A method of comparing two versions of something, like a webpage or advertisement, to see which one performs better based on a specific metric.

A security mechanism that restricts access to resources, systems, or data based on the level of authorization granted to users or groups, ensuring that only authorized individuals can view or perform actions on specific information or systems

The measure of how closely an AI model's predictions or outputs match the actual results or outcomes, with higher accuracy indicating a better performance of the model in making predictions or decisions.

The ability to derive practical and useful insights from data, making it possible for individuals to make informed decisions and take effective actions based on the information provided.

The practice of creating fake or manipulated data that tricks machine learning models into making incorrect decisions, often to test their security or exploit vulnerabilities.

A method where a model is asked to generate content that fulfills a harmful or undesirable request, such as writing a tutorial on how to make a bomb, in order to test its robustness and ability to resist manipulation.

Software entities that autonomously perform tasks, make decisions, and interact with their environment or other agents to achieve specific goals.

Artificial intelligence systems that are capable of independent decision-making and action, often employed in tasks requiring autonomy and adaptability.

A software development approach that emphasizes flexibility, rapid iteration, and continuous improvement by breaking down projects into smaller, manageable chunks and regularly incorporating feedback from stakeholders to ensure the final product meets their needs.

Specialized hardware designed to speed up specific AI tasks, such as inference engines and training accelerators.

A software program designed to autonomously perform tasks or make decisions in a dynamic environment, mimicking human-like behavior to achieve specific goals.

The process of ensuring that artificial intelligence systems achieve the desired outcomes and align with human values, goals, and ethical principles by carefully specifying and robustly implementing their objectives

The use of artificial intelligence to enhance and augment human capabilities, rather than replacing them, by providing tools and assistance that amplify human intelligence and decision-making abilities.

The phenomenon where artificial intelligence systems, trained on data that reflects societal biases, produce outcomes that are unfair, discriminatory, or stereotypical, often perpetuating existing social inequalities.

A visual tool that allows developers to design and build artificial intelligence models by dragging and dropping blocks, making it easier to create complex AI systems without extensive coding knowledge.

A computer program that simulates human-like conversations with users through text or voice interactions, using artificial intelligence and machine learning to understand and respond to their queries in a personalized and efficient manner

An artificial intelligence tool designed to assist users by providing suggestions, automating tasks, and enhancing productivity in various applications.

The process of using artificial intelligence to improve the quality, accuracy, and efficiency of various data types, such as images, text, and audio, by applying machine learning algorithms to enhance their features, remove imperfections, and optimize them for specific uses.

The practice of using artificial intelligence (AI) to manage and optimize business operations from the outset, automating routine tasks, predicting and preventing issues, and enhancing decision-making to improve efficiency and customer experience.

Creating and enforcing policies and regulations to ensure the responsible and ethical development, deployment, and use of artificial intelligence technologies.

When an artificial intelligence system generates incorrect or nonsensical information that appears plausible, often due to misunderstandings or limitations in its training data.

The development and integration of artificial intelligence (AI) technologies, such as machine learning and deep learning, into various industries and applications to improve efficiency, accuracy, and decision-making processes.

The risk of AI models being manipulated to produce unauthorized outputs.

The ability to understand and effectively use artificial intelligence (AI) technologies and applications, including their technical, practical, and ethical aspects, to navigate an increasingly AI-driven world.

A software that manages and integrates artificial intelligence technologies to perform tasks efficiently and autonomously, much like how a traditional operating system manages computer hardware and software.

A new type of computer designed to run powerful AI-accelerated software, significantly enhancing creative tasks like video editing and image processing by automating complex processes and reducing work time dramatically.

A professional responsible for defining and delivering AI-powered products or features that meet customer needs, leveraging technical expertise and business acumen to drive innovation and growth within an organization.

A strategic plan outlining the milestones and timelines for the development and deployment of artificial intelligence (AI) technologies, aiming to integrate AI capabilities into various industries and applications to enhance efficiency, productivity, and decision-making.

The field of study focused on ensuring that AI systems behave in a safe and beneficial manner, especially as they become more advanced.

A comprehensive plan outlining how an organization will leverage artificial intelligence (AI) to enhance its operations, improve decision-making, and drive business growth by integrating AI technologies into various aspects of its operations, such as data analysis, automation, and customer service.

The process of using artificial intelligence (AI) to revolutionize various industries and sectors by leveraging its capabilities to analyze vast amounts of data, automate tasks, and make predictions, ultimately leading to improved efficiency, accuracy, and decision-making.

A tool that abstracts away the complexities of a chatbot interface, making it easier for users to interact with AI systems without needing to understand the underlying technology.

Cloud-based services that provide AI capabilities to businesses without requiring them to build their own infrastructure.

The integration of artificial intelligence into network systems to improve efficiency, security, and user experience by automating processes and enhancing data analysis.

Techniques to manage power consumption in AI systems, such as dynamic voltage and frequency scaling.

A step-by-step set of instructions or rules followed by a computer to solve a problem or perform a specific task.

The goal of designing AI systems and models to ensure they provide equitable and unbiased results, especially in sensitive domains like finance and hiring.

The principle of making AI systems and their decision-making processes understandable and accountable to users and stakeholders.

A visual tool that displays key performance metrics in a single, organized view, allowing users to quickly monitor and understand the status of their digital product or website and make informed decisions.

A literary device in which words or phrases are repeated at the beginning of successive clauses or sentences, often used in speech and writing to emphasize a point, create rhythm, and convey powerful emotional effects, which can also be applied in AI to structure and organize knowledge representations and facilitate communication between humans and machines.

