circuit coupled to the memory set. The repair circuit includes a first repair circuit and a second repair circuit. The repair circuit also includes a test controller configured to select between the first repair circuit and the second repair circuit to perform an in-field self-repair of the memory set.

Abstract: One example includes an integrated circuit (IC). The IC includes non-volatile memory and logic. The logic is configured to receive repair code associated with a memory instance and assign a compression parameter to the repair code based on a configuration of the memory instance. The logic is also configured to compress the repair code based on the compression parameter to produce compressed repair code and to provide compressed repair data that includes the compressed repair code and compression control data that identifies the compression parameter. A non-volatile memory controller is coupled between the non-volatile memory and the logic. The non-volatile memory controller is configured to transfer the compressed repair data to and/or from the non-volatile memory.

Abstract: In a described example, an integrated circuit (IC) includes a repairable memory system. A repair controller is coupled to the repairable memory system. The repair controller includes compression logic configured to encode memory repair code data for a respective instance of the repairable memory system and provide compressed repair data. A non-volatile memory controller is coupled to the repair controller and to non-volatile memory. The non-volatile memory controller is configured to transfer the compressed repair data to the non-volatile memory for storage.

Abstract: A carrier assembly is configured to support a wafer, including during back end of line (BEOL) processing. The carrier assembly includes dual carriers. A first carrier includes a stepped structure so as to situate the wafer. A side of the wafer is bonded to the first carrier without adhesive. The first carrier is positioned atop the second carrier, so as to be mechanically supported by the second carrier. Each carrier is made by wet etching of laminated glass, without mechanical polishing.

Abstract: A mobile application notification system that includes a cloud node including a subscription service and a publication service, each executed on the cloud node, wherein the subscription service is configured to manage a plurality of users associated with a tenant of multiple tenants, each of the plurality of users have a corresponding user device that executes a monitoring application thereon, wherein management via the subscription service includes subscribing each of the plurality of users and configuring the tenant and associated messages, and wherein the publication service is configured to communicate with the corresponding user device of the plurality of users and to communication to a plurality of publisher threads, for exchanging messages therebetween, based on the subscribing and the configuring, and wherein at least two corresponding user device of the plurality of users utilize a different operating system and platform from one another.

Abstract: An automated agent may communicate with a user via a chat channel to proactively alert the user of an L1 IT support issue. The L1 IT support issue may be determined based on monitoring indications of human-initiated activities maintained by a system of record, and may, prior to the automated agent's alert, be unknown to the user. In some instances, a natural language understanding (NLU) module may be used to identify an entity and intent from the indications of human-initiated activities, and the L1 IT support issue may be determined based on the determined entity and intent. After alerting the user of the L1 IT support issue, the automated agent may inform, via the chat channel, the user of a remediation step available to address the L1 IT support issue. Upon obtaining the user's permission, the automated agent may perform the remediation step to address the L1 IT support issue.

Abstract: Systems and methods for visualization monitoring data from a cloud-based system include obtaining the monitoring data, wherein the monitoring data is based on transactions associated with a plurality of users of the cloud-based system; providing a Graphical User Interface (GUI); obtaining a plurality of filter selections for a plurality of filter types; and displaying a visualization comprising a Sankey diagram of the monitoring data with nodes in the Sankey diagram including each of the plurality of filter types and links between the nodes indicative of the transactions in the monitoring data. The monitoring data can be for one or more of cloud security service transactions, application access via a Zero Trust Network Access (ZTNA) service, and user experience metrics.

Abstract: Systems described herein may use transformer-based machine classifiers to perform a variety of natural language understanding tasks including, but not limited to sentence classification, named entity recognition, sentence similarity, and question answering. The exceptional performance of transformer-based language models is due to their ability to capture long-term temporal dependencies in input sequences. Machine classifiers may be trained using training data sets for multiple tasks, such as but not limited to sentence classification tasks and sequence labeling tasks. Loss masking may be employed in the machine classifier to jointly train the machine classifier on multiple tasks simultaneously. The user of transformer encoders in the machine classifiers, which treat each output sequence independently of other output sequences, in accordance with aspects of the invention do not require joint labeling to model tasks.

Abstract: A mobile application notification system that includes a cloud node including a subscription service and a publication service, each executed on the cloud node, wherein the subscription service is configured to manage a plurality of users associated with a tenant of multiple tenants, each of the plurality of users have a corresponding user device that executes a monitoring application thereon, wherein management via the subscription service includes subscribing each of the plurality of users and configuring the tenant and associated messages, and wherein the publication service is configured to communicate with the corresponding user device of the plurality of users and to communication to a plurality of publisher threads, for exchanging messages therebetween, based on the subscribing and the configuring, and wherein at least two corresponding user device of the plurality of users utilize a different operating system and platform from one another.

Abstract: An automated agent may communicate with a user via a chat channel to proactively alert the user of an L1 IT support issue. The L1 IT support issue may be determined based on monitoring indications of human-initiated activities maintained by a system of record, and may, prior to the automated agent's alert, be unknown to the user. In some instances, a natural language understanding (NLU) module may be used to identify an entity and intent from the indications of human-initiated activities, and the L1 IT support issue may be determined based on the determined entity and intent. After alerting the user of the L1 IT support issue, the automated agent may inform, via the chat channel, the user of a remediation step available to address the L1 IT support issue. Upon obtaining the user's permission, the automated agent may perform the remediation step to address the L1 IT support issue.

