AUTOMATED IDENTIFICATION OF CODE CHANGES
    1.
    发明申请

    公开(公告)号:US20200371778A1

    公开(公告)日:2020-11-26

    申请号:US16418767

    申请日:2019-05-21

    Abstract: Implementations are described herein for automatically identifying, recommending, and/or effecting changes to a legacy source code base by leveraging knowledge gained from prior updates made to other similar legacy code bases. In some implementations, data associated with a first version source code snippet may be applied as input across a machine learning model to generate a new source code embedding in a latent space. Reference embedding(s) may be identified in the latent space based on their distance(s) from the new source code embedding in the latent space. The reference embedding(s) may be associated with individual changes made during the prior code base update(s). Based on the identified one or more reference embeddings, change(s) to be made to the first version source code snippet to create a second version source code snippet may be identified, recommended, and/or effected.

    PREDICTING CLIMATE CONDITIONS BASED ON TELECONNECTIONS

    公开(公告)号:US20210405252A1

    公开(公告)日:2021-12-30

    申请号:US16911278

    申请日:2020-06-24

    Abstract: Implementations are described herein for predicting a future climate condition in an agricultural area. In various implementations, a teleconnection model may be applied to a dataset of remote climate conditions such as water surface temperatures to identify one or more of the most influential remote climate conditions on the future climate condition in the agricultural area. A trained machine learning model may be applied to the one or more most influential remote climate conditions and to historical climate data for the agricultural area to generate data indicative of the predicted future climate condition. Based on the data indicative of the predicted future climate condition, one or more output components may be caused to render output that conveys the predicted future climate condition.

    SYSTEMS AND METHODS FOR GREENHOUSE GAS MITIGATION

    公开(公告)号:US20250029042A1

    公开(公告)日:2025-01-23

    申请号:US18776120

    申请日:2024-07-17

    Abstract: A method includes: generating a set of tasks; determining, by a machine learning model and based on multiple data types from multiple sources, that an overall risk score exceeds a first failure threshold due to a risk score of a task exceeding a second threshold; selecting a replacement task for the task, the selecting including: receiving, replacement candidates, each replacement candidate including a candidate offset potential and one or more candidate failure mechanisms; assigning, by the machine learning model and to each of the replacement candidates, a replacement score for the replacement candidate based on a failure correlation of the replacement candidate with respect to each other sets of the set of tasks; ranking the replacement candidates based on the replacement scores; and selecting, based on the ranking, the replacement task; and generating, an updated set of tasks including the replacement task.

    PLATFORM FOR SHIPPING LOGISTICS SIMULATION AND EXECUTION

    公开(公告)号:US20230351310A1

    公开(公告)日:2023-11-02

    申请号:US18193045

    申请日:2023-03-30

    CPC classification number: G06Q10/083 G06F30/20

    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for planning shipping logistics routes. A computer-implemented method includes: receiving a request for a first shipment to occur during a first time duration, the request being provided by a requestor; obtaining shipment data representing scheduled shipments to occur during a second time duration, the second time duration overlapping the first time duration; providing the request for the first shipment and the shipment data as input to a shipping model; obtaining, as output from the shipping model, simulation results including predicted shipments during the second time duration, the predicted shipments including the first shipment and the scheduled shipments, the simulation results including predicted movements of shipping resources executing the predicted shipments during the second time duration; and assigning shipping resources to the predicted shipments based on the simulation results.

    PREDICTING GEOSPATIAL MEASURES
    7.
    发明申请

    公开(公告)号:US20220290989A1

    公开(公告)日:2022-09-15

    申请号:US17200023

    申请日:2021-03-12

    Abstract: Implementations are described herein for leveraging teleconnections and location embeddings to predict geospatial measures for a geographic location of interest. In various implementations, a plurality of reference geographic locations may be identified that are disparate from a geographic location of interest and influence a geospatial measure in the geographic location of interest. One or more features may be extracted from each of the plurality of reference geographic locations. The extracted features and a location embedding generated for the geographic location of interest may be encoded into a joint embedding. A sequence encoder may be applied to the joint embedding to generate encoded data indicative of the predicted geospatial measure.

    PREDICTING CLIMATE CONDITIONS BASED ON TELECONNECTIONS

    公开(公告)号:US20220120934A1

    公开(公告)日:2022-04-21

    申请号:US17567448

    申请日:2022-01-03

    Abstract: Implementations are described herein for predicting a future climate condition in an agricultural area. In various implementations, a teleconnection model may be applied to a dataset of remote climate conditions such as water surface temperatures to identify one or more of the most influential remote climate conditions on the future climate condition in the agricultural area. A trained machine learning model may be applied to the one or more most influential remote climate conditions and to historical climate data for the agricultural area to generate data indicative of the predicted future climate condition. Based on the data indicative of the predicted future climate condition, one or more output components may be caused to render output that conveys the predicted future climate condition.

    Predicting climate conditions based on teleconnections

    公开(公告)号:US11243332B2

    公开(公告)日:2022-02-08

    申请号:US16911278

    申请日:2020-06-24

    Abstract: Implementations are described herein for predicting a future climate condition in an agricultural area. In various implementations, a teleconnection model may be applied to a dataset of remote climate conditions such as water surface temperatures to identify one or more of the most influential remote climate conditions on the future climate condition in the agricultural area. A trained machine learning model may be applied to the one or more most influential remote climate conditions and to historical climate data for the agricultural area to generate data indicative of the predicted future climate condition. Based on the data indicative of the predicted future climate condition, one or more output components may be caused to render output that conveys the predicted future climate condition.

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