How ChatGPT Works Technically? | What is Transformer? | Understand the model behind

Hey everyone! 👋 Welcome back to ALGOBRAIN AI! Ever wondered how GPT, the AI behind ChatGPT, learns to talk like a human? 🤔 We hear about GPT and use it a lot, but have you thought about how it’s actually trained to understand and respond to us? Today, I'm breaking it all down for you in simple terms!

In this video, we'll go step-by-step through the whole process of training a language model like GPT:

Data Collection: First things first, we need a LOT of data! We gather texts from all over the internet—articles, books, websites, you name it! The goal? To give the model a variety of language patterns and contexts to learn from.

Preprocessing: Next up, we clean up all that data. It’s like tidying up a messy room—fixing spelling mistakes, removing junk, and making sure everything is in a standard format so the model doesn’t get confused.

Tokenization: Then comes tokenization! This is where we break down the text into tiny pieces called tokens, like chopping up a big paragraph into smaller, more digestible parts. This helps the model understand the text better.

Vectorization: Now, we turn those tokens into numbers! This helps the model figure out what words mean in different contexts. For example, is "bank" a place where you save money or the side of a river? Vectorization helps the model decide!

Training the Model: This is the core part! We use something called the Transformer architecture (fancy word, I know!) that has a cool "attention mechanism" to help the model learn relationships between words in sentences.

Attention Mechanism: Think of it like this: when you're reading a sentence, some words matter more than others, right? This mechanism helps the model figure that out too!

Fine-Tuning: After the heavy lifting of training, we fine-tune the model on specific tasks. For example, to make it a great chatbot, we fine-tune it on conversational data.

Evaluation: And finally, we test it! We check how well it performs based on accuracy, fluency, and relevance. If it’s good to go, it’s ready for the real world!

We'll also dive into the groundbreaking research paper, “Attention is All You Need” by Google, which introduced the world to the amazing Transformer model! This changed everything in the AI world. 🌍

If you're curious about AI, love tech, or just want to understand how these models learn to "think," this video is for you! 🚀 Don’t forget to hit that like button, subscribe for more from ALGOBRAIN AI, and let me know your thoughts in the comments below! ✨

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