METHODS AND APPARATUS FOR AMBIENT COMPUTING

    公开(公告)号:US20250165647A1

    公开(公告)日:2025-05-22

    申请号:US18430950

    申请日:2024-02-02

    Applicant: Arm Limited

    Abstract: A method of operating a personal intelligent agent in an ambient computing environment, comprising receiving input; analyzing input to derive a user personal preference; associating the personal preference with a first context indicator; determining whether the personal preference is exposable; responsive to determining that the personal preference is exposable, storing the preference with the associated context indicator; detecting when the agent enters a detectable context and responsively creating a second context indicator; determining if there is a match between the second and the first context indicator; retrieving the exposable personal preference associated with the context indicator; creating an anonymous preference indicator comprising the exposable personal preference with the matched context; emitting the preference indicator over the ambient computing environment; and monitoring the ambient computing environment to detect any broadcast message indicating ability to satisfy the preference shown in the preference indicator.

    ACTIVITY PLANNER
    2.
    发明申请

    公开(公告)号:US20250036979A1

    公开(公告)日:2025-01-30

    申请号:US18523411

    申请日:2023-11-29

    Applicant: Arm Limited

    Abstract: A machine learning and inferencing system to generate a personalised activity plan comprises a trained world context knowledge base; a trained personal digital memory store; a goal engine to establish an activity goal; an activity decomposition engine to decompose an activity into a logically-consistent sub-activities connected by; a ponderation engine to assign value weights to potential sub-activities; a graph generation engine to generate a multi-layer weighted graph to train a model of personalised outcomes of the sub-activities according to the value weights; a scenario generation engine to analyze the network of logically-consistent potential sub-activities connected by paths to determine a selected scenario path to the activity goal according to at least the model of personalised user outcomes; a feedback engine to apply learning from the scenario generation engine to the world context knowledge base and/or the personal digital memory store; and an output channel to output a personalised activity plan comprising recommended actions to implement the selected scenario path.

    RUNTIME CONFIGURABLE MODULAR PROCESSING TILE

    公开(公告)号:US20240370267A1

    公开(公告)日:2024-11-07

    申请号:US18430952

    申请日:2024-02-02

    Applicant: Arm Limited

    Abstract: The present disclosure relates to a data processing system comprising: at least one modular processing tile comprising runtime-configurable processing circuitry; and a control module to control the at least one modular processing tile, said control module comprising: instruction decoding circuitry to decode instructions; information collecting circuitry to collect information relating to said at least one modular processing tile; and instruction processing circuitry to process instructions decoded by the instruction decoding circuitry, wherein, in response to an instruction to perform a processing task, said instruction processing circuitry generates configuration instruction based on the collected information relating to said at least one modular processing tile, and said runtime-configurable processing circuitry is configured at runtime to perform said processing task in response to said configuration instruction. In some embodiments, plural modular processing tiles may be aggregated and configured at runtime to perform a dedicated function similar to a cortical column in the human brain.

    Method and system for data generation

    公开(公告)号:US11308699B2

    公开(公告)日:2022-04-19

    申请号:US16823003

    申请日:2020-03-18

    Applicant: Arm Limited

    Abstract: A computer-implemented method includes generating, using a scene generator, first candidate scene data; obtaining reference scene data corresponding to a predetermined reference scene; processing the first candidate scene data and the reference scene data, using a scene discriminator, to generate first discrimination data for estimating whether each of the first candidate scene data and the reference scene data corresponds to a predetermined reference scene; updating a set of parameter values for the scene discriminator using the first discrimination data; generating, using the scene generator, second candidate scene data; processing the second candidate scene data, using the scene discriminator with the updated set of parameter values for the scene discriminator, to generate second discrimination data for estimating whether the second candidate scene data corresponds to a predetermined reference scene; and updating a set of parameter values for the scene generator using the second discrimination data.

    TRAINING A SENSING SYSTEM TO DETECT REAL-WORLD ENTITIES USING DIGITALLY STORED ENTITIES

    公开(公告)号:US20230004794A1

    公开(公告)日:2023-01-05

    申请号:US17465569

    申请日:2021-09-02

    Applicant: Arm Limited

    Abstract: Disclosed subject matter relates generally to forming a set of training parameters applicable to detection of two or more entities between and/or among a distribution of entities from a plurality of digitally stored observations. One or more training parameters of the set of training parameters may be modified to define a translation, which is applicable to detection of real-world entities corresponding to the two or more entities in the distribution of the digitally stored observations, wherein the forming of the translation is to be based, at least in part, on a first process to generate the two or more entities in the distribution of digitally stored observations and a second process to discriminate between and/or among the generated two or more entities based, at least in part, on the modified one or more training parameters

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