Patents Assigned to AIVITAE LLC
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Publication number: 20240078438Abstract: In some embodiments, a method includes sending, from a first set of computing devices, a distributed instance of a machine learning model to a client computing device, where the client computing device is caused to provide a set of outputs related to the noise data, and where the set of outputs is an output of the distributed instance derived from inputting the noise data into the distributed instance. The method further includes receiving the set of outputs from the client computing device and configuring another instance of the machine learning model based on the noise data and the set of outputs related to the noise data.Type: ApplicationFiled: September 2, 2022Publication date: March 7, 2024Applicant: Aivitae LLCInventor: Bob Sueh-chien HU
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Patent number: 11625608Abstract: Methods and systems are disclosed for improved operation of applications through user interfaces. In some embodiments, the methods and systems relate to training an artificial neural network to complete a task within an application by mimicking and emulating interactions of human operators with the application interface.Type: GrantFiled: June 22, 2021Date of Patent: April 11, 2023Assignee: Aivitae LLCInventors: Bob Sueh-Chien Hu, Steven Chen Reiley
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Patent number: 11593653Abstract: In some embodiments, noise data may be used to train a neural network (or other prediction model). In some embodiments, input noise data may be obtained and provided to a prediction model to obtain an output related to the input noise data (e.g., the output being a prediction related to the input noise data). One or more target output indications may be provided as reference feedback to the prediction model to update one or more portions of the prediction model, wherein the one or more portions of the prediction model are updated based on the related output and the target indications. Subsequent to the portions of the prediction model being updated, a data item may be provided to the prediction model to obtain a prediction related to the data item (e.g., a different version of the data item, a location of an aspect in the data item, etc.).Type: GrantFiled: May 3, 2021Date of Patent: February 28, 2023Assignee: Aivitae LLCInventors: Bob Sueh-chien Hu, Joseph Yitang Cheng
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Publication number: 20220215550Abstract: The present disclosure pertains to autonomous control of an imaging system. In some embodiments, training information including at least a plurality of images and action information are received. The plurality of images and action information are provided to a prediction model to train the prediction model. Further, an image capturing device is controlled to capture an image of a portion of a living organism, the image is processed, via the prediction model, to determine an action to be taken with respect to the image, and the determined action is taken with respect to the image.Type: ApplicationFiled: March 25, 2022Publication date: July 7, 2022Applicant: Aivitae LLCInventor: Bob Sueh-chien HU
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Patent number: 11321827Abstract: The present disclosure pertains to autonomous control of an imaging system. In some embodiments, training information including at least a plurality of images and action information are received. The plurality of images and action information are provided to a prediction model to train the prediction model. Further, an image capturing device is controlled to capture an image of a portion of a living organism, the image is processed, via the prediction model, to determine an action to be taken with respect to the image, and the determined action is taken with respect to the image.Type: GrantFiled: September 4, 2018Date of Patent: May 3, 2022Assignee: Aivitae LLCInventor: Bob Sueh-chien Hu
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Publication number: 20210365783Abstract: In some embodiments, noise data may be used to train a neural network (or other prediction model). In some embodiments, input noise data may be obtained and provided to a prediction model to obtain an output related to the input noise data (e.g., the output being a prediction related to the input noise data). One or more target output indications may be provided as reference feedback to the prediction model to update one or more portions of the prediction model, wherein the one or more portions of the prediction model are updated based on the related output and the target indications. Subsequent to the portions of the prediction model being updated, a data item may be provided to the prediction model to obtain a prediction related to the data item (e.g., a different version of the data item, a location of an aspect in the data item, etc.).Type: ApplicationFiled: May 3, 2021Publication date: November 25, 2021Applicant: Aivitae LLCInventors: Bob Sueh-Chien HU, Joseph Yitang CHENG
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Publication number: 20210312292Abstract: Methods and systems are disclosed for improved operation of applications through user interfaces. In some embodiments, the methods and systems relate to training an artificial neural network to complete a task within an application by mimicking and emulating interactions of human operators with the application interface.Type: ApplicationFiled: June 22, 2021Publication date: October 7, 2021Applicant: Aivitae LLCInventors: Bob Sueh-chien Hu, Steven Chen Reiley
