On the power of language: the shift from “controlling nature” to “cooperating with living systems” isn’t just semantic—it fundamentally changes what we design and why. A better future is designed with desire, not desperation—we need visions that inspire genuine excitement, not just mitigate harm.
Hi, I’m Julia Bunte-Mein, one of the Interact residents this summer. This talk explores two interconnected ideas: first, regenerative technology—a framework that moves beyond sustainability to actively enhance ecological systems through innovation. Second, how we can apply regenerative thinking to emerging technologies at the intersection of AI and biotech.
For context on how I arrived at these questions, I have worked as an operator and product builder in the climate tech ecosystem for the last half decade or so. For most of my career so far, I’ve focused on renewables, grid infrastructure, and net-zero commitments, working both on the startup side and with large corporates trying to meet their sustainability goals. My past work has been motivated by a vision of companies continuing to be successful in their technological goals and aspirations for human progress, while also being carbon neutral or carbon free.
What is regenerative technology?
I came into the residency asking: can we challenge our assumptions about whom technology serves, and whether technology is inherently harmful or beneficial to the biosphere? There is an assumption that technology is created by humans, for humans alone—and that when it serves us, it often harms everything else, or at best remains neutral. I take a techno-optimistic stance and have long rejected the zero-sum argument between our economies and our environments, or between humans and other biologies. But I understand why that’s not an obvious take for everyone. When we look at the last century of human technology and economic growth, it has, evidently, taken an enormous toll on our environment. Assuming a fixed paradigm/system, it is understandable that limiting our behavior, or cutting back our growth in order to minimize damage, makes sense. It takes the assumption that our goals are inherently at odds. In reality, each 1°C of warming correlates with a 12% GDP decline—human and planetary wellbeing are interdependent.
Regenerative technology moves beyond sustainability toward actively enhancing ecological systems, reframing our economic paradigm from degenerative to regenerative. This allows us to build technology that actively supports economic growth and is not at odds with ecological flourishing. The central question is: what does symbiotic relationship between technology and living systems look like? Can we achieve both human and ecological flourishing—and does that require fundamentally rethinking technology and growth? Regenerative technologies try to reimagine our way of life from the atom up. It’s not just that we’re creating a sense of mutualism between humans ourselves and other living forms, but we’re operating in a new paradigm.
For example, rather than only decarbonizing beef production—which we should absolutely continue—how can we rethink food systems entirely? This is a ‘yes, and’ approach where we don’t abandon current sustainability efforts, but expand our vision. Along with decarbonizing steel, cement, and other heavy industry, what new materials can we invent, discover, or develop? Moreover, in the built environment, can we construct buildings with materials that embed organisms that actually remove CO₂ from the atmosphere as they provide shelter?
Regenerative models represent a new mindset that extends beyond climate tech to our broader visions of technological futures. Rather than simply minimizing damage, can we imagine a future of flourishing? This thinking applies to our goals with AI and AI-human co-evolution, challenging us to move beyond harm reduction toward mutual enhancement.
It’s a time for radical dreaming…
If there’s one thing that could summarize the shift in thinking over the last year, it’s that I’ve decided it’s a time for radical dreaming. I’ve been dreaming much bigger around what’s possible for ourselves and a future of technology. Art is a wonderful way to express visions of the future and help create a sense of collective visioning. I could easily have spent an hour presenting on artists and designers exploring technology-biology relationships. But for today, I’ll share one piece by Anicka Yi called In Love with the World.
This piece prompts us to explore a relational stance toward technology and AI, imagining machines adapted to their environments like living organisms, coexisting symbiotically. Yi reimagined the Tate Modern’s Turbine Hall (formerly the Bankside Power Station) as an aquarium inhabited by marine-inspired mechanical organisms. The tentacular and amoeba-like aerobes, coated in cilia-like protrusions, moved dynamically through the hall, interacting with other elements of the biosphere and occasionally nesting in a maintenance area to recharge their batteries. This piece teases out the fuzzy boundaries between organic and artificial, living and mechanical.
Bio-convergence: computation meets biology
Computation and biology have complemented each other for decades. Artificial neural networks for models are based on the brains of organic organisms. Take protein folding—a problem that stumped biochemists for decades until DeepMind’s AI solved it. Today, these same algorithms generated in natural language can also be used to decode nature and generate new biological life forms. Biology is our most powerful technology, that currently, we are only scratching the surface of.
Why now? What makes the intersection of computation and biology so compelling at this moment? The cost of gathering biological data has never been lower, and precision has never been higher. We can now sequence DNA in an afternoon for a fraction of what it used to cost. We have enhanced computational power, algorithms, and data that give us the ability to read from and edit DNA at industrial scales. We’re switching from more intuitive trial-and-error testing approaches to high-throughput experimentation, as well as non-destructive data collection methods.
I’ve bucketed three key opportunity areas in this space. One is opportunities to model technology on biology, what I’m calling ‘enhanced biomimicry.’ This is the idea that building technology from evolutionarily-selected biology leads to more resilient, efficient, and adaptive solutions. There is a set of novel technologies bridging machine learning and neuroscience, building AI models using biological first principles. For example, a group called Biological Black Box (BBB) is building ‘organic’ computers using living brain cells, creating bio-LLMs far more efficient than silicon-based models. There’s also a robotics company, Opteran, that reverse-engineers the brain algorithms of insects as the model and data source for their ‘natural intelligence’ machines, using neuroscience as opposed to data science. ARIA has embarked on a research initiative based on the core belief that we can build dramatically more efficient computers by applying the principles found ubiquitously in nature.
