Generative AI

Generative AI is a class of artificial-intelligence models that create new content—text, images, audio, code, 3-D assets—by learning patterns in massive training datasets and sampling from those distributions. Powered chiefly by Transformer architectures (GPT-4, Gemini) or diffusion models (Stable Diffusion), these systems predict the next token or pixel, iteratively building coherent outputs from noise. Fine-tuning, instruction tuning, and reinforcement learning from human feedback (RLHF) align generations with task goals, while prompt engineering and Retrieval-Augmented Generation (RAG) ground responses in real-time facts. Metrics such as BLEU, FID, and human preference scores measure fluency and creativity; guardrails, watermarking, and bias audits address safety. Generative AI fuels chatbots, design tools, synthetic data engines, and drug-discovery platforms—turning imagination into deployable digital artifacts at scale.