Two students had an idea at a scrapyard. They went on to "upcycle" 80,000 airbags, 100,000 seatbelts and 28,000 belt buckles – the equivalent of 60 tons of car trash
Luckily, two college freshmen at the Rotterdam School of Management, Erasmus University, were naïve enough to take their bicycles to the scrapyard. In a previous stroke of fortune, the freshmen, Adrian Goosses and Michael Widmann, had been assigned as roommates and had quickly hit it off. Now they were looking for a cool recycling project for their first semester “strategic entrepreneurship” course—maybe they could turn old tires into comfortable lounge chairs, they thought.
“Everybody gets around by bike in Rotterdam,” says Goosses, now 32, from his home in Cologne, Germany. “The tires were way too heavy and cumbersome to transport by bike,” Widmann chimes in via Zoom from Bolzano, Italy, where he lives.
Sifting through the car trash for something handier led the two students to an idea that has since flourished: Could the airbag and seatbelts from a banged up compact car be salvaged and turned into a sustainable backpack? The size of the airbag was already a natural fit. The seatbelts made perfect shoulder straps. After returning from the scrapyard, “We stitched the prototype together by hand with a needle and yarn,” says Goosses. “Yet we didn’t even know how to sew!”
Much to their surprise, their classmates responded with so much enthusiasm to their “trash bag” concept that it convinced the two innovators to keep going. Every semester, they improved the prototype further. With the help of YouTube videos, they taught themselves how to sew. Because modern electric sewing machines had a difficult time breaking through the tough nylon of the airbags, Goosses and Widmann went to a second-hand shop and purchased an ancient Singer from 1880 for 10 Euros. They dyed the first airbags in a saucepan in the garden outside of the apartment they shared.
“By the time we graduated, we had a presentable prototype and a business plan,” Goosses says.
Despite their progress, Goosses and Widmann are up against a problem that’s immense: Cars are notoriously difficult to recycle because many parts are considered toxic waste.
It’s an example of “upcycling,” when you spot a potential new use in something that’s been trashed, shelved or otherwise retired. The approach has received increasing attention and support from the U.S. Environmental Protection Agency and others to boost sustainability in all kinds of areas, from fashion (where even luxury brands like Balenciaga or Coach repurpose vintage clothing and bags) to architecture, where reusing wood, steel and bricks significantly reduces a building’s carbon footprint.
In addition to helping the planet, those who do it well can make a living from it. These days, Goosses and Widmann own a flourishing company: Airpaq. A crowdfunding campaign in 2017 yielded 70,000 Euros to get them started. Since then, they have upcycled 80,000 airbags, 100,000 seatbelts and 28,000 belt buckles – the equivalent of 60 tons of car trash.
For the successful upcycling, they received the 2021 German Design Award and, earlier this year, the renowned German Sustainability Award. The jurors evaluating the product commented that the startup “convinced us not only because of their uncompromising quality and functionality but also because of their ecological and ethical values….How well the startup translates upcycling and green fashion into an urban lifestyle brand is impressive.”
Despite their progress, Goosses and Widmann are up against a problem that’s immense: Cars are notoriously difficult to recycle because many parts are considered toxic waste. Therefore, up to 25% of vehicle scraps get shredded every year in Germany alone, the equivalent of over 501,000 tons. Because airbags and seatbelts are nearly indestructible, they are costly to recycle and almost always end up in landfills. Given that airbags and seatbelts save lives, they are subject to stringent security regulations, and manufacturers have a sky-high reject rate. “If a tiny filament protrudes somewhere, the manufacturer will throw out the entire output,” Widmann explains.
The nearly indestructible qualities that make this material very difficult to recycle render it an excellent resource for backpacks. “The material is so durable, you almost cannot tear it,” Goosses adds and demonstrates with a hard tug that even when the material already has a hole, it won’t rip it further. The material is also water repellent and extremely light.
The antique Singer is still in their Cologne headquarters but only as decoration. Their company with 12 employees is producing 500 backpacks and fanny packs every week in Romania, where the parts are professionally cut by laser, dyed and sewed. Airpaq still procures the belt buckles at scrapyards but they get most of the airbags directly from the reject pile of a nearby airbag producer. “We process the materials where they are produced,” Goosses explains. Only about 15 miles lie between one of Europe’s biggest airbag manufacturers and the Airpaq seamsters in Romania.
