Abstract: Artificial Intelligence (AI) system that uses a Vision-and-Language Model (VLM) or a Large Multi-Modalities Model (LMMM) to improve energy conservation and to increase efficiency of energy consumption in households. Video cameras capture live video from rooms in the household, and feed them into the VLM; which also monitors or receives copies of email messages and instant messages that were sent and received by household residents. The VLM generates unique insights and proposals on how to reduce energy consumption or how to improve energy efficiency in the household. The energy-saving insights, that were generated by the VLM, are transferred to a Home Automation Device or to a Smart Home hub unit, which is triggered by the VLM-generated outputs to remotely control devices and appliances in the household. Innovative capabilities of AI are harnessed, in combination with Computerized Vision and Natural Language Processing, to deduce energy-saving proposals and to automatically implement them.

Abstract: Dynamic adjustment of navigation guidance information, based on user-specific attributes or characteristics that are estimated using predictive Artificial Intelligence (AI) engines. A user of a smartphone requests navigation guidance for walking to a destination location. A mapping and navigation application generates a regular route, and estimates that it will take N minutes of walking for a regular user. Innovatively, a Large Language Model (LLM) analyzes email and text and SMS messages that the user sent and received, and social media posts of the user, and contextual information extracted from applications running on the user's smartphone, to predict that this specific user will make a specific stop or detour for a particular purpose, such as to purchase a cold drink on a hot day or to pick-up a ready-for-pickup medication at a pharmacy.