Uses of Artificial Intelligence
What makes a system or process automatic. For example, robotic process automation (RPA) can be programmed to perform high-volume, repeatable tasks normally performed by humans. RPA differs from IT automation in that it can adapt to changing conditions.
The science of making a computer act without programming. Deep learning is a subset of machine learning that can very simply be thought of as the automation of predictive analytics. There are three types of machine learning algorithms:
Datasets are labeled in such a way that tags can be detected and used to label new datasets.
Datasets are not labeled and are sorted by similarities or differences
Datasets are not labeled but give feedback to the AI system after performing an action or several actions
The science of allowing computers to see. This technology captures and analyzes visual information using a camera, analog-to-digital conversion and digital signal processing. It is often compared to the human eye, but machine vision is not limited to biology and can be programmed to see through walls, for example. It is used in a variety of applications, from signature identification to medical image analysis. Computer vision, which focuses on machine-based image processing, is often combined with machine vision.
Natural Language Processing
The processing of computer language, not human language, with a computer program. One of the earliest and best known examples of NLP is spam detection, which looks at the subject line and text of an email and decides if it's junk. Current approaches to NLP are based on machine learning. NLP tasks include text translation, sentiment analysis, and speech recognition.
An engineering field that focuses on the design and manufacture of robots. Robots are often used to perform tasks that are difficult for humans to do or perform consistently. They are used on assembly lines for car production or by NASA to transport large objects in space. Researchers are also using machine learning to create robots that can interact in social settings.
They use a combination of computer vision, image recognition and deep learning to develop an automatic skill in piloting a vehicle, while staying in a given lane and avoiding unexpected obstacles such as pedestrians.