Abstract: An automated agent may communicate with a user via a chat channel to proactively alert the user of an L1 IT support issue. The L1 IT support issue may be determined based on monitoring indications of human-initiated activities maintained by a system of record, and may, prior to the automated agent's alert, be unknown to the user. In some instances, a natural language understanding (NLU) module may be used to identify an entity and intent from the indications of human-initiated activities, and the L1 IT support issue may be determined based on the determined entity and intent. After alerting the user of the Ll IT support issue, the automated agent may inform, via the chat channel, the user of a remediation step available to address the L1 IT support issue. Upon obtaining the user's permission, the automated agent may perform the remediation step to address the L1 IT support issue.

Abstract: A method for improving performance of a streaming media session between a plurality of communicating entities. Observation reports are collected from a plurality of monitoring entities. Each observation report includes information pertaining to events observed and recorded at a corresponding monitoring entity. A size of at least one window to be used for analyzing the observation reports is determined. The observation reports are analyzed using the at least one window of the determined size, to determine a correlation between the events across the observation reports. A problem encountered during the streaming media session is identified, based upon the correlation between the events. A notification is sent to at least one of the monitoring entities, based upon the problem. The notification is sent during the streaming media session.

Abstract: A multi-domain chatbot is used to service a message of a user. An automated agent of the multi-domain chatbot may act as an intermediary between the user and a plurality of domain-specific modules of the multi-domain chatbot. The automated agent may receive the message from the user, determine an intent of the message, and based on the intent, determine a group of the domain-specific modules that should be investigated. The automated agent may then investigate the group of domain-specific modules by sending the user message to and receiving responses from the domain-specific modules within the group. Based on the received responses, the automated agent may determine whether to provide, to the user, one of the domain-specific responses or a null response, in the event that none of the domain-specific responses is aligned with the intent of the message.

Abstract: Systems and methods include obtaining log data from a storage cluster associated with a cloud-based security system, wherein the log data includes transaction data associated with a plurality of users of the cloud-based security system, wherein the transaction data is for one or more of cloud security service transactions, application access via a Zero Trust Network Access (ZTNA) service, and user experience metrics, and wherein the cloud-based security system includes a plurality of tenants with the plurality of users each assigned thereto; analyzing the log data to determine a plurality of visualizations of the transaction data for a tenant; providing a User Interface (UI) to a mobile application with the plurality of visualizations; and providing a risk score summarizing an overall risk posture of the tenant in a single metric.

Abstract: Roughly described, a database accelerator is installed in a network having client systems which makes database queries to a particular IP address and port, and database servers which accept queries received at an IP address and port. The accelerator includes a cache, and is arranged to receive, through a network port, a database query made by a client system and directed to the particular IP address and port, return response data from the cache if available there, and if not, then forward the query through a network port to the database servers. Upon receipt of response data from the servers, the accelerator can retain it in its cache in addition to forwarding it back to the client. By installing the accelerator transparently in the network, no changes are required to either the client or server software in order to add query caching functionality to an existing client/server database arrangement.

Abstract: An automated service agent may be used to service issues discussed by users of a group communication channel. In the process of servicing the issue, the automated service agent may differentiate the roles of the users and identify a requester of the issue. In one scenario, the automated service agent may contact the requester in a private communication channel to collect more detailed or private information from the requester. The issue may be resolved in the private communication channel with the requester. Information may be posted back to the group communication channel to inform the other users as to the successful resolution of the issue and how the issue was resolved. While communicating with the requester in the private communication channel, messages may be posted to the group communication channel to keep the other users up to date on the progress of resolving the issue in the private communication channel.

Abstract: A method for improving performance of a streaming media session between a plurality of communicating entities. Observation reports are collected from a plurality of monitoring entities. Each observation report includes information pertaining to events observed and recorded at a corresponding monitoring entity. A size of at least one window to be used for analyzing the observation reports is determined. The observation reports are analyzed using the at least one window of the determined size, to determine a correlation between the events across the observation reports. A problem encountered during the streaming media session is identified, based upon the correlation between the events. A notification is sent to at least one of the monitoring entities, based upon the problem. The notification is sent during the streaming media session.

Abstract: An automated agent may communicate with a user via a chat channel to proactively alert the user of an L1 IT support issue. The L1 IT support issue may be determined based on monitoring indications of human-initiated activities maintained by a system of record, and may, prior to the automated agent's alert, be unknown to the user. In some instances, a natural language understanding (NLU) module may be used to identify an entity and intent from the indications of human-initiated activities, and the L1 IT support issue may be determined based on the determined entity and intent. After alerting the user of the L1 IT support issue, the automated agent may inform, via the chat channel, the user of a remediation step available to address the L1 IT support issue. Upon obtaining the user's permission, the automated agent may perform the remediation step to address the L1 IT support issue.

Abstract: Machine classifiers in accordance with embodiments of the invention capture long-term temporal dependencies in particular tasks, such as turn-based dialogues. Machine classifiers may be used to help users to perform tasks indicated by the user. When a user utterance is received, natural language processing techniques may be used to understand the user's intent. Templates may be determined based on the user's intent in the generation of responses to solicit information from the user. A variety of persona attributes may be determined for a user. The persona attributes may be determined based on the user's utterances and/or provided as metadata included with the user's utterances. A response persona may be used to generate responses to the user's utterances such that the generated responses match a tone appropriate to the task. A response persona may be used to generate templates to solicit additional information and/or generate responses appropriate to the task.