Palantir Technologies Patente

Systems and methods for code rebasing/conflict resolution are provided. For example, method for rebasing a software project is comprises: determining a set of changes between a branch version and a main version of the software project; identifying, from the set of changes, a conflict between the branch version and the main version; generating a user interface comprising at least one of: a first graphical representation of the conflict as implemented in the main version; or a second graphical representation of the conflict as implemented in the branch version; receiving, via the user interface, user input indicating a resolution for the presented conflict; and updating the branch version of the software project according to the indicated resolution, thereby resolving the conflict to facilitate merging of the branch of the software project onto the main version of the software project; wherein the method is performed using one or more processors.

A computer-implemented method may include: generating an interactive graphical visualization including a first node representing an automation object, a second node representing an action object, and a third node representing a data object type or a data object; determining one or more conditions of the automation object which, when satisfied, trigger an automation of the automation object; determining that the one or more conditions reference the data object or a property; determining that execution of an action of the action object causes the one or more conditions to be satisfied; updating the interactive graphical visualization to include a first edge connecting the second node and the first node to represent that the execution of the action of the action object can cause the one or more conditions to be satisfied to trigger the automation.

Systems and methods for context-aware attachments and large language model (LLM) analyses. An example method includes presenting an assistant application and a development application in a browser, the applications being in communication with a back-end system. Communications are established between the applications using a communication channel. A user prompt and indication of context to be included in an LLM prompt are obtained, with the user prompt and indication of context being routed to the back-end system and the indication of context being specified based on attachment of a repository, a code file being edited in the development application, or a portion of the code file selected in the development application. A response from an LLM is triggered and the response is presented in the assistant application.

Disclosed herein are computing environments and processes for protocol-agnostic inbound data ingestion to securely and intuitively support a wide and varied range of push-based data integrations. An event detector on a perimeter network can receive inbound data from an external system. A data ingestion engine of a permissioned system can access a repository of the permissioned system, can validate the inbound data based on one or more attributes of data in the repository, and can provide a validation indication to the event detector. The event detector can provide the inbound data to the permissioned system responsive to the validation indication from the data ingestion engine.

Computer-implemented systems and methods are disclosed for transitioning interactive workflow graphical user interface generation to local software development environments. A computer-implemented method may include receiving, via interactive user interface and from a user, definitions of one or more data object types including respective one or more properties. A computer-implemented method may execute a build process on the definitions to generate: an ontology definition file; and an ontology software development kit ("SDK"). A computer-implemented method may automatically communicate the ontology definition file to a backend server that may be usable by the backend server to generate an ontology implementation that may be usable in execution of software applications that operate on data objects. A computer-implemented method may include automatically implementing the ontology SDK in the software development environment, wherein the ontology SDK is configured to provide functionality to the software development environment for developing software applications that operate on data objects.

Computer-implemented systems and methods are disclosed, including systems and methods utilizing language models for extracting and resolving entities mentioned in unstructured text data. A computer-implemented method may include at least: receiving first text data from a data source; generating and transmitting a first prompt for a large language model ("LLM"), the first prompt comprising the first text data; receiving a first output from the LLM in response to the first prompt; generating, based at least on the first output, and transmitting a second prompt to the LLM; receiving a second output from the LLM in response to the second prompt, the second output comprising first one or more entities extracted by the LLM from the first part of the first semantically related text portion and first metadata or context associated with the first one or more entities.

In some examples, systems and methods for multiple-sensor object tracking are provided. For example, a method includes: receiving one or more first image transformations generated based on a plurality of previous images from a plurality of sensor feeds respectively; receiving a plurality of images from the plurality of sensor feeds; generating a transformation update based on the one or more image transformations and the plurality of images using an image registration model; generating a second image transformation based on the transformation update and the one or more first image transformations; applying the second image transformation to the plurality of images to generate a set of transformed images; and identifying a plurality of objects using a multiple object tracking model based on the set of transformed images.

In some examples, systems and methods for multiple-sensor object tracking are provided. For example, a method includes: receiving a plurality of tracks generated based on a plurality of images from a plurality of sensor feeds, the plurality of sensor feeds including a first sensor feed and a second sensor feed, the plurality of tracks including a first track detected in a first image from the first sensor feed and a second track detected in a second image from the second sensor feed; determining a candidate association between the first track and the second track; generating an association confidence score corresponding to the candidate association based at least in part on a track history; evaluating whether the candidate association meets one or more association criteria; and in response to the candidate association meeting the one or more association criteria, merging the first track and the second track to generate a merged track; and updating the plurality of tracks to include the merged track replacing the first track and the second track.

In some examples, systems and methods for data mapping are provided. An example method includes a method for data mapping is provided. In some examples, the method includes receiving the unstructured data including text data; receiving one or more extracted data parts from the GenAI model; accessing a hierarchical data model, the hierarchical data model including one or more sub-hierarchies; generating a search prompt using the unstructured data and the one or more highest-level structure elements; providing the search prompt to the GenAI model; receiving one or more identified sub-hierarchies; for each data part of the one or more extracted data parts, traversing each identified sub-hierarchy of the one or more identified sub-hierarchies to determine a list of relevant structure elements in the hierarchical data model based on a relevance scoring; and generating a mapping prompt based on the list of relevant structure elements and the unstructured data.

A computing system can facilitate discovery and one-on-one communication among multiple software applications of a multi-application execution environment. The system can enable software applications to broadcast and/or detect advertisement messages indicative of discoverable software applications and supported capabilities, such as for targeted messaging, sharing state, and/or the like. The system can enable software applications to detect and invoke capabilities of other software applications from outside said software applications. The system can enable software applications to share their states such that states are synchronized among multiple software applications. In some embodiments, the system can cause generation and display of interactive graphical user interfaces (GUIs) and/or of various GUI elements configured to indicate and/or facilitate discovery and/or one-on-one communication among multiple software applications, such as for detecting and invoking functionalities of software applications from outside said software applications, and/or such as for sharing states among multiple software applications.

