Abstract: In an example, an apparatus comprises a plurality of execution units comprising at least a first type of execution unit and a second type of execution unit and logic, at least partially including hardware logic, to expose embedded cast operations in at least one of a load instruction or a store instruction; determine a target precision level for the cast operations; and load the cast operations at the target precision level. Other embodiments are also disclosed and claimed.

Abstract: A method and system for detecting vulnerable wireless networks coexisting in a wireless environment of an organization are provided. The method includes receiving intercepted traffic, wherein the intercepted traffic is transmitted by at least one wireless device operable in an airspace of the wireless environment, wherein the intercepted traffic is transported using at least one type of wireless protocol; analyzing the received traffic to detect at least one active connection between a legitimate wireless device of the at least one wireless device and at least one unknown wireless device, wherein the legitimate wireless device is at least legitimately authorized to access a protected computing resource of the organization; and determining if the at least one detected active connection forms a vulnerable wireless network.

Abstract: A system and method for securing deployment of computing infrastructure resources. A method includes determining, based on a unique identifier of a computing infrastructure resource indicated in an alert, a source identifier of a resource component including the computing infrastructure resource, wherein the resource component includes at least one source file, wherein the source identifier of the resource component is a combination of characteristics of the resource component which collectively uniquely identify the resource component with respect to the directory in which the at least one source file of the resource component reside; contextually enriching the alert by adding the source identifier of the resource component including the computing infrastructure resource to the alert; and performing at least one remediation action with respect to the contextually enriching alert.

Abstract: In an example, an apparatus comprises at least one execution platform; and logic, at least partially including hardware logic, to receive a trained neural network model in a model optimizer and convert the trained neural network model to an optimized model comprising parameters that are fit to the at least one execution platform. Other embodiments are also disclosed and claimed.

Abstract: A computing system that determines employee and organizational compliance includes one or more databases that store organizational data and one or more processors to execute instructions to perform various operations.

Abstract: A system and method for securing deployment of computing infrastructure resources.

Abstract: In an example, an apparatus comprises a plurality of execution units comprising at least a first type of execution unit and a second type of execution unit and logic, at least partially including hardware logic, to expose embedded cast operations in at least one of a load instruction or a store instruction; determine a target precision level for the cast operations; and load the cast operations at the target precision level. Other embodiments are also disclosed and claimed.

Abstract: A mechanism is described for facilitating memory handling and data management in machine learning at autonomous machines. A method of embodiments, as described herein, includes detecting multiple tables associated with multiple neural networks at multiple autonomous machines, where each of the multiple tables include an index. The method may further include combining the multiple tables and multiple indexes associated with the multiple tables into a single table and a single index, respectively, where the single table is communicated to the multiple autonomous machines to allow simultaneous processing of one or more portions of the single table using one or more memory devices and one or more processors of one or more of the multiple autonomous machines.

Abstract: In an example, an apparatus comprises a plurality of execution units comprising and logic, at least partially including hardware logic, to receive a plurality of data inputs for training a neural network, wherein the data inputs comprise training data and weights inputs; represent the data inputs in a first form; and represent the weight inputs in a second form. Other embodiments are also disclosed and claimed.

Abstract: Systems and methods for identifying security control steps in software development pipelines. A method includes enumerating a plurality of steps in a software development infrastructure by analyzing software development pipeline data of the software development infrastructure, wherein each step includes a set of computer instructions for performing at least one task; identifying a plurality of step properties for each of the plurality of steps in step data of the step; and classifying at least one of the plurality of steps as a security control step based on the plurality of step properties identified for each of the plurality of steps, wherein each step classified as a security control step includes instructions for at least analyzing code in order to determine whether at least one security requirement is met.

Abstract: A method and system for detecting vulnerable wireless networks coexisting in a wireless environment of an organization are provided. The method includes receiving intercepted traffic, wherein the intercepted traffic is transmitted by at least one wireless device operable in an airspace of the wireless environment, wherein the intercepted traffic is transported using at least one type of wireless protocol; analyzing the received traffic to detect at least one active connection between a legitimate wireless device of the at least one wireless device and at least one unknown wireless device, wherein the legitimate wireless device is at least legitimately authorized to access a protected computing resource of the organization; and determining if the at least one detected active connection forms a vulnerable wireless network.

