This glossary will help jumpstart your AI exploration

IBJ asked ChatGPT—an artificial intelligence chatbot created by the organization OpenAI—to define some key AI-related terms. IBJ double-checked the definitions and made tweaks for grammar and style.

Artificial intelligence

Artificial intelligence—or AI—refers to the simulation of human intelligence in machines that are programmed to think and learn like humans. It encompasses various techniques, including machine learning and deep learning, to enable computers to perform tasks typically requiring human intelligence, such as problem solving, decision making, speech recognition and language understanding.

Generative AI

Generative AI refers to a class of artificial intelligence techniques that focus on generating new data—such as text, images or sound—that resembles human-created content. This often involves using models like generative adversarial networks or variational autoencoders.

◗ Generative adversarial networks: GANs are a class of deep-learning models used in generative AI. They consist of two neural networks, a generator and a discriminator, which are trained simultaneously through a competitive process. The generator aims to produce data (e.g., images, text) that is indistinguishable from real data, while the discriminator’s role is to distinguish between real and generated data. This adversarial training process forces the generator to continually improve its ability to generate realistic data. GANs are often used for generating realistic images, videos and other content, and they have numerous applications in art, image synthesis and data augmentation.

◗ Variational autoencoders: VAEs are a type of generative model that is used to learn and generate new data points, typically in the context of high-dimensional data like images or text. They consist of an encoder network and a decoder network. The encoder maps the input data into a lower-dimensional latent space, where it captures the underlying structure and distribution of the data. The decoder then takes samples from this latent space and reconstructs the original data. VAEs are particularly useful for generating new data points by sampling from the learned latent space, and they are known for their applications in image generation, data compression and generating new content, such as images or text, with variations. They are also used in unsupervised learning and feature learning tasks.

Machine learning

Machine learning is a broader field of artificial intelligence in which algorithms are trained to learn patterns and make predictions or decisions based on data. It doesn’t necessarily involve deep neural networks and can include various techniques such as decision trees, support vector machines and clustering.

Deep learning

Deep learning is a subset of machine learning that employs neural networks with multiple layers (deep neural networks) to learn and make predictions from large datasets. It has been particularly successful in tasks such as image and speech recognition, natural-language processing and reinforcement learning.

Predictive AI

Predictive AI refers to AI systems that use data and machine-learning algorithms to forecast future events or make predictions about specific outcomes. It’s commonly used in areas like financial forecasting, weather prediction and predictive maintenance.

Natural-language processing

NLP is a subset of AI that focuses on the interaction between computers and human language. It involves tasks like text analysis, sentiment analysis, language translation and speech recognition, enabling machines to understand, interpret and generate human language.

Large-language model

A large-language model is a type of AI model, typically based on deep learning, that is trained on vast amounts of text data to generate humanlike text or perform various natural-language processing tasks.

Enterprise AI

Enterprise AI refers to the use of artificial intelligence technologies within businesses and organizations to optimize processes, enhance decision-making, automate tasks, and improve overall efficiency and productivity.

Sentiment analysis

Sentiment analysis, also known as opinion mining, is a natural-language processing technique that aims to determine the sentiment or emotion expressed in a piece of text, such as a social media post or customer review. It’s commonly used for gauging public opinion or customer satisfaction.

Prompts

Prompts are input queries or text prompts that users provide to instruct the model and receive specific responses or generate content tailored to their request.

Hallucination

Hallucination refers to the generation of information or content that is not based on factual or accurate data. It’s a concern in AI systems where the model may create misleading or false information.

Chatbot

A chatbot is a computer program or AI application designed to simulate human conversation. It can interact with users through text or speech and is used for various purposes, including customer support, information retrieval and entertainment.

Source: ChatGPT (which cited several academic papers, textbooks, online learning platforms, software documentation and AI research websites as its sources)