US 2023/0412470 A1 · CONDITIONAL ARTIFICIAL INTELLIGENCE, MACHINE LEARNING MODEL, AND PARAMETER SET CONFIGURATIONS

Abstract

Methods, systems, and devices for wireless communications are described. A user equipment (UE) may receive a message from a network entity indicating a set of machine learning models, a set of parameter sets, or both and one or more usage conditions associated with the machine learning models and parameter sets. Based on a usage condition being satisfied, the UE may select a machine learning model, a parameter set, or both for generating a machine learning inference. For example, the UE may select the machine learning model or the parameter set based on a priority, whether sufficient input data is provided, or based on other usage conditions. The UE may generate the machine learning inference using the selected machine learning model or the selected parameter set, and the UE may transmit a report indicating an output of the machine learning inference to the network entity.

Claims30

Dependent claims

An apparatus for wireless communication at a user equipment (UE), comprising:

a processor;
memory coupled with the processor;
and
instructions stored in the memory and executable by the processor to cause the apparatus to:
receive a first message indicating a plurality of machine learning models, a plurality of parameter sets, or both, and indicating one or more usage conditions for selecting one of the plurality of machine learning models, one of the plurality of parameter sets, or both, for performing a machine learning inference;
select a first machine learning model of the plurality of machine learning models, a first parameter set of the plurality of parameter sets, or both, for performing the machine learning inference based at least in part on a usage condition of the one or more usage conditions being satisfied;
and
transmit a report indicating the machine learning inference that is generated by the first machine learning model or by using the first parameter set.

5 more elements

An apparatus for wireless communication at a network node, comprising:

a processor;
memory coupled with the processor;
and
instructions stored in the memory and executable by the processor to cause the apparatus to:
transmit a first message indicating a plurality of machine learning models, a plurality of parameter sets, or both, and indicating one or more usage conditions for selecting one of the plurality of machine learning models, one of the plurality of parameter sets, or both, for performing a machine learning inference;
and
receive a report indicating the machine learning inference that is generated by a first machine learning model or by using a first parameter set selected by a user equipment (UE) based at least in part on a usage condition of the one or more usage conditions being satisfied.

4 more elements

A method for wireless communication at a user equipment (UE), comprising:

receiving a first message indicating a plurality of machine learning models, a plurality of parameter sets, or both, and indicating one or more usage conditions for selecting one of the plurality of machine learning models, one of the plurality of parameter sets, or both for performing a machine learning inference;
selecting a first machine learning model of the plurality of machine learning models, a first parameter set of the plurality of parameter sets, or both, for performing the machine learning inference based at least in part on a usage condition of the one or more usage conditions being satisfied;
and
transmitting a report indicating the machine learning inference that is generated by the first machine learning model or by using the first parameter set.

1 more element

Dependencies are inferred from the claim text.

Conditional artificial intelligence, machine learning model, and parameter set configurations

Life of this patent

Conditional artificial intelligence, machine learning model, and parameter set configurations

Life of this patent

Abstract

Claims30