Deep Learning is currently the most widely used type of
machine learning and the foundation of modern
generative AI. Unlike other types, it uses
neural networks with many layers and large amounts of data to automatically learn to process complex information.
Think of Deep Learning as a system that learns by observing millions of examples, organized in increasingly deeper levels of understanding. For example, to recognize faces, the first level detects edges and shadows, the next identifies features like eyes and mouth, and the deeper levels recognize expressions or specific identities.
Its power lies in its ability to automatically discover important
patterns in data without humans needing to specify them beforehand, making it particularly effective for complex tasks.
This technology powers the main
AI systems we use today, from conversational assistants, to everyday applications like voice recognition and language translation, or specialized tools for medical diagnosis and generative design.