Dear friends,
I’m writing this in Orlando, Florida, where I just spoke at the A3 Business Forum, a group that works to advance industrial automation through AI, robotics, and other tools. This was my first large conference since the pandemic started, and it was good to get out and meet more people (taking appropriate health precautions, of course).
I was heartened by the number of AI people at A3. I met entrepreneurs working on computer vision systems for warehouse logistics (for example, finding and moving packages automatically), automated inspection (which I spoke about), controlling fleets of mobile robots, and building factory simulations.
Some trends that I took away from the conference:
- Many attendees observed that manufacturing and industrial automation are still in an early phase of adopting cloud computing and AI, and the number of viable use cases is still small but growing.
- Several CEOs commented on the high cost of customizing systems for different environments and seemed to be considering vertical platforms — where the customer does the customization — as a promising solution.
- Some executives in manufacturing and AI told me about overhyped AI applications that had failed and poisoned the well for other teams now trying to follow. This speaks to the importance of avoiding hype.
- The supply-chain disruptions you read about in the news are real! I heard many stories about nearly-finished products that would have shipped months ago if they weren’t missing a part. It made me feel grateful that, in the software world, we can easily supply as many copies as a customer wishes to purchase.
I was pleased to find, in an audience of manufacturing professionals, many learners taking online AI courses. On the flip side, I’m enjoying the opportunity to learn the lingo and techniques of industrial automation. And there is much for all of us to learn! For example, despite having developed and implemented sophisticated computer vision algorithms, many AI practitioners don’t yet appreciate the importance of imaging system design — to make sure your image data is of high quality — as part of building a practical system.
Applied AI is inherently interdisciplinary. Melonee Wise, an old friend and roboticist who recently sold her company Fetch Robotics, gave me permission to share that her biggest regret was taking too long to bring in someone with warehouse experience. Let’s approach our work with an awareness that knowledge of other fields is critical to building useful systems. Stay curious and . . .
Keep learning!
Andrew