公开(公告)号：US10191545B1

公开(公告)日：2019-01-29

申请号：US15391038

申请日：2016-12-27

Applicant: X Development LLC

Inventor： Sarah Ann Laszlo ,  Gabriella Levine ,  Philip Edwin Watson ,  Matthew Dixon Eisaman ,  Brian John Adolf

IPC: A61B5/04 ,  G06F3/01 ,  G06T11/60

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for receiving brain activity data of a user from a brain wave sensor. Identifying Alpha wave activity from the brain activity data. Determining a synchronization timing for presenting content to the user such that the content appears on a display device during a predetermined phase of the Alpha wave activity based on the Alpha wave activity. Causing the content to be displayed on the display device according to the synchronization timing, where the content includes a first content item and a second content item that is associated with the first content item.

公开(公告)号：US20230342589A1

公开(公告)日：2023-10-26

申请号：US17728398

申请日：2022-04-25

Applicant: X Development LLC

Inventor： Sarah Ann Laszlo ,  Julia Renee Watson ,  Garrett Raymond Honke ,  Estefany Kelly Buchanan ,  Hailey Anne Trier ,  Grayr Bleyan ,  Blair Armstrong ,  Rebecca Dawn Finzi

IPC: G06N3/04 ,  G06N20/20 ,  G06K9/62

CPC classification number: G06N3/0454 ,  G06N20/20 ,  G06K9/6215 ,  G06K9/6227 ,  G06K9/6262

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for executing ensemble models that include multiple reservoir computing neural networks. One of the methods includes executing an ensemble model comprising a plurality of reservoir computing neural networks, the ensemble model having been trained by operations comprising, at each training stage in a sequence of training stages: obtaining a current ensemble model that comprises a plurality of current reservoir computing neural networks; determining a respective performance measure for each current reservoir computing neural network in the current ensemble model; determining one or more new reservoir computing neural networks to be added to the current ensemble model based on the performance measures for the current reservoir computing neural networks; and adding the new reservoir computing neural networks to the current ensemble model.

公开(公告)号：US20230142885A1

公开(公告)日：2023-05-11

申请号：US17524574

申请日：2021-11-11

Applicant: X Development LLC

Inventor： Sarah Ann Laszlo ,  Hailey Anne Trier

IPC: G06N3/06 ,  G06N3/04 ,  G06F16/901

CPC classification number: G06N3/061 ,  G06N3/04 ,  G06F16/9024

Abstract: In one aspect, there is provided a method performed by one or more data processing apparatus, the method including: obtaining data defining a connectivity graph that represents synaptic connectivity between multiple biological neuronal elements in a brain of a biological organism, where the connectivity graph includes: multiple nodes, and multiple edges that each connect a respective pair of nodes, determining a partition of the connectivity graph into multiple community sub-graphs by performing an optimization that encourages a higher measure of connectedness between nodes included within each community sub-graph relative to nodes included in different community sub-graphs, and selecting a neural network architecture for performing a machine learning task using multiple community sub-graphs determined by the optimization that encourages the higher measure of connectedness between nodes included within each community sub-graph relative to nodes included in different community sub-graphs.

公开(公告)号：US11636349B2

公开(公告)日：2023-04-25

申请号：US16829107

申请日：2020-03-25

Applicant: X Development LLC

Inventor： Sarah Ann Laszlo ,  Matthew Sibigtroth ,  Bin Ni

IPC: G06N3/10 ,  G06N3/04 ,  G06N3/08

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for identifying one or more regions of a brain of a biological organism that are predicted to be functionally-specialized for performing a task. In one aspect, a method comprises: obtaining data defining a synaptic connectivity graph representing synaptic connectivity between neurons in the brain of the biological organism; identifying a plurality of sub-graphs of the synaptic connectivity graph; determining, for each sub-graph of the plurality of sub-graphs, a performance measure characterizing a performance of a neural network having a neural network architecture that is specified by the sub-graph in accomplishing the task; and determining, based on the performance measures, that one or more sub-graphs of the plurality of sub-graphs correspond to regions of the brain of the biological organism that are predicted to be functionally-specialized for performing the task.

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.

