SYSTEMS AND METHODS FOR ANONYMIZING PRIVATE DATA FOR USE IN MACHINE LEARNING MODELS

    公开(公告)号:US20240362363A1

    公开(公告)日:2024-10-31

    申请号:US18646090

    申请日:2024-04-25

    Applicant: Synthpop Inc.

    Abstract: Described herein are techniques for performing a task using a trained external machine learning model. In some embodiments, a user request comprising a task and one or more protected health information (PHI) parameters associated with a patient may be received. Using one or more trained machine learning models, the PHI parameters may be extracted and a revised user request may be generated by replacing the PHI parameters with one or more synthetic PHI parameters. The revised user request may be provided to the trained external machine learning model and a response to the task comprising the synthetic PHI parameters may be received. The trained machine learning models may generate a revised response to the task by replacing the synthetic PHI parameters with the PHI parameters of the user request.

    SPECULATIVE DECODING IN AUTOREGRESSIVE GENERATIVE ARTIFICIAL INTELLIGENCE MODELS

    公开(公告)号:US20240354345A1

    公开(公告)日:2024-10-24

    申请号:US18538912

    申请日:2023-12-13

    CPC classification number: G06F16/9027 G06F40/284

    Abstract: Certain aspects of the present disclosure provide techniques and apparatus for generating a response to a query input in a generative artificial intelligence model. An example method generally includes receiving a plurality of sets of tokens generated based on an input prompt and a first generative artificial intelligence model, each set of tokens in the plurality of sets of tokens corresponding to a candidate response to the input prompt; selecting, using a second generative artificial intelligence model and recursive adjustment of a target distribution associated with the received plurality of sets of tokens, a set of tokens from the plurality of sets of tokens; and outputting the selected set of tokens as a response to the input prompt.

    Multilingual content recommendation pipeline

    公开(公告)号:US12124812B2

    公开(公告)日:2024-10-22

    申请号:US17510850

    申请日:2021-10-26

    CPC classification number: G06F40/56 G06F40/284 G06F40/47

    Abstract: A data processing system implements obtaining first textual content in a first language from a first client device; determining that the first language is supported by a first machine learning model; obtaining a guard list of prohibited terms associated with the first language; determining that the textual content does not include one or more prohibited terms associated based on the guard list; providing the first textual content as an input to the first machine learning model responsive to the textual content not including the one or more prohibited terms; analyzing the first textual content with the first machine learning model to obtain a first content recommendation; obtaining a first content recommendation policy that identifies content associated with the first language that may not be provided as a content recommendation; determining that the first content recommendation is not prohibited; and providing the first content recommendation to the first client device.

    SYSTEMS, DEVICES, AND METHODS FOR GENERATING A DOMAIN NAME USING A USER INTERFACE

    公开(公告)号:US20240340263A1

    公开(公告)日:2024-10-10

    申请号:US18748959

    申请日:2024-06-20

    Inventor: Aubry CHOLLETON

    CPC classification number: H04L61/3025 G06F3/048 G06F40/284 H04L61/302

    Abstract: Embodiments relate to systems, devices, computer-readable media, and computer-implemented methods for generating domain name suggestions by receiving an input string via a user interface, determining an alternative of the input string, determining affixes of the input string, determining top level domains associated with the input string, determining registration availability of domain names including one-step string sequences from the input string based on the alternative input string, the affixes of the input string, and the top level domains associated with the input string, and generating a display for the user interface, where the display includes: the input string, the alternative of the input string, the affixes of the input string, and the top level domains associated with the input string; and indications of the registration availability of the domains names including the one-step string sequences.

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