ARTIFICIAL NEURAL NETWORK REMAPPING IN MEMORY

    公开(公告)号:WO2022231817A1

    公开(公告)日:2022-11-03

    申请号:PCT/US2022/023805

    申请日:2022-04-07

    Abstract: An artificial neural network can be allocated to memory and operated. An error can occur in the memory and/or be detected in the memory. Layers of the artificial neural network can be remapped in the memory at least partially in response to the error. Performance of the artificial neural network can be evaluated before and/or after the remapping.

    ARTIFICIAL NEURAL NETWORK RETRAINING IN MEMORY

    公开(公告)号:WO2022231816A1

    公开(公告)日:2022-11-03

    申请号:PCT/US2022/023801

    申请日:2022-04-07

    Abstract: An artificial neural network can be allocated to memory and operated. Performance of the artificial neural network can be periodically evaluated. The evaluation can include inputting a representative dataset to the artificial neural network and comparing an output of the artificial neural network to a known output for the representative dataset. The artificial neural network can be retrained at least partially in response to the evaluation yielding a sub-threshold result.

    ARTIFICIAL NEURAL NETWORK BYPASS
    4.
    发明申请

    公开(公告)号:WO2022109103A1

    公开(公告)日:2022-05-27

    申请号:PCT/US2021/059843

    申请日:2021-11-18

    Abstract: Apparatuses and methods can be related to compiling instructions for implementing an artificial neural network (ANN) bypass. The bypass path can be used to bypass a portion of the ANN such that the ANN generates an output with a particular level of confidence while utilizing less resources than if the portion of the ANN had not been bypassed. A compiler can determine where to place the bypass path in an ANN.

    ARTIFICIAL NEURAL NETWORK BYPASS
    5.
    发明申请

    公开(公告)号:WO2022108693A1

    公开(公告)日:2022-05-27

    申请号:PCT/US2021/055343

    申请日:2021-10-18

    Abstract: Apparatuses and methods can be related to implementing bypass paths in an ANN. The bypass path can be used to bypass a portion of the ANN such that the ANN generates an output with a particular level of confidence while utilizing less resources than if the portion of the ANN had not been bypassed.

Patent Agency Ranking