The molten metal, now 3,000°F, is channeled from ladle to caster, cooling to form a burning orange slab. This work has been repeated billions of times over decades. For the last 70 years, it has happened in steel mills around the world; today, it happens in data factories.
Modern industry may look much the same from the outside, but a quiet revolution is underway: Manufacturers are going online. A steep drop in sensor costs over the past decade has allowed businesses to collect data at every stage of production. Fifteen billion machines are currently connected to the internet, and in 2020, the number will pass 50 billion.1 By 2025, McKinsey forecasts that “smart factories” will generate as much as $3.7 trillion in value.2
These modern manufacturers are producing unfathomable volumes of data, and artificial intelligence is needed to make sense of it all.
“Modern machine learning can identify patterns from huge, messy data sets,” explains data scientist Alp Kucukelbir. “With human expertise alone, you can't really tease out the insights that you want. Machine learning allows us to unravel those patterns that would be difficult or impossible for people to identify.”
“Machine learning allows us to unravel those patterns that would be difficult or impossible for people to identify.”
“If you're hidebound, if you're stuck to the old way and don't have the capacity to digitalize manufacturing processes, your costs are probably going to rise, your products are going to be late to market, and your ability to provide distinctive value-add to customers will decline.”