Definitions:
Accessibility Standards: Guidelines and best practices to ensure digital products are usable by people with disabilities. These standards ensure that websites, applications, and other digital interfaces are designed to be accessible to users with various impairments, such as visual, auditory, physical, speech, cognitive, language, learning, and neurological disabilities.Advanced Analytics: The use of sophisticated techniques and tools to predict future trends, events, and behaviours. Advanced analytics goes beyond basic business intelligence to include predictive and prescriptive analytics, using machine learning algorithms and statistical models to uncover hidden patterns, make predictions, and recommend actions.Agile Development: An iterative and incremental approach to software development that emphasises flexibility and customer collaboration. Agile methodologies promote continuous improvement, iterative development, and rapid delivery of software, with a focus on collaboration, customer feedback, and small, incremental releases.AI Ethics: The principles and guidelines for developing and deploying artificial intelligence responsibly. AI ethics address issues such as fairness, accountability, transparency, privacy, and the potential social and economic impacts of AI technologies.AI Explainability (XAI): The ability of AI to explain its decisions and actions in a way that humans can understand. XAI aims to make AI systems more transparent and interpretable, which is crucial for building trust, ensuring accountability, and facilitating debugging and improvement.AI Governance: The frameworks and processes for managing AI systems to ensure they are ethical, fair, and transparent. AI governance encompasses the policies, procedures, and practices that organisations implement to oversee the development, deployment, and use of AI technologies, ensuring they align with ethical guidelines and regulatory requirements.AI Solutions: Comprehensive systems and applications that utilise AI to solve complex problems. AI solutions can include a wide range of technologies, such as machine learning, natural language processing, computer vision, and robotics, and are designed to automate tasks, improve decision-making, and enhance overall efficiency and effectiveness.Anomaly Detection: Identifying unusual patterns or outliers in data that do not conform to expected behaviour. Anomaly detection is used in various applications, such as fraud detection, network security, and predictive maintenance, to identify and respond to deviations from normal patterns.API (Application Programming Interface) Architecture: The design of the interface that allows different software systems to communicate with each other. API architecture defines the structure, protocols, and standards for APIs, enabling seamless integration and interaction between different applications, services, and platforms.Application Security: Measures taken to protect applications from threats and vulnerabilities. Application security encompasses the processes, tools, and techniques used to identify, mitigate, and prevent security risks in software applications, ensuring the confidentiality, integrity, and availability of data.Artificial General Intelligence (AGI): Hypothetical AI that understands, learns, and applies knowledge across a wide range of tasks at a level equal to or beyond human capabilities. AGI aims to replicate the general intelligence and problem-solving abilities of humans, enabling AI systems to perform any intellectual task that a human can.Artificial Intelligence (AI): The simulation of human intelligence processes by machines, especially computer systems. AI encompasses a broad range of technologies and techniques, including machine learning, natural language processing, computer vision, and robotics, which enable machines to perform tasks that typically require human intelligence.Artificial Narrow Intelligence (ANI): AI designed and trained to perform a narrow range of specific tasks. ANI is focused on solving particular problems or performing specific functions, such as image recognition, speech recognition, or recommendation systems, and does not possess the general problem-solving capabilities of AGI.Artificial Neural Network (ANN): A computing system modeled after the human brain, designed to recognise patterns and make predictions. ANNs consist of interconnected layers of artificial neurons, which process input data through a series of mathematical operations to generate output predictions.Attention Mechanisms: Techniques used in neural networks to selectively focus on important parts of the input data. Attention mechanisms enable models to weigh the importance of different input features, allowing them to focus on relevant information and ignore irrelevant or noisy data.Augmented Reality (AR): Technology that overlays digital information and virtual objects onto the real-world environment. AR enhances the user's perception of the real world by adding computer-generated sensory input, such as visual, auditory, or haptic feedback, to create an immersive and interactive experience.AutoEncoders: Neural networks used for dimensionality reduction or denoising by learning efficient data codings. Autoencoders consist of an encoder that compresses input data into a lower-dimensional representation and a decoder that reconstructs the original data from the compressed representation.Automation: The use of technology to perform tasks with minimal human intervention. Automation encompasses a wide range of technologies and techniques, including robotic process automation, machine learning, and artificial intelligence, which enable machines to perform repetitive, rule-based, or complex tasks efficiently and accurately.Azure Active Directory (AAD): Microsoft's cloud-based identity and access management service. AAD provides a comprehensive identity and access management solution, enabling organisations to manage user identities, control access to applications and resources, and enforce security policies across on-premises and cloud environments.Azure Cognitive Services: A set of APIs, SDKs, and services available on Azure that enable developers to easily add AI capabilities to their applications. Azure Cognitive Services include a wide range of pre-built AI models and tools for vision, speech, language, knowledge, and search, allowing developers to integrate advanced AI functionality into their applications with minimal effort.Azure DevOps: A set of development tools from Microsoft for planning, developing, delivering, and monitoring applications. Azure DevOps provides a comprehensive suite of tools and services for continuous integration, continuous delivery, and continuous deployment, enabling organisations to streamline their software development lifecycle and improve collaboration and productivity.Azure Functions: An event-driven, serverless compute service on the Microsoft Azure cloud platform. Azure Functions allows developers to build and run small, discrete pieces of code in response to events, without the need to manage infrastructure, enabling scalable and efficient event-driven applications.Azure Kubernetes Service (AKS): A managed Kubernetes container orchestration service on Azure. AKS simplifies the deployment, management, and scaling of containerised applications, providing a fully managed Kubernetes environment with built-in security, monitoring, and compliance features.Azure Machine Learning (AML): A cloud-based environment for building, training, and deploying machine learning models. AML provides a comprehensive set of tools and services for data preparation, model training, evaluation, and deployment, enabling data scientists and developers to build and deploy machine learning models efficiently and effectively.Azure Storage: Microsoft's cloud storage solution for modern data storage scenarios. Azure Storage provides a range of storage services, including blob storage, file storage, queue storage, and table storage, enabling organisations to store and manage large amounts of unstructured and structured data in the cloud.
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