Every manufacturing plant needs a custom AI system

The concept of AI in manufacturing is a divisive topic which splits the audience into the essential for the future vs destroying jobs camps. This will not be the base, as the need to utilise AI in manufacturing will fuel new highly skilled workers. As Prof Andrew Ng predicts the next 10 years in AI he quotes “In manufacturing, every plant makes something different. So every manufacturing plant needs a custom AI system that is trained on their data.”

In 2017, Andrew Ng founded Landing AI, a startup working on facilitating the adoption of AI in manufacturing. This effort has contributed to shaping Ng’s perception of what it takes to get AI to work beyond big tech.

Ng, among the most prominent figures in AI, is founder of LandingAI and DeepLearning.AI, co-chairman and cofounder of Coursera, and adjunct professor at Stanford University. He was also chief scientist at Baidu and a founder of the Google Brain Project. Yet, his current priority has shifted, from “bits to things,” as he puts it

The next 10 years in AI: From bits to things, from big data in the lab to expert knowledge in the field. Featuring Landing AI Founder Andrew Ng

Listen to this episode from Orchestrate all the Things podcast: Connecting the Dots with George Anadiotis on Spotify. Did you ever feel you’ve had enough of your current line of work, and wanted to shift gears? If you have, you’re definitely not alone.

There is a growing trend: According to a 2021 survey from The Manufacturer, 65% of leaders in the manufacturing sector are working to pilot AI. Over the next decade these pilots will shift to full deployments. Our need to combine domain knowledge (knowing the process) and data knowledge (how to use the data) as a core skill and discipline in manufacturing will rise.

“In consumer software, you can build one monolithic AI system to serve a hundred million or a billion users, and truly get a lot of value in that way,” he said. “But in manufacturing, every plant makes something different. So every manufacturing plant needs a custom AI system that is trained on their data.”

The challenge that many companies in the AI world face, Ng commented, is how, for example, to help 10,000 manufacturing plants build 10,000 customer systems.

The data-centric approach advocates that AI has reached a point where data is more important than models. If AI is seen as a system with moving parts, it makes more sense to keep the models relatively fixed, while focusing on quality data to fine-tune the models, rather than continuing to  push for marginal improvements in the models.

How will we change and evolve to maximise the opportunity with AI?

Read more about Andrew Ng thoughts and a great write up on the future of AI here:

Andrew Ng predicts the next 10 years in AI

We are excited to bring Transform 2022 back in-person July 19 and virtually July 20 – 28. Join AI and data leaders for insightful talks and exciting networking opportunities. Register today! Did you ever feel you’ve had enough of your current line of work and wanted to shift gears?