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公开(公告)号:US20240062114A1
公开(公告)日:2024-02-22
申请号:US18452044
申请日:2023-08-18
Applicant: X Development LLC
Inventor: Bertrand Louis Rene Delorme , Alexandre Szenicer , Antoni Jordi Ballester , Bianca Bahman , Julia Black Ling
CPC classification number: G06N20/00 , B64G1/1021 , A01G33/00 , G06Q50/02
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for predicting features of an aquatic ecosystem. One of the methods includes generating, using ground truth data, first training input, wherein the first training input includes training labels; generating an augmented dataset from multiple data sources as second training input, wherein the augmented dataset is generated using (i) bathymetric data and (ii) simulated data based on satellite data indicating one or more coastal ecosystems; and training the machine learning model using (i) the first training input and (ii) second training input, such that the machine learning model is trained to predict biomass growth.
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公开(公告)号:US11908547B2
公开(公告)日:2024-02-20
申请号:US16870838
申请日:2020-05-08
Applicant: X Development LLC
Inventor: Bradley Michael Zamft , Logan Graham
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for governing phenotypic outcomes in plants. One method includes obtaining a model input comprising time series data, wherein the time series data comprises, for each previous time point of one or more previous time points, at least one of i) first multi-omics data corresponding to a plant at the previous time point, or ii) phenotypic data corresponding to the plant at the previous time point; and processing the model input using a machine learning model to obtain a model output that comprises, for each future time point of one or more of future time points, a prediction of at least one of i) a phenotype of the plant at the future time point, or ii) second multi-omics data corresponding to the plant at the future time point.
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公开(公告)号:US20240046637A1
公开(公告)日:2024-02-08
申请号:US17880892
申请日:2022-08-04
Applicant: X Development LLC
Inventor: Grace Calvert Young
CPC classification number: G06V20/05 , G06V10/225 , G06V10/25 , G06T7/11 , G06T7/70 , A01K61/13 , A01K61/80 , G06T2207/20081 , G06V2201/07
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for monocular underwater camera biomass estimation. In some implementations, an exemplary method includes obtaining an image of a fish captured by an underwater camera; identifying portions of the image corresponding to one or more areas of interest; extracting the portions of the image from the image; providing the portions of the image to a model trained to detect objects in the portions of the image; and determining an action based on output of the model indicating a number of object detections.
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公开(公告)号:US11893484B2
公开(公告)日:2024-02-06
申请号:US17111364
申请日:2020-12-03
Applicant: X Development LLC
Inventor: Ardavan Oskooi , Christopher Hogan , Alec M. Hammond , Steven G. Johnson
Abstract: In some embodiments, a method for optimal parallel execution of a simulation of a design is provided. A computing device extracts one or more features from the design. The computing device provides at least the one or more features as inputs to one or more machine learning models to determine one or more predictions of execution times. The computing device determines an optimum execution architecture based on the one or more predictions of execution times. The computing device distributes portions of the design for simulation based on the optimum execution architecture. In some embodiments, one or more machine learning models are trained to generate outputs for predicting an optimal parallel execution architecture for simulation of a design.
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公开(公告)号:US20240034675A1
公开(公告)日:2024-02-01
申请号:US17874935
申请日:2022-07-27
Applicant: X Development LLC
Inventor: Antonio Raymond Papania-Davis , Ray Jr. Anthony Nagatani , Shijian Jin
CPC classification number: C04B18/167 , C04B20/1066 , C04B2111/00017
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing recycled concrete aggregate (RCA). A method includes obtaining an aqueous carbonate solution by exposing an aqueous alkaline solution to a carbon dioxide laden fluid; performing a treatment process on a first portion of RCA particles using a first set of parameters, the treatment process including exposing the first portion of RCA particles to the aqueous carbonate solution; after performing the treatment process, obtaining measurements of the first portion of RCA particles; determining, using the measurements of the first portion of RCA particles, a second set of parameters; and performing the treatment process on a second portion of RCA particles using the second set of parameters. Exposing the first portion of RCA particles to the aqueous carbonate solution includes soaking the first portion of RCA particles in the aqueous carbonate solution.
