Generative VS Predictive
- Amir Bder
- Apr 22
- 2 min read
Updated: May 3
Everything in AI is separated under two categories; Generative and predictive AI. Though similar they have their key differences which is what this blog is going to talk about.
Generative AI is used to create or generate new data or content. It takes information from existing data to create the new data. An example of this is ChatGPT which is trained on a large dataset of text from the internet, books, articles, and other sources to help it answer questions. particularly comparing data to make a result.
Predictive AI is used to predict an outcome based on data it has using Machine Learning or ML for short. It takes data from the past or present and uses it to predict a reasonable outcome of the data. It doesn't create anything knew like Generative AI does but similarly to Generative it uses data from the past or present.
Some examples of Generative AI:
Chat GPT
generating images
generating essays on a topic
composing music
writing code
making videos
making audios that sound like real people
Some examples of Predictive AI:
Predicting the outcome of a campaign
Predicting arrival times on a GPS
Predicting stocks
Predicting which days will produce the most money for a company
Predicting the forecast on any given day
Predicting patterns in data
Generative AI and Predictive AI are very different in many ways. They are both different in the way that they are used for completely different things. Generative AI creates something based off data that is very similar to what's being generated and Predictive AI predicts and outcome based off very similar data or patterns in the information given. Although very different they do have their similarities. The both gather information from data and use it for their own separate purposes. They both are based of Machine Learning and are trained over time by the users to become more and more accurate, as AI with minimal information isn't as good as AI with the knowledge of years of learning.
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