On the left, a Hermès bag made using fine mycelium as a leather alternative, made in partnership with the biotech company MycoWorks; on right, a sheet of mycelium "leather."
A natural material that looks and feels like real leather is taking the fashion world by storm. Scientists view mycelium—the vegetative part of a mushroom-producing fungus—as a planet-friendly alternative to animal hides and plastics.
Products crafted from this vegan leather are emerging, with others poised to hit the market soon. Among them are the Hermès Victoria bag, Lululemon's yoga accessories, Adidas' Stan Smith Mylo sneaker, and a Stella McCartney apparel collection.
The Adidas' Stan Smith Mylo concept sneaker, made in partnership with Bolt Threads, uses an alternative leather grown from mycelium; a commercial version is expected in the near future.
Adidas
Hermès has held presales on the new bag, says Philip Ross, co-founder and chief technology officer of MycoWorks, a San Francisco Bay area firm whose materials constituted the design. By year-end, Ross expects several more clients to debut mycelium-based merchandise. With "comparable qualities to luxury leather," mycelium can be molded to engineer "all the different verticals within fashion," he says, particularly footwear and accessories.
More than a half-dozen trailblazers are fine-tuning mycelium to create next-generation leather materials, according to the Material Innovation Initiative, a nonprofit advocating for animal-free materials in the fashion, automotive, and home-goods industries. These high-performance products can supersede items derived from leather, silk, down, fur, wool, and exotic skins, says A. Sydney Gladman, the institute's chief scientific officer.
That's only the beginning of mycelium's untapped prowess. "We expect to see an uptick in commercial leather alternative applications for mycelium-based materials as companies refine their R&D [research and development] and scale up," Gladman says, adding that "technological innovation and untapped natural materials have the potential to transform the materials industry and solve the enormous environmental challenges it faces."
In fewer than 10 days in indoor agricultural farms, "we grow large slabs of mycelium that are many feet wide and long. We are not confined to the shape or geometry of an animal."
Reducing our carbon footprint becomes possible because mycelium can flourish in indoor farms, using agricultural waste as feedstock and emitting inherently low greenhouse gas emissions. Carbon dioxide is the primary greenhouse gas. "We often think that when plant tissues like wood rot, that they go from something to nothing," says Jonathan Schilling, professor of plant and microbial biology at the University of Minnesota and a member of MycoWorks' Scientific Advisory Board.
But that assumption doesn't hold true for all carbon in plant tissues. When the fungi dominating the decomposition of plants fulfill their function, they transform a large portion of carbon into fungal biomass, Schilling says. That, in turn, ends up in the soil, with mycelium forming a network underneath that traps the carbon.
Unlike the large amounts of fossil fuels needed to produce styrofoam, leather and plastic, less fuel-intensive processing is involved in creating similar materials with a fungal organism. While some fungi consist of a single cell, others are multicellular and develop as very fine threadlike structures. A mass of them collectively forms a "mycelium" that can be either loose and low density or tightly packed and high density. "When these fungi grow at extremely high density," Schilling explains, "they can take on the feel of a solid material such as styrofoam, leather or even plastic."
Tunable and supple in the cultivation process, mycelium is also reliably sturdy in composition. "We believe that mycelium has some unique attributes that differentiate it from plastic-based and animal-derived products," says Gavin McIntyre, who co-founded Ecovative Design, an upstate New York-based biomaterials company, in 2007 with the goal of displacing some environmentally burdensome materials and making "a meaningful impact on our planet."
After inventing a type of mushroom-based packaging for all sorts of goods, in 2013 the firm ventured into manufacturing mycelium that can be adapted for textiles, he says, because mushrooms are "nature's recycling system."
The company aims for its material—which is "so tough and tenacious" that it doesn't require any plastic add-on as reinforcement—to be generally accessible from a pricing standpoint and not confined to a luxury space. The cost, McIntyre says, would approach that of bovine leather, not the more upscale varieties of lamb and goat skins.
Already, production has taken off by leaps and bounds. In fewer than 10 days in indoor agricultural farms, "we grow large slabs of mycelium that are many feet wide and long," he says. "We are not confined to the shape or geometry of an animal," so there's a much lower scrap rate.
Decreasing the scrap rate is a major selling point. "Our customers can order the pieces to the way that they want them, and there is almost no waste in the processing," explains Ross of MycoWorks. "We can make ours thinner or thicker," depending on a client's specific needs. Growing materials locally also results in a reduction in transportation, shipping, and other supply chain costs, he says.
Yet another advantage to making things out of mycelium is its biodegradability at the end of an item's lifecycle. When a pair of old sneakers lands in a compost pile or landfill, it decomposes thanks to microbial processes that, once again, involve fungi. "It is cool to think that the same organism used to create a product can also be what recycles it, perhaps building something else useful in the same act," says biologist Schilling. That amounts to "more than a nice business model—it is a window into how sustainability works in nature."
A product can be called "sustainable" if it's biodegradable, leaves a minimal carbon footprint during production, and is also profitable, says Preeti Arya, an assistant professor at the Fashion Institute of Technology in New York City and faculty adviser to a student club of the American Association of Textile Chemists and Colorists.
On the opposite end of the spectrum, products composed of petroleum-based polymers don't biodegrade—they break down into smaller pieces or even particles. These remnants pollute landfills, oceans, and rivers, contaminating edible fish and eventually contributing to the growth of benign and cancerous tumors in humans, Arya says.
Commending the steps a few designers have taken toward bringing more environmentally conscious merchandise to consumers, she says, "I'm glad that they took the initiative because others also will try to be part of this competition toward sustainability." And consumers will take notice. "The more people become aware, the more these brands will start acting on it."
A further shift toward mycelium-based products has the capability to reap tremendous environmental dividends, says Drew Endy, associate chair of bioengineering at Stanford University and president of the BioBricks Foundation, which focuses on biotechnology in the public interest.
The continued development of "leather surrogates on a scaled and sustainable basis will provide the greatest benefit to the greatest number of people, in perpetuity," Endy says. "Transitioning the production of leather goods from a process that involves the industrial-scale slaughter of vertebrate mammals to a process that instead uses renewable fungal-based manufacturing will be more just."
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.”