How Data-Centric AI Bolsters Deep Learning for the Small-Data Masses

It's no coincidence that deep learning became popular in the AI community following the rise of big data, since neural networks require huge amounts of data to train. But organizations with much smaller data sets can benefit from pre-trained neural networks, especially if they follow the premise of data-centric AI, Andrew Ng said this week at the Nvidia GPU Technology Conference. Ng, a prominent AI researcher and a Datanami 2022 Person to Watch, is at the forefront of the data-centric AI movement, which is aimed at helping millions of smaller organizations leverage the promise of AI. "We know that in consumer software companies, you may have a billion users [in] a giant data set. But when you go to other industries, the sizes are often much smaller," Ng said during his Nvidia GTC session, titled "The Data-centric AI Movement." "From where I'm sitting, I think AI–machine learning, deep learning–has transformed the consumer software Internet. But in many other industries, I think it's frankly not yet there."