Abstract: Systems and methods for automatic service discovery and inter-service communications in a peer-to-peer network are disclosed. A device connected to a peer-to-peer network multicasts information about services that are active on the device (e.g., local services) and accessible to other devices on the network. The device can receive, from other devices on the network, multicasted information about services that are active on the other devices (e.g., remote services). The device includes a registry for maintaining information about available local and remote services. Each device in the network can send queries to active services on other devices on the network and receive notifications from those remote services when the remote services identify relevant data (e.g., data that satisfies the query).

Abstract: Methods, systems, and computer program products are provided for a compute cluster comprising placement and load balancing (PLB) logic that receives data (e.g., state metadata) relating to a service (e.g., database service) executing on the compute cluster, from a resource manager executing on the compute cluster, via a first API associated with the resource manager. The PLB logic receives second data from the service via a second API and determines whether a PLB action is indicated based on one of the second data or a combination of the first data and the second data. When a PLB action is indicated, the PLB logic sends a command to the resource manager to execute the PLB action. The PLB logic also receives queries from clients external to the compute cluster and may spawn a child PLB logic to offload PLB operations, respond to queries, or perform software validation in the child.

Abstract: One aspect of this disclosure relates to a method for operating a quantum computing device. A request to execute a first n-qubit gate on a set of n target qubits is received. The first n-qubit gate is representable as an m-qubit diagonal gate conjugated by a Clifford gate, where m?n. A set of m interface qubits on which to perform the m-qubit diagonal gate are identified. A Clifford operation is executed on each interface qubit and its corresponding target qubits. The m-qubit diagonal gate is executed on the set of m interface qubits.

Abstract: A technique trains an interest-generating model that maps activity data to a set of candidate interest key phrases. The activity data describes prior action in interacting with computer-implemented services. Once trained, the interest-generating model is used to select and serve items. The technique for training reduces noise in its output results by first filtering the activity data using a filtering model, to produce filtered activity data. The technique then trains the interest-generating model to produce key phrases that are effective in both (1) expressing the interests underlying the filtered activity data and (2) retrieving items from a retrieval engine that are likely to consumed when served, given the identified interests. The technique accomplishes the above goals using reward-based training, which involves scoring candidate interest key phrases based on their effectiveness in retrieving relevant items, and fine-tuning the interest-generating model based on the scored candidate interest key phrases.

Abstract: Examples of the present disclosure describe systems and methods for implementing a confidential virtual machine generation system. In examples, read-only and read-write volumes are generated to store operating system binaries and user-generated content, respectively, on filesystems indexed using hash trees. The hash values of the roots of the two hash trees are stored in a location accessed as part of loading an operating system. The example system accesses the roots of the two hash trees to access the current state of read-only and read-write volumes and verify the states using a checksum. The verified states are merged to generate an operating system image associated image with the confidential virtual machine. Additionally, the system merges the namespaces of filesystems of read-only and read-write volumes into a single filesystem namespace concealing multiple volumes.

Abstract: An issue source scanning system scans a source of information about an issue to identify characteristics of code which indicate that the issue will manifest in code. A code scanning system scans code to match the identified characteristics against the code to determine whether the source code includes the identified characteristics. The code scanning system automatically generates a suggested operation to perform based upon a match between the identified characteristic and the code.

Abstract: A scheme of optimizing an operation on tensors for a processing device is provided. In this scheme, based on a size of a target tensor, a target window size is determined for a target operation associated with the target tensor to be processed on a processing device. At least one data block is determined based on the target window size and the target tensor. A set of elements included in the at least one data block cover at least the target tensor. For each data block, at least one predetermined task corresponding to the target operation and target window size are performed based on a position of each element of the data block in the target tensor. These predetermined tasks are precompiled to achieve the target operation. In this way, for various types of processing devices, a universal and efficient scheme may be implemented for tensors with different sizes.