Co-founders Adrian Goosses and Michael Widmann demonstrate their company's equation: airbag plus seatbelt equals a backpack that's durable and eco-friendly.
Airpaq
The founders are aware that with price tags ranging from 100 to 160 Euro - a cost that reflects their intensive production process - Airpaq’s bags are hardly competitive. After all, anybody can buy a discount backpack for a fraction of the cost. So they recently added fanny packs for 30 Euro to their product line. Goosses and Widmann know they will need to lower their prices in the long run if they want to expand. Among other things, they didn’t pay themselves salaries during the first two years after founding the company.
Money-making isn’t their only objective. “Of course, it would be cheaper if we did what almost all textile producers do and move production to Asia,” Goosses says. That wasn’t an option for him. “Ship trash to Vietnam and let seamsters sew it together for cheap? No way, that would be anything but sustainable,” he says.
Michael Widmann’s family was already operating a textile production in Romania, mainly producing thin, elastic sports fashion. The family allowed Widmann and Goosses to produce their first professional prototypes there, but then the two youngsters had to buy their own machines, acquire the necessary knowhow, and hire their staff. They both moved to Romania for six months “to get to know the people behind the machines.” The founders emphasize that they pay fair wages, use eco-certified dyes and clean their own wastewater. “Normal production uses five to six liters of water per kilo material,” Widmann explains. “We only need a fraction because we massage the dye into the material by hand: 100 ml water for washing and dying per kilo.”
However, every time they return to the scrapyard, the abundance of trash sparks new ideas. “When you see how much material ends up there…” Widmann says, shaking his head without finishing the sentence. Goosses picks up the train of thought: “We want to make upcycling the new standard. You just have to be creative to get upcycling into the mainstream.”
And maybe they’ll return to their roots and finally find an idea for the tires after all. “One could turn the rubber into soles for comfortable shoes,” Widmann thinks out loud.
Giving robots self-awareness as they move through space - and maybe even providing them with gene-like methods for storing rules of behavior - could be important steps toward creating more intelligent machines.
Now roboticists are going a step further, training their creations to do even better: understand their own image in space and interact with humans like humans do. Today, there are already robot-teachers like KeeKo, robot-pets like Moffin, robot-babysitters like iPal, and robotic companions for the elderly like Pepper.
But even these reasonably intelligent creations still have huge limitations, some scientists think. “There are niche applications for the current generations of robots,” says professor Anthony Zador at Cold Spring Harbor Laboratory—but they are not “generalists” who can do varied tasks all on their own, as they mostly lack the abilities to improvise, make decisions based on a multitude of facts or emotions, and adjust to rapidly changing circumstances. “We don’t have general purpose robots that can interact with the world. We’re ages away from that.”
Robotic spatial self-awareness – the achievement by the team at Columbia – is an important step toward creating more intelligent machines. Hod Lipson, professor of mechanical engineering who runs the Columbia lab, says that future robots will need this ability to assist humans better. Knowing how you look and where in space your parts are, decreases the need for human oversight. It also helps the robot to detect and compensate for damage and keep up with its own wear-and-tear. And it allows robots to realize when something is wrong with them or their parts. “We want our robots to learn and continue to grow their minds and bodies on their own,” Chen says. That’s what Zador wants too—and on a much grander level. “I want a robot who can drive my car, take my dog for a walk and have a conversation with me.”
Columbia scientists have trained a robot to become aware of its own "body," so it can map the right path to touch a ball without running into an obstacle, in this case a square.
Jane Nisselson and Yinuo Qin/ Columbia Engineering
Today’s technological advances are making some of these leaps of progress possible. One of them is the so-called Deep Learning—a method that trains artificial intelligence systems to learn and use information similar to how humans do it. Described as a machine learning method based on neural network architectures with multiple layers of processing units, Deep Learning has been used to successfully teach machines to recognize images, understand speech and even write text.
