Logical interleaver
    4.
    发明授权

    公开(公告)号:US10122384B2

    公开(公告)日:2018-11-06

    申请号:US15157814

    申请日:2016-05-18

    申请人: ARM Limited

    IPC分类号: G11C29/00 H03M13/29 H03M13/27

    摘要: Various implementations described herein are directed to a memory device. The memory device includes a first interleaving circuit that receives data words and generates a first error correction code based on the received data words. The memory device includes a second interleaving circuit that receives the data words and generates a second error correction code based on the received data words as a complement to the first error correction code. The second interleaving circuit interleaves data bits from multiple different data words and stores modified data words based on the multiple different data words.

    SYSTEM, DEVICES AND/OR PROCESSES FOR AUGMENTING ARTIFICIAL INTELLIGENCE AGENT AND COMPUTING DEVICES

    公开(公告)号:US20220391685A1

    公开(公告)日:2022-12-08

    申请号:US17337317

    申请日:2021-06-02

    申请人: Arm Limited

    IPC分类号: G06N3/08 G06N3/04

    摘要: Briefly, example methods, apparatuses, and/or articles of manufacture are disclosed that may be implemented, in whole or in part, using one or more computing devices to enhance capabilities of peer devices. In an implementation, at least one agent to: identify one or more learnable capabilities enabled by one or more parameters that are accessible via receipt of one or more message at the one or more communication devices from one or more other computing devices; and determine a utility of augmenting at least one of the one or more learning engines with at least one of the one or more learnable capabilities.

    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

    申请人: Arm Limited

    摘要: 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.