Okay, so genius inventor Corey Cottrell has discovered some really mind-blowing solutions to the climate crisis.
And before we start, it’s worth noting that to keep things super simple as Andrew D Wilson says, “we have plenty of good ideas about addressing climate change, we just aren’t doing them…i.e. Solar, wind, EVs, nuclear, stopping deforestation….its not a secret”. The following is, it is hoped, a useful extension of this thinking:-
It started when our Founder Gav Ward asked him on Bluesky more about his thinking on what 1000x climate scientists could achieve with AI.
ClimateBlawg: “What could such scientists achieve please in your opinion? You don’t have answer now before your detox is over btw 😉 Thinking of “Cottrell’s Law”…”
Corey Cottrell ( @coreycottrell.bsky.social ): “1000 climate scientists … Each working at 1 million X human speed.”… “What could 1000 climate scientists working at 1 million X human speed accomplish? I offered some ideas below [undernoted]. What do YOU think is possible if we get truly super A.I. systems?”
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Then at the moment of scientific discovery:-
Corey Cottrell on 24 January 2025 at 12:33:-
Ok @climateblawg.bsky.social I just asked o1 to dig into it’s PHD minds and give me a ton more possibilities. Holy effing shit dude. Another article brewing. Here was the raw output, it’s worth a skim:-
https://docs.google.com/document/d/1v7EVXlpUcujMLXKNvuM6kZ6cumCAyfSxLrCeSOhQ6uk/edit?tab=t.0
Republished with Corey’s retrospective permission (please), per principle three of the Gav Ward Code (like Steve Jobs would have said) (Corey may well publish a further blog on this – a path is made by walking, as Franz Kafka said – so here are the initial draft findings :-
I asked o1 to expand on the few ideas I and about what 1000 AI climate scientists working at 1 million x human speed might accomplish.
OpenAIs o1 worked on it for 25 seconds.
Holy shit.
Below is a (much!) expanded view of what might be possible if we suddenly had 1,000 superintelligent, super-speed “AI climate scientists”—the equivalent of millions of human geniuses all working in concert. I’ve tried to group these ideas into broad domains and push them well beyond what’s currently on our radar. Many of these cross-fertilize, so imagine them overlapping in interesting ways:
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1. Energy Generation and Breakthrough Physics
1.1 Ultra-Efficient Solar
Self-Assembling Solar Materials: AI discovers how to program molecules or nanoparticles so that solar cells ‘grow’ themselves, leveraging principles like crystal growth or DNA origami. Yields can exceed current theoretical limits (the Shockley–Queisser limit) by harnessing multi-photon processes or exotic quantum effects.
Tandem Innovations: Ultra-thin perovskite layers combined with novel layers that harvest unused parts of the solar spectrum (infrared, UV, etc.). AI might optimize the stacking architecture at the atomic scale, pushing efficiency towards 80–90% in lab settings.
Solar Paints: Materials that can be sprayed onto surfaces—rooftops, cars, even roads—to generate electricity. Each “layer” is carefully tuned by AI to handle a different band of light. The end result: entire cities become low-cost solar farms.
1.2 Fusion (and Beyond?)
AI-Optimized Tokamaks: A thousand AI scientists iterating at a million times speed might unravel the instabilities (like turbulence in plasma flows) that plague fusion reactors, systematically engineering materials and feedback loops that maintain stable high-temperature plasmas.
Exotic Reactor Designs: Imagine magnetically-confined, laser-driven, or even muon-catalyzed fusion, each with different ways to overcome the Coulomb barrier. AI might find entirely new phenomena—akin to “micro black hole analogies” or topological states that allow us to fuse at much lower energies.
“Cousins to Fusion”: If we discover new states of matter or new ways to harness quantum vacuum energy, advanced AI might push us toward something that looks like “room-temperature” fusion or quantum-driven chemical bonds that release fusion-scale energy.
1.3 Space-Based Power
Orbiting Solar Platforms: AI solves the main hurdles—long-distance wireless energy transfer (think microwave or laser beaming), low-cost launches, ultra-light structural materials. We set up large solar arrays in orbit, beaming down cheap, constant power.
Lunar Resource Extraction: Mining Helium-3 on the Moon for advanced fusion reactors. AI might find better ways to extract, transport, and use Helium-3—especially if we can drastically cut launch costs.
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2. Energy Storage and Distribution
2.1 Next-Gen Batteries
Solid-State to Exotic: AI accelerates the discovery of new materials for solid-state batteries that don’t degrade, can charge in seconds, and hold 10–50 times current energy densities. Or it identifies stable lithium-air or lithium-sulfur chemistries with near-supercapacitor power output.
Self-Healing Electrodes: Tiny, AI-designed “nanobots” or molecular systems inside the battery that automatically repair microcracks or degrade contaminants to extend battery life nearly indefinitely.
Grid-Level Supercapacitors: High-capacity, nearly lossless capacitors that can handle massive surges and instantly provide the grid with gigawatt-level power.
2.2 Hydrogen and Synthetic Fuels
Sunlight-to-Hydrogen Efficiency: AI designs catalysts for direct photocatalytic water splitting at >50% efficiency, making green hydrogen extremely cheap and widely available.
