2026-04-24 20:55:48
Hi friends 👋,
Happy Friday and welcome to our 190th Weekly Dose of Optimism!
Busy week: cures for cancer, autonomous everything, Sixers actually stole a win off the Celtics, lots of Extra Doses. No time to waste…
Let’s get to it.
Climate Tech is in a weird spot in 2026. The problems are getting bigger, but the money is getting tighter.
SVB’s latest Future of Climate Tech report shows a market that’s easy to misunderstand right now:
$29B was invested in Climate Tech last year, one of the biggest years ever… however, most of that funding went to a only a few companies
Government support is pulling back, making things slower and harder
52% of companies are cutting burn
The conversation is getting quieter. Mentions of climate on public company earnings calls are down 70%.
The market is cutting hype, forcing discipline, and rewarding the companies that actually build. Which is uncomfortable in the short-term, but probably exactly what the category needs long-term.
If you want a clear look at where Climate Tech actually stands in 2026, read SVB’s Future of Climate Tech report.
Kaitlin Sullivan, Marina Kopf and Anne Thompson for NBC News
Pancreatic cancer is often a death sentence. It kills about 87% of the people it’s diagnosed in within five years. Worse, it’s sometimes called the “silent killer” because symptoms don’t show up until very late, and by the time they do, only about 1 in 10 patients has a tumor that’s still operable. For the rest, there are no good options. And for a long time, oncologists thought the disease was biologically incapable of mounting a meaningful immune response at all. Pancreatic cancer was supposed to be the cancer that immunotherapy couldn’t touch.
This week at the AACR annual meeting in San Diego, Dr. Vinod Balachandran of Memorial Sloan Kettering presented six-year follow-up data from a Phase 1 trial of a personalized mRNA vaccine for pancreatic cancer that strongly suggests otherwise.
The trial enrolled 16 patients with early-stage, operable pancreatic cancer. After surgery, each got a custom-built mRNA vaccine (autogene cevumeran, developed by BioNTech and Genentech) alongside the checkpoint inhibitor atezolizumab and standard chemotherapy. Each patient’s tumor was shipped to BioNTech in Germany, sequenced to identify up to 20 mutations most likely to look foreign to the immune system, and then turned into a one-of-one vaccine that was shipped back to New York and infused into the patient.
Eight of the sixteen patients mounted a T-cell response to the vaccine. Six years out, seven of those eight responders are still alive (87.5%), versus two of the eight non-responders (25%). One of those seven — Donna Gustafson, who was the first person in the world to receive one of these vaccines in February 2020 — just hiked Mt. Etna for her 50th wedding anniversary. The immunologic data are equally encouraging: 85% of the T-cell clones primed by the vaccine persisted into memory phase, and the memory T cells were still functional even after chemotherapy, producing cytokines and attacking cancer cells on re-exposure to the original neoantigens.
Of course, there are caveats. This was a 16-person Phase 1. There was no randomization. Half the patients didn’t respond at all, and we don’t know why yet. Operable pancreatic cancer is already the most survivable version of the disease, and a subgroup of patients always lives longer than expected. Phase 2, now running globally under Genentech and BioNTech, will tell us a lot more.
With those out of the way, this is awesome, at the very least for these seven people and their families, and hopefully for a lot more. The belief for years has been that pancreatic tumors were an immune desert because it has too few mutations to flag and too dense a stromal wall to penetrate. This trial suggests the wall can be climbed, if you give the immune system the right map: a personalized neoantigen set, manufactured in weeks, and delivered as mRNA.
As Elliot wrote in Going Founder Mode on Cancer, personalized cancer therapeutics hold a ton of promise, and they’re both expensive and complicated for wide-scale usage today. That said, these are exactly the kind of thing that will get radically cheaper and faster to produce as the underlying biotech stack matures.
If this holds up at scale, it’s a twofer for our anti-cancer canon. One: pancreatic cancer is not immunologically untouchable. Two: the personalized mRNA playbook that Moderna/Merck have been running in melanoma is generalizable, and generalizing fast.
As we like to say here at the Dose: get fucked, cancer.
Speaking of two-fers… SpaceX basically purchasing a call option on Cursor for $10 billion is the kind of story we would have covered in the Dose anyway, and we get to throw in the first Kevin Kwok essay in nearly a year for free.
On Wednesday, SpaceX and Cursor announced that the newly combined SpaceX / xAI was basically buying a $10 billion option to buy Cursor later this year for $60 billion. SpaceX will most likely buy Cursor after its planned IPO for $60 billion. If it doesn’t, it will pay Cursor a $10 billion breakup fee / fee for the work they did together this year.
It sounds a little confusing, which is why I was so happy to see Kevin explain the deal, both from a deal mechanics perspective and the strategic perspective.
On the deal mechanics side, he expects to see more deals like this.
On the strategy side, the deal makes a lot of sense. Cursor has a great coding product and model, but not enough compute to compete with Anthropic and OpenAI. SpaceXAI is really good at building out compute, but pretty bad at making coding models. Put the two together, and you might have something that can compete with the leading labs in a use case that they all agree is incredibly important to win.