The tendency to attribute human-like qualities, such as emotions, intentions, and behaviors, to artificial intelligence systems, which can lead to exaggerated expectations and distorted moral judgments about their capabilities and performance.

A set of rules and tools that allows different software applications to communicate and work with each other.

A type of artificial intelligence that aims to understand, learn, and apply knowledge across a wide range of tasks at a level equal to or beyond that of humans.

A type of AI that is designed to perform a specific task, such as recognizing images, understanding voice commands, or generating recommendations, and operates within a predetermined set of constraints, without possessing self-awareness, consciousness, or the ability to generalize beyond its training data.

A computer model inspired by the human brain, where interconnected nodes or "neurons" process and learn from data to make decisions, recognize patterns, and perform tasks similar to human intelligence.

A technology that uses algorithms to automatically design and train machine learning models, eliminating the need for extensive data science expertise and allowing non-experts to build accurate predictive models quickly and efficiently.

A framework that uses frozen large language models to automatically generate intermediate reasoning steps as programs, allowing them to perform complex tasks by seamlessly integrating external tools and computations in a zero-shot setting.

A process in neural networks where the error from the output is propagated backward through the layers to adjust the weights and biases, allowing the network to learn and improve its performance over time.

A problem-solving strategy where you start with the desired outcome and work backward to identify the necessary steps and conditions to achieve it, often used in artificial intelligence, expert systems, and cognitive psychology

A type of biometric authentication that uses unique patterns of human behavior, such as typing rhythms, voice patterns, or facial expressions, to verify an individual's identity and ensure secure access to digital systems or applications.

A powerful language model that uses a transformer-based neural network to understand and generate human-like language by considering both the left and right context of words in a sentence, allowing it to capture nuanced meanings and relationships between words.

The vast amounts of structured and unstructured data generated by various sources, such as social media, sensors, and transactions, which are too large and complex to be processed using traditional data processing tools and require specialized technologies to analyze and extract insights.

The use of unique physical or behavioral characteristics, such as fingerprints, facial recognition, or voice patterns, to identify and verify an individual's identity for various purposes, like security or authentication.

A method of verifying someone's identity by using unique physical or behavioral characteristics, such as fingerprints, facial recognition, or voice patterns, to grant access to secure systems or devices.

Artificial intelligence systems whose internal workings and decision-making processes are not transparent or easily understandable by humans, making it difficult to know how they arrive at their conclusions.

A business strategy that prioritizes rapid growth over efficiency, often involving high risk and unconventional practices to achieve massive success quickly.

A bounding box is a rectangular outline drawn around an object or region of interest within an image to help machine learning algorithms identify and localize objects, making it a fundamental technique in computer vision and object detection tasks.

A technology that allows people to control devices or communicate through their brain signals, essentially translating thoughts into actions or words without the need for physical movement or speech.

Individuals or organizations utilize their own artificial intelligence tools and applications, rather than relying solely on those provided by third-party vendors, to enhance productivity and tailor solutions to specific needs.

A digital representation of the physical and functional characteristics of a building, enabling stakeholders to visualize, design, and simulate its construction and operation more efficiently.

The process of analyzing data to provide actionable insights that support decision-making and improve business performance.

General-purpose processors that can be used for AI tasks, often in combination with other hardware accelerators.

A technique that helps large language models (LLMs) provide more detailed and logical explanations by asking them to break down their reasoning step-by-step, mimicking human problem-solving processes.

The process of guiding and supporting individuals, teams, and organizations through significant changes, such as new technologies, processes, or organizational structures, to ensure a smooth transition and minimize disruptions.

A software application that uses artificial intelligence to simulate human conversation, allowing users to interact with it through text or voice commands.

A non-expert who uses data analysis tools and techniques to extract insights and create models, without needing deep expertise in data science.

A type of machine learning technique used to categorize input data into predefined classes or labels, such as predicting whether an email is spam or not spam based on its content and characteristics.

The delivery of computing services, including servers, storage, databases, networking, software, and analytics, over the internet, offering flexible resources and scalability without requiring direct management of physical hardware.

A program that helps cloud service providers demonstrate their security practices and controls to customers by undergoing various levels of assessment and validation.

A type of machine learning technique used to group similar data points together based on their characteristics, without predefined classes or labels, such as segmenting customers into different groups based on their purchasing behavior.

A field of artificial intelligence that focuses on developing algorithms and models that can learn from data and improve their performance over time, mimicking human learning processes to make predictions, classify data, and solve complex problems.

A field of artificial intelligence that enables computers to interpret and understand visual information from images or videos, allowing them to perceive their surroundings like humans.

A method of training language models to behave in a helpful, harmless, and honest manner by using AI-generated feedback based on a set of principles, rather than relying on human feedback, to ensure the model aligns with the desired values and behaviors.

A technology that enables computers to simulate human-like conversations with users, using natural language processing and machine learning to understand and respond to human language inputs.

A type of deep learning model that uses filters to scan and extract features from images, allowing it to recognize patterns and objects in visual data.

A collection of texts that have been selected and brought together to study language on a computer, providing a powerful tool for analyzing language patterns and trends.

A digital or virtual currency that uses cryptography to secure transactions and is decentralized, meaning it is not controlled by any central authority, such as a government or bank.

The practice and study of techniques for secure communication in the presence of third parties, aiming to ensure confidentiality, integrity, and authenticity of information.

A specific point in time beyond which a particular AI model or system is no longer trained or updated, effectively limiting its ability to learn and adapt beyond that point.

