Input Embedding in Transformers

Understanding Input Embedding in Transformers Introduction When processing natural language, neural networks cannot directly interpret raw text. Instead, words, subwords, or characters must be converted … Read more

Transformer Architecture in LLM

Understanding Transformer Architecture: The Foundation of Large Language Models Introduction The Transformer architecture has revolutionized the field of natural language processing (NLP) and artificial intelligence … Read more

Bayes’ Theorem

Introduction Bayes’ Theorem is a cornerstone of probabilistic reasoning, serving as a fundamental rule for inference. It describes the probability of an event, based on … Read more

Probabilistic reasoning in AI

Introduction Uncertainty in AI Probability Basics Probabilistic Inference Applications of Probabilistic Reasoning Conclusion References: Note: This content was generated with the assistance of Google’s Gemini … Read more