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公开(公告)号:US11888530B2
公开(公告)日:2024-01-30
申请号:US17698224
申请日:2022-03-18
Applicant: X DEVELOPMENT LLC
Inventor: Baris Ibrahim Erkmen , Devin Brinkley , Eric Teller , Thomas Moore , Jean-Laurent Plateau
CPC classification number: H04B10/614 , G01S7/4817 , G01S17/66 , G02B27/0087 , G02F1/292
Abstract: The optical tracking module includes an optical phased array (OPA), an analog drive, an integrated photodetector, and one or more processors. The OPA includes a plurality of array elements, and a plurality of phase shifters. The analog drive is configured to adjust the plurality of phase shifters. The integrated photodetector is configured to receive light from the OPA. The one or more processors is configured to extract signal information of an incoming beam via the OPA, and control an outgoing beam using the analog drive based on the signal information. The OPA, the analog drive, the integrated photodetector and the one or more processors are in an integrated circuit.
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公开(公告)号:US20240012961A1
公开(公告)日:2024-01-11
申请号:US18339482
申请日:2023-06-22
Applicant: X Development LLC
Inventor: Hamed Khalilinia
IPC: G06F30/20
CPC classification number: G06F30/20 , G06F2113/04
Abstract: Methods, systems, and apparatus, including medium-encoded computer program products, for cloud-based electrical grid component validation can include obtaining a computer model of an electric power grid. The computer model can include asset models for individual assets connected to the electric power grid. Each asset model can be configured to replicate operation of a corresponding type of physical electric grid asset. A first asset model can include a hardware emulator configured to execute firmware specific to the corresponding type of physical electric grid asset. Altered firmware for the first asset model can be received. The computer model can be processed using a simulation engine to obtain simulation results, and the simulation engine can be configured to simulate operation of the individual assets of the computer model including operation of the first asset model according to the altered firmware associated with the first asset model. Simulation results can be provided.
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公开(公告)号:US20240008838A1
公开(公告)日:2024-01-11
申请号:US17858160
申请日:2022-07-06
Applicant: X Development LLC
Inventor: Joel Emilio Bregman Segre , Raj B. Apte , Philipp H. Schmaelzle , Brian John Adolf
CPC classification number: A61B8/0808 , A61N7/02 , A61B5/4064 , A61N2007/0078
Abstract: A system includes: a form factor device sized and shaped to accommodate a subject's skull; an ultrasound array comprising a plurality of transducer elements attached to the form factor device, wherein the plurality of transducer elements are configured to: emit ultrasound pulses through the subject's skull for performing a neuro-modulation of the subject's brain during use of the system, and receive ultrasound signals from the subject's skull and brain in response to the ultrasound pulses being emitted; and a controller coupled to the ultrasound array, wherein the controller is configured, during use of the system, to: generate at least one image depicting at least a portion of the subject's skull and brain based on, at least in part, the received ultrasound signals received, and adapt the neuro-modulation of the subject's brain based on, at least in part, the at least one image during use of the system.
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公开(公告)号:US20240004002A1
公开(公告)日:2024-01-04
申请号:US18239663
申请日:2023-08-29
Applicant: X Development LLC
Inventor: Stefan Bogdanovic , Stefan Leichenauer
CPC classification number: G01R33/323 , G01N24/10 , G01R33/26
Abstract: A magnetometer includes a sample signal device; a reference signal device; a microwave field generator operable to apply a microwave field to the sample signal device and the reference signal device; an optical source configured to emit light including light of a first wavelength that interacts optically with the sample signal device and with the reference signal device; at least one photodetector arranged to detect a sample photoluminescence signal including light of a second wavelength emitted from the sample signal device and a reference photoluminescence signal including light of the second wavelength emitted from the reference signal device, in which the first wavelength is different from the second wavelength; and a magnet arranged adjacent to the sample signal device and the reference signal device.
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公开(公告)号:US11861263B1
公开(公告)日:2024-01-02
申请号:US17846351
申请日:2022-06-22
Applicant: X Development LLC
Inventor: Thomas Hunt , David Andre , Nisarg Vyas , Rebecca Radkoff , Rishabh Singh
IPC: G06F3/0481 , G06F3/16 , G06F3/0484 , G10L15/22
CPC classification number: G06F3/167 , G06F3/0481 , G06F3/0484 , G10L15/22
Abstract: This specification is generally directed to techniques for robust natural language (NL) based control of computer applications. In many implementations, the NL control is at least selectively interactive in that the user feedback input is solicited, and received, in resolving action(s), resolving action set(s), generating domain specific knowledge, and/or in providing feedback on implemented action set(s). The user feedback input can be utilized in further training of machine learning model(s) utilized in the NL based control of the computer applications.
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