Industrial AI Problems: Solving for Industrial Applications
A recent Gartner report predicts half of enterprises will be using some measure of artificial intelligence next year. But most discussions of enterprise AI use cases focus on applications in the digital domain; use cases like getting people to click on ads, making recommendations, personalizing customer experience, predicting customer churn, and detecting fraud of various sorts.
These don’t account for Industrial AI problems; systems in organizations that don’t exist purely in digital form.
There is a huge opportunity for enterprises with Industrial AI problems — including robotics, manufacturing, supply chain, logistics, energy and utilities — to monitor, optimize or control the behavior of these operations and systems for improved efficiency and performance.
To shed some light on the unique challenges and requirements of building intelligence into industrial systems, we have partnered with Sam Charrington (@samcharrington) at CloudPulse Strategies to produce a special report on “AI for Industrial Applications”. You can download the report here.
You can also check out Sam’s podcast, This Week in Machine Learning & AI, where we have sponsored a series of interviews covering Industrial AI from a number of different perspectives. The latest episode with renowned roboticist Pieter Abbeel can be found here.