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Patent number: 11068785Abstract: Methods and systems are disclosed for improved operation of applications through user interfaces. In some embodiments, the methods and systems relate to training an artificial neural network to complete a task within an application by mimicking and emulating interactions of human operators with the application interface.Type: GrantFiled: January 31, 2020Date of Patent: July 20, 2021Assignee: Aivitae LLCInventors: Bob Sueh-chien Hu, Steven Chen Reiley
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Patent number: 10997501Abstract: In some embodiments, noise data may be used to train a neural network (or other prediction model). In some embodiments, input noise data may be obtained and provided to a prediction model to obtain an output related to the input noise data (e.g., the output being a prediction related to the input noise data). One or more target output indications may be provided as reference feedback to the prediction model to update one or more portions of the prediction model, wherein the one or more portions of the prediction model are updated based on the related output and the target indications. Subsequent to the portions of the prediction model being updated, a data item may be provided to the prediction model to obtain a prediction related to the data item (e.g., a different version of the data item, a location of an aspect in the data item, etc.).Type: GrantFiled: February 10, 2020Date of Patent: May 4, 2021Assignee: Aivitae LLCInventors: Bob Sueh-chien Hu, Joseph Yitang Cheng
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Publication number: 20200311550Abstract: Methods and systems are disclosed for improved operation of applications through user interfaces. In some embodiments, the methods and systems relate to training an artificial neural network to complete a task within an application by mimicking and emulating interactions of human operators with the application interface.Type: ApplicationFiled: January 31, 2020Publication date: October 1, 2020Applicant: Aivitae LLCInventors: Bob Sueh-chien HU, Steven Chen REILEY
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Patent number: 10726950Abstract: Methods and systems are described for autonomous control of imaging devices. In particular, the methods and system described herein may account for the differences in normalization of training data and/or test data. The methods and systems may process images through an additional customization layer, which itself may comprise an artificial neural network. The additional customization layer is trained to normalize data for specific applications and/or differences between subsets of data.Type: GrantFiled: January 9, 2020Date of Patent: July 28, 2020Assignee: Aivitae LLCInventor: Bob Sueh-chien Hu
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Patent number: 10690735Abstract: In certain embodiments, a coil circuitry component may be configured to detect RF signals from excited spins of at least a region of an organism, where the coil circuitry component comprises a RF detection coil and a detuning circuit for detuning the RF detection coil. A coil signal detection component may be configured to extract at least some of the RF signals detected by the coil circuitry component and to convert the extracted RF signals from analog signal to digital signals. An excitation estimation component may be configured to estimate the excitation pulses from an excitation source and to generate a control timing signal from the estimated excitation pulses to set a state of the detuning circuit. A wireless communication component may be configured to wirelessly transmit the converted RF signals, the estimated excitation pulses, and the control timing signal to an external computer system.Type: GrantFiled: April 26, 2017Date of Patent: June 23, 2020Assignee: Aivitae LLCInventors: Bob Sueh-chien Hu, Ada Shuk-Yan Poon
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Publication number: 20200175368Abstract: In some embodiments, noise data may be used to train a neural network (or other prediction model). In some embodiments, input noise data may be obtained and provided to a prediction model to obtain an output related to the input noise data (e.g., the output being a prediction related to the input noise data). One or more target output indications may be provided as reference feedback to the prediction model to update one or more portions of the prediction model, wherein the one or more portions of the prediction model are updated based on the related output and the target indications. Subsequent to the portions of the prediction model being updated, a data item may be provided to the prediction model to obtain a prediction related to the data item (e.g., a different version of the data item, a location of an aspect in the data item, etc.).Type: ApplicationFiled: February 10, 2020Publication date: June 4, 2020Applicant: Aivitae LLCInventors: Bob Sueh-chien HU, Joseph Yitang CHENG
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Publication number: 20200168320Abstract: Methods and systems are described for autonomous control of imaging devices. In particular, the methods and system described herein may account for the differences in normalization of training data and/or test data. The methods and systems may process images through an additional customization layer, which itself may comprise an artificial neural network. The additional customization layer is trained to normalize data for specific applications and/or differences between subsets of data.Type: ApplicationFiled: January 9, 2020Publication date: May 28, 2020Applicant: Aivitae LLCInventor: Bob Sueh-chien HU
