Big data is a scary thing. If you’re tasked with moving, storing, or analyzing it, big data can cause all sorts of headaches. But as troublesome as it is, we shouldn’t create monsters where none exist. Anil Gadre, the chief product officer with MapR Technologies, kicked off last week’s MapR Convergence event in San Diego with some myth busting.
His first myth — that succeeding in AI is all about picking the right algorithm — didn’t stand a chance. “In reality, it’s a continuum,” says Gadre, a Silicon Valley veteran who previously worked at Sun Microsystems. Many MapR customers employ a range of computational models in their big data operations, including batch, micro-batch, streaming analytic, and event processing, in addition to deep learning.
Author: Alex Woodie