You know how you put all your recycling—cans, bottles, cardboard, etc.—into the same bin? Well, have you ever wondered how all that stuff gets sorted out at the recycling factory? It’s done mostly by humans. 

If you watch a video about how it’s done, rest assured you’re not likely to apply for this job. These folks are standing at a conveyor belt with recyclable trash whizzing by them at every moment and they need to pick pieces off the line to put into the proper bins at a rate of 40 items per minute! It’s tough to watch the work for 30 seconds, so imagine how tough it must be to do that work for hours every day. 

Well, Matanya Horowitz had a different idea. He’d been obsessed with robots since he was a kid, and fresh out of his PhD program, he wondered whether he could teach robots to sort trash more effectively and efficiently than humans. 

The dude started in 2014 by dumpster diving with his girlfriend to get trash which he could start training his AI on. Then he got some government grants to hire himself and a couple others. Fast forward to today, and Horowitz’s AMP Robotics has raised $75 million from investors, employs 250 humans, has deployed a similar number of robots at recycling factories on three continents that have now sorted billions of pieces of trash, and has even opened their own recycling factory in Ohio. 

Their robots pick at a rate of anywhere from 80 to 120 pieces per minute, don’t need breaks, don’t get covid, and importantly, they alter the economics of recycling to make it far more likely that what goes into the recycling bin actually ends up getting recycled.

In this episode, we talk all about the economics of AMP’s robots, the trajectory Matanya took from being an academic roboticist to becoming a CEO, the role venture capital has played in the company, what mistakes along the way were made, whether he thinks robots will ever become sentient, and more.

It’s an impressive and inspirational story from a scientist who’s using his business to help solve a pressing sustainability problem for humanity.

Discussed in this episode

• Matanya is influenced by the Jewish tale of Golem

• He’s also a big fan of Isaac Asimov’s work

• And he recommends reading The Innovator’s Dilemma and Paul Graham’s essays

• Matanya gave a cool TEDx speech about robotics

 

Want to read a transcript of this episode? You’re in luck! 

 

More about Matanya Horowitz

Dr. Matanya Horowitz is the Founder and CEO of AMP Robotics™ an industrial artificial intelligence (AI) and robotics company that is fundamentally changing the economics of recycling, by lowering processing costs and extracting maximum value from waste streams.

Matanya developed and commercialized AMP’s breakthrough AI platform, AMP Neuron™, and robotics system, AMP Cortex™, which automates high-speed identification, sorting, picking, and processing of material streams. AMP’s machine learning technology continuously improves performance adapting to the complex, ever changing material characteristics of municipal solid waste, construction and demolition (C&D), e-waste, and metal scrap. Recognizing attributes down to the SKU and Brand level, AMP can provide unprecedented data transparency and insights on waste streams to inform decisions and unite the value chain of circularity.

Matanya was just individually recognized as Waste360’s ‘2019 Innovator of the Year’ award, in addition to being named to their ‘40 under 40’ list. AMP has received numerous awards and international recognition, including The Circulars 2018 Award for ‘Circular Economy Top Tech Disruptor’ at the World Economic Forum in Davos, and the NWRA’s (National Waste and Recycling Association) ‘2017 Innovator of the Year’ award.

Matanya earned multiple degrees including a BS in Electrical Engineering, BS in Computer Science, BS in Applied Mathematics, BA in Economics, and MS in Electrical Engineering from the University of Colorado Boulder. Matanya holds a PhD in Control and Dynamical Systems from the California Institute of Technology with publications and research in control theory, path planning, and computer vision.