Artificial intelligence

Terms related to artificial intelligence (AI), including definitions about machine learning and words and phrases about training data, algorithms, natural language processing, neural networks and automation.

linguistic ambiguity - Linguistic ambiguity is a quality of language that makes speech or written text open to multiple interpretations.
Lisp (programming language) - Lisp, an acronym for list processing, is a functional programming language that was designed for easy manipulation of data strings.
logical equivalence - Logical equivalence is the condition of equality that exists between two statements or sentences in propositional logic or Boolean algebra.
machine teaching - Machine teaching is the practice of infusing context -- and often business consequences -- into the selection of training data used in machine learning (ML) so that the most relevant outputs are produced by the ML algorithms.
machine-to-machine (M2M) - Machine-to-machine, or M2M, is a broad label that can be used to describe any technology that enables networked devices to exchange information and perform actions without the manual assistance of humans.
MICR (magnetic ink character recognition) - MICR (magnetic ink character recognition) is a technology invented in the 1950s that's used to verify the legitimacy or originality of checks and other paper documents.
model card in machine learning - A model card is a type of documentation that is created for, and provided with, machine learning models.
neural net processor - A neural net processor is a central processing unit (CPU) that holds the modeled workings of how a human brain operates on a single chip.
neuromorphic computing - Neuromorphic computing is a method of computer engineering in which elements of a computer are modeled after systems in the human brain and nervous system.
neurosynaptic chip - A neurosynaptic chip, also known as a cognitive chip, is a computer processor that is designed to function more like a biological brain than a typical central processing unit (CPU).
Nvidia Omniverse - Nvidia Omniverse is a computing platform built to enhance digital design and development by integrating 3D design, spatial computing and physics-based workflows across Nvidia tools, third-party apps and AI services.
object recognition - Object recognition is at the convergence points of robotics, machine vision, neural networks and AI.
OCR (optical character recognition) - OCR (optical character recognition) is the use of technology to distinguish printed or handwritten text characters inside digital images of physical documents, such as a scanned paper document.
over sampling and under sampling - Over sampling and under sampling are techniques used in data mining and data analytics to modify unequal data classes to create balanced data sets.
overfitting in machine learning - Overfitting in machine learning occurs when a model excessively fits the training data, capturing both relevant patterns and inconsequential noise, resulting in inaccurate predictions of new data.
Pathways Language Model (PaLM) - The Pathways Language Model is the name of a family of AI large language models developed by Google.
pattern recognition - Pattern recognition is the ability to detect arrangements of characteristics or data that yield information about a given system.
personalization engine - A personalization engine is a tool used by businesses to collect and analyze customer behavior and data to create a customized user experience -- including special offers, product recommendations and automated marketing efforts -- in an e-commerce setting.
prediction error - A prediction error is the failure of some expected event to occur.
predictive modeling - Predictive modeling is a mathematical process used to predict future events or outcomes by analyzing patterns in a given set of input data.
prescriptive analytics - Prescriptive analytics is a type of data analytics that provides guidance on what should happen next.
prompt chaining - Prompt chaining is a technique used when working with generative AI models in which the output from one prompt is used as input for the next.
prompt engineering - Prompt engineering is an AI engineering technique encompassing the process of refining LLMs with specific prompts and recommended outputs, as well as the process of refining input to various generative AI services to generate text or images.
PyTorch - PyTorch is an open source machine learning (ML) framework based on the Python programming language and the Torch library.
quantum interference - Quantum interference is when subatomic particles interact with and influence themselves and other particles while in a probabilistic superposition state.
R programming language - The R programming language is an open source scripting language for predictive analytics and data visualization.
recurrent neural networks - A recurrent neural network (RNN) is a type of artificial neural network commonly used in speech recognition and natural language processing.
reinforcement learning from human feedback (RLHF) - Reinforcement learning from human feedback (RLHF) is a machine learning approach that combines reinforcement learning techniques, such as rewards and comparisons, with human guidance to train an artificial intelligence (AI) agent.
retrieval-augmented generation - Retrieval-augmented generation (RAG) is an AI framework that retrieves data from external sources.
Retrieval-Augmented Language Model pre-training - A Retrieval-Augmented Language Model, also referred to as REALM or RALM, is an artificial intelligence language model designed to retrieve text and then use it to perform question-based tasks.
robot - A robot is a machine designed to execute one or more tasks automatically with speed and precision.
robot economy - The robot economy is a scenario in which most of the labor required to sustain human life is automated.
robotic process automation (RPA) - Robotic process automation (RPA) is a technology that mimics the way humans interact with software to perform high-volume, repeatable tasks.
robotic surgery (robot-assisted surgery) - Robotic surgery is the use of computer technologies working in conjunction with robot systems to perform medical procedures.
self-driving car (autonomous car or driverless car) - A self-driving car -- sometimes called an autonomous car or driverless car -- is a vehicle that uses a combination of sensors, cameras, radar and artificial intelligence (AI) to travel between destinations without a human operator.
