A method for operating a voice trigger is provided. In some implementations, the method is performed at an electronic device including one or more processors and memory storing instructions for execution by the one or more processors. The method includes receiving a sound input. The sound input may correspond to a spoken word or phrase, or a portion thereof. The method includes determining whether at least a portion of the sound input corresponds to a predetermined type of sound, such as a human voice. The method includes, upon a determination that at least a portion of the sound input corresponds to the predetermined type, determining whether the sound input includes predetermined content, such as a predetermined trigger word or phrase. The method also includes, upon a determination that the sound input includes the predetermined content, initiating a speech-based service, such as a voice-based digital assistant.

Voice trigger for a digital assistant

Function-as-a-Service (FaaS) platforms and "serverless" cloud computing are becoming increasingly popular. Current FaaS offerings are targeted at stateless functions that do minimal I/O and communication. We argue that the benefits of serverless computing can be extended to a broader range of applications and algorithms. We present the design and implementation of Cloudburst, a stateful FaaS platform that provides familiar Python programming with low-latency mutable state and communication, while maintaining the autoscaling benefits of serverless computing. Cloudburst accomplishes this by leveraging Anna, an autoscaling key-value store, for state sharing and overlay routing combined with mutable caches co-located with function executors for data locality. Performant cache consistency emerges as a key challenge in this architecture. To this end, Cloudburst provides a combination of lattice-encapsulated state and new definitions and protocols for distributed session consistency. Empirical results on benchmarks and diverse applications show that Cloudburst makes stateful functions practical, reducing the state-management overheads of current FaaS platforms by orders of magnitude while also improving the state of the art in serverless consistency.

Cloudburst: Stateful Functions-as-a-Service

A micro-virtualization architecture deploys a threat-aware microvisor as a module of a virtualization system configured to facilitate real-time security analysis, including exploit detection and threat intelligence, of operating system processes executing in a memory of a node in a network environment. The micro-virtualization architecture organizes the memory as a user space and kernel space, wherein the microvisor executes in the kernel space of the architecture, while the operating system processes, an operating system kernel, a virtual machine monitor (VMM) and its spawned virtual machines (VMs) execute in the user space. Notably, the microvisor executes at the highest privilege level of a central processing unit of the node to virtualize access to kernel resources. The operating system kernel executes under control of the microvisor at a privilege level lower than a highest privilege level of the microvisor. The VMM and its spawned VMs execute at the highest privilege level of the microvisor.

Micro-virtualization architecture for threat-aware microvisor deployment in a node of a network environment

Disclosed are a display apparatus and a method of controlling the display apparatus. The display apparatus includes: a signal receiver configured to receive a broadcasting signal; a display configured to display an image based on the received broadcasting signal; a sound receiver configured to receive a sound spoken by a user; a first sound recognizer configured to be supplied with power when the display apparatus is in a standby mode, and determine whether the received sound is a reserved word candidate having a high probability of corresponding to a reserved word; a second sound recognizer configured to be supplied with power when the received sound is determined as the reserved word candidate and to determine whether the received sound is the reserved word; and a controller configured to control the preset operation to be performed when the received sound is determined as the reserved word.

Electronic apparatus and control method thereof

A request to store, in first data store associated with a customer of a computing resource service provider, a software image is received, the request including a set of layers of the software image to be stored. As a result of successful authentication of the request, based at least in part on a security token included with the request, a subset of layers of the software image that have not previously been stored in the first data store are determined, based at least in part on first metadata obtained from a second data store, the subset of layers in the first data store are stored, second metadata about the subset of layers are stored in the second data store, and the software image is caused to be launched in a software container of an instance based at least in part on the subset of layers.

Software container registry service

A service manages a plurality of virtual machine instances for low latency execution of user codes. The service can provide the capability to execute user code in response to events triggered on an auxiliary service to provide implicit and automatic rate matching and scaling between events being triggered on the auxiliary service and the corresponding execution of user code on various virtual machine instances. An auxiliary service may be configured as an event triggering service to detect events and generate event messages for execution of the user codes. The service can request, receive, or poll for event messages directly from the auxiliary service or via an intermediary message service. Event messages can be rapidly converted to requests to execute user code on the service. The time from processing the event message to initiating a request to begin code execution is less than a predetermined duration, for example, 100 ms.

Programmatic event detection and message generation for requests to execute program code

A system for providing security mechanisms for secure execution of program code is described. The system may be configured to maintain a plurality of virtual machine instances. The system may be further configured to receive a request to execute a program code and allocate computing resources for executing the program code on one of the virtual machine instances. One mechanism involves executing program code according to a user-specified security policy. Another mechanism involves executing program code that may be configured to communicate or interface with an auxiliary service. Another mechanism involves splitting and executing program code in a plurality of portions, where some portions of the program code are executed in association with a first level of trust and some portions of the program code are executed with different levels of trust.

Security protocols for low latency execution of program code

A service manages a plurality of virtual machine instances for low latency execution of user codes. The service can provide the capability to execute user code in response to events triggered on an auxillary service to provide implicit and automatic rate matching and scaling between events being triggered on the auxiliary service and the corresponding execution of user code on various virtual machine instances. An auxiliary service may be configured as an event triggering service to detect events and generate event messages for execution of the user codes. The service can request, receive, or poll for event messages directly from the auxiliary service or via an intermediary message service. Event messages can be rapidly converted to requests to execute user code on the service. The time from processing the event message to initiating a request to begin code execution is less than a predetermined duration, for example, 100 ms.

Processing event messages for user requests to execute program code

Systems and methods are described for managing asynchronous code executions in an on-demand code execution system or other distributed code execution environment, in which multiple execution environments, such as virtual machine instances, can be used to enable rapid execution of user-submitted code. When asynchronous executions occur, a first execution may call a second execution, but not immediately need the second execution to complete. To efficiently allocate computing resources, this disclosure enables the second execution to be scheduled accordingly to a state of the on-demand code execution system, while still ensuring the second execution completes prior to the time required by the first execution. Scheduling of executions can, for example, enable more efficient load balancing on the on-demand code execution system.

Asynchronous task management in an on-demand network code execution environment

A service manages a plurality of virtual machine instances for low latency execution of user codes. The plurality of virtual machine instances can be configured based on a predetermined set of configurations. One or more containers may be created within the virtual machine instances. In response to a request to execute user code, the service identifies a pre-configured virtual machine instance suitable for executing the user code. The service can allocate the identified virtual machine instance to the user, create a new container within an instance already allocated to the user, or re-use a container already created for execution of the user code. When the user code has not been activated for a time-out period, the service can invalidate allocation of the virtual machine instance destroy the container. The time from receiving the request to beginning code execution is less than a predetermined duration, for example, 100 ms.

Timothy Allen Wagner

Papers

Programmatic event detection and message generation for requests to execute program code

Security protocols for low latency execution of program code

Processing event messages for user requests to execute program code

Asynchronous task management in an on-demand network code execution environment

Threading as a service