Artificial Intelligence (AI) is already revolutionizing the world. But there’s a catch. For Artificial Intelligence to make the magic happen, it’s going to need data. Massive amounts of data. Data is like the engine which drives the Artificial intelligence capabilities and would decides its extent and impact. Machine and deep learning capabilities largely depends upon the data you feed into the data-crunching AI systems and it’s the biggest need at the start. As the systems keep getting trained, the data gets refined and the requirement comes down to relevant data, be it more data or less.
Even for the data-hungry applications it’s not always imperative that you need to have huge amounts of data to leverage latest advances. That said, if you are trying to push the state of the art technology stack and use very concrete applications, yes, you will need to have internal data that you can leverage to train your cool new deep learning approach.
But the question arises, how much data is needed to make this happen?