Palantir Technologies Inc.

Ryan Norris

Ankit Shankar

Anshuman Prasad

Casey Patton

Rahij Ramsharan

Arjun Mathur

Andrew Ash

Thomas Mathew

Andy Chen

Mitchell Skiles

Sri Krishna Vempati

Jonathan Victor

Nikhil Taneja

Christopher Wynnyk

Samuel Sinensky

Joanna Peller

Christopher Rogers

Scott Adams

Vinoo Ganesh

Anuraag Bahl

Aydin Keskin

Mackenzie Bohannon

Omar Ali

Philipp Shchekin

Christopher Harding

Akshay Agrawal

Christopher Jeganathan

Frauke Hein

Sudarshan Sanjay Ruikar

Dauren Abdykaparov

Claudia Rafaela Rogoz

Oleh Igorovych Busko

Ndeye Fatou Diop

Computer-implemented systems and methods including language models for explaining and resolving code errors. A computer-implemented method may include: receiving or accessing a log comprising an error message, the error message indicating an error in code; determining the error message from the log; determining a context associated with the error; generating a prompt for a large language model ('LLM'), the prompt comprising at least: the error message, and the context associated with the error; transmitting the prompt to the LLM; and receiving an output from the LLM in response to the prompt, the output comprising at least: an explanation of the error message, and a suggested fix for the error.

Language model assisted error analysis system

A system for troubleshooting network problems is disclosed. A model can use demographic information, network usage information, and network membership information to determine an importance of a problem. The importance of the problem for the user who reported the problem, a number of other users affected by the problem, and the importance of the problem to the other users can be used to determine a priority for resolving the problem. Before and after a work order is executed to resolve the problem, network metrics can be gathered, including aggregate network metrics, and automatically presented in various user interfaces. The analysis of the metrics can be used to update a database of which work orders are assigned in response to which problems.

Computer network troubleshooting

Techniques for implementing a streaming transaction in a transaction based data storage system is disclosed. In an embodiment, a server computer system stores a dataset comprising a plurality of files where the dataset comprises a corresponding version number. The server computer system receives a command to modify the dataset and, in response, starts a streaming transaction for the dataset. During the streaming transaction, the server computer system receives a plurality of updates to the dataset, wherein each of the plurality of updates modifies one or more files of the plurality of files. The server computer system executes the plurality of updates in the dataset without modifying the corresponding version number of the dataset. When the server computer system commits the streaming transaction to the dataset, the server computer system increments the corresponding version number of the dataset.

Processing streaming data in a transaction-based distributed database system

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London, United Kingdom

Ryan Norris