12 AI TERMS YOU MUST KNOW
TO NAVIGATE THE WORLD OF AI
“AI is the most important thing humanity has ever worked on.”
— Elon Musk
1. Artificial Intelligence (AI):
AI is the simulation of human intelligence in machines programmed to think and mimic human actions, like learning and problem-solving.
2. Generative AI:
AI system capable of creating content, such as images, text, or music, based on patterns learned from existing data.
3. Machine Learning (ML):
It is a subset of AI where computers learn to recognize patterns and make decisions based on data, without being explicitly programmed.
4. Large Language Models (LLM):
Advanced AI models that can understand and generate human-like text, trained on vast amounts of text data to produce coherent and contextually relevant responses.
5. Artificial Neural Network (ANN):
A computational model inspired by the human brain that processes information through interconnected nodes (neurons), allowing machines to learn from data.
6. Deep Learning (DL):
A type of machine learning inspired by the structure and function of the human brain, using artificial neural networks with many layers to learn from large amounts of data.
“It's going to be interesting to see how society deals with artificial intelligence, but it will definitely be cool.” —Colin Angle
7. Copilots:
AI tools or systems that assist developers in writing code by providing suggestions, autocompletion, and other helpful features based on patterns and knowledge learned from vast code repositories.
8. Responsible AI:
Ethical and thoughtful development and use of AI systems with fairness, transparency, privacy, and societal impact to ensure that AI benefits society while minimizing potential harms.
9. Hallucination:
In AI, hallucination refers to a mistake or error made by a model where it generates incorrect or nonsensical output that do not align with reality or the intended task.
10. Plugins:
Software components or modules that can be added to existing programs or systems to extend their functionality, allowing for customization without altering the core software.
11. Token:
In natural language processing (NLP), a token refers to a unit of text, typically a word or a sub word, that is processed as part of the input data by an AI model.
12. Prompt:
A specific instruction or input is given to an AI model to generate a desired output, guiding its behaviour and responses.