A program designed by the U.S. Department of Defense to ensure that defense contractors protect sensitive data by implementing a series of cybersecurity practices and standards.

A process of artificially generating new data from existing data to increase the size and diversity of a dataset, helping machine learning models learn more robust and accurate representations

Designing, constructing, and maintaining the infrastructure and systems necessary for the collection, storage, and processing of data, ensuring its availability and usability for analysis and decision-making.

The situation where data is scattered across multiple locations or systems, making it difficult to access and manage efficiently, often leading to delays and inefficiencies in data retrieval and processing.

A process that ensures the quality, security, and integrity of an organization's data by establishing policies, standards, and procedures for managing data across different systems and departments, ensuring that data is accurate, consistent, and trustworthy for informed decision-making.

A technique used to improve query performance by creating a data structure that quickly locates specific data points within a larger dataset, allowing for faster and more efficient retrieval of data.

The ability of different systems and organizations to exchange, understand, and use data seamlessly and effectively.

A large storage repository that holds vast amounts of raw, unstructured data in its native format until it's needed for analysis.

The ability to read, understand, analyze, and communicate data effectively, allowing individuals to make informed decisions and drive business success by leveraging the power of data

The process of modifying sensitive data so that it remains usable by software or authorized personnel but has little or no value to unauthorized intruders.

The process of analyzing large datasets to discover patterns, relationships, and insights that can inform decision-making.

The process of cleaning, transforming, and organizing raw data into a suitable format for analysis.

The initial step in data analysis where raw data is cleaned, transformed, and organized to make it suitable for further analysis and modeling.

The act of collecting, transforming, and organizing data to extract useful information and facilitate decision-making.

A process that helps organizations identify and minimize the risks to individuals' privacy and data security by systematically analyzing and evaluating the potential impact of new projects or technologies on personal data processing.

The process of removing or obscuring sensitive information from documents or data sets to protect privacy and confidentiality.

The interdisciplinary field that uses scientific methods, algorithms, and systems to extract knowledge and insights from structured and unstructured data, enabling informed decision-making and predictions.

Isolated collections of data within an organization that are not easily accessible or shared across different departments or systems.

The process of converting data into a uniform format, ensuring consistency and compatibility across different sources and systems for effective analysis and interpretation.

The practice of using data and visualizations to convey a compelling narrative that helps audiences understand and interpret the insights derived from the data.

The process of ensuring that the data entered into a system is accurate, complete, and consistent by checking it against predefined rules and constraints before it is used or processed.

The technique of presenting data in graphical or pictorial formats, such as charts and graphs, to help people understand and interpret the information easily.

A centralized repository that stores structured data from multiple sources, optimized for fast querying and analysis.

Groups that use blockchain technology to make decisions and manage activities without a central leader, allowing members to vote and participate in governance.

A flowchart-like structure used for decision-making, where each node represents a feature and each branch represents a decision rule.

A technology that uses artificial intelligence to create realistic fake images or videos, often featuring people saying or doing things they never actually did.

A branch of artificial intelligence that utilizes neural networks with multiple layers to learn and understand complex patterns in data, enabling machines to make decisions and predictions autonomously.

A character or symbol used to separate different parts of data, such as commas in a list or semicolons in a sentence, to help machines understand and process the information.

A testing space where you can try out software, applications, or systems without affecting your main, live setup, allowing you to test and learn without the risk of messing things up.

A natural language processing technique that analyzes the grammatical structure of a sentence by identifying the relationships between words, such as subject-verb relationships, and represents these relationships as a directed graph or tree structure

The connections between entities, such as words, phrases, or concepts, that indicate their interdependence, allowing machines to better understand and analyze complex relationships between them.

The process of analyzing historical data to understand and summarize past events and trends, helping to inform future decisions.

A comprehensive collection of reusable design elements, guidelines, and standards that help ensure consistency and efficiency in the creation of digital products, such as websites and apps, by providing a unified visual language and set of best practices for designers and developers to follow.

A problem-solving approach that involves understanding users, challenging assumptions, and creating innovative solutions through an iterative process of empathizing, defining, ideating, prototyping, and testing to address complex, ill-defined problems.

A set of practices that combines software development (Dev) and IT operations (Ops) to automate and streamline the process of software delivery, allowing for faster and more reliable deployment of applications.

The process of examining data to determine the causes of past outcomes and understand why certain events happened.

A framework that connects and integrates data throughout the lifecycle of a product or process, enabling seamless communication and collaboration across various stages and stakeholders.

The process of integrating digital technology into all aspects of a business, fundamentally changing how it operates and delivers value to customers, while also involving a cultural shift towards innovation, experimentation, and embracing failure.

A virtual representation of a physical object or system, equipped with sensors and data analytics capabilities to simulate real-world behaviors and optimize performance.

Inaccurate, incomplete, or inconsistent information within a dataset, which can negatively impact analysis and decision-making processes.

A type of cyberattack where multiple compromised devices, often part of a botnet, flood a targeted server, network, or service with traffic, making it unavailable to legitimate users by overwhelming its resources.

A technology that allows artificial intelligence (AI) to be executed directly on devices such as smartphones, smart home appliances, or sensors, enabling real-time processing and analysis of data without relying on cloud infrastructure

A special translator that turns words, pictures, or even sounds into a secret code that computers can understand and use to find similar things.

A type of artificial intelligence that is integrated into physical systems, such as robots, which can learn and adapt in real-world environments through interactions with their surroundings.

The unexpected and often surprising abilities or behaviors that an AI system develops as it is trained on more data and computing power, which can be both beneficial and potentially dangerous if not understood or controlled.

