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公开(公告)号：US12299022B2
公开(公告)日：2025-05-13
申请号：US18632900
申请日：2024-04-11
Applicant: Palantir Technologies Inc.
Inventor： Anirvan Mukherjee , Craig De Souza , Edgar Gomes de Araujo , Johannes Beil , Jessica Winssinger , Michael Zullo , Rushad Heerjee , Shubhankar Sachdev
IPC: G06F16/00 , G06F16/334 , G06F18/2415 , G06N3/0895
Abstract: Computer-implemented systems and methods are disclosed, including systems and methods utilizing language models for generating data objects and/or updating an ontology. A computer-implemented method may include: employing one or more large language models (“LLMs”) to generate at least a data triple and a classified triple; executing, using the classified triple, a similarity search with reference to an ontology to determine that the classified triple at least partially matches one or more data object types defined in the ontology; in response to the determination, adding into a first database at least a first data object of a first data object type that represents a first entity in the data triple and a second data object of a second data object type that represents a second entity in the data triple.
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公开(公告)号：US20250110753A1
公开(公告)日：2025-04-03
申请号：US18794904
申请日：2024-08-05
Applicant: Palantir Technologies Inc.
Inventor： Johannes Beil , Pavlo Tyshevskyi , Max-Philipp Schrader , Sriram Krishnan , Michael Zullo , Rushad Heerjee , Anirvan Mukherjee
Abstract: Computer-implemented systems and methods are disclosed, including systems and methods for automatically solving problems. A computer-implemented method may include: by an agent service configured to interact with an LLM to complete a run: providing an LLM with access to a state machine, executing an initial state of the state machine with the LLM, determining a subsequent state of the state machine based on at least an initial LLM output, and executing the subsequent state of the state machine.
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公开(公告)号：US20240354646A1
公开(公告)日：2024-10-24
申请号：US18639394
申请日：2024-04-18
Applicant: Palantir Technologies Inc.
Inventor： Alexander Edwards , Anirvan Mukherjee , David Kebudi , Megha Arora , Sriram Krishnan , Max-Philipp Schrader , Jessica Winssinger , Philipp Hoefer
IPC: G06N20/00
CPC classification number: G06N20/00
Abstract: Disclosed herein is a method of providing feedback to a machine learning model. The method includes allowing a user to observe an output of a trained machine learning model; allowing the user to input feedback to the machine learning model based on the output, wherein the feedback is on at least one of a model level or on a training dataset level; and incorporating the feedback into the machine learning model to improve the machine learning model, wherein the method is performed using one or more processors. Disclosed herein are one or more computer-readable storage media including computer executable instructions which when executed by the one or more processors cause the one or more processors to perform the method. Disclosed herein is a computer system which includes one or more processors and one or more computer-readable storage media which include computer executable instructions which when executed by the one or more processors cause the one or more processors to perform the method.
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公开(公告)号：US11861515B2
公开(公告)日：2024-01-02
申请号：US17961822
申请日：2022-10-07
Applicant: Palantir Technologies Inc.
Inventor： Daniel Erenrich , Anirvan Mukherjee
IPC: G06N5/048 , G06Q30/01 , G06F16/2455 , G06Q30/0202 , G06N7/00 , G06Q30/0201 , G06N7/01
CPC classification number: G06N5/048 , G06F16/2455 , G06N7/01 , G06Q30/01 , G06Q30/0202 , G06Q30/0201
Abstract: Systems and methods are disclosed for determining a propensity of an entity to take a specified action. In accordance with one implementation, a method is provided for determining the propensity. The method includes, for example, accessing one or more data sources, the one or more data sources including information associated with the entity, forming a record associated with the entity by integrating the information from the one or more data sources, generating, based on the record, one or more features associated with the entity, processing the one or more features to determine the propensity of the entity to take the specified action, and outputting the propensity.
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公开(公告)号：US20230081135A1
公开(公告)日：2023-03-16
申请号：US18051035
申请日：2022-10-31
Applicant: Palantir Technologies Inc.
Inventor： David Lisuk , Daniel Erenrich , Guodong Xu , Luis Voloch , Rahul Agarwal , Simon Slowik , Aleksandr Zamoshichin , Andre Frederico Cavalheiro Menck , Anirvan Mukherjee , Daniel Chin
IPC: G06F16/18 , G06N7/00 , G06F16/13 , G06F16/188 , G06F30/00
Abstract: A model management system provides a centralized repository for storing and accessing models. The model management system receives an input to store a model object in a first model state generated based on a first set of known variables. The model management system generates a first file including a first set of functions defining the first model state and associates the first file with a model key identifying the model object. The model management system receives an input to store the model object in a second model state having been generated based on the first model state and a second set of known variables. The model management system generates a second file including a second set of functions defining the second model state and associates the second file with the model key. The model management system identifies available versions of the model object based on the model key.
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Patent Agency Ranking
公开(公告)号：US11521096B2
公开(公告)日：2022-12-06
申请号：US15689757
申请日：2017-08-29
Applicant: Palantir Technologies Inc.
