Example input
Existing definitions or resources: Company's previous AI glossary
Particular jargons or acronyms to include: AI, ML, DL, NN, RL
Example output
Here's your glossary for Artificial Intelligence related terms:
Artificial Intelligence (AI): The field of computer science dedicated to solving cognitive problems commonly associated with human intelligence, such as learning, problem-solving, and pattern recognition.
Machine Learning (ML): A subset of AI that involves the practice of using algorithms to parse data, learn from it, and make predictions or decisions without being explicitly programmed.
Deep Learning (DL): A type of Machine Learning that trains a computer to perform human-like tasks, such as recognizing speech, identifying images, or making predictions. Deep Learning models are built using neural networks that simulate human decision-making.
Neural Network (NN): A series of algorithms that are designed to recognize patterns. They interpret sensory data through a kind of machine perception, labeling or clustering raw input.
Reinforcement Learning (RL): An aspect of machine learning where an agent learns to behave in an environment, by performing certain actions and observing the results.
Remember, these are beginner-friendly definitions meant to help new employees in your tech company understand the basics of these terms. For a more comprehensive understanding, it would be helpful to explore each of these concepts in depth and in the context of specific projects in your company.