- "Artificial intelligence (AI) is the intelligence of machines or software, as opposed to the intelligence of humans or animals."
How AI interacts with robotics, including machine learning and deep learning.
Machine Learning: Machine Learning is the study of algorithms and statistical models that computer systems use to perform a specific task without using explicit instructions.
Natural Language Processing: Natural Language Processing is a subfield of Artificial Intelligence that focuses on enabling machines to understand human language.
Computer Vision: Computer Vision is the study of how to enable computers to interpret and understand visual information from the world around them.
Robotics: Robotics involves the design, construction, operation, and programming of machines that can perform tasks autonomously, semi-autonomously or manually.
Decision Trees: Decision Trees are a type of supervised learning algorithm that is primarily used in decision analysis, classification, and regression.
Neural Networks: Neural Networks are models designed to recognize patterns and features in enormous data sets.
Genetic Algorithms: Genetic Algorithms are search techniques used to find approximate solutions to optimization and search problems.
Big Data: Big Data is a term used to describe data that is too large, complex, or variable to be dealt with by traditional data processing applications.
Control Systems: Control Systems are designed to regulate the behavior of systems, processes, and devices by using feedback and other control techniques.
Deep Learning: Deep Learning is a subfield of Machine Learning that is concerned with the design and implementation of deep neural networks.
Automated Reasoning: Automated Reasoning techniques are applied to systems that have the ability to reason and make decisions based on input data.
Fuzzy Logic: Fuzzy Logic is a type of logic that provides a framework for dealing with situations that are not precisely defined or have multiple meanings.
Swarm Intelligence: Swarm Intelligence is a type of Artificial Intelligence that is based on the behavior of multi-agent systems.
Ethics and Governance: Ethics and Governance of Artificial Intelligence involve examining the social and ethical implications of developing AI technologies.
Cybersecurity: Cybersecurity is concerned with protecting electronic devices and networks from security threats, including malware, viruses, and cyber attacks.
Expert Systems: Systems that use AI and machine learning techniques to mimic human expertise in a particular domain.
Neural Networks: Computer systems that are designed to simulate the functions of the human brain by learning from data inputs.
Fuzzy Logic: An approach to AI that allows for imprecise or uncertain data inputs, making it useful for decision-making in complex and uncertain environments.
Natural Language Processing (NLP): The use of AI algorithms to help computers understand and interpret human language.
Computer Vision: The use of AI and machine learning algorithms to enable computers to interpret visual information, such as images and videos.
Robotics: Machines that are designed to perform tasks autonomously, using AI and other technologies.
Autonomous Vehicles: Vehicles that use AI and other technologies to operate without human intervention.
Chatbots: AI-powered software programs that can simulate human conversation through text or voice.
Machine Learning: A type of AI that enables computers to learn from data inputs and improve their performance over time.
Reinforcement Learning: A type of machine learning that enables software agents to learn through trial-and-error and feedback from their environment.
Genetic Algorithms: AI algorithms that mimic the process of natural selection to find optimal solutions to complex problems.
Swarm Intelligence: A type of AI that simulates the behavior of social insects like bees and ants to solve complex problems.
Virtual Agents: AI-powered customer service agents that can interact with customers in a simulated environment.
Deep Learning: A type of machine learning that uses neural networks with many layers to model complex patterns and relationships in data.
Cognitive Computing: A type of AI that combines multiple technologies, including NLP, computer vision, and machine learning, to enable computers to interact with humans in a more natural way.
- "It is also the field of study in computer science that develops and studies intelligent machines."
- "AI technology is widely used throughout industry, government, and science."
- "Some high-profile applications are: advanced web search engines (e.g., Google Search), recommendation systems (used by YouTube, Amazon, and Netflix), understanding human speech (such as Siri and Alexa), self-driving cars (e.g., Waymo), generative or creative tools (ChatGPT and AI art), and competing at the highest level in strategic games (such as chess and Go)."
- "Artificial intelligence was founded as an academic discipline in 1956."
- "After 2012, when deep learning surpassed all previous AI techniques, there was a vast increase in funding and interest."
- "The traditional goals of AI research include reasoning, knowledge representation, planning, learning, natural language processing, perception, and support for robotics."
- "General intelligence (the ability to solve an arbitrary problem) is among the field's long-term goals."
- "AI researchers have adapted and integrated a wide range of problem-solving techniques, including search and mathematical optimization, formal logic, artificial neural networks, and methods based on statistics, probability, and economics."
- "AI also draws upon psychology, linguistics, philosophy, neuroscience, and many other fields."
- "Understanding human speech (such as Siri and Alexa)."
- "When deep learning surpassed all previous AI techniques."
- "Generative or creative tools (ChatGPT and AI art)."
- "Self-driving cars (e.g., Waymo)."
- "Advanced web search engines (e.g., Google Search)."
- "The various sub-fields of AI research are centered around particular goals and the use of particular tools."
- "It is the intelligence of machines or software."
- "AI technology is widely used throughout industry, government, and science."
- "The field went through multiple cycles of optimism followed by disappointment and loss of funding."
- "AI researchers have adapted and integrated a wide range of problem-solving techniques, including search and mathematical optimization, formal logic, artificial neural networks, and methods based on statistics, probability, and economics."