Siri - Siri is Apple's virtual assistant for iOS, macOS, tvOS and watchOS devices that uses voice recognition and is powered by artificial intelligence (AI).
smart farming - Smart farming is a management concept focused on providing the agricultural industry with the infrastructure to leverage advanced technology – including big data, the cloud and the internet of things (IoT) – for tracking, monitoring, automating and analyzing operations.
smart machines - A smart machine is a device embedded with machine-to-machine and/or cognitive computing technologies such as artificial intelligence (AI), machine learning (ML) or deep learning, all of which it uses to reason, solve problems, make decisions and even take action.
social robot - A social robot is an artificial intelligence (AI) system that is designed to interact with humans and other robots.
soft computing - Soft computing is the use of approximate calculations to provide approximate solutions to complex computational problems.
spatial intelligence - Spatial intelligence is the concept of being able to successfully perceive and derive insight from visual data.
speech analytics - Speech analytics is the process of analyzing voice recordings or live customer calls to contact centers with speech recognition software to find useful information and provide quality assurance.
speech disfluency - A speech disfluency is any disruption in the flow of spoken language that is caused by the speaker.
stemming - Stemming is the process of reducing a word to its stem that affixes to suffixes and prefixes or to the roots of words known as "lemmas.
structural ambiguity - Structural or syntactic ambiguity is the potential of multiple interpretations for a piece of written or spoken language because of the way words or phrases are organized.
sustainable AI - Sustainable AI is the use of artificial intelligence systems that operate in ways contingent with sustainable business practices.
target function - A target function, in machine learning, is a method for solving a problem that an AI algorithm parses its training data to find.
technological convergence - Technological convergence is a term that describes bringing previously unrelated technologies together, often in a single device.
telepresence robot - A telepresence robot is a robotic device that enables a user to maintain a virtual presence in a remote location.
tensor processing unit (TPU) - A tensor processing unit (TPU) is an application-specific integrated circuit (ASIC) specifically designed to accelerate high-volume mathematical and logical processing tasks typically involved with machine learning (ML) workloads.
TensorFlow - TensorFlow is an open source framework developed by Google researchers to run machine learning, deep learning and other statistical and predictive analytics workloads.
ternary content-addressable memory (TCAM) - Ternary content-addressable memory (TCAM) is a specialized type of high-speed memory that searches its entire contents in a single clock cycle.
text mining (text analytics) - Text mining is the process of exploring and analyzing large amounts of unstructured text data aided by software that can identify concepts, patterns, topics, keywords and other attributes in the data.
transformer model - A transformer model is a neural network architecture that can automatically transform one type of input into another type of output.
truncation error - A truncation error is the difference between an actual and a truncated, or cut-off, value.
uncanny valley - The uncanny valley is a common unsettling feeling people experience when androids or humanoid robots and audio/visual simulations closely resemble humans in many respects but aren't quite convincingly realistic.
vision language models (VLMs) - Vision language models (VLMs) combine machine vision and semantic processing techniques to make sense of the relationship within and between objects in images.
What are AI hallucinations and why are they a problem? - An AI hallucination is when a large language model (LLM) powering an artificial intelligence (AI) system generates false information or misleading results, often leading to incorrect human decision-making.
What are Google's AI Overviews (Formerly SGE)? - Google's AI Overviews are a feature in Google search that uses generative AI (GenAI) to deliver short synopses of topics alongside links to relevant web content in response to certain search queries.
What are graph neural networks (GNNs)? - Graph neural networks (GNNs) are a type of neural network architecture and deep learning method that can help users analyze graphs, enabling them to make predictions based on the data described by a graph's nodes and edges.
What are large language models (LLMs)? - A large language model (LLM) is a type of artificial intelligence (AI) algorithm that uses deep learning techniques and massively large data sets to understand, summarize, generate and predict new content.
What are machine learning algorithms? 12 types explained - A machine learning algorithm is the method by which the AI system conducts its task, generally predicting output values from given input data.
What are masked language models (MLMs)? - Masked language models (MLMs) are used in natural language processing (NLP) tasks for training language models.
What are virtual agents and how are they being used? - A virtual agent -- sometimes called an intelligent virtual agent (IVA) -- is a software program or cloud service that uses artificial intelligence (AI) technologies, such as machine learning (ML) and natural language processing (NLP) to provide automated services or guidance to humans.
What is a backpropagation algorithm? - A backpropagation algorithm, or backward propagation of errors, is an algorithm that's used to help train neural network models.