In short, the world’s greatest rocket company bought a product that can write code as it prepares to colonize the Moon and then Mars, obviously.
M&A. IPOs. Oh my. We are back.
Last week, we led the Dose with Quaise breaking ground on the world’s first commercial superhot geothermal plant. Superhot is a drilling problem, and Quaise is looking to solve it.
This week, the company doing the most to solve geothermal’s economics problem at commercial scale filed to go public. On Friday, Tim Latimer and Jack Norbeck’s Fervo Energy filed an S-1 with the SEC to list on Nasdaq under the ticker FRVO, with J.P. Morgan, BofA, RBC, and Barclays leading.
It’s great to see a new clean power generation source hit the public company milestone, with a real, traditional IPO and all, because it will hopefully mean more money for the space. But it’s also fun because it gives us a better look into what Fervo is up to.
Fervo is operating or developing 3.65 gigawatts of geothermal capacity, a number that, if fully built, would nearly double the total installed geothermal capacity in the United States. Its flagship Cape Station project in Beaver County, Utah, breaks ground to first power later this year; 500 MW is under construction at the site and Fervo has permits in hand for another 1.5 GW on the same piece of land. There’s also a 150 MW site in Nevada under a Google + NV Energy deal, targeting 2030.
The economics are even more interesting, because they give us a firmer sense of where geothermal sits today and where it’s headed. Fervo says Cape Station will deliver carbon-free 24/7 power at $7,000 per kilowatt of installed capacity, which is in the same ballpark as advanced nuclear. The company’s goal is to cut that to $3,000/kW, which would beat natural gas on an unsubsidized basis for always-on power. That would be a massive unlock.
Fervo is able to pull this off by bringing well-worn horizontal drilling and completion techniques over from shale (Latimer was a drilling engineer at BHP before founding Fervo in 2017) to geothermal.
To which we say, drill baby drill and let’s get this frackin’ thing public.
Ana-Maria Stanciuc for TheNextWeb
On Tuesday, a San Francisco startup called Humble came out of stealth with $24 million in seed funding and a design that is so obvious once you’ve seen it that it makes you wonder why no one had done this before. Basically, they got rid of the cab where human drivers sit, because these trucks won’t have human drivers.
Every existing autonomous trucking company, including Aurora, Kodiak, Waabi, and Einride, retrofits driverless tech onto a tractor-trailer architecture designed around a human sitting in front of a steering wheel. As founder Eyal Cohen put it, “Trucks were never designed to be autonomous.”
Humble built one that was. Remove the cab, and you get 360-degree sensor coverage, a significantly lighter vehicle, and a geometry you can optimize for intermodal containers. The Humble Hauler is built for 40- and 53-foot shipping containers and goes dock-to-dock, unloading at the destination rather than handing off to a human driver at a yard near city limits like Aurora does. Eclipse led the seed with participation from Energy Impact Partners.
Cohen, Humble’s CEO, has been on this problem for a while, and on hardware even longer. He previously worked at Apple, Uber ATG, and Waabi, and co-founded Spark AI (acquired by John Deere in 2023). That experience helped him get to a prototype in under 6 months.
This is an idea that keeps popping up as we talk about autonomy: when you design around the actual constraint instead of the inherited one, you end up with a different machine. Kalanick’s Atoms is explicitly anti-humanoid because most jobs want wheels, not legs. Tesla’s Cybercab has no steering wheel, because they won’t have human drivers. Humble is making an analogous bet with trucks.
Better, faster, cheaper. Ship it.
for & Michelle Lee on X
Here in the Dose, we’ve written a lot about the software side of the AI-for-bio boom: IsoDDE can suggest drug candidates against previously undruggable pockets, Evo 2 can design entirely new genomes, Boltz and AlphaFold have collapsed structure prediction, and Chai is cranking out antibody candidates at a pace that would have sounded insane five years ago. It’s all fantastic and futuristic.
Having said that… a designed molecule is not a validated molecule. Every one of those candidates still has to be synthesized and tested by a physical lab staffed by physical humans who have to sleep and take weekends. Or, I guess that’s an assumption, certainly these candidates need to be synthesized and tested in a physical lab, but…
This morning, Michelle Lee’s company, Medra, formally opened the doors on a 38,000 square foot warehouse in San Francisco where roughly a hundred robotic arms are running biology experiments simultaneously, 24/7, linked by a small courier robot that ferries pipette tips and sealed plates between stations like an extremely focused junior scientist. A pair of scientists could run maybe a dozen antibody-binding experiments in a day. Medra’s arms run hundreds at a time, don’t clock out, and get better at it every week. We love a good robot arm.
Lab automation has been overpromised for two decades. What’s different about Medra is that it doesn’t require the lab to buy new robot-native instruments. Only about 5% of bench equipment in biology has APIs that legacy automation can plug into; the other 95% (centrifuges you open by hand, pipettes you tilt and time, etc…) was built for humans. Medra’s robots use computer vision and manipulation models to operate the same instruments a human would. Lee says the combination can push the share of bio-tech tasks that can be automated from 5% to 75%.
