Sustainable Supply Chains – IEEE Spectrum

This is a sponsored article brought to you by Amazon.

The journey of a package from the moment a customer clicks “buy” to the moment it arrives at their doorstep is one of the most complex and finely tuned processes in the world of e-commerce. At Amazon, this journey is constantly being optimized, not only for speed and efficiency, but also for sustainability. This optimization is driven by the integration of cutting-edge technologies like artificial intelligence (AI), machine learning (ML), and robotics, which allow Amazon to streamline its operations while working towards minimizing unnecessary packaging.

The use of AI and ML in logistics and packaging is playing an increasingly vital role in transforming the way packages are handled across Amazon’s vast global network. In two interviews — one with Clay Flannigan, who leads manipulation robotics programs at Amazon, and another with Callahan Jacobs, an owner of the Sustainable Packaging team’s technology products — we gain insights into how Amazon is using AI, ML, and automation to push the boundaries of what’s possible in the world of logistics, while also making significant strides in sustainability-focused packaging.

The Power of AI and Machine Learning in Robotics

One of the cornerstones of Amazon’s transformation is the integration of AI and ML into its robotics systems. Flannigan’s role within the Fulfillment Technologies Robotics (FTR) team, Amazon Robotics, centers around manipulation robotics — machines that handle the individual items customers order on amazon.com. These robots, in collaboration with human employees, are responsible for picking, sorting, and packing millions of products every day. It’s an enormously complex task, given the vast diversity of items in Amazon’s inventory.

“Amazon is uniquely positioned to lead in AI and ML because of our vast data,” Flannigan explained. “We use this data to train models that enable our robots to perform highly complex tasks, like picking and packing an incredibly diverse range of products. These systems help Amazon solve logistics challenges that simply wouldn’t be possible at this scale without the deep integration of AI.”

At the core of Amazon’s robotic systems is machine learning, which allows the machines to “learn” from their environment and improve their performance over time. For example, AI-powered computer vision systems enable robots to “see” the products they are handling, allowing them to distinguish between fragile items and sturdier ones, or between products of different sizes and shapes. These systems are trained using expansive amounts of data, which Amazon can leverage due to its immense scale.

One particularly important application of machine learning is in the manipulation of unstructured environments. Traditional robotics have been used in industries where the environment is highly structured and predictable. But Amazon’s warehouses are anything but…