公开(公告)号：US20230206059A1

公开(公告)日：2023-06-29

申请号：US17564536

申请日：2021-12-29

Applicant: X Development LLC

Inventor： Sarah Ann Laszlo ,  Lam Thanh Nguyen ,  Baihan Lin

IPC: G06N3/08 ,  G06N3/063

CPC classification number: G06N3/08 ,  G06N3/063

Abstract: In one aspect, there is provided a method performed by one or more data processing apparatus for training a neural network, the method including: obtaining a set of training examples, where each training example includes: (i) a training input, and (ii) a target output, and training the neural network on the set of training examples. Training the neural network can include, for each training example: processing the training input using the neural network to generate a corresponding training output, updating current values of at least a set of encoder sub-network parameters and a set of decoder sub-network parameters by a supervised update, and updating current values of at least a set of brain emulation sub-network parameters by an unsupervised update based on correlations between activation values generated by artificial neurons of the neural network during processing of the training input by the neural network.

公开(公告)号：US20230196059A1

公开(公告)日：2023-06-22

申请号：US17557618

申请日：2021-12-21

Applicant: X Development LLC

Inventor： Sarah Ann Laszlo ,  Lam Thanh Nguyen ,  Baihan Lin ,  Julia Renee Watson ,  Garrett Raymond Honke

IPC: G06N3/00

CPC classification number: G06N3/008

Abstract: In one aspect, there is provided a method performed by one or more data processing apparatus, the method includes: obtaining a network input including a respective data element at each input position in a sequence of input positions, and processing the network input using a neural network to generate a network output that defines a prediction related to the network input, where the neural network includes a sequence of encoder blocks and a decoder block, where each encoder block has a respective set of encoder block parameters, and where the set of encoder block parameters includes multiple brain emulation parameters that, when initialized, represent biological connectivity between multiple biological neuronal elements in a brain of a biological organism.

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.