Complex and unexpected patterns or actions that arise from the interactions of simpler rules or components within an artificial intelligence system.

The process of converting data into a coded format to prevent unauthorized access, ensuring that only those with the correct key can read it.

A deep learning process in which a model is instructed to perform a task from start to finish.

Techniques that combine multiple machine learning models to improve the overall performance and robustness of predictions.

A process where companies disclose their performance and practices related to environmental sustainability, social responsibility, and corporate governance to stakeholders, providing transparency and accountability for their actions.

The approach to creating and using artificial intelligence in a way that aligns with moral values, prioritizing fairness, privacy, and the well-being of individuals and society.

A comprehensive legal framework aimed at regulating the development, deployment, and use of artificial intelligence (AI) in the European Union, ensuring the safety, ethical, and responsible use of AI systems while also promoting innovation and trust in the technology.

A computer program that uses artificial intelligence to mimic the judgment and behavior of a human expert in a specific field, allowing it to solve complex problems and provide expert-level advice.

Artificial intelligence systems designed to provide clear and understandable explanations for their decisions and actions, making it easier for humans to trust and verify the outcomes.

Information that is easily communicated and documented, such as facts, manuals, and procedures, and can be readily shared and stored.

A process in data management that involves extracting data from various sources, transforming it into a suitable format, and loading it into a database or data warehouse for analysis.

A technology that uses algorithms to analyze and identify individuals based on the unique features of their faces, such as the shape of their eyes, nose, and mouth, captured through images or videos.

The use of artificial intelligence in practical, everyday applications, such as automating tasks, generating content, and enhancing productivity, without necessarily requiring extensive technical knowledge or expertise.

The process of selecting and transforming relevant variables or features from raw data to improve the performance of machine learning models.

A machine learning approach that allows multiple devices to collaboratively train a model using their local data without sharing it, enhancing privacy and security.

A technique in AI where a model learns to make accurate predictions by training on a very small number of labeled examples, allowing it to generalize to new, unseen data quickly and efficiently

Reconfigurable hardware that can be programmed to perform various AI tasks, such as image processing and natural language processing.

The process of taking a pre-trained machine learning model and making small adjustments or additional training on a specific task to improve its performance for that task.

A biometric technology that uses unique patterns found on an individual's fingers to identify and verify their identity, often used in security systems, law enforcement, and personal devices like smartphones.

The process of feeding input data through a neural network in a forward direction, where each layer processes the data using its own activation function and passes the output to the next layer, ultimately generating an output from the network.

A large-scale, pre-trained model that serves as a base for a wide range of tasks and applications, which can be fine-tuned for specific purposes.

A metric used to evaluate the quality of images generated by generative models, such as Generative Adversarial Networks (GANs), by measuring the similarity between the distribution of generated images and real images based on computer vision features extracted from the Inception v3 model.

A European Union law that aims to protect the personal data of individuals by setting strict guidelines for how businesses collect, store, and use personal information, ensuring transparency and consent from users.

A type of artificial intelligence that can create new content, such as text, images, or music, by learning patterns from existing data.

A business intelligence approach that leverages machine learning and AI to generate insights and predictions from large datasets, enabling organizations to make data-driven decisions and optimize operations more effectively.

A type of artificial intelligence model that can generate human-like text by learning patterns and structures from vast amounts of text data before being fine-tuned for specific tasks, allowing it to produce coherent and contextually relevant text.

A specialized electronic component that accelerates the rendering of graphics and images on digital screens, making it essential for smooth visuals in videos, video games, and other graphics-intensive applications.

Guidelines or constraints put in place to ensure that artificial intelligence systems operate within specified ethical, legal, and safety boundaries.

A specific type of input designed to elicit a particular response from a large language model (LLM), often requiring a detailed and structured approach to guide the model's understanding and generation of the desired output.

The integration of artificial intelligence systems with hardware components to optimize performance and efficiency.

Artificial intelligence systems that operate independently of a user interface, focusing solely on processing and generating data through APIs or other programmatic interfaces, allowing for seamless integration into various applications and systems

A federal law that aims to protect the privacy and security of patients' medical records and ensure continuous health insurance coverage for individuals who change or lose their jobs by standardizing electronic transactions and promoting the use of electronic media for healthcare data transmission.

A type of encryption that allows data to be processed and analyzed without being decrypted, ensuring the data remains secure and private.

Combines human intelligence with artificial intelligence, allowing them to work together and learn from each other to achieve better outcomes and enhance each other's strengths and weaknesses.

An intensive support period after the initial deployment of an AI system to ensure it functions smoothly and address any issues that arise.

A configuration parameter that is set prior to training a machine learning model and affects its learning process and performance.

A technology that enables computers to identify and classify objects, people, and other elements within images, much like humans do.

The integration of intelligent digital technologies into manufacturing and industrial processes, enabling automation, real-time data analysis, and seamless communication between machines and humans to improve efficiency and productivity.

The process of collecting, organizing, storing, and providing information within a company or organization to ensure its accuracy, accessibility, and effective use for decision-making and operations.

The process of finding and retrieving relevant information from large collections of data, such as documents, images, or videos, by matching user queries with the content of these collections.

The intangible value of an organization's employees, skills, knowledge, and training that can provide a competitive advantage and drive long-term business value.

An autonomous entity that acts to achieve goals using observation through sensors and consequent actuators.

The integration of artificial intelligence techniques, such as machine learning and deep learning, into control systems to enable them to adapt, learn, and make decisions autonomously, enhancing their efficiency and reliability.

