Google Cloud and Siemens have announced a new partnership that will see AI and machine learning brought to factory floors.
Siemens is planning on integrating Google Cloud’s data cloud and artificial intelligence (AI) machine learning (ML) technologies with its factory automation tools.
With this partnership, the companies hope manufacturers will be able to harmonise factory data, run cloud-based AI/ML models from that data, and deploy algorithms at the network edge. This could produce applications that visually inspect products, for example, or predict the wear-and-tear of machines on the assembly line.
The ultimate goal, said the companies, is to make the deployment of AI in connection with the Industrial Edge easier. They hope this will empower employees as they work on the plant floor, automate mundane tasks and improve overall quality.
“The potential for artificial intelligence to radically transform the plant floor is far from being exhausted. Many manufacturers are still stuck in AI ‘pilot projects’ today – we want to change that,” said Axel Lorenz, VP of Control at Factory Automation of Siemens Digital Industries.
“Combining AI/ML technology from Google Cloud with Siemens’ solutions for Industrial Edge and industrial operation will be a game changer for the manufacturing industry.”
Google Cloud has forged a number of partnerships, including one with Intel which focused on developing integrating services for network providers to develop 5G innovations across various platforms. The collaboration highlighted Google Cloud’s ambitions in the 5G world, as well as Intel’s goal to develop 5G with software-defined infrastructures.
A month after that announcement, Google Cloud hired Uri Frank, an Intel engineering veteran, to ramp up in-house chip production. This was part of the company’s new server chip design efforts as part of its increasing investments in custom silicon. Frank was VP of Platform and Silicon Engineering at Intel and had been appointed corporate VP of Intel’s Design Engineering Group but chose to leave.