Artificial Intelligence (AI) is a collection of core technologies: Machine Learning, Deep Learning, Natural Language Processing (NLP), Computer Vision, Expert Systems (rule-based AI), and Automated Reasoning (logical problem-solving) are the core technologies that are ultimately helping to advance the development of generative artificial intelligence (Gen-AI). These technologies are combined to work together to give AI systems the ability to learn, reason, adapt, and perform tasks that were once thought to be the exclusive domain of human intelligence.
What does Machine Learning do in Gen AI?
Machine learning algorithms analyze massive datasets to identify patterns and relationships. This allows ML programs to make predictions or decisions on new data.
What does Deep Learning do in Gen AI?
Deep learning uses multiple layers of artificial neural networks to process information. This allows it to tackle complex tasks like image recognition and natural language processing.
What does Natural Language Processing (NLP) do in Gen AI?
Natural Language Processing (NLP) enables high-performance computers to understand and manipulate human language. NLP allows AI systems to interpret text, translate languages, and even generate human-quality writing.
What does Computer Vision do in Gen AI?
Computer Vision is a technology that equips computers with the ability to extract meaning from digital images and videos. It's used in applications like facial recognition, self-driving cars, and medical image analysis.
What is Expert Systems (rule-based AI)?
Expert systems (rule-based AI) rely on a collection of rules in a knowledge base to solve problems or answer questions. These systems store all the expert knowledge in the form of facts, rules, and heuristics (rules of thumb). This allows users to interact with the system, providing data and receiving solutions or explanations.
What is Automated reasoning (logical problem-solving)?
Automated reasoning, a subfield of computer science, develops programs that can reason logically to solve problems. These programs, called automated reasoning systems, follow axioms, formal logic, and inference algorithms to think critically and reach sound conclusions.