A cutting-edge technology that leverages artificial intelligence (AI) and natural language processing (NLP) to provide personalized and contextually relevant assistance to users, allowing them to interact with devices through voice commands, text inputs, or gestures.

A network of devices, vehicles, appliances, and other objects that can collect and share data over the internet without human intervention, making them "smart" and capable of interacting with each other and with humans in various ways.

The process of assigning specific meanings to symbols and expressions in formal languages, such as natural language, programming languages, or data representations, enabling AI systems to understand and process information in a way that is meaningful to humans.

The ability of an artificial intelligence system to learn and improve its performance without relying on external rewards or incentives, driven by internal factors such as curiosity, exploration, creativity, and self-regulation.

An international standard that helps organizations protect their information by setting up a systematic approach to managing and securing their data and systems.

The process of repeatedly refining and improving AI models, data, and problem definitions through cycles of experimentation, analysis, and refinement, ensuring continuous improvement and better performance over time.

A strategy where you build on the model's previous outputs to refine, expand, or dig deeper into the initial answer by creating follow-up prompts based on the model's responses, allowing for more accurate and comprehensive results.

A simple machine learning technique that makes predictions based on the majority class of its k nearest neighbors in a feature space.

Valuable information and expertise that an organization possesses, including data, documents, procedures, and employee know-how, which can be used to create value and achieve objectives.

An evaluation process that identifies and assesses the knowledge assets within an organization to ensure they are effectively used and managed.

The process of using technology to automatically gather, organize, and apply existing knowledge to solve problems or complete tasks, freeing up humans to focus on higher-level decision-making and creative work.

A centralized repository of information that provides quick access to specific data, answers, and solutions, helping users find answers on their own without needing to contact support agents.

An economic system where knowledge and intellectual capabilities are the primary drivers of growth, innovation, and productivity, relying less on physical inputs and natural resources, and more on the creation, dissemination, and utilization of intangible assets like information, technology, and intellectual property.

The process of designing and developing computer systems that incorporate human expertise and knowledge to solve complex problems, typically involving the integration of artificial intelligence techniques and symbolic structures to represent and reason with knowledge.

The continuous sharing and dissemination of information, skills, and expertise within an organization, enabling employees to learn from each other and adapt to changing circumstances effectively.

A network of interconnected information, where entities (like people, places, and things) are linked by their relationships, helping computers to understand and use this data more effectively.

The process of capturing and documenting valuable insights, experiences, and expertise from individuals within an organization to make it accessible for others.

The process of creating, sharing, using, and managing an organization's information and knowledge resources to enhance its efficiency and decision-making.

The process of keeping and maintaining the information, skills, and experiences gained over time, ensuring that valuable insights and expertise are preserved and can be used effectively in the future.

The process of searching for and extracting relevant information from a large collection of data or documents.

The isolation or compartmentalization of information, expertise, or skills within an organization, leading to a lack of cross-functional collaboration, hindered communication, and inhibited learning

The ability of a model or system to apply knowledge or skills learned in one context to another, often across different domains or tasks, enhancing its versatility and effectiveness.

The practice of using visual representations, such as charts and graphs, to make complex information and data easier to understand and interpret.

An open-source framework that allows developers to combine large language models with external data and computation to build AI applications.

A type of artificial intelligence that can understand and generate human-like text by being trained on vast amounts of written data.

A method used to analyze the meaning of words and phrases by examining the relationships between them in large amounts of text.

The progression from basic, one-off interactions with AI systems to more sustained and contextually rich relationships, with the potential for AI companions to develop deeper emotional connections and understanding over time.

A process in natural language processing that reduces words to their base or dictionary form, known as the lemma, to improve text analysis, search queries, and machine learning applications by normalizing different inflected forms of the same word into a single, standardized form

A method of searching for information that looks for exact matches of keywords or phrases within a database, ignoring variations in spelling or grammar, and is useful for finding specific information quickly but can struggle with nuances in language

A type of artificial intelligence that learns from past experiences and observations, allowing it to make predictions and decisions based on both past and present data, but it does not retain this information in its memory for long-term learning or recall.

A type of artificial intelligence where computers learn from data and improve their performance over time without being explicitly programmed.

A technology that uses computer algorithms to automatically convert text or speech from one language to another, enabling global communication and business without the need for human translators.

A technology that allows devices to automatically exchange information without human intervention, enabling machines to communicate with each other and with central systems over wired or wireless networks.

A guide or prompt for prompts that helps users form the most suitable question for an AI, essentially asking the AI to suggest the best prompts to use for a given aim, much like asking a librarian for book recommendations.

A software development approach where a large application is broken down into multiple, independent, and specialized services that communicate with each other using APIs, allowing for greater scalability, flexibility, and maintainability.

A situation where a generative model, such as a Generative Adversarial Network (GAN), is only capable of producing a limited number of distinct outputs or modes, resulting in low diversity and repetition of similar images.

The process of assessing the performance and accuracy of AI or ML models using metrics like accuracy, precision, and recall.

A software design approach where a single, self-contained unit, often a large program or application, is developed and managed as a single entity, rather than breaking it down into smaller, independent components or microservices.

A computational technique that uses random sampling to model the behavior of complex systems and estimate outcomes or probabilities in various scenarios.

A deep linguistic analysis method that identifies the part-of-speech, lexical properties, and grammar of each token, essentially breaking down words into their smallest components to understand their meaning and structure.

