Andrew Ng is one of the biggest names in AI. He makes a few predictions, and I thought the article had some good observations.

His current big focus is using AI in manufacturing. Andrew Ng founded Landing AI in 2017. His focus was primarily consulting, but after working on many customer projects, Ng and Landing AI developed a new toolkit and playbook for making AI work in manufacturing and industrial automation. This led to Landing AI and the development of a data-centric approach to AI.

“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 is how to help 10,000 manufacturing plants build 10,000 customer systems. In short – scale.

In manufacturing, there is often no big data to go by. The data for manufacturing different products is unique. Their first observation was to see 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.

This uniqueness of data also means there is almost never enough images of faults or cases to train models. The only way out of this dilemma is to build tools that empower customers to build their own models and let product experts engineer the data and express their domain knowledge. Ng and Landing AI do that through Landing Lens, which enables domain experts to express their knowledge with data labeling instead of constantly tweaking the models.

Worth a read.