Definitions:
- Infrastructure as a Service (IaaS): A form of cloud computing that provides virtualised computing resources over the Internet. IaaS allows businesses to rent computing resources such as servers, storage, and networking components on a pay-as-you-go basis. This enables organisations to scale their IT infrastructure up or down as needed, without the need for significant upfront investments in hardware.
- Information Retrieval: The activity of obtaining information resources relevant to an information need from a collection of information resources. Information retrieval involves techniques for indexing, searching, and ranking documents to provide users with the most relevant information. This is crucial in fields such as search engines, digital libraries, and knowledge management systems.
- Internet of Things (IoT): The network of physical objects that contain embedded technology to communicate and sense or interact with their internal states or the external environment. IoT devices include sensors, actuators, and other smart devices that collect and exchange data. This enables the creation of smart homes, smart cities, and industrial automation, among other applications.
- IoT Edge: The practice of processing data at or near the source of the data, usually on the IoT devices themselves, rather than relying on the cloud for all processing. Edge computing in IoT reduces latency, improves response times, and enhances the efficiency and reliability of IoT systems. This is particularly useful in applications that require real-time data processing and decision-making.
- Information Architecture (IA): The structural design of shared information environments. IA aims to organise and label content in a way that supports usability and findability. It involves creating a coherent structure for websites, intranets, and other digital platforms, ensuring that users can easily navigate and find the information they need. IA is a critical component of user experience (UX) design.
- Interactive Design: A design discipline focused on creating engaging and intuitive digital products and services. Interactive design involves the creation of user interfaces that respond to user actions and provide dynamic feedback. This includes the design of websites, mobile apps, and other digital interfaces, with a focus on enhancing user engagement and satisfaction.
- Image Processing: The use of algorithms and techniques to analyse and manipulate digital images. Image processing involves tasks such as image enhancement, noise reduction, edge detection, and object recognition. It is widely used in fields such as computer vision, medical imaging, and remote sensing. Image processing is a key component of AI and machine learning applications.
- Intelligent Automation: The use of AI and machine learning to automate complex business processes. Intelligent automation combines robotic process automation (RPA) with AI technologies to create systems that can learn, adapt, and make decisions autonomously. This enables organisations to automate repetitive tasks, improve efficiency, and reduce human error.
- Inference Engine: A component of an expert system that applies logical rules to the knowledge base to deduce new information. Inference engines use reasoning techniques to draw conclusions from the data and rules provided. They are a key component of AI systems, enabling them to make decisions and provide insights based on available data.
- Integration Testing: A type of software testing that involves testing different components or modules of a software system as a group. Integration testing aims to ensure that the various components of a system work together as intended. It is an essential part of the software development lifecycle, helping to identify and resolve issues related to the interaction between different parts of a system.
- Interoperability: The ability of different systems, devices, and applications to communicate and exchange data with each other. Interoperability ensures that different technologies can work together seamlessly, enabling the sharing of information and the integration of various systems. This is crucial in fields such as healthcare, finance, and enterprise IT.
- Intelligent Virtual Assistant (IVA): An AI-powered digital assistant that can understand and respond to user queries and commands. IVAs use natural language processing (NLP) and machine learning to provide personalised and context-aware assistance. Examples include Siri, Alexa, and Google Assistant. IVAs are used in various applications, from customer service to personal productivity.
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