Technical Fundamentals of Generative AI - English
Welcome to the AI Era: Stanford University Course Summary In this blog, I will summarize everything you need to know in the AI era, based on the content of the Stanford University course. Summary: Key Technical Concepts — Fundamentals of Large Language Models Parameters – These are essentially numerical "weights" that the model learns and updates during training. They influence how the model responds and makes decisions. Artificial Neurons – Small computing units that perform simple mathematical operations using the model's parameters. Training Examples – The data from which the model learns. These examples help it understand patterns and update its parameters. Training – A cyclical process in which: The model predicts an answer → Compares it to the desired outcome → Updates itself accordingly. Transformer – An advanced neural network architecture upon which most modern AI models, including ChatGPT, are based. Modern AI models: Are not based on "rigid rules...
