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    Ultrasonic speech recognition
    14.
    发明授权
    Ultrasonic speech recognition 有权

    公开(公告)号：US11323800B2

    公开(公告)日：2022-05-03

    申请号：US16842241

    申请日：2020-04-07

    Applicant: X Development LLC

    Inventor： Thomas Peter Hunt

    IPC: G10L15/28 ,  H04R1/46

    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for analyzing ultrasonic signals to recognize mouthed articulations. One of the methods includes generating an ultrasonic carrier signal and coupling the ultrasonic carrier signal to a person's vocal tract. The method includes detecting a modulated ultrasonic signal, the modulated ultrasonic signal corresponding to the ultrasonic carrier signal modulated by the person's vocal tract to include information about articulations mouthed by the person; analyzing, using a data processing apparatus, the modulated ultrasonic signal to recognize the articulations mouthed by the person from the information in the modulated ultrasonic signal; and generating, using the data processing apparatus, an output in response to the recognized articulations.

    NUCLEAR RADIATION DETECTION
    16.
    发明公开
    NUCLEAR RADIATION DETECTION 审中-公开

    公开(公告)号：US20230194735A1

    公开(公告)日：2023-06-22

    申请号：US18164380

    申请日：2023-02-03

    Applicant: X Development LLC

    Inventor： Thomas Peter Hunt

    IPC: G01T3/06 ,  G01T7/02

    CPC classification number: G01T3/06 ,  G01T7/02

    Abstract: A nuclear radiation detector is disclosed. The detector includes a housing including therein: a scintillator; and a multi-pixel optical sensor positioned, relative to the scintillator, to receive photons emitted by the scintillator in response to interactions with nuclear radiation. The housing isolates the scintillator and the multi-pixel optical sensor from external light. The detector includes one or more processors operably connectable to the multi-pixel optical sensor; and one or more data stores coupled to the processors having instructions stored thereon which cause the processors to perform operations. The operations include: responsive to the multi-pixel optical sensor detecting photons emitted by the scintillator, receiving, from the multi-pixel optical sensor, data signals indicating 1) spatial locations of individual pixels that detected the photons and 2) temporal data indicating when the detections occurred; and generating, from the data signals, a spatially and temporally resolved image of radiation incident on the scintillator.

    Subsurface lithological model with machine learning
    17.
    发明授权
    Subsurface lithological model with machine learning 有权

    公开(公告)号：US11592594B2

    公开(公告)日：2023-02-28

    申请号：US17229391

    申请日：2021-04-13

    Applicant: X Development LLC

    Inventor： Kenton Lee Prindle ,  Artem Goncharuk ,  Neil David Treat ,  Kevin Forsythe Smith ,  Thomas Peter Hunt ,  Karen R Davis ,  Allen Richard Zhao

    IPC: G01V99/00 ,  G01V1/28

    Abstract: This disclosure describes a system and method for generating a subsurface model representing lithological characteristics and attributes of the subsurface of a celestial body or planet. By automatically ingesting data from many sources, a machine learning system can infer information about the characteristics of regions of the subsurface and build a model representing the subsurface rock properties. In some cases, this can provide information about a region using inferred data, where no direct measurements have been taken. Remote sensing data, such as aerial or satellite imagery, gravimetric data, magnetic field data, electromagnetic data, and other information can be readily collected or is already available at scale. Lithological attributes and characteristics present in available geoscience data can be correlated with related remote sensing data using a machine learning model, which can then infer lithological attributes and characteristics for regions where remote sensing data is available, but geoscience data is not.

    SYSTEMS AND METHODS FOR BRAIN IMAGING AND STIMULATION USING SUPER-RESOLUTION ULTRASOUND
    18.
    发明申请
    SYSTEMS AND METHODS FOR BRAIN IMAGING AND STIMULATION USING SUPER-RESOLUTION ULTRASOUND 有权

    公开(公告)号：US20220379142A1

    公开(公告)日：2022-12-01

    申请号：US17335426

    申请日：2021-06-01

    Applicant: X Development LLC

    Inventor： Matthew Dixon Eisaman ,  Thomas Peter Hunt ,  Vladimir Miskovic ,  Benoit Schillings

    IPC: A61N7/00 ,  A61B8/08 ,  A61N1/36 ,  A61N2/00 ,  G16H20/30 ,  G16H50/50

    Abstract: A system includes ultrasound transducers configured to generate and direct ultrasound beams at a region within a portion of a subject's brain, sensors configured to measure a response from the portion of the subject's brain in response to one or more ultrasound beams, and an electronic controller in communication with the ultrasound transducers configured to generate, based on a measured response from the portion of the subject's brain in response to two or more ultrasound beams generated from two or more different angles, a model of the portion of the subject's brain, wherein the model has a higher resolution than a maximum resolution of a single ultrasound beam, and generate, based on the model of the portion of the subject's brain, stimulation parameters for the ultrasound transducers to generate and direct a stimulation ultrasound beam at the region within the portion of the subject's brain.

    Blast patterns
    19.
    发明授权
    Blast patterns 有权

    公开(公告)号：US11475659B2

    公开(公告)日：2022-10-18

    申请号：US16991757

    申请日：2020-08-12

    Applicant: X Development LLC

    Inventor： Neil David Treat ,  Thomas Peter Hunt ,  Artem Goncharuk ,  Karen R Davis ,  Vikram Neal Sahney

    IPC: G06T17/00 ,  G06V20/13 ,  F42D3/04 ,  G06K9/62 ,  G06N3/08 ,  G06V10/25

    Abstract: Techniques for improving a blast pattern at a mining site include conducting an initial blast and recording the initial blast as a high speed optical video. The high speed optical video, and the blast pattern used in the initial blast are sent as inputs to a machine learning model, which correlates one or more characteristics of the region being blasted with measurements associated with characteristics of the region being blasted obtained from the high speed optical video. The machine learning model can then determine an improved blast pattern based on the correlation made. This improved blast pattern can be displayed on a user computing device, or transmitted to a drilling system to automatically drill the improved blast pattern for subsequent blasts.

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