Palantir Technologies Inc. patent applications on October 24th, 2024
Patent Applications by Palantir Technologies Inc. on October 24th, 2024
Palantir Technologies Inc.: 9 patent applications
Palantir Technologies Inc. has applied for patents in the areas of G06F21/62 (3), G06F16/33 (2), G06F16/36 (2), G06F16/23 (1), G06F18/2415 (1) G06F16/367 (2), G06F16/2336 (1), G06F16/3344 (1), G06F21/6209 (1), G06F21/6227 (1)
With keywords such as: data, ontology, user, methods, object, disclosed, access, programmed, updates, and client in patent application abstracts.
Patent Applications by Palantir Technologies Inc.
Inventor(s): JAMES BAKER of Maidenhead (GB) for palantir technologies inc., XAVIER FALCO of London (GB) for palantir technologies inc., SAMUEL FLAVIO BARROSO SOUZA of London (GB) for palantir technologies inc., HELEN YU of New York NY (US) for palantir technologies inc., AMR AL MALLAH of Tacoma WA (US) for palantir technologies inc., YIXUN XU of Jersey City NJ (US) for palantir technologies inc., ARSENY BOGOMOLOV of Arlington VA (US) for palantir technologies inc.
IPC Code(s): G06F16/23
CPC Code(s): G06F16/2336
Abstract: a system for resolving conflicts between data source updates and user edits to an ontology before applying the resulting changes to the ontology and related methods are disclosed. the system is programmed to receive data source updates from data sources and transform the data source updates to updates to ontology data. the system is also programmed to receive edits to ontology data from user accounts. the system is programmed to review these updates or edits to the ontology and resolve conflicts according to a predetermined strategy, such as prioritizing a user edit over a data source update. the resulting changes are incorporated to one or more databases where representations of the ontology data are stored.
Inventor(s): Anirvan Mukherjee of Brooklyn NY (US) for palantir technologies inc., Craig De Souza of Jersey City NJ (US) for palantir technologies inc., Edgar Gomes de Araujo of Sao Paulo (BR) for palantir technologies inc., Johannes Beil of Copenhagen (DK) for palantir technologies inc., Jessica Winssinger of New York NY (US) for palantir technologies inc., Michael Zullo of Scarsdale NY (US) for palantir technologies inc., Rushad Heerjee of New York NY (US) for palantir technologies inc., Shubhankar Sachdev of New York NY (US) for palantir technologies inc.
IPC Code(s): G06F16/33, G06F18/2415
CPC Code(s): G06F16/3344
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.
Inventor(s): JAMES BAKER of Maidenhead (GB) for palantir technologies inc., XAVIER FALCO of London (GB) for palantir technologies inc., SAMUEL FLAVIO BARROSO SOUZA of London (GB) for palantir technologies inc., HELEN YU of New York NY (US) for palantir technologies inc., AMR AL MALLAH of Tacoma WA (US) for palantir technologies inc., YIXUN XU of Jersey City NJ (US) for palantir technologies inc., ARSENY BOGOMOLOV of Arlington VA (US) for palantir technologies inc.
IPC Code(s): G06F16/36
CPC Code(s): G06F16/367
Abstract: a system for indexing changes to an ontology into multiple databases and related methods are disclosed. the system is programmed to receive original data from data sources, transform the original data to ontology data, represent the ontology data in multiple forms respectively in the multiple databases, and process requests to access the ontology data from user accounts using the multiple databases. the system is programmed to subsequently merge changes to the ontology data based on updates from the data sources and edits from user accounts, create index data for the merged changes, and transmit the index data to the multiple databases.
Inventor(s): JAMES BAKER of Maidenhead (GB) for palantir technologies inc., XAVIER FALCO of London (GB) for palantir technologies inc., SAMUEL FLAVIO BARROSO SOUZA of London (GB) for palantir technologies inc., HELEN YU of New York NY (US) for palantir technologies inc., AMR AL MALLAH of Tacoma WA (US) for palantir technologies inc., YIXUN XU of Jersey City NJ (US) for palantir technologies inc., ARSENY BOGOMOLOV of Arlington VA (US) for palantir technologies inc.