Direct Air-to-Fuel: Carbon dioxide from the air plus renewable hydrogen is turned into drop-in synthetic hydrocarbons (liquid fuels) for aviation and shipping. AI ensures the process is cost-competitive with oil extraction.
2.3 Post-Grid Paradigms
Localized Energy Autonomy: Homes, buildings, neighborhoods generate, store, and trade energy in real time using AI-driven microgrids. The “macro” grid only balances large flows, while local nodes do the rest.
Energy Internet: Transparent, AI-managed digital marketplaces where any renewable energy producer can instantly sell to any consumer. Secure digital ledgers ensure minimal overhead and near-zero friction.
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3. Carbon Removal and Geoengineering
3.1 Direct Air Capture (DAC)
Molecular Filters: AI designs filters that selectively capture CO₂ at record efficiencies, requiring far less energy than today’s DAC. Some might be self-assembling or self-cleaning, drastically lowering operational cost.
Carbon-Transforming Organisms: Genetically engineered microbes that thrive in specific climates—deserts, open oceans, contaminated soils—and bind CO₂ into stable forms like carbonates or long-chain polymers.
Scalable Mineralization: AI finds new chemical routes to turn CO₂ into rock at scale, possibly using “living concrete” or advanced mineral-based capture. Instead of pumping CO₂ underground, we transform it into building materials.
3.2 Nature-Led Solutions
Synthetic Photosynthesis: Instead of waiting for trees, we harness nature’s best catalysts and artificially improve them, effectively creating “super algae” or “super phytoplankton” that fix carbon at 10–100 times normal rates.
Forest/Soil Restoration: AI-optimized reforestation that chooses the exact species mix, planting density, and microbial companions to maximize carbon drawdown and biodiversity. Robots or drones do the planting at massive scales.
3.3 “High-Risk” Geoengineering
Stratospheric Aerosol Management: If worst comes to worst, AI could help design extremely precise aerosol injections that reduce insolation just enough to buy time, without catastrophic side effects on weather patterns.
Cloud Brightening: Automated fleets of vessels that fine-tune marine cloud brightness to reflect sunlight. AI’s high-resolution climate models help us do this regionally, in real-time, with minimal ecological disruption.
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4. Climate Modeling and Forecasting
4.1 Real-Time Global Simulations
Hyper-Resolved Earth System Models: With near-infinite AI capacity, we can run Earth climate simulations at one-meter resolution in real time, factoring in every single forest, city block, ocean eddy, and atmospheric swirl. Policy decisions could be tested in silico before real-world implementation.
Integrated Prediction: Combine weather, climate, energy, agriculture, economics, and geopolitics into one big “Earth operating system.” We see the trade-offs instantly—for example, how a new carbon tax would affect deforestation, or how reforestation in the Amazon impacts fisheries.
4.2 Disaster Resilience
Advanced Early Warnings: AI-driven data from satellites, sensors, and social media to forecast and mitigate extreme weather events—floods, hurricanes, droughts—weeks or even months ahead with pinpoint precision.
Adaptive Infrastructure: Buildings and roads that shift, expand, contract, or reposition in response to real-time climate predictions (e.g., a coastal city with modular floating architecture to handle rising tides).
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5. Food and Agriculture
5.1 Precision Agriculture
AI-Engineered Crops: Drought-, pest-, salt-, and heat-resistant variants that maintain high yields with minimal water and fertilizers. CRISPR or advanced gene-editing guided by AI combinatorial searches.
Soil Microbiome Management: Smart microbial cocktails that fix nitrogen, break down toxins, and maintain nutrient-rich soils. Our farmland becomes self-sustaining without synthetic fertilizers.
Vertical and Bioreactor Farming: AI optimizes LED spectra, nutrient flow, and genetic lines for plants grown in stacked indoor farms. Maybe we see full city blocks turned into automated vertical forests that feed millions using minimal land and water.
5.2 Protein Alternatives
Lab-Grown Meats 2.0: AI tunes cell culture media, scaffolds, and processes for perfect texture, flavor, and nutrition. Meat production uses a fraction of the land and water, with negligible emissions.
Synthetic Dairy and Egg Proteins: Yeast or bacterial strains produce casein, albumin, or other proteins—no cows, no chickens, minimal methane. AI engineers them to be molecularly identical to natural ones.
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6. Water and Resource Management
6.1 Desalination Breakthroughs
Zero-Energy Osmosis: New membrane technologies with near-zero pressure requirements or that exploit natural salinity gradients in the ocean to generate power while producing fresh water.
Localized Nanotech Water Filters: Inexpensive, high-throughput nanoporous materials that remove pollutants and salt from water in a single pass. Entire municipalities can supply themselves with on-site micro-desal units.
6.2 Circular Economy for Water
Fully Closed Loops: Cities re-use 100% of wastewater, capturing not just water but nutrients and heat. AI automates the entire cycle, from sorting out contaminants to recirculating purified water back into the system.