Abstract: A computing system for artificial intelligence-automated review of agentic flows includes processing circuitry configured to implement an agentic flow in an artificial intelligence agent. The agent includes an assistant, a user proxy, and a critic. The user proxy receives information related to an event and instructions to process the event. In a first conversation between the assistant and the user proxy, the user proxy receives a recommendation for a tool and returns a tool response to the assistant after executing the tool. The assistant generates a tool response report and sends the tool response report to the user proxy. In a second conversation between the user proxy and the critic, the user proxy sends the tool response report to the critic. The critic reviews the tool response report for errors and returns any detected errors to the user proxy. The user proxy relays the detected errors to the assistant.

Abstract: Aspects of the present disclosure relate to assisting a requestor to manage activities a cross a plurality of diverse actors. In examples, a system is provided that includes at least one processor, and memory storing instructions that, when executed by the at least one processor, causes the system to perform a set of operations. The set of operations include receiving a request for a task to be completed, from the requestor, receiving actor context data, recording an assignment of the task to an actor, based on the actor context data, generating a communication to request that the actor complete the assigned task, and sending the communication to the actor.

Abstract: A data processing system implements detecting an occurrence of a trigger condition during an online meeting among a plurality of client devices associated with participants of the session, the occurrence of the trigger condition indicating that an ideation session for collecting ideas from the participants should be initiated; selecting an ideation session template based on meeting information associated with the online meeting, each ideation session template comprising a natural language prompt template that includes instructions to a language model to generate an agenda for a specific type of ideation session and to conduct the ideation session according to the agenda; constructing a prompt based on the natural language prompt template of the ideation session template; and providing the prompt as an input to the language model to cause the language model to generate the agenda for the ideation session and conduct the ideation session according to the agenda.

Abstract: The description relates to context-aware management of satellite images. One example can track a satellite relative to locations on earth, ground stations, and other satellites and identify parameters associated with the tracked satellite. The example can manage images captured by the satellite for individual locations based upon the identified parameters.

Abstract: In various examples there is a computer-implemented method, comprising ingesting into a memory a batch of media items. Duplicate media items in the batch are identified. For each duplicate media item, the duplicate media item is ranked with respect to duplicates of the media item. Filtering the duplicate media items is performed using the ranks of the duplicate media items to obtain filtered media items. Metadata of individual ones of the filtered media items is computed. Individual ones of the filtered media items are labelled with part of the metadata. For each filtered media item having metadata and a label, input into a Large Language Model, LLM, the media item, the label, the metadata and a request, and receive from the LLM a description of content depicted in the media item. A graph database of the filtered media items is created using the descriptions, the metadata, and the labels.

Abstract: A client system interacts with a multi-modal automated agent via an agent interface in an efficient manner. The client system captures instance of image data from a camera or user-interface (UI) system at a prescribed image-capturing rate while a question is being asked. The client system sends the captured instances of query data and accompanying instances of query data to the automated agent via the agent interface in a series of content-bearing messages, and, in return, receives one or more replies from the automated agent via the agent interface. Other system features provide for the reduction in resolution of the instances of image data by the client system, the selective forwarding of only updated parts of the instances of image data that to the agent interface, and the static or dynamic insertion of prompt information into a system prompt by the agent interface.

Abstract: Implementations for simplified and efficient error correction code schemes with multiple codewords are provided. One aspect includes a computing system comprising: processing circuitry and memory storing instructions that, during execution, causes the processing circuitry to: encode data comprising user data and metadata in a memory module comprising a plurality of dies by: logically partitioning the memory module into a plurality of partitions; on a first partition: storing a first portion of the user data on one or more memory segments of the first partition; and storing a first cyclic redundancy check (CRC) codeword and the metadata on a memory segment of the first partition different from the one or more memory segments of the first partition, wherein the first CRC codeword is generated based on the first portion of the user data and the metadata; and storing parity data on one of the plurality of dies.

