AI lexicon

• AI (Artificial Intelligence): Computer systems designed to perform tasks that typically require human intelligence, such as visual perception, speech recognition, and decision-making.
• AGI (Artificial General Intelligence): A theoretical type of AI that would be as smart as humans across all areas, not just in specific tasks.
• Administrative Automation: Tools that handle routine office tasks without human input, like scheduling or data entry.
• Agile: A flexible approach to project management that breaks work into small, manageable chunks.
• API (Application Programming Interface): A set of rules that allow different software programs to communicate with each other.
• API Gateway: A tool that manages and secures the flow of data between different software applications.
• API Key: A unique code that identifies and authorizes a user or program to access an API.
• Augmented Automation: The combination of human skills with AI to enhance work processes and outcomes.
• Backend: The behind-the-scenes part of a website or app where data is processed and stored.
• Base Model: A pre-trained AI system that serves as a starting point for more specialized AI tasks.
• BI (Business Intelligence): Tools and techniques used to turn raw data into meaningful information for business decision-making.
• BPA (Business Process Automation): Using technology to automate complex, repetitive business tasks and workflows.
• ChatOps: The integration of chat platforms with various work tools to streamline communication and operations.
• Cloud Computing: The delivery of computing services over the internet, including storage, processing, and software.
• Concurrent Processing: The ability of a system to handle multiple tasks or operations at the same time.
• Containerization: A method of packaging software so it can run reliably on different computing environments.
• CRM (Customer Relationship Management): Software that helps businesses manage their interactions with current and potential customers.
• CRUD Operations: The four basic functions of persistent storage: Create, Read, Update, and Delete.
• CSS (Cascading Style Sheets): A language used to describe the look and formatting of a document written in HTML.
• Data Lake: A storage system that holds a vast amount of raw data in its original format until it's needed.
• Data Mining: The process of finding patterns or relationships in large datasets to guide decision-making.
• Data Warehouse: A large store of data collected from various sources within an organization used for analysis.
• Deep Learning: A type of machine learning that uses layered algorithms inspired by the human brain.
• DevOps: A set of practices that combines software development and IT operations to shorten development cycles.
• Digital Transformation: The process of using digital technologies to create new or modify existing business processes and customer experiences.
• Docker: A platform that makes it easier to create, deploy, and run applications by using containers.
• ETL (Extract, Transform, Load): The process of taking data from multiple sources, changing it, and then loading it into a database.
• Embeddings: A way to represent words, phrases, or other data as numbers that capture their meaning and relationships.
• Enterprise Architecture: The practice of analyzing, designing, planning, and implementing enterprise-wide changes in business processes and IT.
• Fine-tuning: The process of adjusting a pre-trained AI model to perform well on a specific task.
• Frontend: The part of a website or application that users interact with directly.
• Generative AI: AI systems that can create new content, such as text, images, or music, based on what they've learned from existing data.
• GraphQL: A query language for APIs that allows clients to request exactly the data they need.
• Growth Hacking: Creative, low-cost strategies focused on growing a business's customer base quickly.
• GUI (Graphical User Interface): A visual way of interacting with a computer using icons and graphics instead of text commands.
• HTML (HyperText Markup Language): The standard language used to create web pages.
• Hyperautomation: An approach that combines multiple technologies like AI and machine learning to automate as many business processes as possible.
• IaaS (Infrastructure as a Service): A type of cloud computing that provides virtualized computing resources over the internet.
• Integration: The process of combining different IT systems, software, or data to work together as a unified system.
• JavaScript: A programming language that makes websites interactive.
• Kubernetes: An open-source system for automating the deployment, scaling, and management of containerized applications.
• LLM (Large Language Model): An AI model trained on vast amounts of text data, capable of understanding and generating human-like text.
• Legacy System: An old computer system or application that continues to be used, despite being outdated.
• Machine Learning: A subset of AI that enables systems to learn and improve from experience without being explicitly programmed.
• Microservices: An architectural style that structures an application as a collection of small, loosely coupled services.
• MVP (Minimum Viable Product): A basic version of a new product with just enough features to satisfy early customers and provide feedback for future development.
• NLP (Natural Language Processing): A branch of AI that helps computers understand, interpret, and generate human language.
• Neural Networks: Computing systems inspired by the human brain, designed to recognize patterns.
• No-Code Platform: Tools that allow users to create software applications without writing code, typically using visual interfaces.
• OAuth: A standard that allows users to grant websites or applications access to their information on other websites, without sharing passwords.
• OCR (Optical Character Recognition): Technology that converts different types of documents, such as scanned paper documents, PDF files, or images, into editable and searchable data.
• PaaS (Platform as a Service): A cloud computing model where a third-party provider delivers hardware and software tools to users over the internet.
• Predictive Analytics: The use of data, statistical algorithms, and machine learning techniques to identify the likelihood of future outcomes based on historical data.
• PWA (Progressive Web App) A web app that can be installed on a device as a standalone application. They provide a user experience similar to a platform-specific app, but with the flexibility of a website.
• Prompt Engineering: The skill of crafting effective instructions or queries for AI models to produce desired outputs.
• Python: A popular programming language known for its simplicity and versatility, often used in AI and data science.
• RAG (Retrieval Augmented Generation): A technique that enhances AI language models by allowing them to access and use external information sources.
• REST API: A set of rules for building web services that are lightweight, maintainable, and scalable.
• RPA (Robotic Process Automation): Technology that uses software robots or "bots" to automate repetitive tasks and processes.
• SaaS (Software as a Service): A method of software delivery where a provider hosts applications and makes them available to customers over the internet.
• Scalability: The ability of a system, network, or process to handle a growing amount of work, or its potential to be enlarged to accommodate that growth.
• Scrum: An agile framework for managing knowledge work, with an emphasis on software development.
• Semantic Search: A search technique that aims to improve search accuracy by understanding the searcher's intent and the contextual meaning of terms.
• SSO (Single Sign-On): An authentication method that allows users to access multiple applications with one set of login credentials.
• SQL (Structured Query Language): A standard language for managing and manipulating databases.
• Tech Stack: The combination of programming languages, tools, and technologies used to create and run a single application.
• Technical Debt: The implied cost of additional work caused by choosing an easy (limited) solution now instead of using a better approach with an initial cost.
• TTS (Text-to-Speech): Technology that converts written text into spoken words.
• Tokenization: The process of breaking down text into smaller units (tokens) for AI processing.
• Transfer Learning: A machine learning method where a model developed for one task is reused as the starting point for a model on a second task.
• UI (User Interface): The point of interaction between the user and a digital device or product.
• UX (User Experience): The overall experience of a person using a product, especially in terms of how easy or pleasing it is to use.
• User Story: A simple description of a product feature written from the perspective of the end user.
• Vector Database: A specialized database designed to store and search vector embeddings, which are numerical representations of data used in machine learning.
• Version Control: A system that records changes to a file or set of files over time so that specific versions can be recalled later.
• Webhook: Automated messages sent from apps when something happens; they're a way for apps to communicate with each other in real-time.
• Workflow Automation: The design, execution, & automation of processes based on workflow rules, where tasks, information, or documents are passed from one participant to another for action.
• WYSIWYG: Stands for "What You See Is What You Get," referring to editing software where the on-screen content appears very similar to the final output.
• Zero-shot Learning: An AI's ability to recognize or categorize things it hasn't been explicitly trained on, based on its understanding of related concepts.

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