Inventor： Daniel Erenrich , Anirvan Mukherjee
IPC: G06N5/04 , G06N7/00 , G06Q30/00 , G06F16/2455 , G06Q30/02
Abstract: Systems and methods are disclosed for determining a propensity of an entity to take a specified action. In accordance with one implementation, a method is provided for determining the propensity. The method includes, for example, accessing one or more data sources, the one or more data sources including information associated with the entity, forming a record associated with the entity by integrating the information from the one or more data sources, generating, based on the record, one or more features associated with the entity, processing the one or more features to determine the propensity of the entity to take the specified action, and outputting the propensity.
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公开(公告)号：US20240354584A1
公开(公告)日：2024-10-24
申请号：US18632958
申请日：2024-04-11
Applicant: Palantir Technologies Inc.
Inventor： Anirvan Mukherjee , Craig De Souza , Edgar Gomes de Araujo , Johannes Beil , Jessica Winssinger , Michael Zullo , Rushad Heerjee , Shubhankar Sachdev
IPC: G06N3/0895
CPC classification number: G06N3/0895
Abstract: Computer-implemented systems and methods are disclosed, including systems and methods utilizing language models for creating and/or updating an ontology. A computer-implemented method may include: receiving tabular data from one or more data sources; generating an interactive graphical representation of at least a portion of the tabular data and connections between the portion of the tabular data; providing, via a user interface, the interactive graphical representation; receiving a user operation via the user interface, updating an ontology and/or generating transformations for adding data objects into a database.
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公开(公告)号：US20240354436A1
公开(公告)日：2024-10-24
申请号：US18505912
申请日：2023-11-09
Applicant: Palantir Technologies Inc.
Inventor： Anirvan Mukherjee , Craig De Souza , Edgar Gomes de Araujo , Johannes Beil , Jessica Winssinger , Michael Zullo , Rushad Heerjee , Shubhankar Sachdev
CPC classification number: G06F21/6227 , G06F16/3344 , G06F16/3347
Abstract: Computer-implemented systems and methods are disclosed, including systems and methods utilizing language models for searching a large corpus of data. A computer-implemented method may include: receiving a first user input comprising a natural language query; vectorizing the first user input into a query vector; executing, using the query vector, a similarity search in a document search model to identify one or more similar document portions, where the document search model includes a plurality of vectors corresponding to a plurality of portions of a set of documents; generating a first prompt for a large language model (“LLM”), the first prompt including at least the first user input, and the one or more similar document portions; transmitting the first prompt to the LLM; receiving a first output from the LLM in response to the first prompt; and providing, via a user interface, the first output from the LLM.
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公开(公告)号：US20240152490A1
公开(公告)日：2024-05-09
申请号：US18415253
申请日：2024-01-17
Applicant: Palantir Technologies Inc.
Inventor： David Lisuk , Daniel Erenrich , Guodong Xu , Luis Voloch , Rahul Agarwal , Simon Slowik , Aleksandr Zamoshchin , Andre Frederico Cavalheiro Menck , Anirvan Mukherjee , Daniel Chin
IPC: G06F16/18 , G06F16/13 , G06F16/188 , G06F30/00 , G06N7/00
CPC classification number: G06F16/1873 , G06F16/13 , G06F16/196 , G06F30/00 , G06N7/00 , G06F2111/20
Abstract: A model management system provides a centralized repository for storing and accessing models. The model management system receives an input to store a model object in a first model state generated based on a first set of known variables. The model management system generates a first file including a first set of functions defining the first model state and associates the first file with a model key identifying the model object. The model management system receives an input to store the model object in a second model state having been generated based on the first model state and a second set of known variables. The model management system generates a second file including a second set of functions defining the second model state and associates the second file with the model key. The model management system identifies available versions of the model object based on the model key.
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公开(公告)号：US11907175B2
公开(公告)日：2024-02-20
申请号：US18051035
申请日：2022-10-31
Applicant: Palantir Technologies Inc.
Inventor： David Lisuk , Daniel Erenrich , Guodong Xu , Luis Voloch , Rahul Agarwal , Simon Slowik , Aleksandr Zamoshchin , Andre Frederico Cavalheiro Menck , Anirvan Mukherjee , Daniel Chin
IPC: G06F16/00 , G06F16/18 , G06N7/00 , G06F16/13 , G06F16/188 , G06F30/00 , G06F111/20
CPC classification number: G06F16/1873 , G06F16/13 , G06F16/196 , G06F30/00 , G06N7/00 , G06F2111/20
Abstract: A model management system provides a centralized repository for storing and accessing models. The model management system receives an input to store a model object in a first model state generated based on a first set of known variables. The model management system generates a first file including a first set of functions defining the first model state and associates the first file with a model key identifying the model object. The model management system receives an input to store the model object in a second model state having been generated based on the first model state and a second set of known variables. The model management system generates a second file including a second set of functions defining the second model state and associates the second file with the model key. The model management system identifies available versions of the model object based on the model key.
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