Group of young business people are working together in modern office. According to research from IDC, the global spending on AI (Artificial Intelligence) is expected to hit $97.9 billion by 2023, up from $37.5 billion in 2019. This represents a compound annual growth rate of 28.4%. No doubt, this is an enormous opportunity for startups. "These days, almost every company needs to leverage AI in order to thrive and build a meaningful future," said Saar Yoskovitz, who is the CEO of Augury.

Group of young business people are working together in modern office. According to research from IDC, the global spending on AI (Artificial Intelligence) is expected to hit $97.9 billion by 2023, up from $37.5 billion in 2019. This represents a compound annual growth rate of 28.4%. No doubt, this is an enormous opportunity for startups. "These days, almost every company needs to leverage AI in order to thrive and build a meaningful future," said Saar Yoskovitz, who is the CEO of Augury.

Group of young business people are working together in modern office. According to research from IDC, the global spending on AI (Artificial Intelligence) is expected to hit $97.9 billion by 2023, up from $37.5 billion in 2019. This represents a compound annual growth rate of 28.4%. No doubt, this is an enormous opportunity for startups. "These days, almost every company needs to leverage AI in order to thrive and build a meaningful future," said Saar Yoskovitz, who is the CEO of Augury.

But while the industrial macrocosm, measured by various productivity indices, putters along, there are a growing number of success stories emerging from industrial companies embracing IIoT technologies in tandem with machine learning. The startup FogHorn, for instance, helped the Japanese industrial electronics company Daihen eliminate 1,800 hours' worth of manual data entry in a single factory. And a top beverage company saved the equivalent of 1 million cans of beer through predictive maintenance in one fell swoop. The firm installed machine monitoring technology from the firm Augury, which marries wireless vibration, ultrasonic, temperature and magnetic sensors with machine learning to detect machine problems for a range of industrial machines, including those used by breweries. "And we detected severe bearing wear on a filler -- the machine that fills cans with beer," said Saar Yoskovitz, co-founder and chief executive officer at Augury.

Brakes squeal, hard drives crunch, air conditioners rattle, and their owners know it's time for a service call. But some of the most valuable machinery in the world often operates with nobody around to hear the mechanical breakdowns, from the chillers and pumps that drive big-building climate control systems to the massive turbines at hydroelectric power plants. That's why a number of startups are working to train computers to pick up on changes in the sounds, vibrations, heat emissions, and other signals that machines give off as they're working or failing. The hope is that the computers can catch mechanical failures before they happen, saving on repair costs and reducing downtime. "We're developing an expert mechanic's brain that identifies exactly what is happening to a machine by the way that it sounds," says Amnon Shenfeld, founder and CEO of 3DSignals, a startup based in Kfar Saba, Israel, that is using machine learning to train computers to listen to machinery and diagnose problems at facilities like hydroelectric plants and steel mills.