Huawei is a global information and communications technology (ICT) company that designs and supplies telecom network equipment, consumer devices, and enterprise IT infrastructure. It also develops cloud and computing platforms used to support digital transformation across industries, making it a major player in global connectivity and technology ecosystems.
This is like having a smart early-warning system that spots which mobile or internet customers are about to leave and suggests the best way to keep them—before they call to cancel.
Mist AI is like an intelligent autopilot for corporate Wi‑Fi and wired networks. It watches everything happening on your network, spots problems before people complain, and automatically fixes or guides IT on what to do.
Think of DGS’s technology as an AI-driven traffic controller for mobile networks. It constantly watches how phones and devices are using 4G and 5G, then automatically adjusts the network so customers get faster, more reliable service with less wasted capacity.
Imagine your mobile network like a huge city of traffic lights. Today, most lights stay on even when no cars are passing. AI for greener 5G makes the ‘traffic lights’ of the network smart: they dim, sleep, or reroute traffic automatically so energy isn’t wasted when there’s little or no data traffic, while still keeping the roads (connections) flowing smoothly.
Think of the mobile network as a huge city full of roads (radio links) and traffic (data). AI in 5G/6G is like a smart traffic control system that constantly watches congestion, predicts where it will build up, and automatically opens new lanes, changes traffic lights, and reroutes cars so everything flows faster and more reliably without humans having to tweak every detail.
This is like a smart thermostat for a mobile network: when there’s no one in a room, it turns the lights and heating off automatically. Here, AI detects when parts of the cellular network aren’t carrying traffic and safely powers them down, then wakes them up when needed.
Think of this as turning the power grid into a ‘smart internet of energy’ where 5G connects all the equipment and AI acts like a traffic controller, constantly balancing where electricity should go, when to store it, and how to avoid waste or outages.
This is like giving the mobile network its own team of smart digital engineers who constantly watch how it’s performing, spot problems early, and automatically fix or optimize things before customers notice.
Think of a huge telecom network like a busy, complex city traffic system. Today, human engineers are the traffic cops, constantly tweaking lights and routes to keep everything moving. AI‑native autonomous network management is like upgrading to a smart city where sensors and AI automatically detect jams, reroute cars, repair issues, and optimize flows in real time, with humans supervising instead of micromanaging every intersection.
Think of a smart city as a city with a digital nervous system. AI is the brain that helps it see traffic jams, power usage, crime hotspots, and public service demand in real time, then quietly adjusts lights, signals, and services to keep everything running smoother and safer.
Think of a city’s road network as a giant, messy orchestra. This use case is about putting an AI ‘conductor’ in charge that can see what’s happening on the roads in real time (via cameras and sensors), predict where jams and accidents might happen, and then adjust traffic lights, signals, and routing instructions to keep everything flowing smoothly.
Imagine your telecom network as a huge, complex city with roads, traffic lights, and repair crews. AI here is like a smart traffic control center that watches everything in real time, predicts where traffic jams and accidents will happen, and automatically sends crews or reroutes cars before customers even notice a problem.
Think of this as an autopilot for telecom networks. Instead of engineers constantly watching dashboards and tweaking settings by hand, AI continuously watches the network, predicts problems before they happen, and automatically adjusts things to keep calls, video, and data flowing smoothly.
Think of this as putting a very smart co-pilot brain next to the traditional self-driving software. Classic autonomous driving systems are good at seeing and controlling the car, but they’re narrow and rigid. Large AI models add a ‘common sense’ layer that can understand complex road situations, follow natural-language instructions, and coordinate with humans and other systems more flexibly.