Understanding the concept of Self Attention Mechanism in Generative AI & LLM

In the last two posts of the series ‘Key Concepts for Transformers,’ I covered Tokens, Tokenization, and Word Embeddings. In this post, I will explain the concept of ‘Self-Attention Mechanism.’ This is a crucial concept and a powerful tool for empowering Language Models (LMs) to understand text more like humans. We will cover the following topics in this document:

1. We will take a few examples and see how Self-Attention distinguishes between the same word present in different sentences.
2. The examples will cover various situations in an English sentence such as:
a) Disambiguation with Homonyms
b) Sarcasm Detection
c) Sentiment Analysis with Negation
d) Ambiguity Resolution with Pronouns
e) Word Sense Disambiguation with Idioms
3. Summarize the definition on the last page.

I hope you find this document useful for understanding the concept in simple language. Feel free to message for queries. In the next post, I will dive deeper into the technicalities of Self-Attention and how it works in Language Models.

#GenAI #AI #DataScience #SelfAttention #Attention #LLM“