Week 2 - BALT 4364 - Different types of AI

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When most people think of AI, what comes to mind is generative AI such as ChatGPT and X's Grok. This was the only AI I was familiar with, but there is also conventional (rule-based) AI and Predictive AI. All three have their uses, but it is important to understand the differences and when to apply each one. Conventional AI follows predefined rules to make decisions. It can recognize patterns and respond to specific inputs, but it will not learn or improve. Real-world examples of this type of AI would be customer service chatbots with scripted answers and rule-based fraud detection. 

Predictive AI is used when you want the system to learn from the data and then forecast future outcomes or trends. It uses machine learning and data analysis. It is dynamic and data-driven, which allows it to improve accuracy over time without manual reprogramming. Real-world examples include personalized product recommendations and forecasting equipment failures or inventory needs. Generative AI takes both of these a step further and creates new content from what it has learned. It can do this using deep learning. You can give generative AI a prompt as simple or as complicated as you would like, and within seconds to minutes, it will generate an answer.



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