An intelligent automated assistant system engages with the user in an integrated, conversational manner using natural language dialog, and invokes external services when appropriate to obtain information or perform various actions. The system can be implemented using any of a number of different platforms, such as the web, email, smartphone, and the like, or any combination thereof. In one embodiment, the system is based on sets of interrelated domains and tasks, and employs additional functionally powered by external services with which the system can interact.

Intelligent Automated Assistant

Systems and methods are described for obtaining and acting upon information indicative of circulatory health and related phenomena in human beings or other subjects.

Circulatory monitoring systems and methods

This paper addresses the problem of Named Entity Recognition in Query (NERQ), which involves detection of the named entity in a given query and classification of the named entity into predefined classes. NERQ is potentially useful in many applications in web search. The paper proposes taking a probabilistic approach to the task using query log data and Latent Dirichlet Allocation. We consider contexts of a named entity (i.e., the remainders of the named entity in queries) as words of a document, and classes of the named entity as topics. The topic model is constructed by a novel and general learning method referred to as WS-LDA (Weakly Supervised Latent Dirichlet Allocation), which employs weakly supervised learning (rather than unsupervised learning) using partially labeled seed entities. Experimental results show that the proposed method based on WS-LDA can accurately perform NERQ, and outperform the baseline methods.

/pdf/named-entity-recognition-in-query-4k228ovuxk.pdf

Named entity recognition in query

A method and apparatus are provided for building an intelligent automated assistant. Embodiments of the present invention rely on the concept of “active ontologies” (e.g., execution environments constructed in an ontology-like manner) to build and run applications for use by intelligent automated assistants. In one specific embodiment, a method for building an automated assistant includes interfacing a service-oriented architecture that includes a plurality of remote services to an active ontology, where the active ontology includes at least one active processing element that models a domain. At least one of the remote services is then registered for use in the domain.

Method and apparatus for building an intelligent automated assistant

An electronic device may capture a voice command from a user. The electronic device may store contextual information about the state of the electronic device when the voice command is received. The electronic device may transmit the voice command and the contextual information to computing equipment such as a desktop computer or a remote server. The computing equipment may perform a speech recognition operation on the voice command and may process the contextual information. The computing equipment may respond to the voice command. The computing equipment may also transmit information to the electronic device that allows the electronic device to respond to the voice command.

Electronic Devices with Voice Command and Contextual Data Processing Capabilities

A method and apparatus for including in a processor instructions for performing multiply-add operations on packed data. In one embodiment, a processor is coupled to a memory. The memory has stored therein a first packed data and a second packed data. The processor performs operations on data elements in said first packed data and said second packed data to generate a third packed data in response to receiving an instruction. At least two of the data elements in this third packed data storing the result of performing multiply-add operations on data elements in the first and second packed data.

Method and apparatus for performing multiply-add operations on packed data

Personalized named entity recognition may be accomplished by parsing input text to determine a subset of the input text, generating a plurality of queries based at least in part on the subset of the input text, submitting the queries to a plurality of reference resources, processing responses to the queries and generating a vector based on the responses, and performing classification based at least in part on the vector and a set of model parameters to determine a likelihood as to which named entity category the input text belongs.

Method for personalized named entity recognition

A method and apparatus for executing floating point and packed data instructions using a single physical register file that is aliased. According to one aspect of the invention, a processor is provided that includes a decode unit, a mapping unit, and a storage unit. The decode unit is configured to decode instructions and their operands from at least one instruction set including at least a first and second set of instructions. The storage unit includes a physical register file. The mapping unit is configured to map operands used by the first set of instructions to the physical register file in a stack referenced manner. In addition, the mapping unit is configured to map operands used by the second set of instructions to the same physical register file in a non-stack reference manner.

Method and apparatus for executing two types of instructions that specify registers of a shared logical register file in a stack and a non-stack referenced manner

Most programs are repetitive, where similar behavior can be seen at different execution times. Algorithms have been proposed that automatically group similar portions of a program's execution into phases, where samples of execution in the same phase have homogeneous behavior and similar resource requirements. In this paper, we examine applying these phase analysis algorithms and how to adapt them to parallel applications running on shared memory processors. Our approach relies on a separate representation of each thread's activity. We first focus on showing its ability to identify similar intervals of execution across threads for a single run. We then show that it is effective at identifying similar behavior of a program when the number of threads is varied between runs. This can be used by developers to examine how different phases scale across different number of threads. Finally, we examine using the phase analysis to pick simulation points to guide multithreaded simulation.

/pdf/detecting-phases-in-parallel-applications-on-shared-memory-2hs1z4fkou.pdf

Detecting phases in parallel applications on shared memory architectures

A computer implemented apparatus and method for transferring information from one set or sets of memory locations to another set or sets of memory locations. The present invention has particular advantageous use within a computer system specially implemented for pattern recognition applications, such as handwriting or voice recognition. The present invention includes a system with an automatic sequencer able to sequentially generate sequential source and destination addresses and able to generate appropriate data requests to internal and external memory controllers. The present invention memory to memory transfer unit allows memory transfer operations to occur in parallel with the operation of arithmetic pipelines that process pattern recognition procedures. Therefore, using the present invention, no additional processing time is consumed by a memory transfer. Double buffering is utilized to transfer information and process information in the same time frame.

Carole Dulong

Papers

Method and apparatus for performing multiply-add operations on packed data

Method for personalized named entity recognition

Method and apparatus for executing two types of instructions that specify registers of a shared logical register file in a stack and a non-stack referenced manner

Detecting phases in parallel applications on shared memory architectures

Memory transfer apparatus and method useful within a pattern recognition system