Heavy machinery meets high-tech smarts: The dawn of a new industrial era
For nearly two centuries, Deere & Company has been a titan of agricultural innovation, from the self-scouring plow of 1837 to the self-driving tractor of 2022. Their latest marvel, the See & Spray, exemplifies this fusion of tradition and technology. This behemoth boasts a 120-foot carbon-fiber boom equipped with 36 cameras, scanning a staggering 2,100 square feet per second. Powered by onboard AI and deep learning, it identifies weeds with pinpoint accuracy, eliminating them with targeted herbicide application. All without human intervention.
This data-driven approach extends beyond a single machine. Deere collects billions of measurements on soil, crops, and weather from its vast network of 500,000 machines, operating across 325 million acres. Analyzed through the JDLink cloud system, this information fuels continuous improvement for both equipment and farm operations. Deere leverages machine learning to create a comprehensive suite of digital and physical services, optimizing everything from seed selection to fertilizer use.
Deere is just one example of a seismic shift occurring across the industrial landscape. Until recently, established manufacturers in construction, mining, and other heavy machinery sectors lagged behind in digital adoption. But the tide is turning. Today, they're harnessing the power of generative AI and machine learning to unlock hidden insights from a wealth of data, including text, 3D images, voice recordings, video, and even sound. This empowers them to design complex machinery in a matter of seconds.
Traditionally, industrial companies focused primarily on sales and marketing data, analyzing demographics and purchasing behavior. Digital systems were seen as cost-cutting measures or ways to add basic features like Wi-Fi. However, the focus has shifted to the post-sale experience. Now, it's about how the combined power of digital and physical products empowers customers to achieve success. Fusion strategies go beyond simply connecting a sensor to a machine. They involve a complete reimagining of product design, leveraging every available digital tool and functionality.
The Four Pillars of
Fusion Strategies:
Fusion Products:
Designed from the ground up to collect and analyze real-time usage data. This data is then fed into AI for three key purposes: traditional AI for product improvement, generative AI for creating digital twins of products to train robots, and large language models within generative AI to develop customer-centric insights.
Think Tesla: Their cars were built from the start as cloud-connected computers on wheels. Every sensor feeds real-time performance data to AI, enabling over-the-air updates for everything from optimizing braking systems to correcting minor rattles.
Fusion Services:
Utilizing AI to deliver customized recommendations based on product-in-use data. Imagine on-site technicians replaced by automated, AI-powered solutions that diagnose problems and offer personalized solutions to customers.
Case in Point: New ventures like Norm, a ChatGPT app for agriculture, leverage weather, soil conditions, and current events data to provide farmers with instant, customized advice on managing their operations.
Fusion Systems:
Optimizing complex systems comprised of multiple machines from various manufacturers. Fusion system integrators not only connect these machines but also ensure continual improvement as new technologies emerge. Real-time data from various sources is fed into generative AI to create digital twins of entire systems. This enables experimentation with different combinations of products and peripherals to identify the most efficient setups.
Fusion Solutions:
The ultimate fusion, combining products, services, and systems to deliver a holistic solution that directly improves customer performance. These solutions are not one-size-fits-all but rather data-driven and designed for broad applicability.
Partnering with Granular, an agricultural software company, Deere is developing yield models for farmers. Granular utilizes satellite imagery and historical data to predict costs, revenues, and profits, empowering Deere to offer farmers a comprehensive solution for optimizing their operations.
The future of industry belongs to those who embrace "collaborative intelligence," where human and machine intelligence work in synergy. Companies that view AI not as a replacement but as an enhancement will be the ones to thrive.
