AI pioneer looks to specialize products for real-world business

A pioneering AI scientist and entrepreneur argues that technology needs to be specialized to work effectively in manufacturing.

Why it matters: AI has been slower to make a difference in many forms of business because it still takes expertise and investment to use it effectively. For now, that means models will need to be trained individually to be effective on the factory floor.

What's happening: Landing AI, a company started by former Google and Baidu AI pioneer Andrew Ng, last month launched LandingLens, a visual inspection platform for manufacturers.

• Visual inspection — which usually involves human workers checking a product for defects as it's made — is laborious and repetitive, which should make it a perfect use case for AI in manufacturing.
• But visual inspection demonstrates what Ng calls the "customization problem" of AI in manufacturing. "Every factory and every unique product needs its own trained AI model to check for defects."

How it works: LandingLens works as a visual interface through which companies can train the model to understand the inspection needs of individual products.

• Manufacturers take pictures of a successfully finished product, as well as images of various defects. Once human inspectors have created labels for defects, the model can run experiments that will over time refine its ability to identify even minor defects.

The catch: LandingLens points to both the benefits and limitations of AI at its current level of development. Manufacturers can get real value out of AI platforms, but it requires investment in time, as well as skills many executives don't have.

• While 84% of C-suite executives believe that they must leverage AI to achieve their growth objectives, according to a survey last year, 76% report they don't really know how to do it.

"AI has transformed consumer software, but if you look at the impact it has had on the broader economy, then candidly we are just beginning the path of transformation."