There’s a second layer on top of the hardware that is maybe even more interesting. Every arm and bench is instrumented with cameras and nine kinds of sensors, so the system logs the exact pipette angle, the exact depth of insertion, the exact timing between reagent additions. The AI scientist on top reads the results, proposes protocol changes, and rewrites the protocol itself. Lee describes one customer whose antibodies weren’t binding at all (the readout came back at zero); the AI scientist narrowed the cause to two hypotheses, proposed adding a vortexing step, and watched binding jump to over 70%.
Lee’s frame for what she’s building is TSMC for biology. TSMC is what makes it possible for chip designers to exist without owning a fab. Medra wants to be what makes it possible for drug discovery companies to run experiments without owning a wet lab.
Just yesterday, in The Great Blue Frontier, Will and I wrote that AI for bio is data-limited, and suggested the 91% of sea creatures we’ve yet to discover as one source. Madra is another. Lee believes that with more throughput, we “cure cancer, Alzheimer’s, infectious disease.” This, she thinks, is also how we keep American bio competitive with China by speeding ourselves up.
All sounds great. Get to work, robots.
2026-04-23 20:59:00
Welcome to the 2,250 newly Not Boring people who have joined us since our last essay! Join 263,454 smart, curious folks by subscribing here:
Hi friends 👋 ,
Growing up, I sailed a little sailboat called a Sunfish. I was OK, not great, which is a shame, because had I been a little more competitive, I would have raced against the next town over, whose team included a young Taylor Swift.
When I turned 16, I became a beach lifeguard, which is pretty much the greatest job ever for a 16-year-old, and I held onto it for the next four summers. I wasn’t a great swimmer or a great rower, but I was a good enough runner to make up for it so they kept me around. Over those summers, I fell in love with Wes Anderson’s The Life Aquatic with Steve Zissou, which was based, red knit cap and all, on the life of Jacques Cousteau.
All of which is to say, while I spent a lot of time by the ocean, I had a tourist’s relationship with it. I enjoyed it, swam in it, sailed in it, and then went back to the real world, where classes and eventually a real economy awaited.
This, Will O’Brien argues, is how we’ve all handled the ocean until now. We come, we explore or exploit, and we get back to dry land. This, Will thinks, is no longer how we will handle the ocean. With Ulysses, The Ocean Company of which he is co-founder and President, Will plans to help build the infrastructure that would allow us to treat the ocean as a permanent fixture of the economy, and potentially even as a new home for humanity. The way our grandparents and JFK thought we would.
Since meeting Will two and a half years ago, he’s become one of my favorite people in tech to talk to about everything from Irish omnipresence to religion to aliens to vertical integration. I’ve been asking him to put his gift of gab to paper with me for a while, and now that the company has successfully raised $46M from a group of investors led by a16z American Dynamism, he finally had the time to oblige.
Note: not boring capital is not an investor in Ulysses, but I am a huge fan.
In this co-written essay, Will tells a history of the future of the ocean that I’d never heard, before making the case that the ocean is the last great frontier and one of the greatest economic opportunities available to humanity. It’s an adventure, and in the words of Steve Zissou, “Anyone who wants to tag along is more than welcome.”
So throw on the most underrated soundtrack of the 2000s…
And let’s get to it.
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With Ulysses President Will O’Brien
At 4 AM on February 17, 1969, Berry Cannon was lowered 610 feet below the surface of the Pacific in a steel personnel transfer capsule to make repairs to the Navy’s “yellow submarine,” Sealab 3. At that depth, normal air becomes toxic to humans and the nitrogen can send you delirious, so Cannon was breathing helium instead. Helium keeps your mind clear, which was helpful for Cannon. He had been awake for twenty straight hours. Unfortunately, helium also strips heat from your body six times faster than air does. This was a problem. That particular morning, the capsule’s heater was broken.
No matter. Cannon, one of history’s greatest maritime frontiersmen, was running on amphetamines and conviction. When the capsule reached the seafloor, he dropped through the hatch into open water and began swimming through pitch darkness toward a leaking underwater habitat. This habitat, the U.S. Navy believed, would be humanity’s first permanent foothold on the ocean floor.
It was a routine fix as far as deep sea habitat fixes go. Except for one fact: Cannon’s rebreather’s CO₂ scrubber canister was empty of Baralyme. He didn’t know that. Nobody did. On a TV monitor topside, Captain George Bond watched Cannon swim gracefully—and then he watched Cannon’s body suddenly jackknife.
“Any time you see rapid motion in a diver,” Bond would say later, “you know he’s in trouble.”
Berry Cannon was dead. And with him died America’s plans to conquer the ocean.
Five months later, Neil Armstrong walked on the Moon, fulfilling one of JFK’s most ambitious promises. It’s been over half a century, and we all know Neil Armstrong’s name.
But nobody remembers the man who died trying to live on the seafloor. Nor do we remember the ocean dream he represented.
