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Glacier, the San Francisco-based AI robotics startup, announced a $16 million Series A funding round on Tuesday to expand deployment of its waste-sorting robots across U.S. recycling facilities.
The round was led by Ecosystem Integrity Fund, with participation from the Amazon Climate Pledge Fund and other investors. According to GeekWire, Amazon (NASDAQ:AMZN), which is already working with Glacier to test plant-based plastic sorting at its Seattle sustainability lab, has included the startup in its broader strategy to reduce single-use fossil fuel plastics across Amazon Fresh and Whole Foods packaging lines.
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The fresh capital brings Glacier's total funding to $29 million. With robots currently active in five states and vision technology operating in four others, the company plans to scale rapidly, GeekWire reports.
AI Vision Targets Plastics, Bottles, And Cans Missed By Humans
Recology, a major waste management company with operations across the West Coast, is using Glacier's technology to modernize recycling at its South Seattle material recovery facility, according to GeekWire.
Glacier's robots are designed to operate in material recovery facilities, where trucks deliver around 300 tons of mixed recyclables daily, GeekWire says. Equipped with AI vision trained on billions of images, the robots identify and grab items like shampoo bottles, milk jugs, and soda cans using suction-powered arms.
According to GeekWire, there are four Glacier robots already at Recology's South Seattle site. Two straddle conveyor belts, each scanning for a specific type of high-density polyethylene plastic. A third grabs stray bottles missed upstream, and a fourth pulls cans before they reach the end of the line.
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“AI is more accurate in detecting the material it’s going after,” Justin Johnson, operations manager at Recology told Seattle's KOMO-TV. He highlighted that these robots can sort through 45 items a minute, efficiently picking up materials and depositing them into the appropriate recycling bins.
According to GeekWire, Glacier co-founder Areeb Malik, a former Facebook engineer, said that the machines can recover 80%–90% of target materials, roughly matching the accuracy of human sorters.