ECOTEK students Noah Harris, 8, and Amir Muhammad, 10, doing measurements for their wind turbine project.
When Keith Young was a young father shepherding his three children through the Detroit public school system, he felt something was missing.
The students are working on issues ranging from robotics to 3D printing to finding a cure for a rare form of cancer.
"What I'd observed was a gap between the resources that were being offered to university-level folks and in the professional ranks compared to what had been offered to kids in K-12, and in particular, the ones that were in urban and rural communities," he recalls. "There was always a Boys and Girls Camp, always a YMCA. There was never a YMCA for scientists."
Thus, the concept of ECOTEK Lab was born. Young's vision was to narrow that gap -- by financing pop-up labs for students who want to find a scientific solution to hard-to-solve problems that can be found in their own backyards.
He began in 2005, guiding his own children through foundational experiments for eventual startup companies, focusing on climate change, DNA, making biofuels and other fields of research. In addition to the labs, Young says ECOTEK has also reached young people by way of field trips, science fairs, and in-class demonstrations at schools. Young considers himself a venture capitalist, lending resources to kid and teen scientists.
Keith Young, foreground, is the founder of ECOTEK. Behind him, from left, are his daughter, Amber, son, Keith Jr., and ECOTEK students Emmanuel Jefferson and Antoine Crews.
(Courtesy Young)
In 2008, he took a group of six students from Detroit who had been researching brownfields, or previously developed land that's now vacant, and how they affect climate change; their work culminated in a research trip to Cape Town, South Africa, and participation in a conference there.
Today, he's helping transform the lives of around 250 student scientists across the country in places like Detroit, Florida and Maryland. Those students are working on issues ranging from robotics to 3D printing to finding a cure for a rare form of cancer.
Participating students do not receive a grade -- "they have to have passion to do the work." To take part, students must complete an application process and pay a small fee to use the lab, which is based on family resources, Young says. Students usually work in groups of two to three and are matched with a STEM mentor who can help when they run into research roadblocks.
In one lab in Detroit, a trio of teens is working to develop battery technology for smart mobility along with microbial fuel cells. In another lab, students focus on plant-based drug discovery. One of their projects is using plant DNA to better understand how the breast cancer gene mutation called BRCA1 works in the human body. In the African American population, about 35 percent of women with triple-negative breast cancer test positive for this mutation, and they usually don't learn of their diagnosis until the cancer has spread.
ECOTEK students have also had a slightly larger audience – the United Nations.
A third Detroit-based lab is led by Keith Young's daughter and one of ECOTEK's original students: Founder Briana Young, 23, runs a spin-off business called SmartFarms, which works on food security and developing food safety systems for urban farming using advanced drone technology and biochemical sensory systems. According to a recent report, more than 30,000 Detroiters don't have access to a full-service grocery store, and 48 percent are considered food insecure.
"We don't tell them which subjects to do – that's why [the labs] are not working on the same thing," explains Young. "We're trying to give student scientists a place to find their way."
The gap that Young noticed for urban students exists also among rural communities, and the problems they face are different. Students in a lab in Polk County, Florida, decided to tackle citrus greening, a bacterial disease that causes citrus fruit to bear bitter-tasting and underdeveloped fruit. The culprit is the Asian psyllid, a pest common to citrus plants. The problem is so pervasive that it's caused a precipitous decline in the industry, which had been a major one in Polk. At Bok Academy in Lake Wales, also in Florida, students are using drones to get an overhead view of the patterns they can detect to better understand which trees to treat and when.
"With the majority of our area dependent on citrus and various other crops, why not get students involved in problem-solving and research that's going to truly make a difference?" says David Lockett, a STEM facilitator at Bok Academy.
To this end, the students have shared their findings with scientists at the University of Florida and a research lab in Colorado.
A young woman who started in ECOTEK as an elementary-school student will now, at age 24, return to run the research arm of the company.
ECOTEK students have also had a slightly larger audience – the United Nations. The Detroit students have traveled to New York since 2013 to share their learnings with international diplomats from countries like Belize, Cuba, and Antigua.
The students' hands-on experience in the lab often inspires them to pursue academic success across the board at school. Young says that graduating students usually receive an average of $150,000 in college scholarships and score an average of 1450 on the SATs and in the 90th percentile on ACT tests.
Young plans to continue his work to develop these scientists, and after having invested "millions" of dollars of his own money, he's now seeing the fruits of his labor come full circle. A young woman who started in ECOTEK as an elementary-school student will now, at age 24, return to run the research arm of the company.
"It was," he says proudly, "a 14-year investment payback."
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.
