Five Challenges I Face Using Generative AI As A Data Analyst
If there’s one thing creating hype in 2023, it’s Generative AI
Heard the word ChatGPT or Bard or Generative AI?
Generative AI is THE talk wherever you go — in conferences, happy hours, school reunions, your favorite morning podcast, startup conventions…you get the point. By now, you might have already heard or read about the advantages, limitations, and lawsuits that ChaptGPT alone has evoked.
But if you are new(er) to the Generative AI space and as a data professional, you’re interested in knowing more about it, this blog is for you!
What is Generative AI?
Generative AI is a branch of artificial intelligence where the algorithms apply probabilistic approaches to produce new instances that reflect on the original data but with enhanced creative and inventive behavior. In short, Generative AI can create novel content based on inputs, including text, audio, images, videos, animations, 3D models, and more.
It is different from AI in a way that AI algorithms depend on vast data to excel at specific tasks whereas Generative AI can create output with human-level intellect.
