AI refers to the simulation of human intelligence in machines, enabling them to perform tasks that typically require human intelligence, such as learning, problem-solving, perception, and language understanding.
A subset of AI, ML focuses on the development of algorithms that allow computers to learn from data and make predictions or decisions without explicit programming. It involves the creation of models that can improve their performance over time through experience.
A type of machine learning that involves neural networks with multiple layers (deep neural networks). It mimics the human brain’s structure, enabling machines to learn and make decisions in a way that is similar to human thought processes.
Computational models inspired by the structure and functioning of the human brain. They consist of interconnected nodes (neurons) organized in layers, allowing the system to recognize patterns and make decisions.
A branch of AI that focuses on the interaction between computers and humans using natural language. NLP enables machines to understand, interpret, and generate human language, facilitating communication and interaction.
The field of AI that enables machines to interpret and understand visual information from the world, including images and videos. Computer vision involves tasks such as image recognition, object detection, and facial recognition.
A set of instructions or rules designed to perform a specific task or solve a particular problem. In AI, algorithms are crucial for data processing, decision-making, and learning.
Extremely large and complex datasets that traditional data processing tools are inadequate to handle. AI systems often leverage big data to uncover patterns, trends, and insights that can inform decision-making.
The integration of AI and machine learning in the design and development of robots. AI-powered robots can perform various tasks autonomously, making them valuable in industries like manufacturing, healthcare, and logistics.
AI applications designed to simulate conversation with human users, typically through text or voice. Chatbots use natural language processing to understand and respond to user queries, providing assistance and information.
A type of machine learning where an algorithm learns by interacting with its environment. The system receives feedback in the form of rewards or penalties, allowing it to improve its performance over time through trial and error.
The practice of developing and using AI systems in a way that aligns with ethical principles and values. It involves addressing issues such as bias, transparency, accountability, and the impact of AI on society.
The effort to create AI systems that can provide clear explanations for their decision-making processes. XAI aims to enhance transparency and trust in AI systems, especially in critical applications like healthcare and finance.
Vehicles equipped with AI technologies, such as computer vision and machine learning, that enable them to navigate and operate without human intervention. Autonomous vehicles include self-driving cars, drones, and robotic systems.
A hypothetical point in the future when AI systems surpass human intelligence, leading to rapid and unpredictable advancements. The concept raises ethical and existential questions about the potential impact of superintelligent machines on society.