I grew up in County Cork, on the south coast of Ireland, and spent every summer at Garrettstown jumping off the pier or the cliffs, bodyboarding and pulling crabs out of rock pools, or heading out in the boat with my dad to catch mackerel. I loved the ocean the way you love something before you understand it. The textures, the cold, the endlessness of it. As a kid, I loved explorers too. Steve Irwin, especially. He wasn’t an ocean guy, but he had that renegade explorer energy, that willingness to just get in there and figure it out. I think I always assumed someone was figuring the ocean out, that there was a Steve Irwin of the Deep. That someone was down there, mapping it, understanding it, and protecting it.
As I got older, I realized nobody was.
So I’ve made the oceans my life’s work. In just the past few months, my office has rotated between Washington D.C., San Francisco, Los Angeles, London, Western Australia, Maine, Virginia, Florida, New Orleans, and San Diego. I would do this for free; I might even pay to do it. But as I’ve been living out my childhood dream, I’ve found that the ocean economy is something like a sunken treasure that’s been waiting on the bottom of the sea for anyone intrepid enough to go grab it.
Today, I’m going to let you in on the secret I’ve discovered down there: Earth’s largest domain and last great frontier is also its grandest economic opportunity.
In the 1960s, America was a country dreaming at full volume. You could taste optimism in the air — and in the sea.
Most of us alive today never learned how important ocean exploration was to the future our grandparents imagined. Americans were fantasizing about ocean exploration in the same way they were about going to the Moon. They were as captivated by The Great Blue Frontier as they were by the Space Race.
At the 1964 New York World’s Fair, GM’s Futurama II ride carried more than 26 million visitors past a vision of the near future. Alongside the lunar base and the Antarctic weather station, guests saw ocean-floor oil rigs, submarine trains hauling minerals to shore, and Hotel Atlantis, a sub-oceanic resort around which vacationers explored in various personal oxygenated craft.
The ocean stood right beside the Moon in the American imagination, and it promised just as much: food and living space for a rapidly growing country, minerals and energy for a booming industry, and the upper hand in the Cold War.
President John F. Kennedy saw the problem clearly. “We know less of the oceans at our feet, where we came from, than we do of the sky above our heads,” he told the National Academy of Sciences in 1963.
His administration had been trying to close that gap from the start. In a March 1961 letter to Congress, he called for “a national effort in oceanography,” warning that “knowledge of the oceans is more than a matter of curiosity — our very survival may hinge upon it.” Kennedy’s FY1962 budget request nearly doubled federal oceanography spending, funded ten new research vessels, and expanded shore facilities fivefold. Two years later, he sent Congress a ten-year, $2 billion plan called Oceanography: Science for Survival, and directed the Navy to begin SEALAB — an underwater habitat program explicitly conceived as the ocean floor’s answer to the Space Race.
President Kennedy placed the ocean alongside space as the twin frontiers of American ambition and coequal national priorities, and his ambition was matched by action.
While Kennedy persuaded Americans about the ocean’s importance as a governmental priority, French naval officer, explorer, and filmmaker Jacques Cousteau charmed them in their living rooms.
Cousteau had co-invented the modern scuba regulator and was one of the most famous people in the world. He built Conshelf, a series of underwater habitats where teams of divers lived for weeks at a time on the seabed. Conshelf II, built in the Red Sea in 1963, was essentially an underwater village: a starfish-shaped structure at a depth of 33 feet with bedrooms, a kitchen, hot showers, and a television.
A parrot named Claude served as the carbon dioxide detector. If Claude fell off his perch, the air was bad. You couldn’t whistle because of the helium. Matches wouldn’t light, although the crew still managed to light cigarettes. Sparkling wine went flat under pressure. Fried food was forbidden because greasy fumes couldn’t be scrubbed from the air.
The documentary about this village, World Without Sun, won the Academy Award. The Undersea World of Jacques Cousteau ran on prime-time American television from 1966 to 1976. The ocean was mainstream culture, Academy Award-winning cinema, and prime-time television. It had become a fixture of the popular imagination.
Simultaneously, the U.S. Navy was building permanent undersea infrastructure with the same seriousness that the Army had when it built forts across the American West. Its program, SEALAB, consisted of three progressively deeper underwater habitats that were designed to prove that humans could live and work on the ocean floor for extended periods. We were going to settle the ocean. On SEALAB II, astronaut Scott Carpenter, one of the original Mercury Seven, spent 30 consecutive days underwater, becoming the only astronaut-aquanaut in history.
By the late 1960s, more than 60 underwater habitats dotted the world’s seabeds: Hydrolab, Helgoland, Tektite, Aquabulle, Hippocampe, dozens more.
Kids wanted to be aquanauts the way they wanted to be astronauts. The ocean was a national obsession on par with the Moon.
Then, in roughly five years, it all died.
