AI, or artificial intelligence, is the ability of a computer system to do tasks that normally need human intelligence, such as understanding language, recognizing images, learning from experience, making decisions and solving problems. The key idea is that the system is not given a fixed answer for every situation. Instead, it uses data and algorithms to figure out what to do, and it can often improve with more experience.
Three major sub-fields are machine learning (systems that learn patterns from data instead of being programmed with explicit rules), natural language processing (understanding and generating human language, as in chatbots and translation) and computer vision (understanding images and video, as in face recognition or medical scans). Other sub-fields include robotics, speech recognition, knowledge representation and planning.
The main ideas behind AI are old, but three things came together in recent years. First, there is now a huge amount of data, because people constantly produce text, images and videos online. Second, computers became much more powerful, especially GPUs, which can train large neural networks quickly. Third, there were important algorithmic improvements, such as deep learning and the transformer architecture, which made it possible to build very large models that work well. On top of this, a lot of money and attention has gone into the field, and tools like ChatGPT made AI easy for ordinary people to use.
Three sectors are manufacturing, logistics and warehousing, and healthcare. In factories, robots weld, assemble and paint because they are fast, precise and never get tired. In warehouses, robots move and sort packages, which helps companies handle the growing number of online orders. In healthcare, robots assist surgeons and disinfect rooms, which gives more accuracy and reduces risk to people. Other sectors include agriculture, space exploration and cleaning.
In general, robots are used where tasks are repetitive, dangerous, very precise or need to be done around the clock, and where they can reduce cost and mistakes.
The first challenge is navigation in a busy, changing environment. Shopping malls are full of moving people, strollers, carts and temporary displays, so the robot must localize itself, avoid obstacles and plan safe routes, while also dealing with glass walls, shiny floors and different floors connected by ramps or elevators.
The second challenge is power. A robot that works for 24 hours has to manage its battery, find its charging station by itself and still cover the whole facility. Charging breaks can leave some areas unwatched for a while, so the patrol schedule must be planned carefully.
The third challenge is reliable perception and decision making. The robot must detect unusual behavior or security problems in different lighting (day, night and crowded or empty hours), without raising too many false alarms. It also has to work safely and responsibly around people, including privacy concerns and communication with human security staff.