Palantir Technologies Inc.

Thomas Powell

Andre Frederico Cavalheiro Menck

Peter Maag

Ezra Spiro

Mark Elliot

Myles Scolnick

Jim Inoue

Lawrence Manning

Spencer Tank

Bianca Rahill-Marier

Anshuman Prasad

Arthur Thouzeau

Jasjit Grewal

Samuel Rogerson

Benjamin Lee

Joanna Peller

Charles Shepherd

Nitish Kulkarni

Benjamin Grabham

Caroline Henry

Jennifer Yip

Marco Diciolla

Matthew Todd

Arion Sprague

Gregoire Omont

Andrew Kaier

Corey Garvey

Robert Fink

Benjamin Duffield

Eric A Lee

Thomas Pearson

Audrey Kuan

Samantha Woodward

Willi Raschkowski

Michael Xiaoxuan Yang

Jack Grossman

Quentin Spencer-Harper

Steven Fackler

Ryan Rowe

William Seaton

Andy Chen

Rick Ducott

Maciej Albin

Andrew Poh

Paul Gribelyuk

Aakash Goenka

Richard Niemi

Jonah Scheinerman

Alexander Taheri

Jeremy Kong

Thomas Mcintyre

Diogo Bonfim Moraes Morant De Holanda

Tarik Benabdallah

Subbanarasimhiah Harish

Andrew Higgins

Tao Wei

Kyle Patron

Francis Screene

Ragnar Vorel

Pierre Lucotte

Tam-Sanh Nguyen

Alexandru Antihi

Alexandru-Viorel Antihi

Eric C Lee

Systems, methods, and non-transitory computer-readable media can be configured to perform receiving a notification of a maintenance event associated with a resource. The method includes retrieving historic maintenance data in relation to the resource with which the fault is associated, the maintenance information originating from a time period preceding the time of the maintenance event. The method includes identifying at least a portion of the retrieved historic maintenance data as being indicative of the maintenance event. The method also includes causing the portion of the retrieved historic maintenance data identified as being indicative of the maintenance event to be stored as a precursor signal of the maintenance event. The method also includes causing future maintenance data received from a plurality of resources related to the resource with which the maintenance event is associated to be monitored to predict a future occurrence of the maintenance event in the plurality of resources.

Predictive modelling

Systems and methods are provided for enhanced processing of time series data via parallelization of instructions. An example method includes receiving a query indicating time series datasets and operations to be performed on the time series datasets. Nodes associated with the query are identified, with each node associated with a time series dataset. Nodes associated with operations to be performed are generated. The nodes are assembled into query tree, with parent nodes of the query tree indicating operations that are to be applied to children nodes. Instructions for processing the query tree are generated. At least a subset of the instructions is provided to one or more compute systems for processing in parallel. Results are received, and presented in a user interface.

Enhanced processing of time series data via parallelization of instructions

An apparatus, and a method, performed by one or more processors are disclosed. The method receives a build request associated with performing an external data processing task on a first data set, the first data set being stored in memory associated with a data processing platform to be performed at a system external to the data processing platform. The method generates a task identifier for the data processing task, and provides, in association with the task identifier, the first data set to an agent associated with the external system with an indication of the data processing task, the agent being arranged to cause performance of the task at the external system, to receive a second data set resulting from performance of the task, and to provide the second data set and associated metadata indicative of the transformation. The method receives the second data set and metadata from the agent associated with the external system and stores the second data set and associated metadata.

Providing external access to a processing platform

An apparatus, and a method, performed by one or more processors are disclosed. The method receives a build request associated with performing an external data processing task on a first data set, the first data set being stored in memory associated with a data processing platform to be performed at a system external to the data processing platform. The method generates a task identifier for the data processing task, and providing, in association with the task identifier, the first data set to an agent associated with the external system with an indication of the data processing task, the agent being arranged to cause performance of the task at the external system, to receive a second data set resulting from performance of the task, and to provide the second data set and associated metadata indicative of the transformation. The method receives the second data set and metadata from the agent associated with the external system and stores the second data set and associated metadata.

