Abstract: Techniques for implementing and utilizing capacity cluster resource reservations are described. A managed compute service receives a user's request to identify a capacity block for use in launching compute instances. A schedule with pre-computed blocks, each corresponding to an amount of instances and an amount of time, is used to identify a block satisfying the request's criteria. The user can later obtain the capacity block and launch instances into the reservation during its time window, where placement rules associated with the reservation ensure the instances are hosted in locations enabling low-latency intercommunications.

Abstract: A configuration hardening system is disclosed. A first phase collects and stores configuration structure information and threat intelligence information in a knowledge graph. A second phase receives configuration information of a container orchestration system. The configuration information is scanned for misconfigurations. Resolutions, such as patches, to the misconfigurations are determined using the knowledge graph and a human in the loop mechanism. The resolutions are applied and, when necessary, a zero trust system is provided with sufficient data to monitor the vulnerabilities or weaknesses associated with the misconfigurations. When the resolutions are ready, the resolutions, which may include updated configuration information, are implemented in the container orchestration system.

Abstract: Techniques and systems are provided for processing one or more frames or images. For instance, a process for determining exposure for one or more frames includes obtaining a motion map for one or more frames. The process includes determining, based on the motion map, motion associated with the one or more frames of a scene. The motion corresponds to movement of one or more objects in the scene relative to a camera used to capture the one or more frames. The process includes determining, based on the determined motion, a number of frames and an exposure for capturing the number of frames. The process further includes sending a request to capture the number of frames using the determined exposure duration.

Abstract: One example method includes receiving a data file at a large language model (LLM). Arbitrary tags that include labels that are attachable to the data file and prompts are also received. The prompts are paired with the arbitrary tags to form arbitrary tag-prompt pairs and include information that is used by the LLM to find the paired arbitrary tag. The LLM determines a selected subset of the arbitrary tags that apply to the data file. A trust module receives the selected subset of the arbitrary tags that apply to the data file and data access policies that specify access rules for the data file. A conditional access decision is determined that specifies whether access should be given to the data file.

Abstract: This disclosure provides systems, methods, and devices for image signal processing that support efficient cache usage in an image processing system. In a first aspect, a method of image processing includes storing, by an image processor, a first portion of a first stripe of a first frame in a cache, the first portion of the first stripe overlapping a second portion of a second stripe of the first frame, reading, by the image processor, a third portion of the second stripe from a memory, reading, by the image processor, the first portion of the first stripe from the cache, and processing, by the image processor, the second stripe using the first portion of the first stripe and the third portion of the second stripe. Other aspects and features are also claimed and described.

Abstract: Approximating state vector sparsity for quantum computing operations. A recurrent model is trained to predict sparsity indexes (sparsity vector) for a quantum circuit and its subcircuits. The computational requirements of a knitting operation can be estimated or predicted more efficiently using the predicted sparsity indexes. Cutting operations and decisions can also be based on the predicted sparsity indexes.

Abstract: One example method includes providing quantum circuit information, concerning a quantum circuit, to a first machine learning model that has been trained with first training data generated as a result of execution of a group of quantum circuits on a simulation engine, providing the quantum circuit information to a second machine learning model that has been trained with second training data generated as a result of execution of the group of quantum circuits on quantum hardware, estimating, by the first machine learning model and the second machine learning model, respective values of a quantum circuit execution parameter of the quantum circuit, comparing the estimates of the quantum circuit execution parameter, and based on the comparing, orchestrating the quantum circuit to either the simulation engine, or the quantum hardware, for execution.

Abstract: Warm up or look up tables are generated for training reinforcement learning models. Rather than wait for a metric, such as execution times, that are required to determine a reward, previously generated warm up tables that include a probability distribution of the metric are used such that the reward can be determined without waiting for a workload to finish executing. The ability to determine the reward more quickly can shorten training times and help compensate for the exploration/exploitation trade-off experienced in training reinforcement learning models. The warm up table considers averages of a relevant metric and standard deviation of different workload instance-device associations such that the metric can be sampled from the probability distribution.

Abstract: Host systems for resuming operation of a virtual compute instance may be identified that support features enabled for the virtual compute instance. Virtual compute instance features may be enabled at runtime prior to a virtual compute instance being stopped. When a virtual compute instance is started again, these features may be used to identify a host system that supports at least these features so that when the virtual compute instance resumes operation on the identified host, the features can be enabled.

Abstract: The present disclosure generally relates to image processing. For example, aspects of the present disclosure include systems and techniques for performing spatial and temporal processing of image data. Certain aspects provide an apparatus for processing frame data. The apparatus generally includes a memory, and one or more processors coupled to the memory, the one or more processors configured to: perform a first noise reduction operation based on first frame data via a machine learning component to generate first processed frame data; generate first feedback data based on the first processed frame data; and perform, via the machine learning component, a second noise reduction operation based on second frame data and the first feedback data.

