公开(公告)号：US20220391692A1

公开(公告)日：2022-12-08

申请号：US17341859

申请日：2021-06-08

Applicant: X Development LLC

Inventor： Sarah Ann Laszlo ,  Bin Ni

IPC: G06N3/08 ,  G06N3/04 ,  G06T7/20 ,  G06K9/00 ,  G06K9/62

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for receiving sensor data generated by one or more sensors that characterizes motion of an object over multiple time steps, providing the sensor data characterizing the motion of the object to a motion prediction neural network having a brain emulation sub-network with an architecture that is specified by synaptic connectivity between neurons in a brain of a biological organism, and processing the sensor data characterizing the motion of the object using the motion prediction neural network having the brain emulation sub-network to generate a network output that defines a prediction characterizing the motion of the object.

公开(公告)号：US20220284279A1

公开(公告)日：2022-09-08

申请号：US17190915

申请日：2021-03-03

Applicant: X Development LLC

Inventor： Sarah Ann Laszlo ,  Lam Thanh Nguyen

IPC: G06N3/08 ,  G06N3/04

Abstract: In one aspect, there is provided a method performed by one or more data processing apparatus that includes obtaining a point cloud dataset representing a brain of a biological organism. The point cloud dataset includes a collection of brain points that each define a respective spatial location in the brain. The method further includes identifying multiple brain points from the point cloud dataset as being located on a surface of the brain by repeatedly performing operations including initializing a current value of a position parameter and iteratively adjusting the current value of the position parameter until a termination criterion is satisfied. The termination criterion is satisfied if at least one brain point from the point cloud dataset is included in an interior of a shape parameterized by the current value of the position parameter. The operations further include, after determining that the termination criterion is satisfied, identifying each brain point from the point cloud dataset that is included in the interior of the shape parameterized by the current value of the position parameter as being located on the surface of the brain.

公开(公告)号：US20220202348A1

公开(公告)日：2022-06-30

申请号：US17139144

申请日：2020-12-31

Applicant: X Development LLC

Inventor： Sarah Ann Laszlo ,  David Andre ,  Doris Tang ,  Farooq Ahmad

IPC: A61B5/00 ,  G06N3/04 ,  G06N3/08

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for implementing brain emulation neural networks on user devices. One of the methods includes obtaining, by a first component of a user device, a network input; processing, by the first component of the user device, the network input using an artificial neural network to generate a network output, wherein the artificial neural network has a network architecture that has been determined according to a synaptic connectivity graph, wherein the synaptic connectivity graph represents synaptic connectivity between neurons in a brain of a biological organism; and providing the network output for use by one or more second components of the user device.

公开(公告)号：US20220188605A1

公开(公告)日：2022-06-16

申请号：US17119288

申请日：2020-12-11

Applicant: X Development LLC

Inventor： Sarah Ann Laszlo ,  Bangyan Chu

IPC: G06N3/06 ,  G06N3/04 ,  G06N3/08 ,  G10L17/18 ,  G10L17/04

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for implementing a recurrent neural network that includes a brain emulation subnetwork. One of the methods includes obtaining an input sequence; and processing the input sequence using a recurrent neural network, wherein the recurrent neural network comprises a brain emulation subnetwork having a network architecture that has been determined according to a synaptic connectivity graph, the processing comprising: at a first time step, processing a first input element in the input sequence to generate a hidden state of the recurrent neural network; at each of a plurality of subsequent time steps, updating the hidden state of the recurrent neural network; and at each of one or more of the plurality of time steps, generating an output element for the time step based on the updated hidden state for the time step.

公开(公告)号：US20210304011A1

公开(公告)日：2021-09-30

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：US20210201131A1

公开(公告)日：2021-07-01

申请号：US16731186

申请日：2019-12-31

Applicant: X Development LLC

Inventor： Sarah Ann Laszlo ,  Philip Edwin Watson

IPC: G06N3/08 ,  G06N3/04 ,  G06N3/00

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training a student neural network. In one aspect, there is provided a method comprising: processing a training input using the student neural network to generate a student neural network output comprising a respective score for each of a plurality of classes; processing the training input using a brain emulation neural network to generate a brain emulation neural network output comprising a respective score for each of the plurality of classes; and adjusting current values of the student neural network parameters using gradients of an objective function that characterizes a similarity between: (i) the student neural network output for the training input, and (ii) the brain emulation neural network output for the training input.

公开(公告)号：US20210201111A1

公开(公告)日：2021-07-01

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 ,  G06T7/00 ,  G06F16/901

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：US10952680B2

公开(公告)日：2021-03-23

申请号：US15855870

申请日：2017-12-27

Applicant: X Development LLC

Inventor： Sarah Ann Laszlo ,  Brian John Adolf ,  Gabriella Levine ,  Joseph R. Owens ,  Patricia Prewitt ,  Philip Edwin Watson

IPC: A61B5/378 ,  A61B5/00 ,  G06N20/00 ,  G06F3/01 ,  G06F3/0484 ,  A61B5/291 ,  A61B5/369 ,  A61B5/375 ,  G06K7/14 ,  G06N3/02 ,  G06K7/10

Abstract: A bioamplifier for analyzing electroencephalogram (EEG) signals is disclosed. The bioamplifier includes an input terminal for receiving an EEG signal from a plurality of sensors coupled to a user. The bioamplifier also includes an analogue-to-digital converter arranged to receive the EEG signal from the input terminal and convert the EEG signal to a digital EEG signal. A data processing apparatus within the bioamplifier is arranged to receive the digital EEG signal from the analogue-to-digital converter and programmed to process, in real time the digital EEG signal using a first machine learning model to generate a cleaned EEG signal having a higher signal-to-noise ratio than the digital EEG signal. The bioamplifier further includes a power source to provide electrical power to the analogue-to-digital converter and the data processing apparatus. The bioamplifier includes a housing that contains the analogue-to-digital converter, the data processing apparatus, the power source, and the sensor input.

公开(公告)号：US10901508B2

公开(公告)日：2021-01-26

申请号：US15926520

申请日：2018-03-20

Applicant: X Development LLC

Inventor： Sarah Ann Laszlo ,  Philip Edwin Watson ,  Carl Ferman McCleary Smith ,  Aysja Johnson

IPC: G06F3/01 ,  A63F13/212 ,  G06N20/00

Abstract: A method for analyzing electroencephalogram (EEG) signals is disclosed. EEG signals are received from a sensor coupled to a user. Contextual information from one or both of the user and the user's environment is also received. The EEG signals are processed in real time using a machine learning model to predict an action of the user, which is associated with the contextual information. Output associated with the predicted action is then generated.

公开(公告)号：US20210016113A1

公开(公告)日：2021-01-21

申请号：US16931778

申请日：2020-07-17

Applicant: X Development LLC

Inventor： Thomas Peter Hunt ,  Matthew Dixon Eisaman ,  Sarah Ann Laszlo

IPC: A61N7/00 ,  A61B8/00

Abstract: Closed-loop neurostimulation of large-scale brain networks includes a neurostimulation headset having at least two ultrasound transducer modules configured to generate within a first time period, a first focused ultrasound wave at a region within a portion of a subject's brain, one or more sensors configured to measure, within the first time period, a response from the portion of the subject's brain in response to the first focused ultrasound wave, and an electronic controller in communication with the at least two emitters and the one or more sensors configured to dynamically adjust, based on the measured response from the portion of the subject's brain, a power level of one or more of the at least two ultrasound transducer modules to generate a second focused ultrasound wave at the region within the portion of the subject's brain.