SEALAB was suspended immediately after Cannon’s death. The Navy, which could invest in the future during peacetime, was pulled into the Vietnam War. Even Jacques Cousteau, the man who had done more than anyone alive to prove humans could live underwater, the man who had unmatched cultural authority on anything to do with the ocean, pivoted from exploration to activism. He founded the Cousteau Society in 1973 to protect and preserve the oceans instead of exploring and settling them.
By the 1992 Rio Earth Summit, he was dubbed “Captain Planet.” America, in some sense, always followed Cousteau’s lead on the ocean. When he explored, we wanted to explore. When he said “protect,” oceanic policy and funding priorities fell in line. The regulations that followed, including the Marine Mammal Protection Act, UNCLOS, the IWC whaling moratorium, and the High Seas Treaty, were individually important protections, responding to real ecological crises that demanded our attention. But their cumulative effect, compounded by Cousteau’s cultural reframing, led to a collective shift in how we considered the ocean as a domain to build in. Within a generation, any proposal for persistent ocean activity faced a default presumption of harm.
In the 1960s, America set its sights on two frontiers. By the 2010s, we had all but stagnated on those hopes. We landed on the Moon, went back a few times, and then decided to keep our eyes on the ground. We gave up on settling the ocean altogether.
But we are going back to the Moon, this time to settle it. Just this month, the Artemis II astronauts orbited the Moon for the first time since 1972 in an important step towards settlement. NASA Administrator Jared Isaacman has laid out a plan to begin building a permanent base in 2028, a mission made possible by progress in the commercial space sector over the past two decades. We are going to be an interplanetary species! The Moon should be a state, experts are saying.
It’s time that we settle the ocean too.
This forgotten frontier is no less economically or geopolitically important than space; in fact, it is both larger and more urgently strategic. Through our forgetfulness, the ocean has become a wild and lawless domain whose potential to benefit humanity lies dormant, one which is being abused by those who care nothing for protection or preservation.
In 2015, a wooden fishing boat washed ashore on the coast of Japan carrying the skeletal remains of its crew. Then another arrived. And another. Over the next several years, hundreds of these “ghost boats” drifted onto Japanese beaches, small wooden vessels with many carrying only bones and tattered North Korean flags.
Investigators eventually pieced together the story, which turned out to be more tragic than supernatural. 900 Chinese distant-water fishing vessels had moved into North Korean waters in violation of UN sanctions (sanctions that China itself had signed and ignored), strip-fishing the stocks and pushing local fishermen further and further offshore in boats not built to take on the open ocean. Those fishermen starved at sea, and their boats drifted east until Japan’s coastline caught them. Nobody stopped the Chinese fleet, and nobody rescued the fishermen, because there was nobody out there to stop or rescue.
A 2024 study in Nature found that three out of four industrial fishing vessels are invisible to public tracking, which is wild in a modern society that tracks everything.
Consider the pandemonium that broke out when MH370 went missing, because planes, unlike fishing vessels, don’t just go missing. Last weekend, I spoke with a man who was in a terrible car accident on a Canadian highway in 1994; his right leg and hip were crushed, but he lived because a helicopter arrived to whisk him to the hospital within five minutes. In the air and on land, we track our people and our critical assets with stunning accuracy.
But the ocean doesn’t operate like that, in large part because we don’t have the infrastructure to make monitoring possible. So we’ve kind of given up. Two-thirds of the ocean falls outside any country’s jurisdiction, and there is no police force or coast guard with global reach. There is a reason that so many ocean movies involve protagonists lost at sea, hoping that someone chances upon them.
As a result, we often find boats doing bad things, too late. Fleets of hundreds of Chinese vessels have been caught operating illegally off the coast of Ecuador, right at the edge of the Galápagos Marine Reserve, one of the most ecologically sensitive places on Earth. In 2017, Ecuador intercepted a single vessel, the Fu Yuan Lu Leng 999, which was carrying 6,000 sharks, many of them endangered species, fished from Galápagos waters. Workers on distant-water fishing vessels are held for years, passports confiscated, in conditions that meet every definition of slavery.
There is no way of knowing how many illegal vessels go undetected, because so much of the ocean remains unmonitored, and we have less of a clue the further beneath the surface we go. While humanity has mapped 100% of the surface of Mars, a planet with no known life 140 million miles and seven months (if you time it just right) away, we have mapped only 27% of the ocean floor with modern sonar, and much of that is coarse, low resolution.
“If you just look at the size of the ocean,” Bob Lazar (yes, that Bob Lazar) recently told Jesse Michels, “you can hide an entire civilization down there. Especially if they’re immune to the effect of the ocean. You just gotta be deep. We’ll never find ‘em.”
While we can neither confirm nor deny the existence of subsea civilizations (except for maybe Atlantis), the fact is there is certainly enough space and little enough visibility to get away with it. The ocean is unfathomably large, and we haven’t even begun to fathom what’s happening all those fathoms below.
This, as President Kennedy warned in 1963, is more than a matter of curiosity. Our survival, or at least our flourishing, may hinge upon it.
Sixty-three years later, we have failed to heed his words, and to capitalize on the opportunity. The ocean covers 70% of our planet, carries 99% of our internet traffic and 80% of our trade. It contains more critical minerals than all known land reserves. And we still know critically little about any of it.