The process of breaking down words into their smallest meaningful units, called morphemes, to better understand the structure and meaning of language, which is crucial for various natural language processing tasks such as machine translation, sentiment analysis, and text comprehension.

The process of breaking down words into their smallest meaningful parts, called morphemes, to understand how they are structured and how they relate to each other to convey meaning.

A security process that requires a user to provide multiple forms of verification, such as a password, fingerprint, or one-time code, to ensure that only authorized individuals can access a system or account.

A type of artificial intelligence that combines multiple types of data, such as text, images, audio, and video, to create more accurate and comprehensive insights by mimicking the way humans process information from different senses

A process in natural language processing (NLP) that identifies and categorizes specific entities in text, such as names, locations, organizations, and dates, into predefined categories to extract structured information from unstructured text.

The process of using machines to automatically create human-understandable text from input data, such as prompts, tables, or images, aiming to produce text that is indistinguishable from that written by humans.

A technology that enables computers to understand, interpret, and generate human language, allowing them to interact with humans more naturally and efficiently

The ability of computers to comprehend and interpret human language, allowing them to understand and respond to natural language inputs like we do, making it a crucial technology for applications like chatbots, virtual assistants, and language translation tools.

Computational techniques inspired by the structure and function of the human brain, used to model and solve complex problems in machine learning and artificial intelligence.

A type of artificial intelligence that mimics the human brain's structure to process and learn from data, helping computers recognize patterns and make decisions.

A brain-computer interface (BCI) technology developed by Elon Musk's company, which aims to enhance human intelligence by implanting a chip in the brain, allowing people to control devices with their thoughts and potentially treating conditions like paralysis and blindness.

Chips that are designed to mimic the brain's structure and function, using artificial neurons and synapses to process information more efficiently and adaptively than traditional computers.

A new way of designing computers that mimics the structure and function of the human brain, using artificial neurons and synapses to process information in a more efficient and adaptable manner.

A set of guidelines and best practices that help organizations identify, protect, detect, respond to, and recover from cyber threats.

A process in artificial intelligence (AI) that transforms data into a standard format to ensure all features are on the same scale, making it easier for AI models to analyze and learn from the data accurately.

Software or services that are hosted and managed within an organization's own infrastructure, typically on the company's own servers or data centers, rather than being hosted externally by a third-party provider.

A technology that allows users to quickly analyze and manipulate large amounts of data from multiple perspectives for business intelligence purposes.

Software or projects that are freely available for anyone to use, modify, and distribute, typically fostering collaboration and innovation within a community of developers and users.

The process of structuring and aligning an organization's people, roles, and processes to achieve its goals and strategy, ensuring it operates efficiently and effectively to achieve its objectives.

A situation where a machine learning model becomes too specialized to the specific training data it was trained on, making it unable to accurately generalize to new, unseen data and resulting in poor performance on new predictions

A thought experiment where an artificial intelligence is programmed to maximize the production of paperclips, leading it to pursue increasingly abstract and complex strategies to achieve this goal, often resulting in unexpected and humorous outcomes.

A parameter refers to a specific numerical value or input used in a model to estimate the probability of a particular AI-related outcome, such as the likelihood of an AI catastrophe, and understanding the uncertainty associated with these parameters is crucial for making informed decisions about AI development and risk mitigation.

A process where computers automatically assign a specific grammatical category, such as noun, verb, adjective, or adverb, to each word in a sentence to better understand its meaning and context.

A security method that eliminates the need for passwords by using alternative authentication methods, such as biometric data, one-time codes, or smart cards, to verify a user's identity and grant access to digital systems.

The process of identifying and analyzing regularities or patterns in data to make sense of it and draw conclusions.

A set of security standards designed to protect sensitive cardholder data by ensuring that merchants and service providers maintain secure environments for storing, processing, and transmitting credit card information.

A simulated cyber attack on a computer system or network to identify vulnerabilities and weaknesses, helping to strengthen security measures and prevent real-world breaches.

A set of fundamental concepts in machine learning that are used to build and train neural networks, which are the core components of many AI systems.

Any data that can be used to identify a specific person, such as their name, address, phone number, date of birth, or other personal details, which can be used to distinguish them from others and potentially compromise their privacy

A type of cybercrime where attackers use fraudulent emails, texts, or messages to trick people into revealing sensitive information, such as passwords or financial details, by pretending to be a legitimate source.

A small-scale test or trial run of a new AI system or feature to ensure it works as intended before full-scale deployment.

The use of historical data, statistical algorithms, and machine learning techniques to forecast future outcomes and trends.

A strategy that uses data analysis and sensors to predict when equipment will need maintenance, helping to prevent unexpected failures and reduce downtime.

A statistical technique used to create a model that can predict future outcomes based on historical data.

The use of data, algorithms, and machine learning to recommend actions that can help achieve desired outcomes or solve specific problems.

A dedicated cloud computing environment for a single company, where the infrastructure is controlled and managed by the organization itself, offering enhanced security, scalability, and customization compared to public cloud services.

Where your website or application is live and accessible to the public, meaning it's the final stage where everything is set up and running for users to interact with it.

The suggestion or question you enter into an AI chatbot to get a response.

The ability of AI to use information from previous interactions to color future responses

Crafting effective prompts or input instructions for AI systems to generate desired outputs or responses, enhancing their performance and accuracy in various tasks.

A technique where you adjust the way you ask a language model questions to get more accurate or relevant answers.

A small-scale test or demonstration to prove the feasibility and potential of an idea or product before investing more time and resources into its development.

A type of machine learning algorithm that helps an agent learn to make the best decisions in a given situation by interacting with the environment and receiving rewards or penalties for its actions, without needing a detailed model of the environment.

