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
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.
Artificial Intelligence is already helping to grow some of the food we eat.
The chef-farmers choose from among 45 types of herb and leafy-greens seeds, plop them into grow trays, and a few weeks later they pick and serve. While success is predicated on at least a small amount of these humans’ care, the systems are autonomously surveilled round-the-clock from Babylon’s base of operations. And artificial intelligence is helping to run the show.
Babylon piloted the use of specialized cameras that take pictures in different spectrums to gather some less-obvious visual data about plants’ wellbeing and alert people if something seems off.
Imagine consistently perfect greens and tomatoes and strawberries, grown hyper-locally, using less water, without chemicals or environmental contaminants. This is the hefty promise of controlled environment agriculture (CEA) — basically, indoor farms that can be hydroponic, aeroponic (plant roots are suspended and fed through misting), or aquaponic (where fish play a role in fertilizing vegetables). But whether they grow 4,160 leafy-green servings per year, like one Babylon farm, or millions of servings, like some of the large, centralized facilities starting to supply supermarkets across the U.S., they seek to minimize failure as much as possible.
Babylon’s soilless hydroponic growing system
Courtesy Babylon Micro-Farms
Here, AI is starting to play a pivotal role. CEA growers use it to help “make sense of what’s happening” to the plants in their care, says Scott Lowman, vice president of applied research at the Institute for Advanced Learning and Research (IALR) in Virginia, a state that’s investing heavily in CEA companies. And although these companies say they’re not aiming for a future with zero human employees, AI is certainly poised to take a lot of human farming intervention out of the equation — for better and worse.
Most of these companies are compiling their own data sets to identify anything that might block the success of their systems. Babylon had already integrated sensor data into its farms to measure heat and humidity, the nutrient content of water, and the amount of light plants receive. Last year, they got a National Science Foundation grant that allowed them to pilot the use of specialized cameras that take pictures in different spectrums to gather some less-obvious visual data about plants’ wellbeing and alert people if something seems off. “Will this plant be healthy tomorrow? Are there things…that the human eye can't see that the plant starts expressing?” says Amandeep Ratte, the company’s head of data science. “If our system can say, Hey, this plant is unhealthy, we can reach out to [users] preemptively about what they’re doing wrong, or is there a disease at the farm?” Ratte says. The earlier the better, to avoid crop failures.
Natural light accounts for 70 percent of Greenswell Growers’ energy use on a sunny day.
Courtesy Greenswell Growers
IALR’s Lowman says that other CEA companies are developing their AI systems to account for the different crops they grow — lettuces come in all shapes and sizes, after all, and each has different growing needs than, for example, tomatoes. The ways they run their operations differs also. Babylon is unusual in its decentralized structure. But centralized growing systems with one main location have variabilities, too. AeroFarms, which recently declared bankruptcy but will continue to run its 140,000-square foot vertical operation in Danville, Virginia, is entirely enclosed and reliant on the intense violet glow of grow lights to produce microgreens.
Different companies have different data needs. What data is essential to AeroFarms isn’t quite the same as for Greenswell Growers located in Goochland County, Virginia. Raising four kinds of lettuce in a 77,000-square-foot automated hydroponic greenhouse, the vagaries of naturally available light, which accounts for 70 percent of Greenswell’s energy use on a sunny day, affect operations. Their tech needs to account for “outside weather impacts,” says president Carl Gupton. “What adjustments do we have to make inside of the greenhouse to offset what's going on outside environmentally, to give that plant optimal conditions? When it's 85 percent humidity outside, the system needs to do X, Y and Z to get the conditions that we want inside.”
AI will help identify diseases, as well as when a plant is thirsty or overly hydrated, when it needs more or less calcium, phosphorous, nitrogen.
Nevertheless, every CEA system has the same core needs — consistent yield of high quality crops to keep up year-round supply to customers. Additionally, “Everybody’s got the same set of problems,” Gupton says. Pests may come into a facility with seeds. A disease called pythium, one of the most common in CEA, can damage plant roots. “Then you have root disease pressures that can also come internally — a change in [growing] substrate can change the way the plant performs,” Gupton says.
AI will help identify diseases, as well as when a plant is thirsty or overly hydrated, when it needs more or less calcium, phosphorous, nitrogen. So, while companies amass their own hyper-specific data sets, Lowman foresees a time within the next decade “when there will be some type of [open-source] database that has the most common types of plant stress identified” that growers will be able to tap into. Such databases will “create a community and move the science forward,” says Lowman.
In fact, IALR is working on assembling images for just such a database now. On so-called “smart tables” inside an Institute lab, a team is growing greens and subjects them to various stressors. Then, they’re administering treatments while taking images of every plant every 15 minutes, says Lowman. Some experiments generate 80,000 images; the challenge lies in analyzing and annotating the vast trove of them, marking each one to reflect outcome—for example increasing the phosphate delivery and the plant’s response to it. Eventually, they’ll be fed into AI systems to help them learn.