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7. Materials Science and Manufacturing
7.1 Carbon-Negative Construction
Super-Concrete: AI develops binders that incorporate CO₂ directly into the curing process (e.g., magnesium-based cements or polymer cements) that sequester more carbon than they emit.
Graphene or CNT Construction: With cheap and abundant energy, we can mass-produce carbon nanotubes or graphene at scale. Ultra-strong, ultra-light materials that transform everything from wind turbines to skyscrapers, drastically reducing resource use.
7.2 Zero-Waste Manufacturing
Self-Assembling Consumer Goods: Using advanced computational chemistry, products can form layer-by-layer in specialized 3D “factories” with almost zero waste.
Molecular Recycling: AI-enabled catalysts break down plastics back into reusable monomers without energy-intensive processes. No more landfills—everything is feedstock for new materials.
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8. Governance, Economics, and Social Systems
8.1 AI-Enhanced Policy
Dynamic Carbon Markets: Real-time carbon pricing that factors in location, time-of-day, and upstream/downstream effects. Industries get immediate incentives to shift to cleaner processes.
Citizens’ Assemblies on Steroids: AI organizes and informs massive global assemblies where participants can run thousands of policy “what-if” scenarios, discovering surprising synergies or trade-offs.
8.2 Equitable Development
AI-Driven Global Finance: Automated climate finance that directs capital to climate hotspots in the Global South, invests in local green tech, and measures social outcomes in real time to ensure equity.
Universal “Climate Dividend”: If direct air capture and other technologies prove profitable, global carbon removal could fund a basic income for all, bridging inequalities and accelerating climate adaptation.
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9. High-Level (Speculative) “Frontiers”
9.1 Thermoregulation of Earth
If we produce 100x current global energy and cause warming from waste heat, we may simultaneously manage Earth’s “energy balance.” AI might design Earth-orbiting “heat mirrors” or advanced IR-laser systems that direct excess thermal radiation into space.
9.2 Biosphere Editing
Rewilding at Scale: AI orchestrates entire ecosystems, reintroducing keystone species (like wolves, beavers, apex predators) in a systematically balanced way. Large areas revert to healthy carbon sinks.
Terraforming “Edge Cases”: Maybe we even learn to terraform large desert areas or restore areas with severe biodiversity loss—basically “turning the Sahara green” in a stable, sustainable way.
9.3 Surprising Physics
With thousands of AIs iterating at insane speeds, we could discover new fundamental phenomena—like exotic quantum states or novel forms of energy generation—that shift the entire conversation beyond known science.
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10. The Central Takeaway
Ultimately, the single biggest shift is going from a few thousands of scientists working at human timescales to thousands of ultra-intelligent AI entities iterating millions of times faster. We can’t even begin to guess at all the solutions they might concoct—but we can be sure of a few things:
They’ll question all assumptions: Materials limitations, cost structures, known laws of physics—these might all be re-examined in the search for bigger leaps forward.
They’ll cross-pollinate: Insights from computational biology might solve chemistry bottlenecks, or breakthroughs in quantum computing might crack fusion turbulence.
They’ll scale solutions globally: Implementation at planetary scale becomes feasible if solutions are cheap, robust, and easy to replicate.
They’ll catalyze new social and economic systems: Because the technology alone isn’t enough—governance, equity, and policy innovations will be just as significant.
In short, if civilization can handle the transition responsibly, “thinking much bigger” is exactly right. We might find ourselves with climate solutions so profound and abundant that our concept of climate crisis flips from existential dread to a story of transformation—and it might happen faster than we think.
Cottrell’s Law
Based on all of this, Gav Ward has coined the term Cottrell’s Law which states that when 1,000 climate scientists work with ultra-intelligent AI, they can operate at the speed of a million human minds and can, therefore, unlock transformative solutions that transcend scientific, technological, and societal boundaries. This synergy redefines possibility, turning global crises into opportunities for rapid, scalable innovation and sustainable progress.
This is a working thesis and hypothesis and indeed the above is the first edition of this thinking so may well be open to change soon.
Undernote: Corey’s Cottrell’s Initial Ideas Before Scientific Discoveries
“We r headed home today. I’m gonna ease back in but this is a fun one to contemplate. Anything that doesn’t break the laws of physics. And maybe defined by new found laws of physics. 100x solar panel efficiency somehow? Fusion is so close. If/when they solve that it’s over for carbon. 👇
Corey Cottrell @coreycottrell.bsky.social
I mean completely over. Energy will become as cheap as information is now. We won’t think about it ever again. And every joule will be climate neutral except for the heat output which will begin to get interesting once we 100x humanities energy output. Which will happen. 👇
Corey Cottrell @coreycottrell.bsky.social
Even that will only be another interesting challenge. Maybe they’ll design infrared lasers to beam heat energy into space where orbiting platforms can use it for zero G manufacturing lol Then add 100 insane innovations in economics, governance, climate equity, food production, clean H2O 👇
Corey Cottrell @coreycottrell.bsky.social
I think the main thing I’d like to convey is that WE DONT KNOW. Our civilization has come amazingly far with a very few geniuses. We have no idea what millions of them working together could do. But we should all start thinking MUCH bigger. Because we r going to find out.”