公开(公告)号：US20240403634A1

公开(公告)日：2024-12-05

申请号：US18676339

申请日：2024-05-28

Applicant: Palantir Technologies Inc.

Inventor： Matthew Hawes ,  Ankit Shankar ,  Morten Telling ,  Adil Majid ,  Jack Dobson

IPC: G06N3/08

Abstract: An artificial intelligence system can be used to respond to natural language inputs. The AI System may, for example, receive a first user input for a LLM, generate a first prompt based on the first user input, transmit the first prompt to an LLM, receive an output from the LLM, and evaluate the output from the LLM with reference to one or more validation tests. Responsive to determining that the output from the LLM is not validated, generate a second prompt for the LLM, where the second prompt indicates at least an aspect of the output that caused the output to not be evaluated (e.g., a portion of the output that may need to be updated or corrected), transmit the second prompt to the LLM, and receive an updated output from the LLM. The AI system can include an application for testing functions that utilize interactions with language models.

公开(公告)号：US20240403289A1

公开(公告)日：2024-12-05

申请号：US18674628

申请日：2024-05-24

Applicant: Palantir Technologies Inc.

Inventor： Matthew Hawes ,  Ankit Shankar ,  Morten Telling ,  Jack Dobson ,  Adil Majid

IPC: G06F16/242 ,  G06F16/2455

Abstract: A system may receive a natural language query. A system may receive indications of one or more data object types, wherein each of the one or more data object types is associated with a respective one or more properties. A system may receive references to one or more data sets, wherein the one or more data sets are each associated with at least a respective data object type. A system may transmit a prompt to a large language model (“LLM”), the prompt comprising at least: the natural language query, the indications of the one or more data object types, and the references to the one or more data sets. A system may receive, from the LLM, a response to the prompt, wherein the response includes indications of: at least a first reference to a first data set and a query to be applied to the first data set.

公开(公告)号：US20240403396A1

公开(公告)日：2024-12-05

申请号：US18675587

申请日：2024-05-28

Applicant: Palantir Technologies Inc.

Inventor： Matthew Hawes ,  Ankit Shankar ,  Morten Telling ,  Jack Dobson ,  Adil Majid

IPC: G06F21/31 ,  G06F16/903

Abstract: Computer-implemented systems and methods are disclosed, including for determining permissions for nondeterministic model output. A computer-implemented method may include, for example, receiving one or more user inputs including a first user input providing at least a portion of a first prompt for a query for a first nondeterministic model. A computer-implemented method may in response to receiving the one or more user inputs include: executing the query, by the first nondeterministic model, to generate an output, determining a first one or more data inputs used by the first nondeterministic model during execution of the query, determining a first set of permissions associated with the first one or more data inputs; and applying a second set of permissions to at least a first portion of the output based on the first set of permissions.

公开(公告)号：US20240403194A1

公开(公告)日：2024-12-05

申请号：US18676141

申请日：2024-05-28

Applicant: Palantir Technologies Inc.

Inventor： Matthew Hawes ,  Ankit Shankar ,  Morten Telling ,  Jack Dobson ,  Adil Majid

IPC: G06F11/36

Abstract: The disclosure is directed to methods and systems for improving interactions with a Large Language Model (LLM). An artificial intelligence system (AIS) can receive user inputs via a graphical user interface indicating a task to be performed by the LLM, one or more tools which may be accessed by the AIS in response to tool calls from the LLM, and an output schema for structuring a format of a response from the LLM. The AIS can generate a prompt for the LLM based on the user input. The prompt can include indications of the one or more tools, one or more example tool operations, the task to be performed, and an indication of the output schema. The AIS can include a debugging application or module enabling rich debugging of language model interactions in a single view.