For all the enthusiasm surrounding this technology, it’s not without downsides. Training just one AI system can emit over 250,000 pounds of carbon dioxide, according to MIT Technology Review. AI could also be used “to enhance environmental benefit for CEA and optimize [its] energy consumption,” says Rozita Dara, a computer science professor at the University of Guelph in Canada, specializing in AI and data governance, “but we first need to collect data to measure [it].”
The chef-farmers can choose from 45 types of herb and leafy-greens seeds.
Courtesy Babylon Micro-Farms
Any system connected to the Internet of Things is also vulnerable to hacking; if CEA grows to the point where “there are many of these similar farms, and you're depending on feeding a population based on those, it would be quite scary,” Dara says. And there are privacy concerns, too, in systems where imaging is happening constantly. It’s partly for this reason, says Babylon’s Ratte, that the company’s in-farm cameras all “face down into the trays, so the only thing [visible] is pictures of plants.”
Tweaks to improve AI for CEA are happening all the time. Greenswell made its first harvest in 2022 and now has annual data points they can use to start making more intelligent choices about how to feed, water, and supply light to plants, says Gupton. Ratte says he’s confident Babylon’s system can already “get our customers reliable harvests. But in terms of how far we have to go, it's a different problem,” he says. For example, if AI could detect whether the farm is mostly empty—meaning the farm’s user hasn’t planted a new crop of greens—it can alert Babylon to check “what's going on with engagement with this user?” Ratte says. “Do they need more training? Did the main person responsible for the farm quit?”
Lowman says more automation is coming, offering greater ability for systems to identify problems and mitigate them on the spot. “We still have to develop datasets that are specific, so you can have a very clear control plan, [because] artificial intelligence is only as smart as what we tell it, and in plant science, there's so much variation,” he says. He believes AI’s next level will be “looking at those first early days of plant growth: when the seed germinates, how fast it germinates, what it looks like when it germinates.” Imaging all that and pairing it with AI, “can be a really powerful tool, for sure.”
Researchers from the University of Cambridge have laid the foundations for growing synthetic embryos that could develop a beating heart, gut and brain.
The organoid revolution
In 1981, scientists discovered how to keep stem cells alive. This was a significant breakthrough, as stem cells have notoriously rigorous demands. Nevertheless, stem cells remained a relatively niche research area, mainly because scientists didn’t know how to convince the cells to turn into other cells.
Then, in 1987, scientists embedded isolated stem cells in a gelatinous protein mixture called Matrigel, which simulated the three-dimensional environment of animal tissue. The cells thrived, but they also did something remarkable: they created breast tissue capable of producing milk proteins. This was the first organoid — a clump of cells that behave and function like a real organ. The organoid revolution had begun, and it all started with a boob in Jello.
For the next 20 years, it was rare to find a scientist who identified as an “organoid researcher,” but there were many “stem cell researchers” who wanted to figure out how to turn stem cells into other cells. Eventually, they discovered the signals (called growth factors) that stem cells require to differentiate into other types of cells.
For a human embryo (and its organs) to develop successfully, there needs to be a “dialogue” between these three types of stem cells.
By the end of the 2000s, researchers began combining stem cells, Matrigel, and the newly characterized growth factors to create dozens of organoids, from liver organoids capable of producing the bile salts necessary for digesting fat to brain organoids with components that resemble eyes, the spinal cord, and arguably, the beginnings of sentience.
Synthetic embryos
Organoids possess an intrinsic flaw: they are organ-like. They share some characteristics with real organs, making them powerful tools for research. However, no one has found a way to create an organoid with all the characteristics and functions of a real organ. But Magdalena Żernicka-Goetz, a developmental biologist, might have set the foundation for that discovery.
Żernicka-Goetz hypothesized that organoids fail to develop into fully functional organs because organs develop as a collective. Organoid research often uses embryonic stem cells, which are the cells from which the developing organism is created. However, there are two other types of stem cells in an early embryo: stem cells that become the placenta and those that become the yolk sac (where the embryo grows and gets its nutrients in early development). For a human embryo (and its organs) to develop successfully, there needs to be a “dialogue” between these three types of stem cells. In other words, Żernicka-Goetz suspected the best way to grow a functional organoid was to produce a synthetic embryoid.
As described in the aforementioned Nature paper, Żernicka-Goetz and her team mimicked the embryonic environment by mixing these three types of stem cells from mice. Amazingly, the stem cells self-organized into structures and progressed through the successive developmental stages until they had beating hearts and the foundations of the brain.
“Our mouse embryo model not only develops a brain, but also a beating heart [and] all the components that go on to make up the body,” said Żernicka-Goetz. “It’s just unbelievable that we’ve got this far. This has been the dream of our community for years and major focus of our work for a decade and finally we’ve done it.”
If the methods developed by Żernicka-Goetz’s team are successful with human stem cells, scientists someday could use them to guide the development of synthetic organs for patients awaiting transplants. It also opens the door to studying how embryos develop during pregnancy.
This article originally appeared on Big Think, home of the brightest minds and biggest ideas of all time.
