The who's who of the machine learning industry

In late September, top machine learning experts gathered at Imagine 2022 in the Computer History Museum, California. At the same location where the legendary Steve Jobs also has held presentations, around 250 participants from industry giants such as Google, Microsoft, Sony, Texas Instruments, Samsung, Ready Robotics and others discussed the topic on site. Many more followed the event via livestream. The event was organized by Edge Impulse, a provider of a development platform for machine learning. Hubertus Breier, Head of Technology at Balluff, was also on site, and gave a keynote speech about industrial machine learning (“Machine Learning on the Edge: An Industrial Perspective”), highlighting three important points:

1. Problems are to be solved in practice. To achieve this, it is important to know industries and the corresponding challenges well. This is the only way to provide the right solutions. For example, machine learning can help to detect problems at an early stage, for example by uncovering anomalies.

2. If an IIoT architecture needs to be cloud-based or on-premise depends on what it is used for: cloud-based solutions feature maximum computing power, make it possible to use high-resolution raw data on-site, and latency is low.

3. It is about understanding customers and offer them value propositions that are actually important to them—for example, preventing the very expensive failure of a wind turbine. This can be used as an example to prevent the failure of a wind turbine, which would have high costs for the customer.

Exchange with added value

For Balluff, exchanging ideas with the big players from outside industry is invaluable. Sharing experiences, learning about challenges and solutions, and expanding one’s knowledge—all of this increases expertise. Beyond that, one insight counts for Balluff: It’s the same for everyone—there are no one-size-fits-all solutions. Whether industry or not, the customers always come first.