公开(公告)号：US20220414886A1

公开(公告)日：2022-12-29

申请号：US17360163

申请日：2021-06-28

Applicant: X Development LLC

Inventor： Sarah Ann Laszlo

IPC: G06T7/10 ,  G06K9/62 ,  G06N3/08 ,  G06N3/04

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training a segmentation neural network. In one aspect, a method comprises: obtaining data defining: (i) an image, and (ii) a respective class of each pixel in the image from a set of possible classes; determining a target segmentation of the image that comprises one or more target contrastive channels, wherein each target contrastive channel corresponds to a respective pair of classes including a respective first class and a respective second class from the set of possible classes; and training the segmentation neural network to process the image to generate a predicted segmentation that matches the target segmentation.

公开(公告)号：US20220414433A1

公开(公告)日：2022-12-29

申请号：US17362721

申请日：2021-06-29

Applicant: X Development LLC

Inventor： Sarah Ann Laszlo ,  Lam Thanh Nguyen

IPC: G06N3/06 ,  G06N3/08

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining network architectures based on synaptic connectivity. One of the methods includes processing a network input using a neural network to generate a network output, comprising: processing the network input using an encoder subnetwork of the neural network to generate an embedding of the network input; processing the embedding of the network input using a first connectivity layer of the neural network to generate a first connectivity layer output; processing the first connectivity layer output using a brain emulation subnetwork of the neural network to generate a brain emulation subnetwork output; processing the brain emulation subnetwork output using a second connectivity layer of the neural network to generate a second connectivity layer output; and processing the second connectivity layer output using a decoder subnetwork of the neural network to generate the network output.

公开(公告)号：US20220343134A1

公开(公告)日：2022-10-27

申请号：US17236647

申请日：2021-04-21

Applicant: X Development LLC

Inventor： Bangyan Chu ,  Sarah Ann Laszlo ,  Michael Jeremiah Crosse

IPC: G06N3/00 ,  G06N3/04 ,  G06N3/08

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating and executing biological convolutional neural network layers. One of the methods obtaining a network input; and processing the network input using a neural network to generate a network output, wherein the neural network is configured to perform operations comprising: generating a layer input to a convolutional neural network layer based on the network input; and generating a layer output of the convolutional neural network layer based on the layer input, comprising applying a convolutional kernel to the layer input, wherein the convolutional kernel corresponds to a specified neuron in a brain of a biological organism and values of parameters of the convolutional kernel are based on synaptic connectivity between the specified neuron and each of a plurality of other neurons in the brain of the biological organism.

公开(公告)号：US20220284268A1

公开(公告)日：2022-09-08

申请号：US17195395

申请日：2021-03-08

Applicant: X Development LLC

Inventor： Sarah Ann Laszlo ,  Farooq Ahmad

IPC: G06N3/04 ,  G06N3/063

Abstract: In one aspect, there is provided a method performed by multiple data processing units for distributed processing of data defining a synaptic connectivity graph that includes multiple nodes and edges and represents synaptic connectivity between neurons in a brain of a biological organism. The method includes obtaining graph data defining the synaptic connectivity graph that represents synaptic connectivity between neurons in the brain of the biological organism. The method further includes dividing the graph data defining the synaptic connectivity graph into multiple sub-graph datasets that each define a respective sub-graph of the synaptic connectivity graph. The method further includes distributing multiple sub-graph datasets over multiple data processing units and processing multiple sub-graph datasets using multiple data processing units.

公开(公告)号：US20220207354A1

公开(公告)日：2022-06-30

申请号：US17139125

申请日：2020-12-31

Applicant: X Development LLC

Inventor： Sarah Ann Laszlo ,  Benoit Schillings ,  Raj B. Apte

IPC: G06N3/08 ,  G06N3/063 ,  G06N3/06 ,  G06K9/62

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for implementing brain emulation neural networks using analog circuits. One of the methods includes obtaining data defining a synaptic connectivity graph representing synaptic connectivity between neurons in a brain of a biological organism, wherein the synaptic connectivity graph comprises a plurality of nodes and edges, wherein each edge connects a pair of nodes, each node corresponds to a respective neuron in the brain of the biological organism, and each edge connecting a pair of nodes in the synaptic connectivity graph corresponds to a synaptic connection between a pair of neurons; determining an artificial neural network architecture corresponding to the synaptic connectivity graph; and generating, from the artificial neural network architecture, a design of an analog circuit that is configured to execute a plurality of operations of an artificial neural network having the artificial neural network architecture.