Curs AI PDF

Curs AI 1 AGI (Artificial General Intelligence): AGI refers to highly autonomous systems that can perform a wide range of tasks and exhibit human-like intelligence. 2 LLM (Large Language Model): An LLM is a type of artificial intelligence model that is trained on large amounts of text data. These...

Curs AI 1 AGI (Artificial General Intelligence): AGI refers to highly autonomous systems that can perform a wide range of tasks and exhibit human-like intelligence. 2 LLM (Large Language Model): An LLM is a type of artificial intelligence model that is trained on large amounts of text data. These models can generate human-like text, translate languages, and perform other language-related tasks. 3 AI (Artificial Intelligence): AI refers to the development of computer systems that can perform tasks that typically require human intelligence, such as understanding natural language, recognizing images, and making decisions. 4 Machine Learning: Machine learning is a subset of AI that involves the development of algorithms that can learn from and make predictions or decisions based on data. 5 Deep Learning: Deep learning is a subset of machine learning that involves the use of artificial neural networks (see number 9) with multiple layers to learn and make predictions or decisions based on data. 6 Natural Language Processing (NLP): NLP is a field of AI that focuses on the development of algorithms and models that can understand, interpret, and generate human language. 7 Computer Vision: Computer vision is a field of AI that focuses on the development of algorithms and models that can understand and interpret visual information from the world, such as images and videos. 8 Reinforcement Learning: Reinforcement learning is a subset of machine learning that involves the development of algorithms that can learn to make decisions by interacting with an environment and receiving feedback in the form of rewards or penalties. 9 Neural Network: A neural network is a type of artificial intelligence model that is inspired by the structure and function of the human brain. Neural networks are composed of layers of interconnected nodes or "neurons" that can learn to recognize patterns in data.