Abstract: A computing system that determines employee and organizational compliance includes one or more databases that store organizational data and one or more processors to execute instructions to perform various operations.

Abstract: A system and method for software containers attribution are provided. The method includes de-compiling a configuration file of a container image of a software container; identifying at least one candidate build file in the de-complied configuration file, wherein the at least one candidate build potentially formed the container image; determining if at least one matching condition is satisfied between each of the at least one candidate build file and the de-complied configuration file; associating the configuration file with each candidate build file satisfying the matching condition; and updating an inventory with the associated configuration file and the respective candidate build, wherein such association provides a direct mapping between the container image and the build files formed the container image.

Abstract: Systems and methods for alert management. A method includes analyzing alerts with respect to cybersecurity issues indicated in the alerts to identify at least one group of matching alerts. Each group of matching alerts includes alerts generated by multiple cybersecurity detection tools. A software component associations database is queried based on software components indicated in each of the groups of alerts. The software component associations database stores associations between configuration files of software containers and build files used to build the software containers. At least one group of duplicate alerts is identified among the groups of matching alerts based on associations returned by the software component associations database. The software component indicated by a first alert of each group of duplicate alerts is associated with the software component indicated by a second alert of the group of duplicate alerts. The alerts are managed based on the groups of duplicate alerts.

Abstract: In an example, an apparatus comprises logic, at least partially including hardware logic, to implement a lossy compression algorithm which utilizes a data transform and quantization process to compress data in a convolutional neural network (CNN) layer. Other embodiments are also disclosed and claimed.

Abstract: A mechanism is described for facilitating memory handling and data management in machine learning at autonomous machines. A method of embodiments, as described herein, includes detecting multiple tables associated with multiple neural networks at multiple autonomous machines, where each of the multiple tables include an index. The method may further include combining the multiple tables and multiple indexes associated with the multiple tables into a single table and a single index, respectively, where the single table is communicated to the multiple autonomous machines to allow simultaneous processing of one or more portions of the single table using one or more memory devices and one or more processors of one or more of the multiple autonomous machines.

Abstract: In an example, an apparatus comprises a plurality of execution units comprising and logic, at least partially including hardware logic, to receive a plurality of data inputs for training a neural network, wherein the data inputs comprise training data and weights inputs; represent the data inputs in a first form; and represent the weight inputs in a second form. Other embodiments are also disclosed and claimed.

Abstract: In an example, an apparatus comprises logic, at least partially including hardware logic, to save one or more outputs of a deep learning neural network in a storage system of an autonomous vehicle and upload the one or more outputs to a remote server. Other embodiments are also disclosed and claimed.

Abstract: Systems and methods for automating alert remediation. A method includes extracting entity-identifying values from cybersecurity event data included in alerts generated for a software infrastructure. Queries are generated based on the entity-identifying values. An entity graph is queried. The entity graph has nodes representing respective entities. The entities include software components of the software infrastructure and event logic components of cybersecurity event logic deployed with respect to the software infrastructure. Paths are identified in the entity graph based on the query results. Each identified path is between one of the software components and one of the event logic components. One or more root cause entities are identified based on the identified paths. A fix action plan is generated for the alerts based on the root cause entities.

Abstract: A system and method for remediating cybersecurity events. A method includes querying a knowledge base using a query generated based on semantic concepts and entity-identifying values extracted from cybersecurity event data, wherein the knowledge base includes an entity graph having nodes representing respective entities, wherein the entities include software components of software infrastructure and event logic components of cybersecurity event logic deployed with respect to the software infrastructure; identifying at least one path in the entity graph based on results of the query, wherein each identified path is between one of the software components and one of the event logic components; identifying at least one root cause entity based on the identified at least one path; and performing at least one remedial action based on the identified at least one root cause entity.