Abstract: Embodiments of the disclosed technologies include receiving a first query including at least one first query term and configuring at least one prompt to cause a large language model to translate the at least one first query term into a set of functions that can be executed to obtain at least one second query term and generate and output a plan that is executable to create a modified version of the first query based on the at least one second query term. The plan is obtained by applying the large language model to the at least one prompt as configured. The plan is executed to determine the at least one second query term and create the modified version of the first query. The modified version of the first query is executed to provide, via the user interface, a response to the first query.

Abstract: This disclosure describes a framework for generating real-time audio translations of videos on a client device. Specifically, this disclosure describes a video dubbing system that utilizes a concurrent batch-processing architecture to provide real-time audio translations of videos on a client device. Additionally, in one or more implementations, the video dubbing system utilizes time-aware segmentation to prevent audio misalignment of the translated audio. As described below, the video dubbing system efficiently provides high-quality audio translations of videos that accurately align with the video content for the entire video, regardless of the video's length.

Abstract: A method comprises receiving a read instruction and determining a read address in computer memory corresponding to the read instruction, where the read address references a cell within a row of read-destructive computer memory. The method further comprises determining a discard state for data stored in the row according to a usage of the data, the discard state being positive for data to be read only once and negative for data to be read more than once. The data is read from the row and written back to the row if the discard state is negative. If the discard state is positive, then the method returns without writing the data back to the row.

Abstract: Example solutions for clustering data include: encoding a plurality of source records into a plurality of vectors, each source record containing source terms being encoded as one vector of the plurality of vectors; computing a similarity score for each unique pair of vectors of the plurality of vectors; constructing a similarity graph by: adding a node to the similarity graph for each vector; and adding an edge between each pair of nodes in which the similarity score for the associated pair of vectors exceeds a first similarity threshold; identifying a cluster of nodes within the similarity graph, the cluster of nodes representing a disconnected subgraph within the similarity graph; and generating a graphical representation of the one or more clusters on a display device.

Abstract: Systems and methods are provided for offloading a task from a central processor in a radio access network (RAN) server to one or more heterogeneous accelerators. For example, a task associated with one or more operational partitions (or a service application) associated with processing data traffic in the RAN is dynamically allocated for offloading from the central processor based on workload status information. One or more accelerators are dynamically allocated for executing the task, where the accelerators may be heterogeneous and my not comprise pre-programming for executing the task. The disclosed technology further enables generating specific application programs for execution on the respective heterogeneous accelerators based on a single set of program instructions.

Abstract: A system may include a first node having a first display device configured to display a first spatiotemporal pattern. A system may include a second node having a second display device configured to display a second spatiotemporal pattern. A system may include a camera. A system may include a means for selectively imaging one of the first spatiotemporal pattern and the second spatiotemporal pattern with the camera.

Abstract: A first device initiates a template state phase of executing an executable file comprising portable bytecode, including supplying a non-deterministic value request with a deterministic value. After completing the template state phase, the first device generates a memory snapshot for a set of memory pages used by the executable file. The first device then initiates an operational phase of executing the executable file, including generating a memory delta comprising each mutation to the memory pages since the snapshot point. The first device exports the memory delta to a second device. The second device initiates the template state phase of executing the executable file, including supplying a non-deterministic value request with the deterministic value. After completing the template state phase, the second device applies the memory delta to the memory pages used by the executable file and continues the execution of the executable file.

Abstract: Caching a memory descriptor across input/output (I/O) requests. Based at least on receiving a request from a buffer consumer to register a buffer, a memory descriptor describing a layout of a set of physical memory pages assigned to the buffer is created. Creating the memory descriptor includes assigning and locking the set of physical memory pages to the memory descriptor. For each I/O request of a plurality of I/O requests on the buffer, at least a subset of the memory descriptor for use by the I/O request is returned, and a reference count is used to track the I/O request as pending on the memory descriptor. Later, the memory descriptor is destroyed, including unlocking the set of physical memory pages, based at least on the reference count indicating that there is no pending I/O request on the memory descriptor.

