Almost everyone is familiar with some form of AI. Some of us use it to improve our workflow, generate images, or get recommendations on what to buy next. But what many people do not realise is that AI comes in different types and it is designed for different purposes. However, there are two common ones that you have most likely come across, which are: Generative AI and Predictive AI. They both rely on data, but they serve very different functions. Here is everything you need to know about them.
Generative AI
Just like the name implies, generative AI is used to create or generate something new. These are the ones you give prompts to, and they can help you write essays, design logos, compose music, generate videos, and even write code. A common example is ChatGPT. Generative AI works by studying endless amounts of text, images, or sound and then remixing those patterns into outputs that look and feel original.
It can be used in creating content like articles, blogs, and marketing copy, code generation and software prototyping, and personalised learning materials for education.
One disadvantage of generative AI is that it can generate false or misleading information, which also raises copyright and plagiarism concerns, so you have to be careful when using this.
Predictive AI
Predictive AI is used to forecast outcomes. Unlike generative AI, which creates content, predictive AI looks at past and present data to predict what is likely to happen next. Some of the common examples we have include Netflix recommending your next movie, banking apps like Opay flagging suspicious transactions, or weather apps forecasting rainfall in your area.
The limitation here is that its accuracy depends heavily on the quality of data, and the predictions are never 100% guaranteed. So while it is a useful tool, do not rely on it blindly.
What is interesting about both types of AI is how one can empower human creativity, and the other can help save lives with accurate forecasting.
AI is here to reduce our stress and help us progress, but we should not let either of them take over everything we do as humans. We must learn how to use them responsibly and effectively.
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