Artificial Intelligence (AI): When robots or machines are intended to perform tasks that require human intelligence, this is AI. AI consists of things like recognizing habits, making decisions, and learning about experiences as well as past actions.

Machine Learning (ML): This is a type of AI that allows computers to automatically learn from experience without being explicitly programmed. For example, a machine learning system can analyze lots of examples to recognize patterns in pictures, allowing computers to automatically learn and improve.

Neural Network: This term describes a particular model of computer system that resembles the human brain. It is constructed of interconnected neural networks, called neurons, that can rewire and adapt to new details.

Algorithm: This refers to a set of rules and instructions, known as a program, that a computer system can use to complete a specific task or solve a specific problem. It’s like a recipe that tells the computer what to do. Algorithms are used widely in artificial intelligence and machine-learning applications.

Data: Information that a computer can use to make decisions is data. It can come in many different formats, including text, images, and numbers.

Deep Learning: This form of machine learning uses neural networks to learn about problems and make conclusions. It’s called “deep” because it consists of multiple layers of neurons which discover and recognize intricate patterns.

Natural Language Processing (NLP): This is when a computer can understand human language. It can be used to develop chatbots or virtual assistants that can understand and respond to spoken or written language.

Training data:- It is used for machine learning is the data used to train a learning model how to classify information. For example, if you want to teach a computer to recognize dogs, you can give it a lot of photos of dogs as training data.

Testing Data:This is the data that is typically used to test a machine learning system’s ability to recognize patterns. For example, after you’ve trained a computer to recognize dogs, you might try it out by giving it a fresh batch of images to view and seeing how successfully it can identify the dogs.

Computer Vision: This is when a computer is designed to recognize images and videos. It’s used in things like facial recognition, self- driving cars, and security systems.

Big Data:This is when there are a lot of different pieces of information that needs to be analyzed. Big data may be used during such activities as scientific research, business analytics, and social media analysis.

Analytics:This analysis of data is used to find its details and make decisions. It’s utilized in markets and sectors such as business intelligence, market research, and business.

Predictive Analytics: This is when predictive analytics is used to predict future outcomes. For example, predictive analytics could be used in weather forecasting, financial analysis, and sports statistics.

Large Language Model(LLM):A type of machine learning model that is trained on an enormous amount of text data and is able to generate natural-sounding text is the Large Language Model(LLM).

Prompt:A prompt is a text used to establish a large language model and guide its generation.

Generative art:-Computer-based artwork created by way of an algorithm or set of algorithmic rules. It enables artists to produce intricate patterns and distinctive formatting that would be more complicated to generate manually. The resulting output is unpredictable, making computer-generated art a type of innovative artistic expression.

OpenAI :-OpenAIis a nonprofit organization promoting the development of artificial intelligence technologies that are safe, transparent, and beneficial to society.

AI Tools:-Artificial intelligence (AI) tools are applications that use AI technologies to relieve and improve different tasks. These tools makes it easier for developers and data scientists to produce and deploy AI-powered applications easily and quickly, and are the primary means for businesses to improve productivity and efficiency.