US 2026/0065155 A1 · DRIFT-BASED FRAMEWORK FOR LIFELONG LEARNING OF LARGE AI SYSTEMS

Abstract

A computer-implemented method includes receiving data and while using a process that promotes exploration during training, training a new set of model parameters using the received data. The new set of model parameters is used to form a collection of sets of model parameters. Data is separately applied to each set of model parameters in the collection to identify sets of model parameters that perform similarly on the set of data. The sets of model parameters that perform similarly on the data are grouped together in a group of sets of model parameters and test data is applied to groups of sets of model parameters to obtain an uncertainty measure for each group. A group with the lowest uncertainty measure is selected and outputs produced by the sets of model parameters in the selected group are used to generate an output value for the test data.

Claims20

Dependent claims

A computer-implemented method comprising:

receiving data;
while using a process that promotes exploration during training, training a new set of model parameters using the received data;
placing the new set of model parameters in a collection of previous sets of model parameters to form a new collection of sets of model parameters;
applying a set of data separately to each set of model parameters in the new collection of sets of model parameters to identify sets of model parameters that perform similarly on the set of data;
grouping the sets of model parameters that perform similarly on the set of data together in a group of sets of model parameters;
applying test data to groups of sets of model parameters to obtain an uncertainty measure for each group;
selecting a group with the lowest uncertainty measure;
and
using outputs produced by the sets of model parameters in the selected group to generate an output value for the test data.

6 more elements

Dependencies are inferred from the claim text.

Drift-based framework for lifelong learning of large ai systems

Life of this patent

Drift-based framework for lifelong learning of large ai systems

Life of this patent

Abstract

Claims20