Have you heard? Waste360 has launched a podcast! NothingWasted! brings you one-on-one chats with the most interesting people in waste, recycling and organics. Best of all, you can listen anytime and anywhere.
On our second episode, we chat with Matanya Horowitz of AMP Robotics Inc., a company he founded with the mission of changing the fundamental economics of recycling. We recently got to speak with him about robotics, deep learning, key transition points in the waste industry and more.
Here’s a sneak peek into the discussion:
Waste360: What kinds of uses are you seeing for artificial intelligence and robotics in the waste industry?
Matanya Horowitz: There are a lot of tough problems we’re trying to solve. With the help of robotics, we’re trying to identify all this different packaging … there are so many different types of labels, resins and fibers. In retrospect, it was probably the hardest problem we could have picked. We had to really find a great solution to make it work well—which we did. And now we’re starting to look at other domains like e-waste and construction and demolition recycling.
Waste360: What do you see as your role—or AMP’s role—in the circular economy, and how has that changed over time?
Matanya Horowitz: We initially didn’t have a broader appreciation of the importance of a wider circular economy approach—but now it’s something we talk about a lot and it’s really exciting. Now, we can have really deep insights into how packaging is moving through the waste stream—and we think the technology opens up new avenues for the circularity where you need a lot more specificity in what you’re sorting.
Waste360: What key takeaways can attendees expect from your “Robotics & Recycling: A Dynamic Duo” session at WasteExpo 2019?
Matanya Horowitz: What I hope they come away with is a real understanding of what this robot stuff means and where it can be useful in their facilities.
Listen to the full conversation with Horowitz here. Don’t miss this opportunity to hear his smart insights on the future of automation, neural networks and more.