This guide provides an introduction to artificial intelligence (AI), with a focus on Generative AI. The AI landscape is constantly changing and this guide will be updated periodically with new tools, resources, and information. If you find a broken link or discover something that should be included in this guide, please email us!
Generative AI refers to a class of artificial intelligence (AI) algorithms and models designed to generate new content or data that is similar to, but not identical to, existing examples. These algorithms are capable of producing new content, such as images, text, audio, or video, by learning patterns and relationships from a set of training data.
"Define generative AI" prompt. ChatGPT, GPT-3.5, OpenAI, 10 Apr. 2023, chat.openai.com/chat.
Artificial Intelligence (AI) refers to the simulation of human intelligence processes by machines, especially computer systems. These processes include learning (the acquisition of information and rules for using it), reasoning (using rules to reach approximate or definite conclusions), and self-correction. AI systems can perform tasks that typically require human intelligence, such as visual perception, speech recognition, decision-making, and language translation. AI technology encompasses various approaches, including machine learning, deep learning, natural language processing, computer vision, and robotics. The ultimate goal of AI is to create systems that can function autonomously, learn from experience, and adapt to new situations, ultimately aiming to replicate or even exceed human-level intelligence in various domains.
"Define artificial intelligence" prompt. ChatGPT, GPT-3.5, OpenAI, 10 Apr. 2023, chat.openai.com/chat.
A software application designed to simulate conversation with human users, typically through text-based or voice-based interfaces. Chatbots can be rule-based, meaning they follow pre-defined rules to generate responses, or AI-powered, meaning they employ machine learning algorithms and natural language understanding techniques to learn from interactions with users and improve their responses over time.
"What is a chatbot" prompt. ChatGPT, GPT-3.5, OpenAI, 10 Apr. 2023, chat.openai.com/chat.
Machine learning is a subset of artificial intelligence (AI) that focuses on the development of algorithms and statistical models that enable computers to perform tasks without explicit instructions, relying on patterns and inference instead. In essence, it is the science of getting computers to learn from data and improve their performance over time without being explicitly programmed for every task.
"Define machine learning" prompt. ChatGPT, GPT-3.5, OpenAI, 10 Apr. 2023, chat.openai.com/chat.
A branch of artificial intelligence (AI) that focuses on the interaction between computers and humans through natural language. It encompasses the ability of computers to understand, interpret, and generate human language in a way that is both meaningful and useful.
"Define natural language processing" prompt. ChatGPT, GPT-3.5, OpenAI, 10 Apr. 2023, chat.openai.com/chat.
A type of artificial intelligence (AI) model designed to understand and generate human-like text based on large amounts of training data.
"What is a large language model" prompt. ChatGPT, GPT-3.5, OpenAI, 10 Apr. 2023, chat.openai.com/chat.
In the context of AI, a hallucination refers to a situation where a machine learning model generates outputs that are not grounded in reality or do not correspond to genuine patterns in the data it was trained on.
"What is a hallucination in the context of AI" prompt. ChatGPT, GPT-3.5, OpenAI, 10 Apr. 2023, chat.openai.com/chat.
A specific task or question that is given to an AI system to elicit a response or output.
Prompt engineering refers to the practice of designing and crafting effective prompts to guide the behavior of AI models.
Prompt chaining involves linking together a series of prompts and responses in a conversational context to create a more coherent and contextually relevant interaction with the model.
"What is a prompt in generative AI" prompt. ChatGPT, GPT-3.5, OpenAI, 10 Apr. 2023, chat.openai.com/chat.
The process of teaching a machine learning model to recognize patterns or make decisions by exposing it to a large amount of data.
Training data refers to the set of examples or instances used to train a machine learning model. The training data serves as the foundation for the learning process, allowing the model to identify patterns, relationships, and trends in the data. The quality and quantity of the training data significantly influence the performance and effectiveness of the trained model.
There are different styles of training, including:
Supervised Learning, where algorithms learn from labeled data, where each example is associated with a label or target variable. Humans are involved in the data collection and labeling.
Unsupervised Learning, where algorithms learn from unlabeled data, identifying patterns or structures in the data without explicit guidance from humans.
"What is training in AI" prompt. ChatGPT, GPT-3.5, OpenAI, 10 Apr. 2023, chat.openai.com/chat.