Computer-implemented systems and methods including language models for providing an application-aware model-based assistant. A computer-implemented method, for communicating with a front end device to generate application specific recommended actions, may include: determining lists of available global and application actions; receiving a user query; generating a first prompt for a language model and providing a first response for display to the user; generating a second prompt for a language model; and in response to receiving an output: parsing the output to generate a list of recommended actions, and providing a second response for display to the user, where the second response includes the third list of recommended actions.

A method performed by one or more processors comprises displaying code, receiving user selection of a portion of code, determining one or more settable data items, generating a template, displaying the template, receiving a user input value for the settable data items by the template, and executing the code with each of the settable data items set to the received user input value. A data processing pipeline is configured to pass a data item to a first transformer to provide first transformed data, store the first transformed data in a temporary memory, write the first transformed data to the data storage system, and pass the transformed data from the temporary memory to a second transformer.

An artificial intelligence system (AIS) can improve relevance of LLM responses through selection of appropriate examples to provide in an enhanced user prompt. The system may receive user inputs indicating a task to be performed by the LLM, determine a set of examples based at least on an initial user prompt and to potentially include in an enhanced user prompt, and determine which examples in the set of examples are ideal to include in the enhanced user prompt to increase the usefulness of the LLM response. The AIS can generate an enhanced prompt for the LLM based on the user input and identified ideal examples. The enhanced prompt can include at least a portion of the initial user input and each of the identified ideal examples.

An artificial intelligence system (AIS) can generate documentation documents describing a user's workflow through capturing meaningful and event-based workflow information to provide in an LLM prompt. The system may receive user inputs indicating start of a workflow capture session, monitor a user's use of a software application for selective, meaningful triggers, generate screen captures based on detected triggers and determine associated metadata. The system may record audio. The system may receive user inputs indicating stop of a workflow capture session, transcribe recorded audio to generate a transcript, and may associate text of the transcript with the generated screen captures based on determined metadata. The AIS can generate a prompt for the LLM based on at least some of the meaningful workflow information. The prompt can include at least some of the generated screen captures and associated metadata, some of the transcript, and instructions to generate a documentation document.

Systems and methods for image matching are provided. An example method includes receiving an incoming image of a first imaging modality; receiving a reference image of a second imaging modality, the second imaging modality being different from the first imaging modality; generating a reference view of the reference image based on one or more priors associated with the incoming image; detecting a plurality of features corresponding to a plurality of feature points in the incoming image using a first algorithm that generates relatively even distribution of the plurality of feature points; generating a plurality of feature descriptors corresponding to the plurality of features, at least one of the plurality of feature descriptors being associated with at least one of a plurality of orientation bins.

In some examples, systems and methods for mixed reality are provided. For example, a method includes: generating a three-dimensional image based on target area data from one or more first data sources; receiving object data associated with one or more digital objects from one or more second data sources; generating an object representation including a representation of at least one of the one or more digital objects based on the object data associated with one or more digital objects; overlaying the object representation on the three-dimensional image to generate a three-dimensional representation; and projecting the three-dimensional representation including the overlaid object representation via a virtual reality device; wherein the method is performed by one or more processors.

In some examples, systems and methods for document writing and/or document generation are provided. For example, a method includes: identifying one or more document types associated with a request, each document type being associated with a document template; extracting one or more pieces of evidence from one or more data records based on the request; accessing one or more routes for document generations, each route of the one or more routes using one or more template-specific computing models; generating one or more documents using the one or more routes; and outputting a selected document that is selected from the one or more generated documents.

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A database system comprised of a decoupled compute layer and storage layer is implemented to store, build, and maintain a canonical dataset, a temporary buffer, and an edits dataset. The canonical dataset is a set of batch updated data. The data is appended in chunks to the canonical dataset such that the canonical dataset becomes a historical dataset over time. The buffer is a write ahead log that contains the most recent chunks of data and provides atomicity and durability for the database system. The edits dataset is the set of data that contains edits such as cell mutations, row appends and/or row deletions. The database system enables users to make cell or row-level edits to tables and observe those edits in analytical systems or downstream builds with minimal latency.

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A computing system accesses one or more data sources to determine maintenance optimization data associated with an asset within a set of assets. The maintenance optimization data may include one or more of: upcoming maintenance events for the asset, such as may be predicted based on analysis of historical maintenance information of the asset, a time series of predicted value of the asset over a time period around the upcoming maintenance event, such as within a few days or hours of the maintenance event, and/or a recommended window of time to initiate and/or perform upcoming maintenance events, which may be based on a combination of the expected upcoming maintenance events, and the time series of predicted value of the particular asset, for example.

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Computing systems methods, and non-transitory storage media are provided for receiving an indication to instantiate an audio or video communication channel, among computing devices, within an application, an artifact, or a resource, obtaining an access control attribute associated with the application, the artifact, or the resource, and instantiating the audio or video communication channel among the computing devices according to the access control attribute.

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According to some embodiments, systems and methods for the present disclosure are directed to managing software security including, for example, controlling software deployment via continuous vulnerability scanning. In certain embodiments, a method for managing software security includes the steps of: initiating a vulnerability scan to a software product based on one or more scan parameters; performing the vulnerability scan to the software product to identify one or more security vulnerabilities using one or more scanners; determining a requirement associated with a first identified security vulnerability of the one or more identified security vulnerabilities; determining one or more actions corresponding to the one or more identified security vulnerabilities.

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