Abstract: System and methods for generating, validating, and augmenting question-answer pairs using generative AI are provided. An online interaction server accesses a set of digital content available at a set of designated network locations. The online interaction server further trains a pre-trained large language model (LLM) using the set of digital content to obtain a customized LLM. The online interaction server generates a set of question-answer pairs based on the set of digital content using the customized LLM and validates the set of question-answer pairs by determining if an answer in a question-answer pair is derived from the set of digital content. The online interaction server also selects a digital asset to augment an answer in a validated question-answer pair based on a semantic similarity between the validated question-answer pair and the digital asset.

Abstract: A content generator system receives a request to generate content for a target entity, and one or more keywords. The content generator system retrieves, for the target entity, a current stage identifier linking the target entity to a current stage within a multi-stage objective. The content generator system generates an input vector including the current stage identifier, a target stage identifier, a token embedding comprising the one or more keywords, and a position embedding for each of the one or more keywords, the target stage identifier associated with a target stage within the multi-stage objective different from the current stage. The content generator system generates output text content for the target entity by applying a generative transformer network to the input vector. The content generator system transmits the output text content to a computing device associated with the target entity.

Abstract: The disclosed technology includes a hemostasis valve assembly comprising an elongate body with a first valve disposed near the proximal end and a second valve disposed near the distal end and spaced apart from the first valve. The first valve can allow a member to extend through the first valve and the second valve can allow the member to extend through the second valve. The elongate body can define a cavity comprising a sloped portion including a first distance between an inner surface of the elongate body and the longitudinal axis near the distal end that is greater than a distance between the inner surface and the longitudinal axis near the proximal end such that a gas is directed along the sloped portion to accumulate at an accumulation region in the cavity near the distal end when a member extends through the first valve.

Abstract: A method for identifying a transition of a signal from a defined state to an undefined state when simulating a device includes. Storing a set of breakpoints, each breakpoint associated with a state of the device and identifying a set of signals from the device. A simulation of the device is executed using simulation, and a current state of the device is determined from values of one or more storage elements of the device. A breakpoint list including one or more breakpoints is selected based on the current state of the device. The set of signals from the device identified by the one or more breakpoints included in the breakpoint list is monitored.

Abstract: In some embodiments, techniques for identifying email events generated by bot activity are provided. For example, a process may involve applying bot detection patterns to identify bot activity among email response events.

Abstract: A topic mapping system generates customized mapping schemas for multiple topic sets. The topic mapping system generates document clusters that represent groups of digital documents. The topic mapping system also generates, for each topic set, a document-topic mapping data object (“DTM data object”) that describes a customized mapping schema of the document clusters to labels in the topic set. The topic mapping system identifies customized groups of documents for responding to multiple requests that have a particular keyword. For each request, the topic mapping system identifies a particular topic set and DTM data object associated with a computing system that provided the request. Based on the keyword, the topic mapping system identifies documents that are categorized according to the customized mapping schema in the DTM data object. The topic mapping system can provide customized groups of documents to respective computing systems that provided the multiple requests.

Abstract: An automated security assessment service of a service provider network may identify, and notify a customer of, misconfigured VM instances that can be access (e.g., via the Internet). A scanner tool may call an automated reasoning service to identify any VM instances of a customer that can be accessed, and may receive information from the automated reasoning service that is usable to exchange packets with those identified instances. The scanner tool can use the information to send requests to the identified instances. After receiving responses from the identified instances, the scanner tool can store, in storage of a network-based storage service, and in association with a customer account of the customer, encrypted data about the results of the scan (e.g., any VM instances that are vulnerable to attackers), and this encrypted data is thereby accessible to the customer with proper decrypt permissions.

Abstract: Embodiments include dynamic control of coverage by a verification testbench. Aspects include obtaining a design under test to be verified by the verification testbench and obtaining one or more testcases for execution by the verification testbench on the design under test. Aspects also include obtaining a plurality of triggers corresponding to the design under test, wherein each of the plurality of triggers includes an activation condition, a deactivation condition and a coverage. Aspects further include simulating, by the verification testbench, execution of the one or more testcases by the design under test. Based on detecting the activation condition of one of the plurality of triggers, aspects also include recording, in a coverage database, data specified in the coverage corresponding the one of the plurality of triggers until the deactivation condition is detected.

Abstract: Embodiments include dynamic control of coverage by a verification testbench. Aspects include obtaining a design under test to be verified by the verification testbench and obtaining one or more testcases for execution by the verification testbench on the design under test. Aspects also include obtaining a plurality of triggers corresponding to the design under test, wherein each of the plurality of triggers includes an activation condition, a deactivation condition and a coverage. Aspects further include simulating, by the verification testbench, execution of the one or more testcases by the design under test. Based on detecting the activation condition of one of the plurality of triggers, aspects also include recording, in a coverage database, data specified in the coverage corresponding the one of the plurality of triggers until the deactivation condition is detected.

Abstract: A content generator system receives a request to generate content for a target entity, and one or more keywords. The content generator system retrieves, for the target entity, a current stage identifier linking the target entity to a current stage within a multi-stage objective. The content generator system generates an input vector including the current stage identifier, a target stage identifier, a token embedding comprising the one or more keywords, and a position embedding for each of the one or more keywords, the target stage identifier associated with a target stage within the multi-stage objective different from the current stage. The content generator system generates output text content for the target entity by applying a generative transformer network to the input vector. The content generator system transmits the output text content to a computing device associated with the target entity.

