- "Artificial intelligence (AI) is the intelligence of machines or software, as opposed to the intelligence of humans or animals."
The study of creating intelligent agents that can solve complex problems, including machine learning, natural language processing, and computer vision.
Machine Learning: Machine learning is a subset of artificial intelligence that deals with teaching computers to learn from data rather than programming explicit instructions.
Deep Learning: Deep learning is a subset of machine learning that uses artificial neural networks to model complex data structures and patterns.
Neural Networks: Neural networks are a type of biologically-inspired approach to AI that attempts to mimic the way the human brain processes information.
Computer Vision: Computer vision is a field of AI that focuses on enabling machines to interpret and understand visual data from the world around us.
Natural Language Processing: Natural language processing (NLP) is the ability of machines to process, understand, and generate human language.
Expert Systems: Expert systems are AI systems that incorporate human expertise and knowledge to provide intelligent decision-making capabilities.
Robotics: Robotics involves the design, construction, and operation of robots, which are often used in AI applications.
Cognitive Computing: Cognitive computing uses artificial intelligence technologies and algorithms to simulate human cognitive processes, such as reasoning, learning, and perception.
Fuzzy Logic: Fuzzy logic is a mathematical approach to dealing with uncertainty and imprecision in data, which is particularly useful in robotics and industrial automation.
Reinforcement Learning: Reinforcement learning is a type of machine learning that involves teaching machines to learn from trial and error interactions with their environment.
Evolutionary Algorithms: Evolutionary algorithms are a type of machine learning that involves using genetic algorithms and evolution to optimize complex systems and processes.
Semantic Web: The semantic web is a way of structuring online data with meaning, which can help machines to better understand and interpret this data.
Data Mining: Data mining is the process of analyzing large datasets to uncover hidden patterns and insights, which is particularly useful in machine learning and AI applications.
Bayesian Networks: Bayesian networks are a type of probabilistic graphical model that uses mathematical inference to understand and predict uncertain events.
Expert Systems: Expert systems are a type of AI system that uses expert knowledge to provide intelligent decision-making capabilities.
Rule-Based AI: It is a type of AI that relies on a set of predefined rules to make decisions.
Expert Systems: These are computer programs developed to emulate human expertise in a specific domain.
Fuzzy Logic: Fuzzy logic is a type of logic that allows for uncertainty and imprecision in decision-making.
Neural Networks: Neural networks are made up of interconnected nodes that can learn from data and perform complex tasks like pattern recognition.
Genetic Algorithms: These are a type of search algorithm based on the principles of natural selection and genetics.
Machine Learning: It is a subset of artificial intelligence that includes algorithms that can learn from data.
Deep Learning: Deep learning is a subset of machine learning that involves a neural network with multiple layers.
Natural Language Processing: NLP is a type of AI technology that enables computer systems to understand and process human language.
Computer Vision: This is a field of AI that focuses on enabling machines to interpret and understand visual information.
Robotics: Robotics involves creating intelligent machines that can perform tasks autonomously.
Speech Recognition: It is a type of AI technology that enables computers to interpret and understand human speech.
Cognitive Computing: It refers to the development of computer systems that can learn, reason, and understand like humans.
Sentiment Analysis: This is a type of AI technology that can analyze and interpret human emotions in text or speech.
Virtual Agents: Virtual agents are computer programs or applications that simulate human interaction in a chatbot or customer service context.
Autonomous Vehicles: Autonomous vehicles or self-driving cars are automated machines driven by AI technology.
Augmented Reality: It is a technology that enhances the user's real-world experience with artificial intelligence.
Cybersecurity: AI technology can be used to detect and prevent cyber attacks and intrusion attempts.
Predictive Analytics: Predictive analytics uses data, machine learning, and statistical algorithms to predict future events or trends.
Data Mining: Data mining is an AI technology that involves the process of discovering patterns in large datasets.
Computer-Assisted Design: CAD or computer-assisted design is the use of an AI in designing products or systems.
- "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."