公开(公告)号：US20230178076A1

公开(公告)日：2023-06-08

申请号：US18077194

申请日：2022-12-07

Applicant: DeepMind Technologies Limited

Inventor： Joshua Simon Abramson ,  Arun Ahuja ,  Federico Javier Carnevale ,  Petko Ivanov Georgiev ,  Chia-Chun Hung ,  Timothy Paul Lillicrap ,  Alistair Michael Muldal ,  Adam Anthony Santoro ,  Tamara Louise von Glehn ,  Jessica Paige Landon ,  Gregory Duncan Wayne ,  Chen Yan ,  Rui Zhu

IPC: G10L15/22 ,  G10L15/16 ,  G10L13/02 ,  G06V10/82 ,  G06V20/50 ,  G06F40/284 ,  G06F40/40 ,  G06V10/774 ,  G10L15/06

CPC classification number: G10L15/22 ,  G10L15/16 ,  G10L13/02 ,  G06V10/82 ,  G06V20/50 ,  G06F40/284 ,  G06F40/40 ,  G06V10/774 ,  G10L15/063 ,  G10L2015/223

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for controlling agents. In particular, an interactive agent can be controlled based on multi-modal inputs that include both an observation image and a natural language text sequence.

公开(公告)号：US11580429B2

公开(公告)日：2023-02-14

申请号：US16417580

申请日：2019-05-20

Applicant: DeepMind Technologies Limited

Inventor： Yujia Li ,  Victor Constant Bapst ,  Vinicius Zambaldi ,  David Nunes Raposo ,  Adam Anthony Santoro

IPC: G06N5/04 ,  G06N3/04 ,  G06N3/08 ,  G06N7/00 ,  G06F17/16 ,  G06N5/043

Abstract: A neural network system is proposed, including an input network for extracting, from state data, respective entity data for each a plurality of entities which are present, or at least potentially present, in the environment. The entity data describes the entity. The neural network contains a relational network for parsing this data, which includes one or more attention blocks which may be stacked to perform successive actions on the entity data. The attention blocks each include a respective transform network for each of the entities. The transform network for each entity is able to transform data which the transform network receives for the entity into modified entity data for the entity, based on data for a plurality of the other entities. An output network is arranged to receive data output by the relational network, and use the received data to select a respective action.

公开(公告)号：US20210081795A1

公开(公告)日：2021-03-18

申请号：US17107621

申请日：2020-11-30

Applicant: DeepMind Technologies Limited

Inventor： Mike Chrzanowski ,  Jack William Rae ,  Ryan Faulkner ,  Theophane Guillaume Weber ,  David Nunes Raposo ,  Adam Anthony Santoro

IPC: G06N3/08 ,  G06K9/62 ,  G06N3/04

Abstract: A system including one or more computers and one or more storage devices storing instructions that when executed by the one or more computers cause the one or more computers to implement a memory and memory-based neural network is described. The memory is configured to store a respective memory vector at each of a plurality of memory locations in the memory. The memory-based neural network is configured to: at each of a plurality of time steps: receive an input; determine an update to the memory, wherein determining the update comprising applying an attention mechanism over the memory vectors in the memory and the received input; update the memory using the determined update to the memory; and generate an output for the current time step using the updated memory.

公开(公告)号：US10853725B2

公开(公告)日：2020-12-01

申请号：US16415954

申请日：2019-05-17

Applicant: DeepMind Technologies Limited

Inventor： Mike Chrzanowski ,  Jack William Rae ,  Ryan Faulkner ,  Theophane Guillaume Weber ,  David Nunes Raposo ,  Adam Anthony Santoro

IPC: G06N3/08 ,  G06N3/04 ,  G06K9/62

Abstract: A system including one or more computers and one or more storage devices storing instructions that when executed by the one or more computers cause the one or more computers to implement a memory and memory-based neural network is described. The memory is configured to store a respective memory vector at each of a plurality of memory locations in the memory. The memory-based neural network is configured to: at each of a plurality of time steps: receive an input; determine an update to the memory, wherein determining the update comprising applying an attention mechanism over the memory vectors in the memory and the received input; update the memory using the determined update to the memory; and generate an output for the current time step using the updated memory.

公开(公告)号：US20190324988A1

公开(公告)日：2019-10-24

申请号：US16459113

申请日：2019-07-01

Applicant: DeepMind Technologies Limited

Inventor： Gregory Duncan Wayne ,  Chia-Chun Hung ,  Mevlana Celaleddin Gemici ,  Adam Anthony Santoro

IPC: G06F16/908 ,  G06N3/08

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating sequences of predicted observations, for example images. In one aspect, a system comprises a controller recurrent neural network, and a decoder neural network to process a set of latent variables to generate an observation. An external memory and a memory interface subsystem is configured to, for each of a plurality of time steps, receive an updated hidden state from the controller, generate a memory context vector by reading data from the external memory using the updated hidden state, determine a set of latent variables from the memory context vector, generate a predicted observation by providing the set of latent variables to the decoder neural network, write data to the external memory using the latent variables, the updated hidden state, or both, and generate a controller input for a subsequent time step from the latent variables.