Press release

AMP Robotics Launches New AI Guided Dual-Robot System for the Recycling Industry

Sponsored by Businesswire

AMP Robotics Corp. (“AMP”), a pioneer in artificial intelligence (“AI”)
and robotics for the recycling industry, today announced the launch of
its new AMP Cortex™ dual-robot system (“DRS”) focused on material
recovery in Municipal Solid Waste (“MSW”), Electronic Waste (“E-waste”),
and Construction and Demolition (“C&D”).

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The AMP Cortex DRS expands on their existing product line of high-speed
recycling robotics guided by the AMP Neuron™ AI platform and uses two
high-performance robots that rapidly sort, pick, and place materials at
an unprecedented speed of 160 pieces per minute creating optimum
productivity. AMP Neuron uses computer vision and machine learning to
recognize different colors, textures, shapes, sizes, and patterns to
identify material characteristics. Then, it directs the robots to pick
and place the targeted material. The system can operate 24/7 with
continuous high-precision sorting, preventing contaminants in material
streams, and increasing the overall quality and purity of commodities to
be reclaimed. The system is modularly designed to drop into existing
facilities without requiring a major retrofit or downtime, enabling
customers to quickly benefit from advanced automation.

The unique design of the two robots opens up new material applications,
namely the ability to efficiently process difficult material streams of
post-consumer fiber. From sheets of paper to cardboard, sorting fiber is
a major challenge for recycling lines, often becoming a contaminant for
other recycled commodities. By solving this challenge, AMP’s technology
improves the purity of materials to be recycled, while also increasing
the recycling rates of post-consumer recycled fiber overall.

“The launch of the AMP Cortex dual-robot system marks another key
technology milestone for AMP as we continue to advance the application
of AI and robotics for the industry,” said Matanya Horowitz, chief
executive officer of AMP. “Our latest innovation further improves the
economics of recycling by helping waste management companies meet
increased quality standards, reduce operational costs, and achieve their
productivity goals.”

AMP’s latest announcement follows recent press about their partnership
with Ryohshin Ltd. to develop two new robotic systems using AMP Neuron
AI to recycle C&D materials for the Japanese market. And most recently,
Electronic Recyclers International (ERI), the nation’s largest E-waste
recycler, announced plans for additional installations of the AMP Cortex
system in their facilities.

“We are very pleased about how our latest material application helps
solve the challenge of recycling fiber products,” said Horowitz. “Our
AI platform continues to adapt and deepen with new material applications
proven by what we have recently achieved with C&D and E-Waste. As we
scale our business, we remain focused on continuous improvement and
innovation. The launch of our latest AI robotics system serves as
another great example of this.”

This week, AMP Robotics is exhibiting at WasteExpo 2019, the biggest
waste management and recycling trade show in the U.S. taking place in
Las Vegas from May 7 – 9, 2019. In addition to speaking at the
conference about AI and robotics in recycling, Horowitz will also be
receiving Waste360’s “40 Under 40 Award” and their annualInnovator
of the Year Award”, created to recognize forward thinkers who use
technology to better the waste management industry.

About AMP Robotics Corp.

AMP Robotics™ is transforming the economics of recycling robotics driven
by artificial intelligence (AI). The company’s high-performance
industrial robotics system, AMP Cortex™, precisely automates the
identification, sorting and processing of material streams to extract
maximum value for businesses that recycle municipal solid waste, e-waste
and construction and demolition. The AMP Neuron™ AI platform operates
AMP Cortex using advanced computer vision and machine learning to
continuously train itself by processing millions of material images
within an ever-expanding neural network that experientially adapts to
changes in a facility’s material stream. Visit us at