Abstract: Technology disclosed herein includes a method of operating a communication service. The method includes hosting a conference call comprising bidirectional communications between at least a first endpoint and a second endpoint; receiving, in the context of the conference call, a request from the first endpoint for emergency service on behalf of a user at the second endpoint, wherein the request is initiated by user input received at a user interface on the first endpoint; and establishing a connection between the second endpoint and a public safety access point to obtain the emergency service for the user.

Abstract: Techniques are described herein that are capable of performing a security action based on a communication-based analysis. A security event, which is triggered by an operation performed by a user in an organization, is detected. A security analysis result is generated by determining whether a communication history of the user includes (1) a communication from the user that initiates an interaction with another user in the organization and/or a communication that is addressed specifically to the user from another user in the organization, (2) a communication from the user that references the operation, and/or (3) a communication that provides an explanation of a purpose of the operation that satisfies an explanation criterion. In response to the security event, a security action is performed with regard to the operation as a result of the security analysis result satisfying a security criterion.

Abstract: Example solutions read compressed data from a file in persistent storage, directly into an in-memory store without decompression. Some examples transcode the compression scheme used by the file into the compression scheme used by the in-memory store whereas, in other examples, the in-memory store is compatible with the compression scheme used by the file. In some examples that use transcoding, radix clustering is used to speed up compression dictionary transcoding. The radix clustering minimizes cache misses, thereby increasing the efficiency of memory access. These approaches significantly improve cold start times when responding to queries.

Abstract: A hardware retire circuit includes: one or more input queues, each queue corresponding to an input stream of tasks and being configured to store input task identifiers corresponding to tasks of the input stream; and processing logic configured to: receive a completed task event; determine whether a completed task queue identifier and a completed task identifier of the completed task event match an input task identifier of an input task at a head of an input queue having an input queue identifier corresponding to the completed task queue identifier; and in response to determining a match, pop the task at the head of the input queue and output a task retirement event corresponding to the input task.

Abstract: A lightweight encryption method is disclosed, designed to reduce computational resource demands on devices such as IoT devices and mobile phones. The method utilizes Shamir's three-pass protocol for key exchange, converting the encryption key into a signed digit number using an odd base. The message is broken into portions, with each portion encrypted by applying a sequence of non-commutative functions based on the signed digit representation of the key. This approach provides secure encryption while minimizing power and resource consumption.

Abstract: Innovations in machine learning (“ML”) networks used in video processing scenarios are described. For example, an ML refinement network can be used to refine video after a video decoder has reconstructed the video. Using the ML refinement network for post-processing can mitigate compression artifacts introduced during encoding and otherwise improve the quality of the reconstructed video. Or, as another example, an ML encoder network and ML decoder network can be used, in combination with a core video encoder and core video decoder, for hybrid compression and corresponding decompression. In the hybrid compression, the ML encoder network can transform video before encoding in order to boost rate-distortion performance of the core video encoder.

Abstract: Multi-layer anomaly detection identifies and issues alerts to focus limited resources on the most concerning activities detected in voluminous data. A multi-layer anomaly detector includes a clusterer, a forecaster, and a statistics generator to respectively generate a first, second, and third anomaly lists for input data indicating voluminous events relative to one or more domains, such as access to computing devices; access to real estate; or financial transactions. An ensemble detector may generate an ensemble anomaly list indicating a subset of the voluminous events based on the first, second, and third anomaly lists. The lists may indicate anomaly (e.g., security risk) scores. The ensemble anomaly list may combine the anomaly (e.g., risk) scores in the first, second, and third anomaly lists. An identifier may generate an alert for the subset of events, e.g., with relative security risk scores for the relevant individuals, entities, and/or events.