The second opportunity area lies in bioengineering and synthetic biology, altering biological systems to create novel materials and solutions. In just over an hour, I’ll be hosting a discussion with Maddie Hall, CEO of Living Carbon. Living Carbon is genetically engineering trees to capture and store more CO₂ from the environment. That’s one example of combining plant ecology and genetic engineering for interesting outcomes.
The third area is AI for life sciences and, more specifically, digital biology and virtual cell models. Groups like Tahoe Therapeutics, Markov Bio, and the Arc Institute are exploring how to overcome the bottlenecks in wet lab testing and accelerating the speed of scientific discovery. My next article will be focused on this area, in particular on how to set up Ai-feedback/ training loops in physical lab settings in order to collect the physical, real-world experiment data that is currently missing from models.
A moment for intentionality
Returning to where we started with regenerative thinking—our intentions matter. I have spent a lot of time coming back to the high-level question of our intentions and vision for ourselves as we think about the future of our technology. Simply applying transformative technologies to traditional products risks reinforcing the same extractive systems. I feel that simply updating our traditional products with new, exciting, potentially transformative technologies will lead to a future similar to the present and potentially reinforce the degenerative economics or extractive systems we’ve seen in the past if we don’t bring thoughtful intention setting. Innovation for innovation’s sake—even with biological systems—won’t create a better world. Without intentionality, we risk recreating the same ecological and social problems. You may be familiar with Jevons’ Paradox, which warns us that increased efficiency often drives increased consumption. To avoid falling into the trap of using technology to amplify our consumptive practices, can we really take this opportunity of leveraging our technology with immense productive capabilities to bring in more of a regenerative attitude towards the impacts we have on the rest of the world and take a more relational, cooperative stance with other biologies?
Given this intention-setting, what could that look like in practice? I’ll walk through a couple examples of values-aligned companies using biological data acquisition and plant intelligence at this intersection of AI, biology, and engineering. Foray (Cambridge, MA) builds biomanufacturing tools that could decouple agriculture and forestry from land use entirely. Their technology could eliminate tree harvesting for forest products—not just timber, but molecules for flavoring and therapeutics, scents for cosmetics, and diverse biomanufacturing materials. They are doing a lot of work in cultivating seeds, which is very important for biodiversity. This technology can be used widely, from agriculture to pharma to directly supporting biodiversity, and it leverages plant intelligence for rethinking how we produce natural resources.
Another exciting example is Basecamp Research (UK). They leverage biodiversity’s genetic information alongside computational power for applications from novel enzymes to what they call ‘the OpenAI of plant intelligence.’ More concretely, they use environmental sensing data to collect information like pH, salinity, and temperature of the environment wherever they’re already collecting data on protein. Their BaseFold model (named after AlphaFold) incorporates environmental metadata—pH, salinity, temperature—for even greater precision.
These companies demonstrate how AI can unlock biological intelligence beyond human sensory perception. By fusing diverse sensory data, such systems could detect diseases before symptoms appear, advance sustainable food production, or sense environmental changes previously imperceptible to humans.
More examples of regenerative tech futures:
Gene editing (CRISPR and beyond). We could engineer crops that improve soil health while growing, turning agriculture from an extractive process into a regenerative one.
AI-driven bioinformatics. We could design new proteins that could be helpful in carbon capture or potentially break down synthetic plastics.
Synthetic biology and biomanufacturing. We could replace entire industrial supply chains with living systems that produce materials on demand locally using just sunlight and waste products.
Organoids and adaptive robotics. Create machines that become more capable over time rather than degrading, sensing and responding to environmental needs dynamically.
Precision fermentation. Democratize manufacturing by producing materials and medicines locally using biological systems instead of massive industrial facilities. I hosted an event last week on synthetic biology for food tech. We explored how researchers are creating animal products molecularly identical to the originals—dairy proteins, for instance—without any animals and imagined what’s next.
Bioprinting. Grow solutions to environmental problems—bioprinted coral reefs could restore marine habitats while generating sustainable building materials or capturing carbon from seawater.
The power of language
Throughout this exploration, I’ve taken an intentionally optimistic stance—inviting a technology future that enables a symbiotic flourishing between humans and the environment. These are not technofixes permitting continued fossil fuel use. Rather, decarbonize everything, electrify everything, and reimagine our relationship with living systems. Many interesting questions emerge around these technologies, which are applied in biomedicine and other places, and have potential for environmental remediation. This is where language comes in. My background is in environmental science and linguistic anthropology, and for this entire time working in the climate tech space, I can’t help but notice the words and language we use to describe our goals and intention setting. The relationship we have between ourselves, our technology, and nature is both understood and expressed by the words and language that we use.
Can we collaborate with natural systems rather than control them? What would innovation look like with empathy and reciprocity as core values—where we contribute more than we consume? Despite climate urgency, what if we approached innovation with curiosity, awe, even play—rather than fear of dwindling resources?