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Patent number: 10607138Abstract: In some embodiments, noise data may be used to train a neural network (or other prediction model). In some embodiments, input noise data may be obtained and provided to a prediction model to obtain an output related to the input noise data (e.g., the output being a prediction related to the input noise data). One or more target output indications may be provided as reference feedback to the prediction model to update one or more portions of the prediction model, wherein the one or more portions of the prediction model are updated based on the related output and the target indications. Subsequent to the portions of the prediction model being updated, a data item may be provided to the prediction model to obtain a prediction related to the data item (e.g., a different version of the data item, a location of an aspect in the data item, etc.).Type: GrantFiled: September 12, 2019Date of Patent: March 31, 2020Assignee: Aivitae LLCInventors: Bob Sueh-chien Hu, Joseph Yitang Cheng
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Publication number: 20200057940Abstract: In some embodiments, noise data may be used to train a neural network (or other prediction model). In some embodiments, input noise data may be obtained and provided to a prediction model to obtain an output related to the input noise data (e.g., the output being a prediction related to the input noise data). One or more target output indications may be provided as reference feedback to the prediction model to update one or more portions of the prediction model, wherein the one or more portions of the prediction model are updated based on the related output and the target indications. Subsequent to the portions of the prediction model being updated, a data item may be provided to the prediction model to obtain a prediction related to the data item (e.g., a different version of the data item, a location of an aspect in the data item, etc.).Type: ApplicationFiled: September 12, 2019Publication date: February 20, 2020Applicant: Aivitae LLCInventors: Bob Sueh-chien Hu, Joseph Yitang Cheng
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Patent number: 10482378Abstract: In some embodiments, noise data may be used to train a neural network (or other prediction model). In some embodiments, input noise data may be obtained and provided to a prediction model to obtain an output related to the input noise data (e.g., the output being a prediction related to the input noise data). One or more target output indications may be provided as reference feedback to the prediction model to update one or more portions of the prediction model, wherein the one or more portions of the prediction model are updated based on the related output and the target indications. Subsequent to the portions of the prediction model being updated, a data item may be provided to the prediction model to obtain a prediction related to the data item (e.g., a different version of the data item, a location of an aspect in the data item, etc.).Type: GrantFiled: February 4, 2019Date of Patent: November 19, 2019Assignee: Aivitae LLCInventors: Bob Sueh-chien Hu, Joseph Yitang Cheng
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Patent number: 10430708Abstract: In some embodiments, noise data may be used to train a neural network (or other prediction model). In some embodiments, input noise data may be obtained and provided to a prediction model to obtain an output related to the input noise data (e.g., the output being a prediction related to the input noise data). One or more target output indications may be provided as reference feedback to the prediction model to update one or more portions of the prediction model, wherein the one or more portions of the prediction model are updated based on the related output and the target indications. Subsequent to the portions of the prediction model being updated, a data item may be provided to the prediction model to obtain a prediction related to the data item (e.g., a different version of the data item, a location of an aspect in the data item, etc.).Type: GrantFiled: October 26, 2018Date of Patent: October 1, 2019Assignee: AIVITAE LLCInventors: Bob Sueh-chien Hu, Joseph Yitang Cheng
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Patent number: 10121104Abstract: In some embodiments, anomaly detection may be facilitated via a multi-neural-network architecture. In some embodiments, a first neural network may be configured to generate hidden representations of data items corresponding to a concept. A second neural network may be configured to generate reconstructions of the data items from the hidden representations. The first neural network may be configured to assess the reconstructions against the data items and update configurations of the first neural network based on the assessment of the reconstructions. Subsequent to the update of the first neural network, the first neural network may generate a hidden representation of a first data item from the first data item. The second neural network may generate a reconstruction of the first data item from the hidden representation. An anomaly in the first data item may be detected based on differences between the first data item and the reconstruction.Type: GrantFiled: July 9, 2018Date of Patent: November 6, 2018Assignee: AIVITAE LLCInventor: Bob Hu