Abstract: The technology described herein is related to a hybrid neural network that divides operations of a neural network layer between a server and a client device. In an aspect, one or more liner operations of a neural network layer are performed on the client, while non-linear operations, such as an activation function, are performed on the server. In an aspect, the technology described herein maintains network security by encrypting portions of the client-side components. The encrypted portions may be learned values, which may also be described as learned parameters. In aspects, homomorphic encryption is used.

Abstract: Secure authentication using attestation tokens and inviolable quotes to validate request origins is performed by systems and platforms. An application programming interface (API) service is hosted via secure enclave of a computing platform container. Requests to a resource system for highly confidential/sensitive information persisted in a data storage, or for computational services, are made through the enclave, which is a source from which requests are trusted. An API call is made from the secure enclave to the resource system to establish a secure communication session based on a signed certificate for the secure enclave that is signed using an encrypted memory of the secure enclave. The API call also includes an attestation token used to validate the secure enclave as the source requesting the information or service via the API call. Confidential/sensitive information is provided to the secure enclave if the API call source is validated by the resource system.

Abstract: A cloud-computing system dynamically manages allocation of infrastructure nodes and compute nodes in an edge zone of the cloud-computing system. The edge zone begins with a first number of infrastructure nodes and a second number of compute nodes. As the edge zone executes customer workloads, the cloud-computing system determines whether the infrastructure nodes are over utilized or under utilized. When the infrastructure nodes are under utilized, the cloud-computing system re-assigns an infrastructure node to the compute nodes. When the infrastructure nodes are over utilized, the cloud-computing system re-assigns a compute node to the infrastructure nodes. In this way, the cloud-computing system dynamically maintains an optimal balance between resources devoted to supporting the edge zone (the infrastructure nodes) and resources devoted to executing customer workloads (the compute nodes).

Abstract: A display system includes a waveguide plate comprising an in-coupling grating, an expansion grating, and a sampling grating. The display system includes a projection system configured to direct input light toward the in-coupling grating. The in-coupling grating is configured to diffract the input light to propagate within the waveguide plate. The in-coupling grating is configured to (i) cause a display portion of the input light to propagate toward the expansion grating in a manner that avoids diffraction by the expansion grating and (ii) cause a sampling portion of the input light to propagate toward the sampling grating. The expansion grating is configured to (i) diffract the display portion of the input light to cause the display portion of the input light to continue to propagate within the waveguide plate. The sampling grating is configured to diffract the sampling portion of the input light outward from the waveguide plate.

Abstract: A method of designing a passive metasurface system within an environment includes receiving a three-dimensional model of the environment including one or more transmitter locations and one or more target locations, and determining one or more metasurface designs and placements to achieve a given objective. The method may also include computing a received signal strength at the one or more target locations based on the three-dimensional model of the environment, computing the received signal strength at the one or more target locations based on the three-dimensional model of the environment and the one or more metasurface designs and placements, and/or calculating ray traces and/or using machine learning to determine the received signal strength at the one or more target locations on the three-dimensional model of the environment and the one or more metasurface designs and placements.

Abstract: The present systems and methods enable a web browser to recommend or present features to a user based on the content of a web page. The features, which may include various actions that can be taken and different display configurations for viewing the content of the web page, may be specific to the type(s) of content that are present on the web page. Furthermore, such features may be presented to the user upon detection of a trigger that indicates an intent to arrange or configure a tab of the browser. Such features may be presented as transient graphical elements that illustrate the feature.

Abstract: A computing system for an automated artificial intelligence security operations center alert investigation includes processing circuitry configured to implement an automated artificial intelligence (AI) security operations center (SOC) investigation program. The AI SOC investigation program includes an automated SOC analyst (SA) investigation agent that receives a trigger to initiate an investigation for a security alert, retrieves alert evidence data including at least one entity related to the security alert, implements an investigation workflow to determine one or more entity investigation agents to investigate the entity, and implements the one or more entity investigation agents to investigate the entity.