A method performed by one or more processors, and an apparatus is disclosed. The method may comprise identifying a request from a custom computer program within a sandbox to perform an operation not permitted within the sandbox, and receiving a first indication of security privileges associated with a provider of the custom computer program. The method may also comprise selectively causing the operation to be performed based on the first indication of security privileges.

Security system and method

Systems and methods are provided for identifying relationships between defects. The system may obtain defect items and associated information. Defect items may be compared to one another based on their attributes to determine how related they are. According to the comparisons, defect items may be grouped together into issue items for further analysis by a user. The system may further update a defect comparison model according to user interaction with defect items.

Systems and methods for determining relationships between defects

Systems, methods, non-transitory computer readable media can be configured to access a plurality of sensor logs corresponding to a first machine, each sensor log spanning at least a first period; access first computer readable logs corresponding to the first machine, each computer readable log spanning at least the first period, the computer readable logs comprising a maintenance log comprising a plurality of maintenance task objects, each maintenance task object comprising a time and a maintenance task type; determine a set of statistical metrics derived from the sensor logs; determine a set of log metrics derived from the computer readable logs; and determine, using a risk model that receives the statistical metrics and log metrics as inputs, fault probabilities or risk scores indicative of one or more fault types occurring in the first machine within a second period.

Machine fault modelling

An apparatus, and a method, performed by one or more processors are disclosed. The method may comprise receiving a build request associated with performing an external data processing task on a first data set, the first data set being stored in memory associated with a data processing platform to be performed at a system external to the data processing platform. The method may also comprise generating a task identifier for the data processing task, and providing, in association with the task identifier, the first data set to an agent associated with the external system with an indication of the data processing task, the agent being arranged to cause performance of the task at the external system, to receive a second data set resulting from performance of the task, and to provide the second data set and associated metadata indicative of the transformation. The method may also comprise receiving the second data set and metadata from the agent associated with the external system and storing the second data set and associated metadata.

Systems and methods are provided for providing an object platform for datasets A definition of an object may be obtained. The object may be associated with information stored in one or more datasets. The information may be determined based at least in part on the definition of the object. The object may be stored in a cache such that the information associated with the object is also stored in the cache. One or more interfaces through which requests to perform one or more operations on the object are able to be submitted may be provided.

Systems and methods for providing an object platform for datasets

A method of assigning a task to a resource in a multiple resource environment is performed by one or more processors or special-purpose computing hardware. The method includes receiving task information relating to at least one task to be performed by a resource in the multiple resource environment. The method also includes determining a cost value for each task, the cost value indicating a cost incurred if a maintenance event occurs during performance of the respective task. The method also includes receiving predictive maintenance information in relation to each of the multiple resources in the multiple resource environment, the predictive maintenance information indicating a likelihood of a maintenance event with respect to each of the multiple resources in the multiple resource environment. The method also includes allocating the at least one task to one of the resources in the multiple resource environment dependent on the predictive maintenance information of the multiple resources and the calculated cost score.

Task allocation

Systems, methods, non-transitory computer readable media can be configured to accessing a target sensor log corresponding to a first machine; accessing one or more prior sensor logs corresponding to the first machine and one or more prior sensor logs corresponding to a plurality of second machines which are of the same type as the first machine; accessing a plurality of computer readable logs corresponding to the first machine and the second machines, the computer readable logs for each second machine comprising a maintenance log comprising a plurality of maintenance task objects, each maintenance task object comprising a time and a maintenance task type; determining a set of statistical metrics characterising a difference between the target sensor log and each prior sensor log; selecting a sub-set of the prior sensor logs in dependence upon the statistical metrics; analysing the maintenance logs to correlate each prior sensor log included in the subset to one or more correlated maintenance tasks; selecting a priority maintenance task based on the sub-set of prior sensor logs, t and the correlated maintenance tasks; and outputting the priority maintenance task.

Determining maintenance for a machine

Growing community of inventors

London, United Kingdom

Thomas Powell