Different forms of AI
When we are exploring Artificial intelligence it is important to understand that the term AI encapsulates multiple forms of training and learning models each used for their own systematic process and data handling methods. We are only going to be delving into Artificial Intelligence and its impact and use within the creative industries however as with any technology or terminology it is important to understand its background and forms.
Science fiction would often lead us to think that AI is all about self-learning robots and sentience where we encounter AI almost every day to process information, speed up processes, and generate new outputs. AI is not something to be feared but rather identified and used correctly as such below are most of the current types of AI.
The majority of the content explored in this online AI course will cover mostly generative and learning-based AI models.
-
Machine learning (ML) is a branch of artificial intelligence (AI) and computer science that focuses on using data and algorithms to enable AI to imitate the way that humans learn, gradually improving its accuracy.
-
Computer vision is a field of computer science that focuses on enabling computers to identify and understand objects and people in images and videos. Like other types of AI, computer vision seeks to perform and automate tasks that replicate human capabilities.
-
Edge artificial intelligence refers to the deployment of AI algorithms and AI models directly on local edge devices such as sensors or Internet of Things (IoT) devices, which enables real-time data processing and analysis without constant reliance on cloud infrastructure.
-
Emotional Intelligence in AI refers to the ability of AI systems to detect and respond to human emotions. This technology is also known as Emotion AI or Affective Computing. It involves using artificial intelligence to analyze and interpret human emotions through facial expressions, body language, and other cues.
-
Reinforcement learning (RL) is a machine learning (ML) technique that trains software to make decisions to achieve the most optimal results. It mimics the trial-and-error learning process that humans use to achieve their goals.
-
Explainable artificial intelligence (XAI) is a set of processes and methods that allows human users to comprehend and trust the results and output created by machine learning algorithms. Explainable AI is used to describe an AI model, its expected impact and potential biases.
-
Item description
-
Natural language processing (NLP) is the ability of a computer program to understand human language as it's spoken and written -- referred to as natural language. It's a component of artificial intelligence (AI). NLP has existed for more than 50 years and has roots in the field of linguistics.
-
Autonomous artificial intelligence (AI) is a branch of AI in which systems and tools are advanced enough to act with limited human oversight and involvement. The actions an autonomous AI system can perform range from automating basic, repetitive tasks to analyzing data sets.
-
Deep learning is a subset of machine learning that uses multilayered neural networks, called deep neural networks, to simulate the complex decision-making power of the human brain. Some form of deep learning powers most of the artificial intelligence (AI) applications in our lives today.