CSCMP's Supply Chain Quarterly
Technology
December 19, 2018
Forward Thinking

Artificial intelligence will trigger a new reality for logistics

Comment
Companies that don't adapt before their peers will get run over by this "technology train," GT Nexus exec tells 3PL conference.

The transportation and logistics sectors are on the verge of being upended by a wave of new technology that will cause painful change for companies that don't learn to adapt, according to a keynote address delivered Tuesday at a conference of freight brokers and third party logistics (3PL) providers.

Based on the lightning progress of tech trends and financial pressures, society will soon enter "the age of network intelligence," where artificial intelligence (AI) will allow robots and computers to surmount today's business challenges by learning from human workers and then sharing those lessons between all connected platforms, Kurt Cavano, senior vice president and general manger of the GT Nexus Commerce Network, a division of Infor, said.

That transition has the potential to cause disruption on a scale with the 19thcentury's Industrial Revolution, when American society evolved in just a few decades from a society that was 95 percent agrarian to just 5 percent, as huge portions of the population migrated to new jobs and opportunities in the cities,Cavano said at 3PL Technovations, a conference held in Tucson, Ariz., by the Transportation Intermediaries Association (TIA).

Rising applications of AI have the potential to solve problems from labor shortages to warehouse productivity to highway safety and retail staffing challenges, but to tap into that power, businesses must commit to adopting new approaches before their competitors do, he said. "Technology is advancing faster than any of us can comprehend," said Cavano. "But you're either riding the technology train or you're getting run over by it."

One of the main levers of change in this area has been the dizzying advance of computer chip power predicted by Intel Corp. Founder Gordon Moore in his famous Moore's Law, which postulated that the power of chips (as measured by the number of transistors on each processor) would double every 12 to 18 months, Cavano said.

When applied to graphical processing units (GPUs), a cousin of central processing units (CPUs) that drive typical computers, that law is enabling the colossal computing power that enables machine learning, the engine that powers artificial intelligence (AI), he said.

For example, as people use platforms such as Amazon.com Inc.'s Alexa personal assistant or the collaborative robots (cobots) used for warehouse and industrial tasks, they are training the machines to improve their performance every day.

This process has already led to self-driving cars, nearly "dark" warehouses powered by driverless forklifts, and the "Amazon Go" stores that require no human sales associates, said Cavano.

Another force driving the conversion is the huge amount of money that investors are pouring into logistics technologies as they jostle to position themselves for the new reality. The amount of "dry powder"—a term referring to the funds that venture capital and private equity firms have collected but not yet invested—has skyrocketed in recent months to $1.1 trillion, he said. That figure is the highest in history, but the money is still sitting on the sidelines as investors weigh their options.

In the meantime, entrepreneurs and startup founders are not sitting still to wait for investors to commit, but are spinning out new ideas from think tanks and universities every year, experimenting with concepts like unstaffed or "dark" warehouses, gesture-controlled devices, and radio frequency identification (RFID) chips implanted in humans, he said.

"We're not living in 'The Matrix'," Cavano said, in reference to the 1999 Keanu Reeves science fiction movie about a society of humans enslaved by computer overlords, while being tricked into believing their virtual, digital world was real. "But we're living in a very transformative time."

Ben Ames is Editor at Large and a Senior Editor at Supply Chain Quarterly’s sister publication, DC Velocity.

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