Abstract: In some implementations, the device may include initiating a stream producer that sends formatted data to a topic. In addition, the device may include ingesting, by a sink connector, the formatted data into an object storage service. The device may include implementing an event-driven serverless compute, where the event-driven serverless compute is triggered automatically when any new data is ingested to the object storage service, and where the event-driven serverless compute reads the JSON data, converts it to transformed data, and writes the transformed data to a distributed data store. Moreover, the device may include creating an ETL job, where the ETL job reads the data, further transforms the data, and writes it back into the distributed data store as ETL transformed data. Also, the device may include sending the ETL transformed data to an LLM API in batches to create inference results, where the batches are queued to manage the rate limits.

Abstract: In some implementations, the method may include receiving, by one or more agent applications, a query from a user. In addition, the method may include providing a dataframe to the one or more agent applications. The method may include appending a predetermined number of initial entries from the dataframe to a suffix of the query. Moreover, the method may include constructing a standardized prompt template, where the query is embedded within the standardized prompt template. Also, the method may include Channeling the prompt template to one or more Large Language Models (LLMs). Further, the method may include Utilizing a GPT API to generate a generated code snippet. In addition, the method may include Executing the generated code snippet to create a resulting output. The method may include Relaying the resulting output back to the user.

Abstract: In an example, an apparatus includes a first decoder circuit having a first voltage identification (VID) analog input and a first digital output. The apparatus also includes a precharge circuit having a digital input and a first analog output, the digital input coupled to the first digital output. The apparatus also includes a second decoder circuit having a second VID analog input, a precharge analog input and a second digital output, the precharge analog input coupled to the first digital output. The apparatus also includes a multiplexer having a multiplexer output and first and second multiplexer inputs, the first multiplexer input coupled to the first digital output, and the second multiplexer input coupled to the second digital output.

Abstract: The present disclosure relates to systems, methods, and computer-readable media for facilitating efficient retrieval of diagnostic information from a computing endpoint that experiences a failure condition. For example, systems described herein may detect or otherwise identify a failure condition associating with the computing endpoint operating in an erroneous or unpredictable matter. Systems described herein may involve carving out a portion of memory on the computing endpoint that is accessible to a host system (e.g., a CPU). Systems described herein may further provide a discoverable resource that enables a host system to identify and collect the diagnostic data in response to identifying a failure condition in an efficient manner and without requiring that the computing endpoint be capable of responding to data requests.

Abstract: Systems and methods are disclosed for generating interactive user interfaces for evaluating transactions of an organization. For example, a system can be configured to receive transactions for an organization and determine a first subset of the transactions during a trip at a first location that is different from a home location of a consumer. A respective transaction associated with a second location that occurred during the trip is identified. The respective transaction is assigned to the first subset of the of transactions for the trip. A second subset of the transactions of a spending type is determined. A parameter value associated with the spending type is identified. A parameter adjustment is determined. The system is configured to cause a display of a spending type user interface on a client device and receive a selection of a parameter component.

Abstract: Methods and apparatus to manage infrastructure as code (IaC) implementations are disclosed, A disclosed example system to manage a shared computing resource includes programmable circuitry; and machine readable instructions to cause the programmable circuitry to: determine an IaC type associated with a request corresponding to the shared computing resource; select a template from a plurality of IaC templates based on the IaC type; and service the request based on the template.

Abstract: Systems and processes herein integrate a crude separation unit, a steam cracker unit, a hydrocracker unit, an aromatics processing unit, and a pyrolysis gasoline hydrogenation unit for separating a whole crude oil or other wide boiling hydrocarbon mixtures for producing olefins and aromatics.

Abstract: Methods and apparatus to configure virtual machines (VMs) are disclosed. Am example system to manage a plurality of virtual machines of a shared computing resource, the system includes interface circuitry, programmable circuitry, and machine readable instructions to cause the programmable circuitry to at least one of scan or monitor the plurality of virtual machines, determine whether a master application corresponding to the virtual machines has accepted a minion application corresponding to a first one of the virtual machines, and in response to the determination that the master application has not accepted the minion application, cause the master application to accept the minion application.

Abstract: An example apparatus comprises memory, first instructions, and programmable circuitry to be programmed by the first instructions to associate a first portion of metadata with a first category, the metadata corresponding to a cloud resource of a cloud account, associate a second portion of the metadata with a second category, and determine a template based on the first portion being greater than the second portion, the template associated with the first category, the template including second instructions to define a target state to be enforced on the cloud account.

Abstract: Systems, apparatus, articles of manufacture, and methods are disclosed for converting enforcement policy information into provisioning template information by instantiating or executing machine-readable instructions to determine a type of a first placeholder of a provisioning template with a plurality of placeholders, copy enforcement policy data corresponding to the determined type of the first placeholder, fill the first placeholder of the provisioning template with the copied enforcement policy data, and save the provisioning template.

Abstract: A method of delivering a non-invasive neurostimulation using a Monotonic Amplitude Pulse Train is more charge-efficient than using conventional, uniform waveforms. Monotonic Amplitude Pulse Trains optimize the amplitudes of individual pulses in a train to reduce the total energy required to provide neural stimulation by as much as 50%.

