Generative AI and Predictive AI in the Cloud: Foundational Concepts and Scenarios
Thomas Erl introduces the two common types of AI systems, which are predictive AI and generative AI in this LinkedIn Learning. He describes predictive AI as what “helps the business with its decision making” and generative AI as what “can contribute to new data-driven assets to the business.” One of the things I learned from this LinkedIn Learning was that big data systems can be used to combine and synthesize different data that can then be produced as input into the AI system. I also learned that to produce a certain type of data intelligence, we have to use a specific algorithm for the type of analysis we want the system to perform. Lastly, I learned that some of the common challenges faced when working with AI systems in cloud environments are data bias and bad data and talent shortage. Ensuring the quality of the data being used when using any type of AI is essential for a business to successfully use it and while AI systems advance, it can be difficult for professional data scientists to keep up with demand. Overall, this LinkedIn Learning will help me in my coursework and future career because AI is only improving and we are seeing it be used more and more in the workforce, so getting a better understanding of how it works helps put me ahead in both my coursework and in applying for different jobs.