Generative AI is a rapidly evolving field focused on creating models and systems that can produce new content, such as text, images, music, or code. These models, like GPT and diffusion models, learn from vast datasets and can generate creative outputs that mimic human work. Generative AI is transforming industries by enabling automation, enhancing creativity, and opening new possibilities in art, science, and business. In this category, you'll find articles that explain the fundamentals, showcase real-world applications, and explore the ethical and technical challenges of generative models.
Moving Generative AI from demos to production is no longer about prompts. In 2026, success depends on architecture, cost discipline, observability, and trust at scale.
A hands-on, copy-paste-ready walkthrough to track Keras/TensorFlow experiments in MLflow, run Hyperopt tuning with nested runs, register the best model, and serve it as a REST API.
Meta’s VL-JEPA research challenges the foundations of modern AI. Explore why leading researchers believe token-based language models may not be the future of intelligence.
