How to build/code ChatGPT from scratch?

In a world where technology constantly pushes the boundaries of human imagination, one phenomenon stands out: ChatGPT. You’ve probably experienced its magic, admired how it can chat meaningfully, and maybe even wondered how it all works inside. ChatGPT is more than just a program; it’s a gateway to the realms of artificial intelligence, showcasing the amazing progress we’ve made in machine learning.

At its core, ChatGPT is built on a technology called Generative Pre-trained Transformer (GPT). But what does that really mean? Let’s understand in this blog.

In this blog, we’ll explore the fundamentals of machine learning, including how machines generate words. We’ll delve into the transformer architecture and its attention mechanisms. Then, we’ll demystify GPT and its role in AI. Finally, we’ll embark on coding our own GPT from scratch, bridging theory and practice in artificial intelligence.

How does Machine learn?

Imagine a network of interconnected knobs—this is a neural network, inspired by our own brains. In this network, information flows through nodes, just like thoughts in our minds. Each node processes information and passes it along to the next, making decisions as it goes.

Each knob represents a neuron, a fundamental unit of processing. As information flows through this network, these neurons spring to action, analyzing, interpreting, and transmitting data. It’s similar to how thoughts travel through your mind—constantly interacting and influencing one another to form a coherent understanding of the world around you. In a neural network, these interactions pave the way for learning, adaptation, and intelligent decision-making, mirroring the complex dynamics of the human mind in the digital realm.

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GPT 4 and its advancements over GPT 3

The field of natural language processing has witnessed remarkable advancements over the years, with the development of cutting-edge language models such as GPT-3 and the recent release of GPT-4. These models have revolutionized the way we interact with language and have opened up new possibilities for applications in various domains, including chatbots, virtual assistants, and automated content creation.

What is GPT?

GPT is a natural language processing (NLP) model developed by OpenAI that utilizes the transformer model. Transformer is a type of Deep Learning model, best known for its ability to process sequential data, such as text, by attending to different parts of the input sequence and using this information to generate context-aware representations of the text.

What makes transformers special is that they can understand the meaning of the text, instead of just recognizing patterns in the words. They can do this by “attending” to different parts of the text and figuring out which parts are most important to understanding the meaning of the whole.

For example, imagine you’re reading a book and come across the sentence “The cat sat on the mat.” A transformer would be able to understand that this sentence is about a cat and a mat and that the cat is sitting on the mat. It would also be able to use this understanding to generate new sentences that are related to the original one.

GPT is pre-trained on a large dataset, which consists of:

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