A full 91% of ocean species remain unknown to science. When researchers sequence DNA from deep-sea sediments, they can’t match it to any known organism by species or taxonomic group. The largest library of biological information on earth is functionally unread. Chances are, that library contains a well-stocked pharmacy.
Marine organisms have already given us Ziconotide (a painkiller 1,000x more potent than morphine, from cone snail venom) and Trabectedin (a cancer drug, from a sea squirt). The alien-looking jellyfish Aequorea victoria provided researchers with the green fluorescent protein (GFP) that won them the 2008 Nobel Prize in Chemistry, which now “enables scientists to track, amongst other things, how cancer tumours form new blood vessels, how Alzheimer’s disease kills brain neurons and how HIV infected cells produce new viruses.”
Presumably, there is more where that came from inside the other 91% of sea creatures we have yet to discover. If AI for bio is data-limited, we have a library full of it in the ocean.
There is much for a knowledge-loving people to discover down below, so… let’s just go find out what else is down there. Let’s send people and instruments and start intervening.
Alas, there is nothing to intervene with, because we never built anything that could intervene, and little more to listen with, because we let our ears rot.
Back in the 1950s, back when the nation had aquatic ambitions and a Cold War foe against which to sharpen them, the US Navy built a classified network of undersea hydrophone arrays called the Sound Surveillance System, or SOSUS. By exploiting the deep sound channel, or SOFAR channel, SOSUS could track Soviet submarines across enormous swaths of the Pacific and Atlantic Oceans. Individual listening stations could pick up a submarine across entire ocean basins thousands of miles away.
Turns out, SOSUS could track whales, too. When it was partially declassified in the 1990s, marine biologists realized the Navy had been accidentally collecting the richest dataset on ocean biology ever assembled. They’d captured volcanic eruptions, seismic events, whalesong, species migrations, and, in 1997, the “Bloop,” a mysterious sound that has still not been fully explained…
But the Cold War ended in the ‘90s, and by then, our ocean dreams were already long dead. The US government declassified SOSUS, celebrated its scientific contributions, then cut its funding. Some assets were folded into another program, IUSS, a bunch of the hydrophone arrays were put into standby status, and stations at places like Bermuda, Adak, and Keflavik were shut down.
Today, our greatest effort at ocean observation is a network of 4,000 robotic floats called Argo, the 27-year-old “crown jewel of ocean observing systems.” Each of the 4,000 floats monitors an area larger than Portugal, surfacing once every ten days to transmit a single temperature reading. They are deployed like this…
Or, like this...
The entire program is tax payer-funded. And despite running on just six cents per American per year, those 4,000 floats now generate more subsurface ocean data every month than the entire rest of the observing network combined. Argo is great, but that is much more an indictment of the state of our ocean awareness than a celebration of the system.
Plus, Argo can only observe, just like SOSUS could only listen. If a float detects a chemical anomaly, a biological collapse, or a dangerous trend, there is nothing and no one for miles around to respond, in much the same way a thermometer can tell you that you have a temperature but can’t do a damn thing about it.
The question is, in a time of technological wonder, why the ocean remains dark.
Frontiers are tamed when there’s money to be made from taming them and the technology to tame them is viable.
President Thomas Jefferson sent Lewis and Clark west to wrest the fur trade from the Canadians and establish commercial routes. The Forty-Niners went to find gold. These were risky and potentially highly profitable expeditions, and when they paid off, America built the railroad to connect the West with civilization.
The railroad meant that normal people, not just bold or desperate explorers, could establish their homes, families, and businesses in the West, and it made new industries possible: ranching, mining, commercial agriculture, towns, and cities. The railroad industrialized the Western Front.
Something similar happened in space, a domain accessible only to national governments and a handful of intrepid telecommunications pioneers in search of vast riches before SpaceX collapsed launch costs. Before SpaceX, the biggest satellite constellations were measured in dozens. Today, SpaceX has more than 10,000 Starlinks in orbit; people make fun of Jeff Bezos for flying “only” a couple hundred satellites.
Reusable rockets are the space railroad, and on them fly hundreds of businesses seeking to get to space and stay. SpaceX industrialized space, and the effects of that industrialization are just beginning to be felt.
For all of the exploration and trade we’ve done out there, the ocean has never had this moment. We’ve fished it, laid cables across its floor, drilled rigs into it, plopped wind turbines in it, raced around the globe on it, and shipped goods across it, but nobody has ever cracked the economics of operating within it, broadly and persistently, as a domain. The ocean still runs on an 1800s-era expedition model that puts expensive humans on expensive ships for expensive campaigns, then brings them back to dry land.
There’s a word for a frontier that hasn’t had this moment yet. The ocean is pre-industrial.
To industrialize a frontier means to transform it from a place with industries in it, exploring and opportunistically extracting, to a place built to support industries persistently and economically, at scale.
An industrialized frontier is a platform, not a series of projects. Each new piece of infrastructure makes the next one cheaper and unlocks activities that weren’t possible before. An industrialized frontier compounds.
