Smart messaging for computer-implemented devices

A computer-implemented method of smart messaging, the method comprising:

• initiating a messaging session between a first user of first user device and a second user of a second user device, wherein the first user and the second user are participants in a conversation taking place as part of the messaging session;
• receiving, at a machine learning application from the first user device or the second user device, message context data associated with the messaging session that indicates a characteristic of the conversation;
• determining, at a processor executing the machine learning application based on the characteristic of the conversation that is indicative of context of the conversation and based on prior conversation patterns, a predicted conversation pattern of the conversation;
• determining, at the processor executing the machine learning application based on the predicted conversation pattern, options for suggested responses that are predicted to compete at least part of a response message as part of the conversation, wherein each of the options for suggested responses corresponds to the characteristic of the conversation indicative of the context of the conversation;
• and
• providing, to the first user device or to the second user device, one of the suggested responses;
• and
• displaying, via a graphical user interface, that suggested response within a message field at the first user device or the second user device.

A computer-implemented system, comprising:

• a first user device;
• and
• a system configured to execute a machine learning application, the system comprising:
• a processor and a memory, wherein the memory comprises a non-transitory computer-readable-medium having computer-executable instructions for the machine learning application stored therein that, when executed by the processor, cause the processor to:
• obtain, at the machine learning application from the first user device, message context data indicative of context of a conversation taking place between a first user of the first user device and a second user of a second user device;
• analyze the message context data indicative of the context of the conversation, at the machine learning application, to determine, based on prior conversation patterns between the first user and the second user, a predicted conversation pattern of the conversation that is taking place between the first user and the second user who are participating in the conversation;
• generate, at the machine learning application based on the predicted conversation pattern, options for suggested responses that are predicted to compete at least part of a response message as part of the conversation, wherein each of the options for suggested responses corresponds to the message context data indicative of the context of the conversation;
• and
• provide one of the suggested responses to either the first user device or the second user device.