AI

Generative AI versus Predictive AI

Generative AI and predictive AI, while both under the umbrella of artificial intelligence, function differently. Predictive AI is more like a fortune teller. It’s designed to predict future outcomes based on existing data. It looks at patterns and trends in the data it’s been fed and uses that information to predict what might happen next. For example, predictive AI can forecast stock market trends or suggest the next word in a sentence as you type on your phone.  

Generative AI, like its name suggests, focuses on generating new data or content. Like an artist creating a new painting, it can invent novel ideas, stories, or designs based on trained data. For example, generative AI can be used to create new audio, images, text, and videos by learning from existing ones. You may have had experiences with websites or apps that use generative AI to generate human-like responses in chat conversations.  

Much of the recent buzz around AI has focused on technology advances in generative AI. While generative AI is impressive in its ability to create new content, it’s important to remember that it’s essentially drawing from vast amounts of information it has been trained on and does not possess an understanding of the real world as humans do. For instance, it might generate information about people, places, or facts that seem believable, but may not be accurate. Generative AI extrapolates information from the patterns it has learned and sometimes these patterns can lead to erroneous results. It doesn’t have the ability to independently verify facts or context like humans. So, while generative AI can be a powerful tool for ideation and creativity, it’s always crucial to cross-check the information it provides, especially when it comes to important facts and details. (DFPI)