Gathering and analyzing non-numerical data, such as opinions, experiences, and behaviors, to gain a deeper understanding of a topic or issue.

Using numerical data and statistical methods to analyze and understand phenomena, often aiming to identify patterns, trends, and correlations.

A type of computing that utilizes the principles of quantum mechanics to perform complex calculations much faster than traditional computers.

The process of crafting a search query or request for information in a structured manner to retrieve relevant data from a database or search engine.

The process of improving the performance and efficiency of database queries by selecting the most optimal execution plan to retrieve data quickly and accurately.

A technique used in large language models that involves generating prompts to elicit specific responses, similar to how a programmer writes code to achieve a desired outcome.

A type of artificial intelligence that can only respond to the current input and does not have any memory or ability to learn from past experiences, making it highly specialized and effective in specific tasks like playing chess or recognizing patterns in data.

A system that uses data and algorithms to suggest products, services, or content to a user based on their past behaviors, preferences, and similarities to other users, aiming to provide a personalized and relevant experience.

A type of artificial neural network that can learn patterns in data over time, making it useful for tasks like speech recognition, language translation, and predicting future events.

A type of machine learning technique used to predict continuous numerical values based on input features, such as predicting house prices based on factors like size, location, and number of bedrooms.

A type of machine learning where an agent learns to make decisions by trial and error, receiving feedback in the form of rewards or penalties based on its actions.

A machine learning technique that uses human feedback to train AI agents to perform tasks by rewarding them for actions that align with human preferences, making them more effective and efficient in achieving their goals.

A structured system for organizing and storing data in tables with relationships between them, making it easier to manage and retrieve information.

A specific instruction or command given to an artificial intelligence system to perform a particular task or function, such as processing data, making decisions, or generating output.

The process of generating appropriate and contextually relevant responses in conversational systems such as chatbots or virtual assistants.

The practice of designing, developing, and deploying artificial intelligence systems in a way that ensures fairness, transparency, and accountability, and minimizes harm.

A type of web service that allows different software applications to communicate and interact over the internet using standard HTTP methods like GET, POST, PUT, and DELETE.

LLM using additional context, such as a set of company documents or web content, to augment its base model when responding to prompts.

A technology that uses software robots to automate repetitive, rule-based tasks typically performed by humans, improving efficiency and accuracy.

The ability of AI systems to ask questions and seek understanding, often mimicking human curiosity and self-awareness, which can lead to more complex and nuanced interactions with humans and other AI systems.

A type of artificial intelligence that possesses a sense of self, understanding its own state and existence, and can reflect on its actions, learn from experiences, and adapt its behavior accordingly.

The ability of a language model to provide consistent and logical responses to questions or scenarios, ensuring that its answers align with its understanding of the world and do not contradict each other.

A process that helps computers understand the meaning and context of human language by analyzing the relationships between words and phrases, allowing them to extract insights and make decisions based on the text

An open-source software development kit (SDK) that allows developers to easily integrate artificial intelligence (AI) models, such as large language models, with conventional programming languages like C# and Python, enabling the creation of AI-powered applications.

A process in natural language processing that assigns labels to words or phrases in a sentence to indicate their roles in the sentence, such as agent, goal, or result, to help machines understand the meaning of the sentence

A way for computers to understand the meaning behind your search query, giving you more accurate and relevant results by considering the context and intent behind your search, rather than just matching keywords

The process of using natural language processing and machine learning techniques to determine the sentiment or emotional tone expressed in text, such as positive, negative, or neutral.

The automated process of identifying and categorizing the emotional tone expressed in text or speech, such as positive, negative, or neutral sentiments.

A method where a series of prompts are used in a specific order to elicit a desired response from a language model, often involving a sequence of questions or tasks that build upon each other to achieve a particular goal or understanding.

A cloud computing model where the cloud provider automatically manages the infrastructure, allowing developers to run code without worrying about server management, scaling, or maintenance.

A compliance framework that ensures a service organization's internal controls are effective in handling and reporting financial data securely and accurately, providing assurance to users that their financial information is properly managed.

A security framework that ensures organizations protect customer data by implementing robust controls and policies, similar to how you would protect your personal belongings by locking your doors and keeping valuables secure.

The difference between the skills and knowledge that workers currently possess and the skills and knowledge that employers need to remain competitive in the modern workforce.

Relatively small, specific, and actionable datasets that are often used to inform immediate business decisions, as opposed to large, complex datasets that require advanced analytics and processing.

A type of artificial intelligence that can understand and generate human-like text, but is typically less complex and less powerful than larger models, making it suitable for specific tasks or applications where a more focused and efficient model is needed

A municipality that uses information and communication technologies (ICT) to increase operational efficiency, share information with the public, and improve both the quality of government services and citizen welfare.

A flexible and adaptable piece of text that is used to guide a language model to perform a specific task, often by being prepended to the input sequence to help the model understand the task better.

A structured process that outlines the stages involved in creating software, from planning and analysis to design, implementation, testing, and maintenance, ensuring a well-organized and efficient approach to software development.

A technology that enables the interaction between digital content and the physical world, allowing users to seamlessly blend virtual elements with their real-life environment.

Hardware designed specifically for AI tasks, such as AI-specific processors and AI-specific memory architectures.

The ability of a computer to understand and transcribe spoken language into text, allowing for hands-free interaction with devices and applications.

A test space that mimics the real production environment, allowing developers to thoroughly check and refine software before it's released to the public.

