How do AI systems handle unstructured data?

AI systems handle unstructured data primarily through advanced techniques such as Natural Language Processing (NLP) and computer vision. Unstructured data, which includes formats like text, images, and videos that do not fit neatly into rows and columns, requires sophisticated methods to make sense of it.

NLP enables AI to understand and process human language by analyzing the context, sentiment, and various other linguistic features found in text. This is crucial for applications like sentiment analysis, chatbots, and language translation.

Computer vision, on the other hand, allows AI systems to interpret and understand visual information from the world, identifying objects, faces, and other elements within images or video feeds. This technology is vital for use cases in security, healthcare imaging, and autonomous vehicles.

By employing these methods, AI systems can derive insights, identify patterns, and even make predictions based on unstructured data, thereby creating value from information that would otherwise remain untapped.