Trained by Google, one of these language machine learning geniuses, BERT, can finish sentences. Another one called GPT3, designed by San Francisco-based company OpenAI, can write little stories. Yet, both of them still make funny mistakes in their linguistic exercises that even a child wouldn’t. According to a paper published by Stanford’s Center for Research on Foundational Models, BERT seems to not understand the word “not.” When asked to fill in the word after “A robin is a __” it correctly answers “bird.” But try inserting the word “not” into that sentence (“A robin is not a __”) and BERT still completes it the same way. Similarly, in one of its stories, GPT3 wrote that if you mix a spoonful of grape juice into your cranberry juice and drink the concoction, you die. It seems that robots, and artificial intelligence systems in general, are still missing some rudimentary facts of life that humans and animals grasp naturally and effortlessly.
How does one give robots a genome? Zador has an idea. We can’t really equip machines with real biological nucleotide-based genes, but we can mimic the neuronal blueprint those genes create.
It's not exactly the robots’ fault. Compared to humans, and all other organisms that have been around for thousands or millions of years, robots are very new. They are missing out on eons of evolutionary data-building. Animals and humans are born with the ability to do certain things because they are pre-wired in them. Flies know how to fly, fish knows how to swim, cats know how to meow, and babies know how to cry. Yet, flies don’t really learn to fly, fish doesn’t learn to swim, cats don’t learn to meow, and babies don’t learn to cry—they are born able to execute such behaviors because they’re preprogrammed to do so. All that happens thanks to the millions of years of evolutions wired into their respective genomes, which give rise to the brain’s neural networks responsible for these behaviors. Robots are the newbies, missing out on that trove of information, Zador argues.
A neuroscience professor who studies how brain circuitry generates various behaviors, Zador has a different approach to developing the robotic mind. Until their creators figure out a way to imbue the bots with that information, robots will remain quite limited in their abilities. Each model will only be able to do certain things it was programmed to do, but it will never go above and beyond its original code. So Zador argues that we have to start giving robots a genome.
How does one do that? Zador has an idea. We can’t really equip machines with real biological nucleotide-based genes, but we can mimic the neuronal blueprint those genes create. Genomes lay out rules for brain development. Specifically, the genome encodes blueprints for wiring up our nervous system—the details of which neurons are connected, the strength of those connections and other specs that will later hold the information learned throughout life. “Our genomes serve as blueprints for building our nervous system and these blueprints give rise to a human brain, which contains about 100 billion neurons,” Zador says.
If you think what a genome is, he explains, it is essentially a very compact and compressed form of information storage. Conceptually, genomes are similar to CliffsNotes and other study guides. When students read these short summaries, they know about what happened in a book, without actually reading that book. And that’s how we should be designing the next generation of robots if we ever want them to act like humans, Zador says. “We should give them a set of behavioral CliffsNotes, which they can then unwrap into brain-like structures.” Robots that have such brain-like structures will acquire a set of basic rules to generate basic behaviors and use them to learn more complex ones.
Currently Zador is in the process of developing algorithms that function like simple rules that generate such behaviors. “My algorithms would write these CliffsNotes, outlining how to solve a particular problem,” he explains. “And then, the neural networks will use these CliffsNotes to figure out which ones are useful and use them in their behaviors.” That’s how all living beings operate. They use the pre-programmed info from their genetics to adapt to their changing environments and learn what’s necessary to survive and thrive in these settings.
For example, a robot’s neural network could draw from CliffsNotes with “genetic” instructions for how to be aware of its own body or learn to adjust its movements. And other, different sets of CliffsNotes may imbue it with the basics of physical safety or the fundamentals of speech.
At the moment, Zador is working on algorithms that are trying to mimic neuronal blueprints for very simple organisms—such as earthworms, which have only 302 neurons and about 7000 synapses compared to the millions we have. That’s how evolution worked, too—expanding the brains from simple creatures to more complex to the Homo Sapiens. But if it took millions of years to arrive at modern humans, how long would it take scientists to forge a robot with human intelligence? That’s a billion-dollar question. Yet, Zador is optimistic. “My hypotheses is that if you can build simple organisms that can interact with the world, then the higher level functions will not be nearly as challenging as they currently are.”