The railroad industrialized the West and SpaceX is doing the same for space. Nobody has industrialized the ocean yet.
If we want to gain dominion over Earth’s oceans and steward them properly, we need to make it a place where industry can thrive.
Creating more industry in the ocean would decrease crime, increase our understanding of our home planet, accelerate scientific discovery, grow existing maritime industries and enable new ones altogether, unlock resources that are literally sitting on the floor, and, counterintuitively, incentivize our stewardship of it.
Industrialization has dirty connotations. As you read the word, you might be picturing smokestacks, or worse, the soot-darkened faces of pre-pubescent factory workers.
I’d argue that the industrialization of new frontiers has been one of the most powerful engines of human progress. So I want to tell you how I think about industrializing the ocean while protecting it, because a desire to protect it, to restore it, is where I began this journey.
When we started Ulysses, we set out to help restore the oceans by using underwater robots to replant seagrass more efficiently. Seagrass meadows cover less than 0.2% of the ocean floor but store up to 18% of the ocean’s carbon, support roughly a fifth of the world’s fisheries, and have been declining at about 7% a year since the 1990s. This means we’ve lost roughly a third of all seagrass globally in the past few decades. Restoring these meadows is an important part of bringing back the vitality of the oceans.
That work is underway in Florida, Virginia, Western Australia, and in the Great Barrier Reef. As we waded into the ocean, however, we realized a few things.
First, we realized that the infrastructure we’d need to do restoration well didn’t exist. We’d have to vertically integrate and build most of it ourselves. Soon, we realized that the infrastructure we had to build was exactly what everyone else working in the ocean needed too. We’ll talk about that below.
Second, there are big differences between 19th-century industrialization and modern oceanic industrialization, the biggest of which is the difference between combustion and electric machines. Unlike those factories, or even modern oceanfaring vessels, our vehicles won’t emit smoke or smog. They run on electrons and don’t emit exhaust or greenhouse gases during operation. We will discuss this, too.
Third, we realized that when we expanded our economic ambitions, we also increased our environmental ones. I’ve just shown you what a pre-industrial ocean looks like. There is slavery, overfishing, the extinction of entire species, and ignorance of endless pots of gold. A pre-industrial ocean doesn’t mean an untouched ocean; it just means that the pirates are the ones doing the touching. Commerce brings law and order, if only selfishly, but that law and order has positive externalities. You are far less likely to be murdered in a Western Saloon today than you would have been in 1826. We believe that by industrializing the ocean, we are incentivizing its protection and restoration.
The ocean is too precious to leave to the pirates.
So if we want to industrialize the ocean, how do we do it? There seem to be four stages that frontiers go through on the path to industrialization.
Discovery → Expedition → Access Breakthrough → Industrialization
Discovery proves the frontier is real and reachable. Expedition explores it, maps it, and finds the resources worth pursuing, but it does so episodically and expensively (or illegally). The fruits of expedition incentivize the development of the access breakthrough: a technology that dramatically collapses the cost of reaching and operating at the frontier, making entirely new categories of economic activity viable for the first time. That triggers industrialization: the frontier integrates into the broader economy, and industries emerge that couldn’t have existed at the old cost structure.
The American West went through all four stages. The early explorers proved it was there. For sixty years, wagon trains, fur traders, and the Oregon Trail explored it episodically. Then, in 1869, the Transcontinental Railroad met at Promontory Summit, Utah, collapsing the cost of access, and what followed was the industrialization of half a continent. The Homestead Act alone distributed 270 million acres, an area larger than France, Germany, Italy, and Spain combined. Western mines produced the copper that wired America’s cities, the gold and silver that backed its currency, and the timber and beef that fed its industrial workforce. Over the century that followed, the frontier compounded into trillions of dollars of real economic value and provided the physical substrate of the American century.
Space has followed the same arc. Sputnik proved it was reachable. Apollo and the Shuttle explored it at $1.5 billion per launch. Then SpaceX spotted that rocket materials cost about 2% of the selling price, vertically integrated them, built reusable boosters, and cut costs 20x. The space economy has tripled over the past two decades, reaching $613 billion in 2024, and is projected to hit $1.8 trillion by 2035.
Both of these examples are gross oversimplifications, but what I want to establish is that there is economic activity on the frontier even before industrialization. Risk-seekers are captivated by the promise of the untamed. But true market creation occurs when early economic activity incentivizes and funds access infrastructure, and access infrastructure facilitates normal business creation. Industrialization moves frontiers from limited, risky, low-volume, potentially high ROI trades to higher volume, safer, lower-individual-ROI but higher-overall-output activities.
Today, the ocean’s pre-industrial economy is already enormous. We spend $2.6 trillion a year across shipping, offshore oil, fishing, subsea cables, and coastal ports. That is an order of magnitude larger than the space economy was when SpaceX was founded.
But the economics of the ocean severely limit where we can operate, and therefore the size of the ocean economy.
