DYNAMIC LAYER PARTITIONING FOR INCREMENTAL TRAINING OF NEURAL RADIANCE FIELDS

    公开(公告)号:US20240355111A1

    公开(公告)日:2024-10-24

    申请号:US18758110

    申请日:2024-06-28

    CPC classification number: G06V10/82 G06T7/20 G06T7/90 G06T2207/10024

    Abstract: Example apparatus disclosed herein are to train a neural network based on initial video frames of an input video to generate neural representations of the initial video frames, the neural network having a first group of layers and a second group of layers, the first group of layers to be retrained for subsequent video frames after the initial video frames, the second group of layers to be selectively frozen for the subsequent video frames. Disclosed example apparatus are also to select a layer of the second group of layers to be unfrozen for a first video frame subsequent to the initial video frames, and retrain the first group of layers and the selected layer of the second group of layers to generate a neural representation of the first video frame, unselected ones of the second group of layers to remain frozen in the neural representation of the first video frame.

    SYSTEM, METHOD AND APPARATUS FOR CONDITIONALLY OFFLOADING INSTRUCTION EXECUTION

    公开(公告)号:US20240354107A1

    公开(公告)日:2024-10-24

    申请号:US18754447

    申请日:2024-06-26

    CPC classification number: G06F9/30047 G06F9/321 G06F9/3836

    Abstract: In one example, a processor includes: at least one core to execute instructions; and at least one cache memory coupled to the at least one core, the at least one cache memory to store data, at least some of the data a copy of data stored in a memory. The at least one core is to determine whether to conditionally offload a sequence of instructions for execution on a compute circuit associated with the memory, based at least in part on whether one or more first data is present in the at least one cache memory, the one or more first data for use during execution of the sequence of instructions. Other embodiments are described and claimed.

    Laptop
    439.
    外观设计
    Laptop 有权

    公开(公告)号:USD1047998S1

    公开(公告)日:2024-10-22

    申请号:US29845962

    申请日:2022-07-12

    Abstract: FIG. 1 is a front, right perspective view of a laptop.
    FIG. 2 is a front view of the laptop of FIG. 1.
    FIG. 3 is a rear view of the laptop of FIG. 1.
    FIG. 4 is a right side view of the laptop of FIG. 1.
    FIG. 5 is a left side view of the laptop of FIG. 1.
    FIG. 6 is a top view of the laptop pf FIG. 1; and,
    FIG. 7 is a bottom view of the laptop of FIG. 1.

    Integrity protected access control mechanisms

    公开(公告)号:US12126706B2

    公开(公告)日:2024-10-22

    申请号:US17134351

    申请日:2020-12-26

    CPC classification number: H04L9/002 G06F21/602 H04L9/0643 H04L9/3242

    Abstract: Detailed herein are embodiments which allow for integrity protected access control to provide defense against deterministic software attacks. Software attacks such as rowhammer attacks which target the TD bit itself are defended against using cryptographic integrity which the data itself is protected by the TD-bit alone. As such, software is reduced to performing only non-deterministic attacks (e.g., random corruption), but all the deterministic attacks are defended against. Additionally, integrity-protected access control bits are protected against simple hardware attacks where the adversary with physical access to the machine can flip TD bits to get ciphertext access in software which can break confidentiality.

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