DeepMind Technologies Limited patent applications on May 8th, 2025

Patent Applications by DeepMind Technologies Limited on May 8th, 2025

DeepMind Technologies Limited: 4 patent applications

DeepMind Technologies Limited has applied for patents in the areas of G06F9/50 (1), G06N3/08 (1), G06N7/01 (1), G06V10/82 (1), G06N3/045 (1) G06F9/5038 (1), G06N3/08 (1), G06V10/82 (1), G10L19/018 (1)

With keywords such as: task, network, neural, input, computer, computational, sequence, resources, methods, and respective in patent application abstracts.

Patent Applications by DeepMind Technologies Limited

20250147810. SCHEDULING JOBS USING SCORED COMPUTATIONAL RESOURCES AND EFFICIENT SCHEDULING ALGORITHMS_simplified_abstract_(deepmind technologies limited)

Inventor(s): Bernardino Romera-Paredes of London GB for deepmind technologies limited, Alexander Novikov of London GB for deepmind technologies limited, Mohammadamin Barekatain of London GB for deepmind technologies limited, Matej Balog of London GB for deepmind technologies limited, Pawan Kumar Mudigonda of London GB for deepmind technologies limited, Emilien Dupont of London GB for deepmind technologies limited, Francisco Jesus Rodriguez Ruiz of London GB for deepmind technologies limited, Alhussein Fawzi of St. Albans GB for deepmind technologies limited

IPC Code(s): G06F9/50

CPC Code(s): G06F9/5038

Abstract: methods, systems, and apparatuses, including computer programs encoded on computer storage media, for scheduling jobs across a plurality of computational resources. scheduling jobs (e.g., compute jobs) on a plurality of computational resources (e.g., a cluster that includes physical machines, virtual machines or both) can include assigning jobs to computational resources using respective scores for the computational resources that take into account several attributes, including central processing unit (cpu) requirements, memory requirements, and availability. that is, by generating a score that more accurately reflects the likelihood that a given computational resource is the optimal computational resource to place a given job, the resulting job schedule significantly minimizes idle time of the set of computational resources and enhances the throughput of completed jobs.

20250148282. TRAINING ACTION SELECTION NEURAL NETWORKS USING LOOK-AHEAD SEARCH_simplified_abstract_(deepmind technologies limited)

Inventor(s): Karen Simonyan of London GB for deepmind technologies limited, David Silver of Hitchin GB for deepmind technologies limited, Julian Schrittwieser of London GB for deepmind technologies limited

IPC Code(s): G06N3/08, G06N7/01

CPC Code(s): G06N3/08

Abstract: methods, systems and apparatus, including computer programs encoded on computer storage media, for training an action selection neural network. one of the methods includes receiving an observation characterizing a current state of the environment; determining a target network output for the observation by performing a look ahead search of possible future states of the environment starting from the current state until the environment reaches a possible future state that satisfies one or more termination criteria, wherein the look ahead search is guided by the neural network in accordance with current values of the network parameters; selecting an action to be performed by the agent in response to the observation using the target network output generated by performing the look ahead search; and storing, in an exploration history data store, the target network output in association with the observation for use in updating the current values of the network parameters.

20250148774. REINFORCEMENT LEARNING FOR ACTIVE SEQUENCE PROCESSING_simplified_abstract_(deepmind technologies limited)

Inventor(s): Viorica Patraucean of London GB for deepmind technologies limited, Bilal Piot of London GB for deepmind technologies limited, Joao Carreira of St. Albans GB for deepmind technologies limited, Volodymyr Mnih of Toronto CA for deepmind technologies limited, Simon Osindero of London GB for deepmind technologies limited

IPC Code(s): G06V10/82, G06N3/045, G06N3/048

CPC Code(s): G06V10/82

Abstract: a system that is configured to receive a sequence of task inputs and to perform a machine learning task is described. an rl neural network is configured to: generate, for each task input of the sequence, a respective decision that determines whether to encode the task input or to skip the task input, and provide the respective decision of each task input to the task neural network. the task neural network is configured to: receive the sequence of task inputs, receive, from the rl neural network, for each task input of the sequence, a respective decision, process each of the un-skipped task inputs in the sequence of task inputs to generate a respective accumulated feature for the un-skipped task input, and generate a machine learning task output for the machine learning task based on the last accumulated feature generated for the last un-skipped task input in the sequence.

20250149048. VERIFYING THE PROVENANCE OF A DIGITAL OBJECT USING WATERMARKING AND EMBEDDINGS_simplified_abstract_(deepmind technologies limited)

Inventor(s): Sven Adrian Gowal of Cambridge GB for deepmind technologies limited, Christopher Gamble of London GB for deepmind technologies limited, Florian Nils Stimberg of London GB for deepmind technologies limited, Sylvestre-Alvise Guglielmo Rebuffi of Sceaux FR for deepmind technologies limited, Sree Meghana Thotakuri of London GB for deepmind technologies limited, Jamie Hayes of Levenshulme GB for deepmind technologies limited, Ian Goodfellow of Mountain View CA US for deepmind technologies limited, Rudy Bunel of London GB for deepmind technologies limited, Miklós Zsigmond Horváth of London GB for deepmind technologies limited, David Stutz of London GB for deepmind technologies limited, Olivia Anne Wiles of London GB for deepmind technologies limited

IPC Code(s): G10L19/018, G06F21/16, G10L21/0232

CPC Code(s): G10L19/018

Abstract: methods, systems, and apparatus, including computer programs encoded on computer storage media, for verifying the provenance of a digital object generated by a neural network, such as an image or audio object. also methods, systems, and apparatus, including computer programs, for training a watermarking neural network and a watermark decoding neural network. the described techniques make efficient use of computing resources and are robust to attack.

DeepMind Technologies Limited patent applications on May 8th, 2025