May 10, 2017

Industrial AI | Understanding the unique requirements for building Industrial AI models

This is the first installment of a six part series from our recently published whitepaper; A fundamentally different approach for building intelligent industrial systems. You can download the complete paper here.

Enterprises of all sizes are actively evaluating artificial intelligence (AI) for a range of use cases beyond business-to-consumer (B2C) and data-centric applications. Shown on the left side of the graphic below, there is a growing need for AI models that can inject greater intelligence, in the form of control and optimization, into sophisticated industrial systems. These systems take many different forms, including robotics, vehicles, factories, supply chains, logistics, warehouse operations, HVAC systems, oil exploration, and resource planning.

Recognizing this trend, market analysts have begun forecasting the size of the opportunity for these intelligent industrial systems. IDC recently pegged the market for Cognitive & Artificial Intelligence Systems at $12.5B today, growing to $46.0B by 2020. David Schubmehl, Research Director, Cognitive Systems and Content Analytics at IDC, commenting on the opportunity for these AI-enabled systems, remarked:

"Cognitive/AI systems are quickly becoming a key part of IT infrastructure and all enterprises need to understand and plan for the adoption and use of these technologies in their organizations."

Breaking down the market opportunity further, he noted:

“From a technology perspective, the largest area of spending in 2017 ($4.5 billion) will be cognitive applications, which includes cognitively-enabled process and industry applications that automatically learn, discover, and make recommendations or predictions.”

In a recent Economist article, The Growth of Industrial Robots, unit sales of industrial robots were cited to have increased by 15% in 2015, while revenues grew 9% to $11bn. In the article, ABI Research, a consultancy, forecasted industry sales to triple by 2025.

Meanwhile, a recent Forbes article discussed the size of the Industrial AI opportunity outside of robotics.

“As sexy and shiny as robots are, the bulk of the value of AI in industrials lies in transforming data from sensors and routine hardware into intelligent predictions for better and faster decision-making. 15 billion machines are currently connected to the Internet. By 2020, Cisco predicts the number will surpass 50 billion. Connecting machines together into intelligent automated systems in the cloud is the next major step in the evolution of manufacturing and industry.”

Across the different applications highlighted above, the business objective is very often to increase automation or enhance operational efficiency. In programming intelligence into these systems, organizations require industrial-strength AI models that can hold up to the unique requirements of these dynamic, unconstrained problem spaces.

To learn how Bonsai enables enterprises to build more programmable, adaptive and trusted AI models, watch this video.

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