Machine Learning

Machine Learning Comes to the Masses

by Jake Bennett

How a new wave of machine learning will impact today’s enterprise

robot brain

This article was originally published on 7/17/2017 in VentureBeat

Advances in deep learning and other machine learning algorithms are currently causing a tectonic shift in the technology landscape. Technology behemoths like Google, Microsoft, Amazon, Facebook and Salesforce are engaged in an artificial intelligence (AI) arms race, gobbling up machine learning talent and start-ups at an alarming pace. They are building AI technology war chests in an effort to develop an insurmountable competitive advantage.

While AI and machine learning are not new, the current momentum behind AI is distinctly different today, for several reasons. First, advances in computing technology (GPU chips and cloud computing, in particular) are enabling engineers to solve problems in ways that weren’t possible before. These advances have a broader impact than just the development of faster, cheaper processors, however. The low cost of computation and the ease of accessing cloud-managed clusters have democratized AI in a way that we’ve never seen before. In the past, building a computer cluster to train a deep neural network would have required access to deep pockets or a university research facility. You would have also needed someone with a Ph.D. in mathematics who could understand the academic research papers on subjects like convolutional neural networks.

Today, you can watch a 30-minute deep learning tutorial online, spin-up a 10-node cluster over the weekend to experiment with, and shut down the cluster on Monday when you’re done – all for the cost of a few hundred bucks. Cloud providers are betting big on an AI future, and are investing resources to simplify and promote machine learning to win new cloud customers. This has led to an unprecedented level of accessibility which is breeding grassroots innovation in AI. A comparable technology democratization occurred with the Internet in the 1990s. If AI innovation follows a similar trajectory, the world will be a very interesting place in five years.