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Artificial intelligence is the simulation of human intelligence processes by computer systems. Specific applications of AI include expert systems, natural language processing, speech recognition and machine vision.
As the hype around AI has accelerated, vendors have been scrambling to promote how their products and services use AI. Often what they refer to as AI is simply one component of AI, such as machine learning. AI requires a foundation of specialized hardware and software for writing and training machine learning algorithms.
Machine learning automates analytical model building. It is based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention. Most AI examples that you hear about today — from chess-playing computers to self-driving cars — rely heavily on deep learning and natural language processing.
Large language models are a type of AI algorithm that use deep learning techniques and massively large data sets to understand, summarize, generate and predict new content. The term generative AI refers to AI that can create new content, including text, images, video and audio, based on what it has been trained on.
Concerns about AI center on ethical issues such as bias, lack of transparency, privacy violations, and potential job displacement. Researchers are actively working on developing AI systems that are more reliable, interpretable, and aligned with human values.