Abstract: An autonomous cleaning robot (e.g., an autonomous vacuum) may clean an environment using a cleaning head that is self-actuated. The cleaning head includes an actuator assembly comprising an actuator configured to control rotation and vertical movement of a cleaning roller, a controller, and a cleaning roller having an elongated cylindrical length connected to the actuator assembly. The cleaning head also includes a computer processor connected to the actuator assembly and a non-transitory computer-readable storage medium that causes the computer processor to map the environment based on sensor data captured by the autonomous vacuum. The computer processor may determine an optimal height for the cleaning head based on the map and instruct the actuator assembly to adjust the height of the cleaning head.

Abstract: A computing device receives an ingest preview request to preview events to be stored by at least one indexer. Responsive to the ingest preview request, the computing device sends a subscription request to the forwarders. The forwarders receive the subscription request and intercept the events that are being sent to at least one of the indexers. The forwarders then clone matching events to the subscription request and responds to the computing device with the matching events. When the computing device receives the matching events, the computing device adds the matching events to a dispatch directory. The user interface is then populated with events in the dispatch directory.

Abstract: A lidar method and system for training and using a machine learning model are disclosed. An example method includes: obtaining a map of a background scene, the map including three-dimensional (3D) point cloud data; obtaining at least one point cloud representation of at least one foreground object, the at least one point cloud representation including 3D point cloud data, wherein one or more lidar sensors were used to generate the 3D point cloud data for the map and the at least one point cloud representation; generating a lidar scene by placing the at least one point cloud representation within the map; and training the machine learning model using the generated lidar scene. The model can be used to identify objects and control a vehicle.

Abstract: Operating a low-latency database analysis system with phrase translation may include obtaining a locale-specific phrase localization rule and a canonical phrase localization rule for a phrase, generating a locale-specific index and a locale-specific finite state machine for the locale using the localization definition data and a canonical finite state machine, generating a resolved-request by obtaining a locale-specific token representing locale-specific input data by traversing the locale-specific index, obtaining a canonical token associated with locale-specific token, obtaining a locale-specific phrase by traversing the locale-specific finite state machine, obtaining a canonical phrase corresponding to the locale-specific phrase, the canonical phrase including the canonical token, generate a data-query based on the canonical phrase, obtaining results data responsive to the data expressing the usage intent by executing a query corresponding to the data-query by an in-memory database of the low-latency datab

Abstract: The systems and methods disclosed herein receives artifacts generated using a first set of models within a multi-model superstructure. The multi-model superstructure includes a second set of models to test the first set of models. The multi-model superstructure dynamically routes the artifacts of the first set of models to one or more models of the second set of models by (i) determining a set of dimensions of the artifacts against which to evaluate the artifacts and (ii) identifying the models in the second set used to test the particular dimension. The second set of models then assesses each artifact against a set of assessment metrics. If an artifact fails to meet one or more assessment metrics, the second set of models generates actions to align the artifact with the set of assessment metrics.

Abstract: A storage device includes: a storage controller to receive one or more notifications corresponding to host data transferred from a host device to the storage device over a storage interface; and a response circuit connected to the storage controller, the response circuit to trigger a response to the host device, and including: a first counter to track the one or more notifications, the one or more notifications corresponding to an entirety of the host data such that each of the notifications corresponds to a portion of the host data; a second counter to track one or more acknowledgements received from the storage controller, the one or more acknowledgments corresponding to the one or more notifications such that each of the acknowledgments corresponds to a notification; and a response trigger to select one of the first counter and the second counter to trigger the response to the host device.

Abstract: Systems, apparatus, articles of manufacture, and methods are disclosed to tag cloud resources. An example apparatus includes interface circuitry, machine readable instructions, and programmable circuitry to at least one of instantiate or execute the machine readable instructions to obtain first accesses of a cloud resource, the first accesses defining a first usage pattern associated with the cloud resource, associate the cloud resource with a business environment based on the first accesses, compare the first usage pattern to a second usage pattern corresponding to historical accesses of reference cloud resources associated with the business environment, and when the first usage pattern is different from the second usage pattern, limit second accesses of the cloud resource based on the second usage pattern.

Abstract: Systems, apparatus, articles of manufacture, and methods are disclosed to generate and monitor security infrastructure. An example apparatus comprises programmable circuitry to at least one of instantiate or execute the machine readable instructions to: provision the security infrastructure based on a security infrastructure generation request; detect a global infrastructure template based on the security infrastructure generation request; and generate the security infrastructure based on the provisioned security infrastructure, the global infrastructure template, and an identified security infrastructure generation authorization, the security infrastructure generation authorization to indicate whether the generation of the security infrastructure is permitted.

Abstract: Techniques for generating and presenting search filter recommendations are disclosed. A system determines a composition of search filter tiles, including a relative number of machine learning-generated search filter tiles and non-machine learning-generated search filter tiles, based on recommendation criteria. The recommendation criteria include an amount of user search history data that exists. The system applies search filter recommendation policies to generate a set of search filter recommendations, including hard-coded search filters, search filter recommendations generated by a user-specific machine learning model, search filter recommendations generated by a machine learning model trained on data from multiple different users, and algorithm-based recommendations. The system generates different sets of search filter recommendations made up of different ratios of recommendations from different sources based on determining if search filter criteria are met.