Abstract: Techniques are described for enabling users of a cloud provider network to request the conditional termination of computing resources based on a forecasted availability of replacement capacity at a specified time or range of time in the future. A cloud provider network provides an application programming interface that can be used to make such requests, where the computing resources are hosted by the cloud provider network as part of a capacity pool shared by tenants of the cloud provider network. This type of request can be generated, for example, by a user desiring to terminate the use of some number of unproductive computing resources only if the user can be reasonably assured by the cloud provider network that capacity will be available at a future time when the user will likely need the capacity again.

Abstract: Techniques and systems are provided for processing one or more frames or images. For instance, a process for determining exposure for one or more frames includes obtaining a motion map for one or more frames. The process includes determining, based on the motion map, motion associated with the one or more frames of a scene. The motion corresponds to movement of one or more objects in the scene relative to a camera used to capture the one or more frames. The process includes determining, based on the determined motion, a number of frames and an exposure for capturing the number of frames. The process further includes sending a request to capture the number of frames using the determined exposure duration.

Abstract: This disclosure is directed to, in part, providing customers with an enhanced shopping experience during a visit to a physical store location. The enhanced shopping experience may include providing the customer with customized delivery of product information. The product information may include demonstrations of product use, samples of products, recommendations of related products or areas of interest to a customer, etc. To provide the customized information, the customer may register to be identified while at the physical store location. The physical store location may include sensors that identify a location of the registered customer. A presentation module may then push relevant content to a device located near the customer, possibly in response to a request from the customer and/or a location of the customer.

Abstract: Active gameplay of a video game on a computer gaming device is overseen by a platform-level in-game recording companion that executes separately from any of a plurality of different video games. During active gameplay of the video game, the active gameplay is continuously and automatically buffered to a temporary storage buffer. During active gameplay the computer gaming device receives a command to save a segment of the active gameplay for subsequent viewing. While displaying gameplay of the currently-executing video game, an interface for the platform-level in-game recording companion is displayed. The segment of the active gameplay is saved from the temporary storage buffer to a library of the platform-level in-game recording companion.

Abstract: Representative embodiments disclose a consistent, low latency, reliable storage system that uses quorum logic. An odd number of storage nodes are selected to store data for a client application. The odd number allows a quorum to be determined. When data is written to the storage nodes, success is identified if the data is successfully written to a majority of the storage nodes. Similarly, when a read is performed, success is identified if the majority of the storage nodes return the same value written in the same write operation. This is determined by matching a value and a version number for each node. Additional data is written to the storage nodes along with the values to allow the system to identify and repair inconsistencies in the data. In some embodiments, both the current data and prior data are stored to aid in repairing inconsistent data.

Abstract: Active gameplay of a video game on a computer gaming device is overseen by a platform-level in-game recording companion that executes separately from any of a plurality of different video games. During active gameplay of the video game, the active gameplay is continuously and automatically buffered to a temporary storage buffer. During active gameplay the computer gaming device receives a command to save a segment of the active gameplay for subsequent viewing. While displaying gameplay of the currently-executing video game, an interface for the platform-level in-game recording companion is displayed. The segment of the active gameplay is saved from the temporary storage buffer to a library of the platform-level in-game recording companion.

Abstract: Active gameplay of a video game on a computer gaming device is overseen by a platform-level in-game recording companion that executes separately from any of a plurality of different video games. During active gameplay of the video game, the active gameplay is continuously and automatically buffered to a temporary storage buffer. During active gameplay the computer gaming device receives a command to save a segment of the active gameplay for subsequent viewing. Without interrupting the active gameplay, the segment of the active gameplay is saved from the temporary storage buffer to a library of the platform-level in-game recording companion.

Abstract: Interfaces for a continuation-based runtime. Some embodiments described herein are directed to a framework using continuation based runtime interface that pertain to an infrastructure for enabling the creation of a wide variety of continuation-based programs that perform a wide-array of tasks. The infrastructure provides a foundation for building continuation-based, declarative applications of various scale and complexity.

Abstract: Representative embodiments disclose a consistent, low latency, reliable storage system that uses quorum logic. An odd number of storage nodes are selected to store data for a client application. The odd number allows a quorum to be determined. When data is written to the storage nodes, success is identified if the data is successfully written to a majority of the storage nodes. Similarly, when a read is performed, success is identified if the majority of the storage nodes return the same value written in the same write operation. This is determined by matching a value and a version number for each node. Additional data is written to the storage nodes along with the values to allow the system to identify and repair inconsistencies in the data. In some embodiments, both the current data and prior data are stored to aid in repairing inconsistent data.

Abstract: Various embodiments relating to providing video game instant replays are disclosed. In one embodiment, a currently playing video game is overseen by a platform-level instant replay companion that executes separately from any of a plurality of different video games. A most recently played portion of rendered gameplay from the currently playing video game is automatically and continuously recorded with the platform-level instant replay companion. A recorded gameplay segment from the most recently played portion of rendered gameplay is displayed with the platform-level instant replay companion.