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公开(公告)号：US11593617B2
公开(公告)日：2023-02-28
申请号：US16776574
申请日：2020-01-30
Applicant: X Development LLC
Inventor： Sarah Ann Laszlo , Philip Edwin Watson , Georgios Evangelopoulos
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for implementing a reservoir computing neural network. In one aspect there is provided a reservoir computing neural network comprising: (i) a brain emulation sub-network, and (ii) a prediction sub-network. The brain emulation sub-network is configured to process the network input in accordance with values of a plurality of brain emulation sub-network parameters to generate an alternative representation of the network input. The prediction sub-network is configured to process the alternative representation of the network input in accordance with values of a plurality of prediction sub-network parameters to generate the network output. The values of the brain emulation sub-network parameters are determined before the reservoir computing neural network is trained and are not adjusting during training of the reservoir computing neural network.
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公开(公告)号：US20210201107A1
公开(公告)日：2021-07-01
申请号：US16776108
申请日：2020-01-29
Applicant: X Development LLC
Inventor： Sarah Ann Laszlo , Philip Edwin Watson , Georgios Evangelopoulos
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for selecting a neural network architecture for performing a machine learning task. In one aspect, a method comprises: obtaining data defining a synaptic connectivity graph representing synaptic connectivity between neurons in a brain of a biological organism; generating data defining a plurality of candidate graphs based on the synaptic connectivity graph; determining, for each candidate graph, a performance measure on a machine learning task of a neural network having a neural network architecture that is specified by the candidate graph; and selecting a final neural network architecture for performing the machine learning task based on the performance measures.
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公开(公告)号：US20210026605A1
公开(公告)日：2021-01-28
申请号：US16523363
申请日：2019-07-26
Applicant: X Development LLC
Inventor： Georgios Evangelopoulos , Benoit Schillings , Bin Ni
Abstract: Implementations are described herein for automatically identifying, recommending, and/or automatically effecting changes to a source code base based on updates previously made to other similar code bases. Intuitively, multiple prior “migrations,” or mass updates, of complex software system code bases may be analyzed to identify changes that were made. More particularly, a particular portion or “snippet” of source code—which may include a whole source code file, a source code function, a portion of source code, or any other semantically-meaningful code unit—may undergo a sequence of edits over time. Techniques described herein leverage this sequence of edits to predict a next edit of the source code snippet. These techniques have a wide variety of applications, including but not limited to automatically updating of source code, source code completion, recommending changes to source code, etc.
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公开(公告)号：US11620487B2
公开(公告)日：2023-04-04
申请号：US16776108
申请日：2020-01-29
Applicant: X Development LLC
Inventor： Sarah Ann Laszlo , Philip Edwin Watson , Georgios Evangelopoulos
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for selecting a neural network architecture for performing a machine learning task. In one aspect, a method comprises: obtaining data defining a synaptic connectivity graph representing synaptic connectivity between neurons in a brain of a biological organism; generating data defining a plurality of candidate graphs based on the synaptic connectivity graph; determining, for each candidate graph, a performance measure on a machine learning task of a neural network having a neural network architecture that is specified by the candidate graph; and selecting a final neural network architecture for performing the machine learning task based on the performance measures.
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公开(公告)号：US20220096249A1
公开(公告)日：2022-03-31
申请号：US17390339
申请日：2021-07-30
Applicant: X Development LLC
Inventor： Elliott J. Rouse , Georgios Evangelopoulos , Kathryn Jane Zealand
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for an exosuit activity transition control structure. In some implementations, sensor data representing an estimate of sensor data that will be produced by sensors of an exosuit at a particular time in the future is generated, where the exosuit is configured to assist mobility of a wearer. Actual sensor data that is generated using the sensors of the exosuit is obtained. A measure of uncertainty is determined based on the forecasted sensor data and the actual sensor data. Based on the measure of uncertainty, a control action for the exosuit to adjust an assistance provided to the wearer is determined.
