What is Generative AI?
Generative AI refers to algorithms designed to synthesize original content — text, code, images, audio, or video. While classical ML categorizes or forecasts, Generative AI models generate brand new tokens.
The Transformer Revolution
Modern Generative AI is built on the Transformer architecture, pioneered in 2017. Transformers leverage a mechanism called Self-Attention, allowing models to weigh the significance of different words in a sentence, regardless of their distance.
Core Generative AI Paradigms:
- Large Language Models (LLMs): Autoregressive networks trained to forecast the subsequent token in vast text corpus.
- Diffusion Models: Generative networks starting with pure noise and iteratively removing pixel values to synthesize images.
Preparing for GenAI Topics
The AIMLOlympiad exam tests foundational mechanics of attention layers, tokenization strategies, temperature settings, and semantic alignment methods.
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