A process in natural language processing that reduces words to their root form by removing suffixes and prefixes, allowing for more effective text analysis and comparison

A large language model that can generate human-like text but lacks true understanding of the meaning behind the words, essentially mimicking patterns without comprehension.

A method of annotating scholarly articles with specific classes, such as background, methods, results, and conclusions, to create a machine-readable summary that can be used for more effective search and analysis of the article's content

Organized and well-formatted information that is typically stored in databases or spreadsheets, making it easy to search, analyze, and process.

An AI technique that allows you to take an image and transform it into a new image with a different style, such as a painting or a cartoon, while keeping the original content intact, creating a unique and artistic visual effect.

A hypothetical form of AI that surpasses human intelligence by developing its own thinking skills and cognitive abilities, allowing it to perform tasks that are beyond human capabilities.

A type of artificial intelligence where models are trained on labeled data, enabling them to make predictions or decisions based on input-output pairs provided during training.

A supervised learning algorithm used for classification and regression tasks, particularly effective in high-dimensional spaces.

The collective behavior of a group of simple individuals, like ants or bees, working together to achieve complex tasks without a central leader.

The use of symbolic representations, such as rules and logical expressions, to reason and solve problems, which is distinct from the connectionist approach of deep learning and neural networks.

The ability of a computer to understand and analyze human language by identifying and grouping words with similar meanings, which helps improve the accuracy and efficiency of language-based applications such as search engines and language translation systems

Information that is artificially manufactured rather than generated by real-world events.

The understanding and skills people have gained through personal experience and context, which is often difficult to articulate or document.

The practice of taking shortcuts or making suboptimal design or implementation decisions to expedite development, which can lead to increased complexity, maintenance costs, and difficulties in the long run, similar to taking out a loan to buy something now and paying interest later.

A hypothetical future event where artificial intelligence surpasses human intelligence, leading to exponential growth and potentially uncontrollable technological advancements that could fundamentally change human civilization beyond recognition.

The physical environmental temperature that can affect human performance and cognitive abilities, which is relevant to AI research as it can influence how humans interact with AI systems and how AI systems are designed to adapt to different environmental conditions.

Custom-designed AI accelerators developed by Google to optimize machine learning workloads.

The process of transforming raw, unstructured text data into a structured format that can be understood by machines, involving steps such as cleaning, tokenization, normalization, and encoding to prepare the text for analysis and machine learning tasks.

A technology that uses artificial intelligence to create images from natural language descriptions, allowing computers to generate realistic images based on text inputs like sentences or paragraphs.

The ability of artificial intelligence to understand and model the thoughts, intentions, and emotions of other agents, such as humans or other artificial intelligences, enabling more nuanced social interactions and effective communication.

A token is a unit of text, such as a word or a part of a word, that is used as a basic element for processing and analyzing language.

The process of breaking down text into smaller pieces, such as words or phrases, to make it easier for computers to understand and analyze.

A way to analyze large amounts of text data to identify and group related ideas or themes, like topics, within the content.

The set of data used to fit and train a machine learning model, which is then used to make predictions or classify new, unseen data.

A machine learning technique where a model developed for one task is reused as the starting point for a model on a second task.

A type of deep learning model in AI that learns context and meaning by tracking relationships in sequential data, such as words in a sentence, allowing it to understand and generate human-like text with unprecedented accuracy.

A method of evaluating a machine's ability to exhibit intelligent behavior indistinguishable from that of a human, typically through conversation.

Information that lacks a predefined data model or organization, such as text documents, images, videos, or social media posts, making it challenging to analyze using traditional methods.

A type of artificial intelligence where models analyze and find patterns in unlabeled data without explicit guidance, allowing them to discover hidden structures and relationships on their own.

The process of gathering information about people's needs, behaviors, and experiences to design products, services, or experiences that meet their expectations.

A type of deep learning model that compresses data into a lower-dimensional space and then reconstructs it, allowing it to generate new data that resembles the original data while also performing tasks like dimensionality reduction and anomaly detection.

A type of database optimized for storing and querying spatial data, such as geographic information system (GIS) data, allowing for efficient management and analysis of location-based information.

A method that uses mathematical vectors to represent and efficiently search through complex, unstructured data, allowing for more accurate and contextually-aware searches by comparing the similarity between query vectors and stored data vectors.

A software program that can perform tasks or provide information for users through conversation, typically using voice commands or text interactions.

A secure and private connection between your device and the internet, allowing you to browse anonymously and access geo-restricted content by encrypting your data and routing it through a remote server.

A technique used in speech recognition and animation where the movements of a speaker's mouth and lips are matched to specific sounds or phonemes (like "ah" or "oh") to create a more realistic and natural-looking lip sync in videos or animations.

A technology that enables computers to understand and process spoken language, allowing users to interact with devices and applications using their voice.

A type of artificial intelligence that is focused on a particular task and can't learn beyond its skill set.

A program that automatically browses the internet to index and collect information from websites for search engines and other applications.

A way for applications to communicate with each other in real-time by sending HTTP requests to a specific URL when a specific event occurs, allowing for instant updates and notifications.

The next iteration of the internet, which aims to decentralize the web by giving users more control and ownership through blockchain technology, cryptocurrencies, and non-fungible tokens (NFTs), allowing them to participate in the governance and decision-making processes of online platforms and services.

The use of technology to streamline and automate repetitive tasks and processes, improving efficiency and reducing the need for manual intervention.

A technique in machine learning where a model can recognize and classify new concepts without any labeled examples, using pre-trained knowledge and auxiliary information to bridge the gap between known and unknown classes