BootcampAI is Eating the World - the Rise of LLMs

AI is Eating the World - the Rise of LLMs

Remember when computers were only better than us at playing chess? Those days are gone. Today ChatGPT helps students understand complex topics, GitHub Copilot assisting developers in writing code, or Claude helping researchers analyze data. These aren’t just incremental improvements - they represent a fundamental shift in how we interact with computers. Just five years ago, these capabilities would have seemed like science fiction.

But how did we get here? How do these models actually work? And most importantly - why are they suddenly everywhere? In this section, we’ll break down the technology behind LLMs, from their fundamental building blocks to the clever tricks that make them work. We’ll explore how they’re trained, how they generate text, and why they’ve become so powerful.

From Neural Networks to Transfomers

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References

Footnotes

  1. Attention Is All You Need

  2. DETR: End-to-End Object Detection with Transformers

  3. Introducing ChatGPT

  4. Llama 3.3 by Meta AI

  5. Emergent Abilities of Large Language Models

  6. Aligning language models to follow instructions

  7. Chain-of-Thought Prompting Elicits Reasoning in Large Language Models