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Patent Agency Ranking
公开(公告)号：US20210349445A1
公开(公告)日：2021-11-11
申请号：US17110537
申请日：2020-12-03
Applicant: X Development LLC
Inventor： Kathryn Jane Zealand , Elliott J. Rouse , Georgios Evangelopoulos
IPC: G05B19/4155 , H04Q9/00 , G06N20/00
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for an exosuit activity transition control structure. In some implementations, sensor data for a powered exosuit is received. The sensor data is classified depending on whether the sensor data is indicative of a transition between different types of activities of a wearer of the powered exosuit. The classification is provided to a control system for the powered exosuit. The powered exosuit is controlled based on the classification.
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公开(公告)号：US11048482B2
公开(公告)日：2021-06-29
申请号：US16523363
申请日：2019-07-26
Applicant: X Development LLC
Inventor： Georgios Evangelopoulos , Benoit Schillings , Bin Ni
Abstract: Implementations are described herein for automatically identifying, recommending, and/or automatically effecting changes to a source code base based on updates previously made to other similar code bases. Intuitively, multiple prior “migrations,” or mass updates, of complex software system code bases may be analyzed to identify changes that were made. More particularly, a particular portion or “snippet” of source code—which may include a whole source code file, a source code function, a portion of source code, or any other semantically-meaningful code unit—may undergo a sequence of edits over time. Techniques described herein leverage this sequence of edits to predict a next edit of the source code snippet. These techniques have a wide variety of applications, including but not limited to automatically updating of source code, source code completion, recommending changes to source code, etc.
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公开(公告)号：US20200205740A1
公开(公告)日：2020-07-02
申请号：US16284561
申请日：2019-02-25
Applicant: X Development LLC
Inventor： Sarah Ann Laszlo , Aysja Johnson , Georgios Evangelopoulos , Nina Thigpen , Yvonne Yip
IPC: A61B5/00 , G06N3/08 , A61B5/04 , A61B5/0478
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for obtaining feature sets for a first number of diagnostic trials performed with a patient for diagnostic testing, wherein each feature set includes one or more features of electroencephalogram (EEG) signals measured from the patient while the patient is presented with trial content known to stimulate one or more desired human brain systems. Iteratively providing different combinations of the feature sets as input data to a diagnostic machine learning model to obtain model outputs, each model output corresponding to a particular one of the combinations. Determining, based on the model outputs, a consistency metric, the consistency metric indicating whether a quantity of feature sets in the combinations is sufficient to produce accurate output from the diagnostic machine learning model. Selectively ending the diagnostic testing with the patient based on a value of the consistency metric.
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公开(公告)号：US11568201B2
公开(公告)日：2023-01-31
申请号：US16776579
申请日：2020-01-30
Applicant: X Development LLC
Inventor： Sarah Ann Laszlo , Georgios Evangelopoulos , Philip Edwin Watson
IPC: G06N3/04 , G06F16/901 , G06T7/00
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining an artificial neural network architecture corresponding to a sub-graph of a synaptic connectivity graph. In one aspect, there is provided a method comprising: obtaining data defining a graph representing synaptic connectivity between neurons in a brain of a biological organism; determining, for each node in the graph, a respective set of one or more node features characterizing a structure of the graph relative to the node; identifying a sub-graph of the graph, comprising selecting a proper subset of the nodes in the graph for inclusion in the sub-graph based on the node features of the nodes in the graph; and determining an artificial neural network architecture corresponding to the sub-graph of the graph.
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公开(公告)号：US11243746B2
公开(公告)日：2022-02-08
申请号：US16458713
申请日：2019-07-01
Applicant: X Development LLC
Inventor： Georgios Evangelopoulos , Olivia Hatalsky , Bin Ni , Qianyu Zhang
Abstract: Techniques are described herein for using artificial intelligence to “learn,” statistically, a target programming style that is imposed in and/or evidenced by a code base. Once the target programming style is learned, it can be used for various purposes. In various implementations, one or more generative adversarial networks (“GANs”), each including a generator machine learning model and a discriminator machine learning model, may be trained to facilitate learning and application of target programming style(s). In some implementations, the discriminator(s) and/or generator(s) may operate on graphical input, and may take the form of graph neural networks (“GNNs”), graph attention neural networks (“GANNs”), graph convolutional networks (“GCNs”), etc., although this is not required.
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