Abstract: A data processing system implements receiving a user request to lay out multimodal design elements in a graphic design; applying a first generative model to categorize the design elements based on their content attributes in an initial layer and at least two pre-defined layers; applying a second generative model to sequentially process the layers until rendering a final composition image, by: processing the initial layer into an initial image, and for each of the pre-defined layers: encoding content attributes of each design element of the layer and a precedent image into combined embeddings, projecting the combined embeddings to match a hidden state dimension, predicting position and size attributes per design element of the layer based on the combined embeddings, and rendering a composition image based on the position and size attributes; and displaying the final composition image.

Abstract: A computing system for an adaptable automated artificial intelligence security operations center alert investigation implements an automated artificial intelligence (AI) security operations center (SOC) investigation program via an automated SOC analyst (SA) investigation agent. The SA investigation agent initiates an investigation for a security alert and retrieves alert data including an entity. An adaptability agent processes the alert data according to adaptability criteria to reach an adaptability verdict. If the adaptability verdict indicates the security alert is malicious or benign, then the SA investigation agent refrains from implementing an investigation workflow and outputs a final verdict. If the adaptability verdict is indeterminate, then the SA investigation agent implements the investigation workflow to determine entity investigation agents to investigate the entity.

Abstract: The description relates to devices that have removable parts, such as feet or pads. One example can include a housing containing electronic components and a receptacle positioned in the housing. A foot assembly can be positioned in the receptacle. The foot assembly can include a locking mechanism that mechanically blocks removal of the foot assembly from the receptacle unless acted upon by a magnetic field that rearranges the locking mechanism and unblocks removal of the foot assembly from the receptacle.

Abstract: Systems and methods are provided for implementing a hollow core fiber (“HCF”)-based optical network line system with multiple multiplexed optical supervisory channels. In examples, a first transponder of an optical line system (“OLS”) receives a first optical data signal at a first signal wavelength range, amplifies the first optical data signal into a second optical data signal, and generates two or more optical supervisory channel (“OSC”) signals at corresponding two or more OSC wavelengths separate from the first signal wavelength range. The first transponder injects the two or more OSC signals in the second optical data signal, and transmits the second optical data signal to a second transponder over an HCF communicatively coupling the two transponders over a fiber path distance. The two or more OSC signals are subsequently extracted from the second optical data signal, and analyzed to identify potential issues and/or measure optical properties in the OLS.

Abstract: A device may include an air handling unit (AHU) including: an inlet, and an outlet, wherein the inlet and outlet define an airflow channel of the AHU. A device may include a heat exchanger positioned in the airflow channel. A device may include a thermal energy storage (TES) device in thermal communication with the heat exchanger.

Abstract: This document relates to providing adaptive teleconferencing experiences using generative image models. For example, the disclosed implementations can employ inpainting and/or image-to-image restyling modes of a generative image model to generate images for a teleconference. The images can be generated based on prompts relating to the teleconference. Users can be superimposed on the generated images, thus giving the appearance that the users are present in an environment generated by the generative image model.

Abstract: Systems and methods are provided for a novel algorithm and system for automatically estimating the loss in an optical circuit switches (“OCS”) network and identifying components with unusually high loss. A computing system receives a first set of optical power data corresponding to optical power emitted from each of a plurality of optical transmitters that is communicatively coupled to input ports of an OCS, via optical fiber cables, while receiving a second set of optical power data measured by a photodetector of each of a plurality of optical receivers that is communicatively coupled to output ports of the OCS, via optical fiber cables. The computing system calculates a plurality of optical signal losses, based on analysis of the first and second sets of optical power data in view of expected ranges of optical power. The computing system generates a report, based on the plurality of optical signal losses.

Abstract: The description relates to automated binary code summarization. In one example, a binary code summarization tool receives binary code and combines the received binary code with natural language in a prompt for a large language model (LLM). The binary code summarization tool receives a semantic summarization from the LLM relating to the received binary code and evaluates the new semantic summarization for malicious functionality in the received binary code.

