What are some examples of AI technology? How is it being used today?
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Artificial intelligence is incorporated into various types of technologies. Here we primarily share the following seven fields:
Automation. When combined with AI technology, automation tools can expand the number and types of tasks performed. One example is Robotic Process Automation (RPA), a type of software that automates repetitive, rule-based data processing tasks traditionally done by humans. When integrated with machine learning and emerging AI tools, RPA can automate a significant portion of enterprise work, enabling tactical bots to leverage AI intelligence and adapt to process changes.
Machine Learning. This is the science of enabling computers to operate without explicit programming. Deep learning, a subset of machine learning, can be thought of as the automation of predictive analytics. Machine learning algorithms are categorized into three types:
- Supervised Learning. Datasets are labeled to detect patterns and classify new datasets.
- Unsupervised Learning. Datasets are unlabeled and sorted based on similarities or differences.
- Reinforcement Learning. Datasets are unlabeled, but the AI system receives feedback after performing one or more actions.
Machine Vision. This technology gives machines the ability to see. Machine vision uses cameras, analog-to-digital conversion, and digital signal processing to capture and analyze visual information. While often compared to human vision, machine vision is not bound by biological limitations—for example, it can be programmed to 'see' through walls. It is used in applications ranging from signature recognition to medical image analysis. Computer vision, which focuses on machine-based image processing, is often conflated with machine vision.
Natural Language Processing (NLP). This involves the processing of human language by computer programs. One of the oldest and most well-known examples of NLP is spam detection, which analyzes the subject line and text of an email to determine if it is spam. Current NLP methods are based on machine learning. NLP tasks include text translation, sentiment analysis, and speech recognition.
Robotics. This engineering field focuses on the design and manufacturing of robots. Robots are often used to perform tasks that are difficult or repetitive for humans. For instance, robots are employed in automotive assembly lines or by NASA to move large objects in space. Researchers also use machine learning to build robots capable of interacting in social environments.
Autonomous Vehicles. Self-driving cars combine computer vision, image recognition, and deep learning to develop automated skills for navigating roads, staying within lanes, and avoiding unexpected obstacles like pedestrians.
Text, Image, and Audio Generation. Generative AI technologies can create various types of media based on text prompts and are widely applied across enterprises to produce seemingly limitless content types, from photorealistic art to email responses and screenplays.