Glossary for Advanced Users
Bias in AI refers to systematic errors or prejudices that can occur within AI systems due to biased training data, faulty algorithms, or human biases. Addressing bias in AI is crucial for ensuring fairness, inclusiveness, and ethical practices in AI applications.
Big Data refers to large, complex datasets that cannot be easily managed or analysed with traditional data processing methods. AI techniques, such as Machine Learning, enable businesses to extract valuable insights from Big Data, revealing patterns, trends, and correlations that can inform decision-making and drive growth.
A ChatBot is an AI-powered robot that communicates with users via written or spoken language, helping them with tasks or providing information. It uses Natural Language Processing and Machine Learning to provide human-like interactions, answering questions, scheduling appointments, and providing relevant information.
ChatGPT is an AI model developed by OpenAI that excels in generating human-like text-based responses. Powered by advanced language models and deep learning techniques, ChatGPT understands user inputs, generates contextually relevant responses, and facilitates dynamic and personalised interactions with customers.
ChatOps combines chat platforms and AI technologies to facilitate collaboration and automate tasks within teams. By integrating AI-powered chatbots and communication tools, businesses can streamline operations, access information, and execute commands within a shared chat interface.
Cloud computing provides on-demand access to shared computing resources, including storage, processing power, and software applications, over the internet. By leveraging cloud computing, businesses can scale operations, reduce infrastructure costs, and access advanced AI technologies without significant upfront investments.
Clustering in AI refers to the process of grouping similar data points together based on their inherent characteristics or attributes. By identifying patterns or relationships within data, clustering algorithms help businesses gain insights, segment customers, detect anomalies, and make data-driven decisions.
Cognitive Automation refers to the use of Artificial Intelligence (AI) and advanced algorithms to automate tasks that traditionally require human intelligence, such as decision-making and problem-solving. By leveraging AI capabilities, businesses can streamline processes, increase efficiency, and free up human resources for more strategic tasks.
Cognitive Computing involves creating computer systems that can imitate human cognitive abilities, such as perception, reasoning, learning, and problem-solving. By combining AI, Machine Learning, and natural language processing, cognitive computing enables machines to understand and interact with humans in more intuitive and human-like ways.
