Machine Learning and AI Market Landscape, 2016

Shivon Zilis and James Cham, O’Reilly:

For the first time, a “one stop shop” of the machine intelligence stack is coming into view—even if it’s a year or two off from being neatly formalized. The maturing of that stack might explain why more established companies are more focused on building legitimate machine intelligence capabilities. Anyone who has their wits about them is still going to be making initial build-and-buy decisions, so we figured an early attempt at laying out these technologies is better than no attempt.

Shivon Zilis and James Cham, Harvard Business Review:

If this year’s landscape shows anything, it’s that the impact of machine intelligence is already here. Almost every industry is already being affected, from agriculture to transportation. Every employee can use machine intelligence to become more productive with tools that exist today. Companies have at their disposal, for the first time, the full set of building blocks to begin embedding machine intelligence in their businesses.

And unlike with the internet, where latecomers often bested those who were first to market, the companies that get started immediately with machine intelligence could enjoy a lasting advantage.