IPC Code(s): G06F16/36, G06F21/62
CPC Code(s): G06F16/367
Abstract: a system for enabling granular access control over ontology data and related methods are disclosed. the system is programmed to receive data source updates from data sources having respective sets of permissions for access control, transform the data source updates to changes to an ontology, and control access to the ontology based on the sets of permissions. the system is further programmed to receive a specification of one or more rules referencing attributes of user accounts or properties of ontology entities and corresponding one or more lists of permissions. the system is programmed to then enforce a security policy based on the specification to further control access to the ontology.
Inventor(s): Peter WILCZYNSKI of San Francisco CA (US) for palantir technologies inc., Stephen FREIBERG of Denver CO (US) for palantir technologies inc.
IPC Code(s): G06F21/62, H04L9/40
CPC Code(s): G06F21/6209
Abstract: systems and methods are provided for obtaining a request for a data object or a data structure from a client; determining an access level of the client and one or more access permissions of the requested data object or data structure; determining whether to transmit the requested data object or data structure to the client based on the access level of the client and the one or more access permissions; and transmitting the requested data object or data structure to the client.
Inventor(s): Anirvan Mukherjee of Brooklyn NY (US) for palantir technologies inc., Craig De Souza of Jersey City NY (US) for palantir technologies inc., Edgar Gomes de Araujo of Sao Paulo (BR) for palantir technologies inc., Johannes Beil of Copenhagen (DK) for palantir technologies inc., Jessica Winssinger of New York NY (US) for palantir technologies inc., Michael Zullo of Scarsdale NY (US) for palantir technologies inc., Rushad Heerjee of New York NY (US) for palantir technologies inc., Shubhankar Sachdev of New York NY (US) for palantir technologies inc.
IPC Code(s): G06F21/62, G06F16/33
CPC Code(s): G06F21/6227
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.
Inventor(s): Anirvan Mukherjee of Brooklyn NY (US) for palantir technologies inc., Craig De Souza of Jersey City NJ (US) for palantir technologies inc., Edgar Gomes de Araujo of Sao Paulo (BR) for palantir technologies inc., Johannes Beil of Copenhagen (DK) for palantir technologies inc., Jessica Winssinger of New York NY (US) for palantir technologies inc., Michael Zullo of Scarsdale NY (US) for palantir technologies inc., Rushad Heerjee of New York NY (US) for palantir technologies inc., Shubhankar Sachdev of New York NY (US) for palantir technologies inc.
IPC Code(s): G06N3/0895
CPC Code(s): 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.
20240354646. OPERATIONALISING FEEDBACK LOOPS_simplified_abstract_(palantir technologies inc.)
Inventor(s): Alexander Edwards of London (GB) for palantir technologies inc., Anirvan Mukherjee of Brooklyn NY (US) for palantir technologies inc., David Kebudi of New York NY (US) for palantir technologies inc., Megha Arora of London (GB) for palantir technologies inc., Sriram Krishnan of Jersey City NJ (US) for palantir technologies inc., Max-Philipp Schrader of Germering (DE) for palantir technologies inc., Jessica Winssinger of New York NY (US) for palantir technologies inc., Philipp Hoefer of Munich (DE) for palantir technologies inc.
IPC Code(s): G06N20/00
CPC Code(s): 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.
Inventor(s): Tom Haramaty of Tel Aviv (IL) for palantir technologies inc., Alon Salhov of Tel Aviv (IL) for palantir technologies inc., Sid Sampangi of Millbrae CA (US) for palantir technologies inc., Ethan Van Andel of Berkeley CA (US) for palantir technologies inc.
IPC Code(s): G06T17/05, G06T15/08
CPC Code(s): G06T17/05
Abstract: a plurality of images is obtained, whether as separate images or part of a video. the plurality of images is used to generate a three-dimensional (3d) model of the imagery. the 3d model is registered to a geographic coordinate system as a first registered 3d model. the first registered 3d model is merged with a second registered 3d model to generate a merged 3d model. a request including a value corresponding to a location within the geographic coordinate system that includes at least a portion of the merged 3d model is received from a client device. a message identifying at least a subset of points in the portion of the merged 3d model is sent to the client device, each point in the subset having a three-dimensional coordinate.
Palantir Technologies Inc. patent applications on October 24th, 2024
