Introduction to common AI terms
In the fast-paced world of SEO, staying updated with the latest technological advancements is crucial. One such game-changer is Artificial Intelligence (AI), which has revolutionised how digital assets perform on search engine result pages (SERPs) spawning many AI terms. As part of Cavefish’s mission to content creation efforts.
Algorithm: A Sequence of Rules
Definition: An algorithm is a sequence of rules that a computer follows to complete a task. It takes input, often from a dataset, performs calculations or tests on it, and generates an output. Algorithms play a crucial role in spotting patterns in data and making predictions.
Algorithmic Bias: Addressing Fairness
Definition: Algorithmic bias refers to decision-making errors or unfair outcomes that can result from flaws in the algorithm’s processing of data or biases in the data itself. Such biases can inadvertently favour or disadvantage certain user groups based on factors like race, gender, sexuality, disability, or ethnicity.
Alignment: Ensuring AI’s Goals Align with Human Values
Definition: Alignment is a critical research area responsible for ensuring that Artificial General Intelligence (AGI) systems have goals that align with human values. This ensures that AGI systems act ethically and responsibly.
Artificial General Intelligence (AGI): The Ultimate Goal
Definition: AGI refers to a computer system’s capability to generate new scientific knowledge and perform any task that humans can do. It aims to create super-intelligent machines that can learn and develop autonomously, understand their environment, and transform the world around them.
Artificial Intelligence (AI): Replicating Human Brainpower
Definition: AI is the science of enabling machines to perform tasks that traditionally required human intelligence, such as reasoning, decision-making, language understanding, learning from mistakes, and problem solving.
Big Data: Unlocking Insights
Definition: Big data refers to vast datasets that can be computationally analysed to reveal patterns, trends, and associations. It’s a valuable resource for businesses seeking insights into human behaviour, transactions, and interactions.
Chatbot: Conversational AI
Definition: A chatbot is a software application that can respond to text questions and engage in human-like conversations. Generative AI has expanded their capabilities, enabling them to create diverse forms of written content.
ChatGPT: Powered by OpenAI
Definition: ChatGPT is a natural language processing chatbot driven by AI technology developed by OpenAI. It can compose articles, essays, emails, stories, and even generate programming code in response to text-based prompts.
Compute: Powering AI Systems
Definition: Compute refers to the computational power required for AI systems to perform tasks such as processing data, training machine learning models, and making predictions. It’s often measured in FLOPS (Floating-point Operations Per Second).
Computer Vision: Extracting Insights from Images
Definition: Computer vision is a field that uses computers to extract information from digital images or videos. It’s used in applications like object recognition, facial recognition, medical imaging, and video surveillance.
Dall-E: Creating Images from Text
Definition: Dall-E is a deep-learning model developed by OpenAI that can generate digital images from text-based natural language descriptions provided by users.
Data Science: Uncovering Insights
Definition: Data science involves processing large amounts of data to identify patterns, spot trends, and gain insights into real-world problems.
Deep Learning (DL): Solving Complex Problems
Definition: Deep learning is a subset of machine learning that can solve complex problems such as speech recognition or image classification. It’s capable of ingesting unstructured data in raw form and distinguishing differences between data categories.
Floating-point Operations Per Second (FLOPS): Measuring Computational Power
Definition: FLOPS is the unit of measurement used to quantify the computational power of supercomputers.
Generative AI: Creating Media
Definition: Generative AI encompasses machine learning models that can generate media such as writing, images, or music. It learns patterns from vast amounts of data to generate contextually relevant responses.
Generative Adversarial Network (GAN): Realistic Data Generation
Definition: GAN is a machine learning technique that generates data, including realistic “deepfake” images, by training a generator to create data that’s difficult to distinguish from real data.
Generative Pre-trained Transformer: Powering ChatGPT
Definition: Generative Pre-trained Transformers are large language models developed by OpenAI. They serve as the foundation for ChatGPT and other AI applications.
God-like AI: The Ultimate Intelligence
Definition: “God-like AI” / AGI are common AI terms often used to describe Artificial General Intelligence (AGI), referring to AI systems with intelligence surpassing that of humans.
Hallucination: An AI Imperfection
Definition: Hallucination in Generative AI refers to models producing false information or inventing realities, which can be problematic in content generation.
Human In The Loop (HITL): Combining Human and AI
Definition: HITL is a system that combines human expertise with AI to improve algorithm performance, making results more useful and accurate.
Large Language Model (LLM): Recognising, Summarising, and Generating Text
Definition: LLMs are machine learning algorithms capable of recognising, summarising, translating, predicting, and generating text.
Machine Learning (ML): Learning from Data
Definition: ML is an AI application where computer programs learn from and adapt to new data without explicit programming. They improve with training and can recognise patterns in new data.
Multi-Agent System: Collaboration with AI
Definition: A multi-agent system involves multiple interacting software programs known as “agents,” often working with humans to complete tasks.
Natural Language Processing (NLP): Understanding Human Language
Definition: NLP is an AI field that focuses on computer understanding of human speech and text. It plays a vital role in customer service chatbots, speech recognition, and automatic translation.
Neural Networks: Inspired by the Brain
Definition: Neural networks are computer systems inspired by the way neurons interact in the human brain. They process data and improve their ability to discern differences over time.
Open Source: Collaboration and Innovation
Definition: Open source refers to software and data that are free to edit and share, facilitating collaboration, replication, and sharing of new developments in the developer community.
Singularity: AI’s Hypothetical Advancement
Definition: Singularity is a hypothetical point in time when AI surpasses human intelligence, potentially accelerating technological progress and automating knowledge-based work.
Superintelligence: AI’s Pinnacle
Definition: Superintelligence refers to AI systems that possess higher intelligence than humans.
Supervised Learning: Guided Machine Learning
Definition: Supervised learning is a form of machine learning that uses labelled data to train algorithms to classify data or predict outcomes accurately.
Turing Test: A test of a machine’s ability to demonstrate humanlike intelligence.
And lastly, a common contender in AI terms, it was first devised by mathematician and computing pioneer Alan Turing as the “imitation game” in his 1950 paper “Computing Machinery and Intelligence”. The test involves a human evaluator asking questions to another human and to a machine via a computer keyboard and monitor. If the evaluator cannot tell from the written responses which is the human and which is the machine, then the machine has passed the Turing test.
Unsupervised learning: a form of machine learning in which algorithms analyse and cluster unlabelled data sets, by looking for hidden patterns in the data — without the need for human intervention to train or correct them.
*AI terms is constantly evolving and will be updated frequenctly.