Generative AI (GenAI) 

What GenAI Is Doing Today

• GenAI is changing the way we create text, images, audio, and more.

• It is powered by Large Language Models (LLMs) like GPT-4 and GPT-3.5, which use a technology called transformers.

How Different Models Work

• Diffusion models create realistic images (used in tools like Stable Diffusion).

• Autoencoders and VAEs (Variational Autoencoders) help compress and rebuild complex data.

• GANs (Generative Adversarial Networks) are used in deepfake creation and image generation.

How Models Learn and Improve

• RLHF (Reinforcement Learning with Human Feedback) helps AI give safer and more helpful answers.

• LoRA (Low-Rank Adaptation) lets developers fine-tune big models quickly and cheaply.

• Prompt Engineering helps users get better results from AI by using well-designed prompts.

NLP: The Core of AI

• Natural Language Processing (NLP) helps AI understand and generate human language.

• Techniques like transfer learning, zero-shot and few-shot learning help models perform tasks with little or no training examples.

• Semantic search finds meaning in text, not just keywords.

Behind the Scenes

• Embeddings turn text into numbers AI can understand.

• Vector databases store these embeddings for fast search.

• Tokenization breaks text into small pieces (tokens) for the model.

• Attention mechanisms help AI focus on the right parts of a sentence.

AI Ecosystem & Tools

• Major AI platforms: OpenAI (GPT), Anthropic (Claude), Google (Gemini), Meta (LLaMA).

• Cloud solutions: Cohere, AWS Bedrock, Azure OpenAI.

• Developer & research tools: Weights & Biases, MLflow, Streamlit, Gradio for training, tracking, and deploying models.