Here is a comprehensive list of terms and concepts in the world of artificial intelligence, supplemented with information from the mentioned site:

Basic concepts

1. Artificial Intelligence (AI): The ability of a computer or machine to perform tasks that typically require human intelligence, such as learning, reasoning, and problem solving.
2. Machine Learning (ML): A subfield of AI that focuses on developing algorithms that enable computers to learn from, predict or make decisions based on data.
3. Deep Learning: A subset of machine learning that uses multi-layered neural networks (deep neural networks) to recognize complex patterns in large amounts of data.
4. Neural Network: A computer model inspired by the human brain, consisting of layers of “neurons” that process and transmit information.
5. Algorithm: A set of steps or instructions that a computer follows to perform a task or solve a problem.

Advanced Concepts

6. Natural Language Processing (NLP): A branch of AI that deals with the interaction between computers and human languages, including speech recognition and text analysis.
7. Computer Vision: A field of AI that focuses on training computers to understand and interpret visual information from the world.
8. Reinforcement Learning: A type of machine learning where an agent learns by interacting with an environment and receives feedback in the form of rewards or punishments.
9. Generative Adversarial Networks (GANs): A type of neural network that pairs two neural networks against each other to generate new, synthetic examples that mimic data.

Applications and Tools

10. Chatbots: Automated programs that mimic human conversations and are often used for customer service and information delivery.
11. Robotics: Using AI to control robots that can perform physical tasks in the real world.
12. Autonomous Vehicles: Vehicles that use AI to navigate and make decisions without human intervention.
13. Text-to-Speech (TTS): Technology that converts text into spoken words, often used in digital assistants.
14. Speech-to-Text: Technology that converts spoken words into text, useful for dictation software and voice-controlled interfaces.
15. Large Language Model (LLM): A type of AI model, such as GPT, that is trained on massive amounts of text and is capable of generating human-like text.

Ethical and Social Considerations

16. Bias and Fairness: The need to design AI systems that are honest and do not reflect biases that may occur in training data.
17. Transparency and Explainability: The ability of AI systems to explain their decisions and processes in a way that people can understand.
18. Privacy: The importance of protecting personal information in AI applications and ensuring confidentiality.
19. Ethics in AI: Considering the moral implications and responsibilities in developing and deploying AI systems.

Underlying Technologies

20. Data Mining: The process of discovering patterns and knowledge from large amounts of data.
21. Big Data: Refers to data sets that are too large or complex for traditional data processing applications, often used in training AI models.
22. Cloud Computing: Using networks of external servers to store, manage, and process data, instead of local servers or personal computers.
23. Edge Computing: Performing data analysis and processing at the edge of a network, close to the data source, to improve response time and save bandwidth.
24. API (Application Programming Interface): A set of rules and protocols that allow different software applications to communicate with each other.

Specifications and Techniques

25. Prompt Engineering: The process of designing and refining prompts to make AI models more effective in generating relevant output.
26. Tokenization: Splitting text into smaller parts (tokens), such as words or phrases, that are processed by AI models.
27. Transfer Learning: A machine learning method where a model trained on one task is reused for another, related task.

These terms and concepts provide a comprehensive picture of the current developments and applications of AI in various domains.

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