10 min • 2 lectures
Artificial intelligence has transitioned from a specialized research field into a ubiquitous consumer technology. This shift began with the rise of generative AI, moving beyond traditional models that simply classified or sorted data. Today, Large Language Models and diffusion systems create original text, images, and code by predicting patterns within massive datasets. This stage of adoption is defined by the scaling of transformer-based architectures and the rapid integration of these tools into daily workflows. By understanding the transition from discriminative to generative systems, listeners can better grasp why AI has become a primary interface for digital interaction. The technology is now moving from passive conversational interfaces to agentic systems. Unlike standard chatbots, AI agents can plan multi-step tasks, use external software tools, and operate autonomously to solve complex problems. This evolution is supported by multimodality, allowing systems to process visual and auditory information alongside text. As these models gain the ability to act on a user's behalf, the industry faces new challenges regarding safety, alignment, and the definition of Artificial General Intelligence. This course examines the technical trajectory of autonomous agents and the changing role of humans in an increasingly automated environment.
