US 2024/0202582 A1Published application

Multi-stage machine learning model chaining

AssigneeMicrosoft Technology Licensing, LLC

InventorsSamuel Edward SCHILLACE, Umesh MADAN, Devis LUCATO

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Abstract

A skill chain comprised of a set of ML model evaluations with which to process an input is generated and used to ultimately produce a model output accordingly. Each ML model evaluation corresponds to a “model skill” of the skill chain. Intermediate output that is generated by a first ML evaluation for a first model skill of the skill chain may subsequently be processed as input to a second ML evaluation for a second model skill of the skill chain, thereby ultimately generating model output for the given input. Such a skill chain can include any number skills according to any of a variety of structures and need not be evaluations using the same ML model.

Claims20

Dependent claims

A system comprising:

at least one processor;
and
memory storing instructions that, when executed by the at least one processor, cause the system to perform a set of operations, the set of operations comprising:
obtaining user input from a user;
generating, based on the user input, a skill chain that includes a set of skills with which to process the user input;
for a first model skill of the skill chain:
generating, based on a first prompt template associated with the first model skill, a first prompt that includes at least a part of the obtained user input;
and
processing, using a first machine learning model associated with the first model skill, the first prompt to obtain intermediate output;
for a second model skill of the skill chain:
generating, based on a second prompt template associated with the second model skill, a second prompt that includes at least a part of the intermediate output as input for the second model skill;
and
processing, using a second machine learning model associated with the second model skill, the second prompt to obtain model output;
and
providing an indication of the model output for display to the user.

12 more elements

A method, comprising:

obtaining user input from a user;
generating, based on the user input, a skill chain that includes a set of skills with which to process the user input;
for a first model skill of the skill chain:
generating, based on a first prompt template associated with the first model skill, a first prompt that includes at least a part of the obtained user input;
and
processing, using a first machine learning model associated with the first model skill, the first prompt to obtain intermediate output;
for a second model skill of the skill chain:
generating, based on a second prompt template associated with the second model skill, a second prompt that includes at least a part of the intermediate output as input for the second model skill;
and
processing, using a second machine learning model associated with the second model skill, the second prompt to obtain model output;
and
providing an indication of the model output for display to the user.

9 more elements

Dependencies are inferred from the claim text.

Facts

Application: 18/122,575Filed 16 Mar 2023
Priority: 19 Dec 2022
Published: 20 Jun 2024
Term ends: Not estimatedThe source records don’t support an estimate.

Classification8 codes

G06N 20/00
Machine learning
G06F 16/90335
Querying: query processing
G06N 3/044
Architecture, e.g. interconnection topology: recurrent networks, e.g. Hopfield networks
G06N 3/045
Architecture, e.g. interconnection topology: combinations of networks

Family

Application63/433,627Us provisional application · filed 19 Dec 2022
US 2024/0202582 A1This patent

From the US filing history. Foreign family members aren’t listed.

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