Abstract: A data processing system implements receiving, in a first silo, configuration parameters for performing federated training of the machine learning model using data stored in the plurality of second silos, generating a federated learning pipeline for automatically executing a plurality of tasks associated with the federated learning of the machine learning model based on the configuration parameters, causing each respective silo of the plurality of second silos to train the local instance of the machine learning model according to the federated learning pipeline, obtaining, at the first silo, the learnable parameters information associated with the local instance of the machine learning model of each silo of the plurality of second silos, and aggregating the learnable parameters information obtained from the plurality of second silos to obtain a primary instance of the machine learning model that has been fine-tuned according to the learnable parameters information.

Abstract: A computing system including one or more processing devices configured to execute a machine learning (ML) assistant interface. The processing devices receive a user input that specifies an interaction with an application interface. The processing devices receive application interface code of the application interface, and based on the application interface code, select an ontology schema from a plurality of ontology schemas. Based on the user input and the ontology schema, the processing devices select an intent schema from a plurality of intent schemas. The processing devices populate the ontology schema with interactable elements of the application interface identified in the application interface code, and, based on the populated ontology schema and the user input, populate the intent schema with one or more interface element interactions. At the application interface, the processing devices perform the interface element interactions at an interactable element specified in the populated ontology schema.

Abstract: Modeled conversions for connection networking are described. A method comprises generating a first input vector comprising a set of sequence features for a group of entities using a transformer layer of a machine learning model, generating a second input vector comprising a set of identity profile features for the group of entities using a generative artificial intelligence layer, receiving a third input vector comprising a set of conversion features, concatenating the first input vector, the second input vector, and the third input vector into a concatenated vector, normalizing the concatenated vector to form a normalized vector, projecting the normalized vector to form a projected vector, and generating a first metric based on the projected vector using a multi-gate mixture-of-experts (MMOE) layer of the ML model, the first metric comprising a value indicating whether there is a deterministic entity level conversion event for a group level conversion event.

Abstract: A high dynamic range (HDR) depth buffer is received at a remote computer. The HDR depth buffer is formed into a plurality of tiles. For each tile, a respective maximum and minimum value of the HDR depth buffer in a region greater than a width of the respective tile is determined. An initial pair of piecewise bilinear bounding functions for the HDR depth buffer is determined using the determined maximum and minimum depth values. For each tile, the initial pair of piecewise bilinear bounding functions is iteratively adjusted to move the respective minimum and maximum depth value of each tile closer to the HDR depth buffer, wherein no adjacent tile is adjusted in the same iteration. Using the adjusted pair of piecewise bilinear bounding functions, a low dynamic range (LDR) depth buffer and tile data are generated and encoded using a video encoder and a lossless compressor respectively.

Abstract: Techniques are described herein that are capable of providing a geographically diversified embedding-based guided response to a security alert. A security alert regarding an identified security incident that is associated with an entity is received. Sets of designated security incidents, which are similar to the identified security incident, may be selected from sets of historical security incidents associated with respective geographical regions based on embeddings of the identified security incident and the historical security incidents in the sets. The identified security incident is classified into selected classes using first model(s) associated with the respective geographical regions. Security actions are selected from a plurality of possible security actions using second model(s) associated with the respective geographical regions. A security recommendation regarding the security alert is generated.

Abstract: A system includes a stored counter value and a stored boot manifest including a manifest type flag. A manifest type of the boot manifest is determined based on the manifest type flag, a tenancy mode is determined based on a parity of the counter value, a first boot is executed if the manifest type is a first manifest type and the tenancy mode is a first tenancy mode, a second boot flow is executed if the manifest type is the first manifest type and the tenancy mode is a second tenancy mode, a third boot flow is executed if the manifest type is a second manifest type and the tenancy mode is the first tenancy mode, and a fourth boot flow is executed if the manifest type is the second manifest type and the tenancy mode is the second tenancy mode.