What is a Consensus Algorithm? - A consensus algorithm is a process in computer science used to achieve agreement on a single data value among distributed processes or systems.
What is a convolutional neural network (CNN)? - A convolutional neural network (CNN) is a category of machine learning model.
What is a decision tree in machine learning? - A decision tree is a flow chart created by a computer algorithm to make decisions or numeric predictions based on information in a digital data set.
What is a generative adversarial network (GAN)? - A generative adversarial network (GAN) is a machine learning (ML) model in which two neural networks compete by using deep learning methods to become more accurate in their predictions.
What is a large action model (LAM)? - A large action model (LAM) is an AI system that understands queries and responds by taking action.
What is a neural network? - A neural network is a machine learning (ML) model designed to process data in a way that mimics the function and structure of the human brain.
What is a perceptron? - A perceptron is a simple model of a biological neuron used in an artificial neural network.
What is a recommendation engine? - A recommendation engine is a system that gives customers recommendations based on their behavior patterns and similarities to people who might have shared preferences.
What is a small language model (SLM)? - A small language model (SLM) is a generative AI technology similar to a large language model (LLM) but with a significantly reduced size.
What is a smart factory? - A smart factory is a highly digitized and connected production facility that relies on smart manufacturing.
What is a support vector machine (SVM)? - A support vector machine (SVM) is a type of supervised learning algorithm used in machine learning to solve classification and regression tasks.
What is a validation set? How is it different from test, train data sets? - A validation set is a set of data used to train artificial intelligence (AI) with the goal of finding and optimizing the best model to solve a given problem.
What is adversarial machine learning? - Adversarial machine learning is a technique used in machine learning (ML) to fool or misguide a model with malicious input.
What is AgentGPT? - AgentGPT is a generative artificial intelligence tool that enables users to create autonomous AI agents that can be delegated a range of tasks.
What is agentic AI? Complete guide - Agentic AI refers to artificial intelligence systems that are capable of autonomous action and decision-making.
What is AI art and how is it created? - Artificial intelligence art (AI art) is any form of art that has been created or enhanced with AI tools.
What is AI ethics? - AI ethics is a system of moral principles and techniques intended to inform the development and responsible use of artificial intelligence technology.
What is AI inference? - AI inference is the process during which a trained AI model applies its understanding to generate original output in real time.
What is AI red teaming? - AI red teaming is the practice of simulating attack scenarios on an artificial intelligence application to pinpoint weaknesses and plan preventative measures.
What is AI? Artificial Intelligence explained - Artificial intelligence is the simulation of human intelligence processes by machines, especially computer systems.
What is an AI accelerator? - An AI accelerator is a type of hardware device that can efficiently support AI workloads.
What is an AI assistant? - An AI assistant, or digital assistant, is software that uses artificial intelligence to understand natural language voice commands and complete tasks for the user.
What is an AI prompt engineer? - An AI prompt engineer is an expert in creating text-based prompts or cues that can be interpreted and understood by large language models and generative AI tools.
What is an AI prompt? - An artificial intelligence (AI) prompt is the input submitted to a large language model (LLM) via a generative AI platform, like OpenAI's ChatGPT or Microsoft Copilot.
What is an inductive argument? - An inductive argument is an assertion that uses specific premises or observations to make a broader generalization.
What is an intelligent agent? - An intelligent agent is a program that can make decisions or perform a service based on its environment, user input and experiences.
What is anomaly detection? An overview and explanation - Anomaly detection is the process of identifying data points, entities or events that fall outside the normal range.
What is Apple Intelligence? - Apple Intelligence is the platform name for a suite of generative AI capabilities that Apple is integrating across its products, including iPhone, Mac and iPad devices.
What is artificial general intelligence (AGI)? - Artificial general intelligence (AGI) is the representation of generalized human cognitive abilities in software so that, faced with an unfamiliar task, the AI system could find a solution.
What is artificial intelligence as a service (AIaaS)? - Artificial intelligence as a service (AIaaS) is a cloud-based service that enables organizations to access artificial intelligence (AI) through a third-party offering.
What is augmented analytics? - Augmented analytics is the use of machine learning (ML) and natural language processing (NLP) to enhance data analytics, data sharing and business intelligence.
What is augmented intelligence? - Augmented intelligence is the use of technology to enhance a human's ability to execute tasks, perform analysis and make decisions.
What is autonomous AI? - Autonomous artificial intelligence (AI) is a branch of AI in which systems and tools are advanced enough to act with limited human oversight and involvement.
What is Bayes' theorem? How is it used in machine learning? - Bayes' theorem is a mathematical formula used in probability theory to calculate conditional probability, i.
What is big data analytics? - Big data analytics is the process of examining big data to uncover information -- such as hidden patterns, correlations, market trends and customer preferences -- that can help organizations make informed business decisions.