Abstract: Certain embodiments involve using machine-learning methods to generate a recommendation for sequential content items. A method involves accessing a content item associated with an interaction stage in an online environment. A stage graph, which includes a ratio of interactions, of the content item is generated. An additional content item that includes additional stage-transition content is identified. A sequencing function outcome indicating a portion of the ratio of interactions is determined. A transition probability of receiving an interaction with stage-transition content and an additional interaction with the additional stage-transition content is calculated. A content provider system is caused to provide a recipient device with interactive content that includes the additional content item.

Abstract: In some embodiments, a non-transitory processor-readable medium stores code representing instructions configured to cause a processor to receive, from an access switch, a first signal including forwarding state information associated with a first peripheral processing device from a set of peripheral processing devices. The code can further represent instructions configured to cause the processor to receive, from the first peripheral processing device, a second signal including a data packet. The code can further represent instructions configured to cause the processor to send, to a replication engine associated with the set of peripheral processing devices, a third signal such that the replication engine (1) defines a copy of the data packet, which is included within the third signal, and (2) sends, to a second peripheral processing device from the set of peripheral processing devices, a fourth signal including the copy of the data packet.

Abstract: Wireless access points detect neighboring wireless access points in different subnets. Upon connecting with a wireless client, a wireless access point determines predictive roaming information for the wireless client. Predictive roaming information identifies the wireless client; its home network subnet; and includes connection information associated with the wireless client. The wireless access point forwards the predictive roaming information associated with a wireless client to neighboring wireless access points while the wireless client is still connected with the wireless access point. Neighboring wireless access points store received predictive roaming information. Upon connecting with a wireless client, a neighboring wireless access point determines if the wireless client matches the stored predictive roaming information.

Abstract: Airtime usage may be used as a factor in controlling network traffic flow to and from client devices via a wireless network interface. Received packets or other data are assigned to a quality of service profile. Additionally, a cost value for communicating the received data is determined at least in part based on an actual or estimated airtime usage for the received packet. The cost value is used to allocate wireless network airtime to data. The allocation of wireless network airtime may be varied dynamically based on operating conditions. The cost value may be based on factors including the airtime used to communicate data; whether the data is a retransmission; and wireless network overhead. The cost value of data may also be different depending on whether the data is being sent from a client device or to a client device.

Abstract: A network device of a subnet determines predictive roaming information for a wireless client. Predictive roaming information can identify the wireless client and a home network subnet of the wireless client. The network device provides predictive roaming information associated with a wireless client to neighboring subnets. Neighboring subnets store received predictive roaming information, and use the predictive roaming information if the wireless client roams to them.

Abstract: Airtime usage may be used as a factor in controlling network traffic flow to and from client devices via a wireless network interface. Received packets or other data are assigned to a quality of service profile. Additionally, a cost value for communicating the received data is determined at least in part based on an actual or estimated airtime usage for the received packet. The cost value is used to allocate wireless network airtime to data. The allocation of wireless network airtime may be varied dynamically based on operating conditions. The cost value may be based on factors including the airtime used to communicate data; whether the data is a retransmission; and wireless network overhead. The cost value of data may also be different depending on whether the data is being sent from a client device or to a client device.

Abstract: Wireless access points detect neighboring wireless access points in different subnets. Upon connecting with a wireless client, a wireless access point determines predictive roaming information for the wireless client. Predictive roaming information identifies the wireless client; its home network subnet; and includes connection information associated with the wireless client. The wireless access point forwards the predictive roaming information associated with a wireless client to neighboring wireless access points while the wireless client is still connected with the wireless access point. Neighboring wireless access points store received predictive roaming information. Upon connecting with a wireless client, a neighboring wireless access point determines if the wireless client matches the stored predictive roaming information.

Abstract: Airtime usage may be used as a factor in controlling network traffic flow to and from client devices via a wireless network interface. Received packets or other data are assigned to a quality of service profile. Additionally, a cost value for communicating the received data is determined at least in part based on an actual or estimated airtime usage for the received packet. The cost value is used to allocate wireless network airtime to data. The allocation of wireless network airtime may be varied dynamically based on operating conditions. The cost value may be based on factors including the airtime used to communicate data; whether the data is a retransmission; and wireless network overhead. The cost value of data may also be different depending on whether the data is being sent from a client device or to a client device.

Abstract: Wireless access points detect neighboring wireless access points in different subnets. Upon connecting with a wireless client, a wireless access point determines predictive roaming information for the wireless client. Predictive roaming information identifies the wireless client; its home network subnet; and includes connection information associated with the wireless client. The wireless access point forwards the predictive roaming information associated with a wireless client to neighboring wireless access points while the wireless client is still connected with the wireless access point. Neighboring wireless access points store received predictive roaming information. Upon connecting with a wireless client, a neighboring wireless access point determines if the wireless client matches the stored predictive roaming information.

Abstract: A network device of a subnet determines predictive roaming information for a wireless client. Predictive roaming information can identify the wireless client and a home network subnet of the wireless client. The network device provides predictive roaming information associated with a wireless client to neighboring subnets. Neighboring subnets store received predictive roaming information, and use the predictive roaming information if the wireless client roams to them.