AI: The New Center of Conversational Support

Exploring the Magic of Transformers in AI

In the previous article, we discussed the meaning of Pretrained in Generative Pre-trained Transformer (GPT). Now, let's explore the 'Transformer' aspect of AI. We'll make it fun and easy to understand. The emergence of the Transformer model represented a major shift in how AI handles language processing and generation. Prior to its arrival, the AI research community largely relied on Recurrent Neural Networks (RNNs), including Long Short-Term Memory (LSTM) and Gated Recurrent Neural Networks, as the go-to methods for sequence modeling and transduction tasks such as language modeling and machine translation.

RAG (Retrieval Augmented Generation) in AI: A Simple Explanation

RAG, which stands for Retrieval Augmented Generation, is a smart technique used in AI. It's like a two-step process for AI to find and give information. RAG is when AI, like a chatbot, first searches for information and then uses that info to answer questions. It's like doing a school project where you first gather facts from books or the internet and then use those facts to write your answers.

What Are the Foundation Models in Generative AI

Foundation models are essentially large neural networks that have been pre-trained on vast amounts of data. This training allows them to learn a wide range of patterns, relationships, and structures within the data. Once trained, these models can be fine-tuned or adapted to specific tasks in generative AI, such as image generation, text creation, or music composition.