Machine learning inference routing
AssigneeFlybits, Inc.
InventorHossein Rahnama
Life of this patent
Estimating the term…
Abstract
According to embodiments described in the specification, an exemplary method and a system including a server is provided for performing a session handshake with an electronic device, receiving an intervention request and contextual data parameters from the electronic device, activating a subset of data sets and at least one Machine Learning (ML) container from a graph data structure maintained by the server, adjusting weight data parameters of the activated data sets, routing the activated data sets to the activated ML container or containers to generate a ML inference or inferences, and providing a notification of the result of the intervention request based on the generated ML inference or inferences.
Claims15
A method of machine learning inference routing comprising the steps of:
- maintaining, in a memory of a remote server, a graph data structure comprising one or more data sets, one or more ML containers and one or more weight data parameters, wherein the one or more weight data parameters associates one or more data items from the one or more data sets with the one or more ML containers;
- receiving, at the remote server, an intervention request from a first electronic device;
- sensing contextual data parameters associated with the first electronic device;
- activating a subset of the one or more data sets and at least one of the one or more ML containers from the graph data structure based on the sensing;
- adjusting one or more weight data parameters of the subset based on the sensing;
- routing the subset of the one or more data sets to the at least one of the one or more ML containers to generate a ML inference;
- provisioning a result of the intervention request based on the ML inference;
- and
- providing a notification of the result on the first electronic device.
A server comprising:
- a server processor;
- and a server memory operable to store instructions that, when executed by the sever processor, causes the server to:
- maintain, in the server memory, a graph data structure comprising one or more data sets, one or more ML containers and one or more weight data parameters, wherein the one or more weight data parameters associates one or more data items from the one or more data sets with the one or more ML containers;
- perform a session handshake with a remote first electronic device, receive an intervention request and contextual data parameters from the first electronic device;
- activate a subset of the one or more data sets and at least one of the one or more ML containers from the graph data structure based on the intervention request and the contextual data parameters;
- adjust one or more weight data parameters of the subset of the one or more data sets;
- route the subset of the one or more data sets to the at least one of the one or more ML containers to generate a ML inference;
- provision a result of the intervention request based on the ML inference;
- and
- transmit, to the first electronic device, the result of the intervention request for notification.
Dependencies are inferred from the claim text.