The CEO and founder of Monolith, artificial intelligence (AI) software provider to the world’s leading engineering teams, has issued a stark warning for engineers to “stay ahead of the curve” when it comes to AI adoption, or risk falling behind.
During a keynote speech at Hannover Messe, the world’s leading trade fair for industrial technology, Dr Richard Ahlfeld told engineering attendees that AI won’t replace them, but engineers using AI will.
He said: “Machine learning is becoming an increasingly important part of our personal and business lives, either as a conscious-decision by the user or subtly through the basic tools we use on a day-to-day basis. AI software is also transforming how automotive and industrial engineers develop complex products.
“The power of AI lies in its ability to reduce the amount of physical testing time and simulations required to successfully develop products, especially those with highly complex, intractable physics.
“Using valuable and sometimes limited engineering test data, AI software can make instant predictions of product performance – or failure – and enable engineers to identify the exact areas where testing should be done, and where it can be skipped. With reduced repetitive, time-consuming physical tests, AI promises increased confidence in product quality whilst accelerating time to market.
“ChatGPT nicely visualises through text how much more you can get out of data. Essentially, the software is taking existing data and delivering an output that the end user finds interesting or useful. However, unlike ChatGPT, engineers don’t need that much data to train a self-learning model. They leverage the test data that exists, but often goes unused, to deliver new engineering insights and accelerate product development.
“With this outcome, it’s clear that self-learning models can become a standard tool for engineering product development. Yet, there’s understandable anxiety among knowledge workers that AI could eventually take work away from humans. But we see much more upside than potential risk of downside.
“Where AI might replace jobs at some point down the line, this technology will not only foster greater engineering creativity but also create many more new jobs. If we’re going to have an economy that grows, we need to reinvent how we do things. We can’t keep doing things the same way and expect progress.”
As AI becomes a trusted part of the product development process, Monolith expects engineers across all industries to significantly reduce verification and validation steps that today take weeks or months.
Using AI, engineers are able to leverage their data to calibrate products for better performance, whether that’s a battery, an engine, or a smart meter.
These engineers do not need to be Python coders or data scientists, just domain experts in their field. AI software that is built by engineers specifically for engineering domain experts allows them to quickly understand and instantly predict complex physics where simulation tools and traditional R&D methods fall short and slow time-to-market.
Monolith is seeing increased adoption of its AI software following customer success stories with Siemens, Mercedes-Benz, BMW Group, Kautex-Textron and Honeywell.
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