We ship across the surface because the surface is the cheapest layer to traverse, and the only one where our GPS and WiFi work. We drill oil from expensive fixed platforms because oil is valuable enough to pay for the helicopters and the two-week crew rotations. We fish from the top of the water column because that is where our tools reach, and as a result, we decimate the stock.
In short, we are limited to the easiest-to-access parts of the ocean, unless an extremely valuable and fairly predictable commodity can justify deeper exploration, just as the fur trade did during America’s westward expansion.
To the extent that we can decrease the cost of access, we can increase the size of the ocean economy. We need the ocean’s railroad. It is surprising that, if $150 billion of activity was enough to trigger a railroad for space, $2.6 trillion of pre-industrial economic activity didn’t trigger one for the ocean long ago.
Why have we not built the ocean’s railroad?
Two factors must be simultaneously present for industrialization to occur: suitable technology and urgent demand.
Humans have had boats for a very long time. As early as 3000 BC, the Austronesian people migrated throughout the islands of the Indo-Pacific using sailboats like this one.
But the ocean has never made traversing its surface easy. During the Age of Sail, an estimated 3-5% of merchant fleet ships were lost per year. Rather than being retired, most wooden ships ended their careers by being wrecked, foundering, or being lost at sea. Over time, we got better at making sturdier boats. But even still, the 1990s’ most popular movie was about the sinking of the “Great Unsinkable” Titanic.
Stewart Brand recently published Maintenance with Stripe Press. He chose to open the book with the story of the 1968 Golden Globe Race, the first solo, non-stop circumnavigation of the earth by sailboat. The race’s sponsor, The Sunday Times, charged no entry fee and laid down almost no rules. Sailors simply had to leave from a British port, travel around the globe, and come back to it without stopping.
Nine sailors entered the race, and historians mainly focus on three of them.
Donald Crowhurst, a brilliant inventor with arguably the most technologically advanced boat in the race, never made it past the Atlantic. His electronics failed, his hull leaked, and the isolation broke him. He falsified his logbook, drifted in circles, and eventually stepped off the back of his trimaran into the sea. His body was never found.
Bernard Moitessier, the most gifted sailor in the fleet, abandoned the race despite being far in the lead. Months alone in the Southern Ocean convinced him he’d rather keep sailing to Tahiti than return to civilization.
Robin Knox-Johnston spent 312 days at sea, and most of them were spent not sailing but repairing. Where the others designed their sailboats for technological superiority or speed, Knox-Johnston designed his to be fixed:
To prepare SUHAILI for a ten-month passage, most of it in the world’s roughest waters, he packed into his small boat all the ‘materials and tools’ he could imagine he might need – specialized wrenches for every exotic nut on the boat; ditto for screwdrivers; a sailmaker’s bag full of needles, sewing palms, and twine; a bosun’s bag with every kind of shackle, thimble, and marlinspike for managing all his steel wire rope; a spare bilge pump and extra rubber pipe; 12 yards of canvas; caulking chisels and cotton; plenty of oil, glue, and Stockholm tar; spare parts for everything mechanical; and medical supplies for repairing himself.
It was the right move, because he spent most of his 312 days on the water fixing. And yet… “I realized I was thoroughly enjoying myself,” he said later. Still, the enjoyment was the enjoyment of a man who understands that the ocean is in a permanent state of war with anything humans put in it.
Knox-Johnston won the race, “and the prize of £5,000 – which he gifted to Donald Crowhurst’s bereaved wife and young children.”
Typically, the story is told as a story of different flavors of the human spirit, and it is certainly about that. But Brand chooses to tell it as a story about maintenance. The universe tends towards entropy, but it does so particularly quickly on the open sea. There is no environment on earth that so persistently attacks those who dare challenge it.
Which is to say that the ocean is the hardest frontier on Earth. It fights you every day that you’re in it. The ocean doesn’t necessarily want to fight you. It is simply a matter of the ocean’s constitution.
Saltwater is one of the most corrosive environments on earth, eating through steel, degrading composites, and attacking every electronic component it reaches. Since water flows happily through cracks, it ultimately reaches almost everything. The North Sea, one of the most developed ocean regions on Earth, is so punishing that corrosion alone accounts for roughly 60% of maintenance costs on production platforms, and lifetime operating spend routinely exceeds the original construction cost. Offshore wind has struggled to meet expectations because maintenance costs 2-3x more than onshore wind, components break down more frequently, and turbine performance degrades by an average of 4.5% per year. The global cost of marine corrosion runs to $50 to $80 billion a year, and that’s just for the structures we’ve bothered to build.
Then there’s biofouling (think barnacles): the moment you put something in the water, organisms begin to colonize it. Within weeks, without active maintenance, a clean sensor is blind, and a clean hull is dragging tons of extra weight. The offshore oil industry spends billions per year fighting exactly this. Everyone who chooses to operate on the ocean must become a Robin Knox-Johnston.
Below the surface, the battle only intensifies. Pressure increases by one atmosphere every ten meters of depth. At the average seafloor, you’re looking at 370 atmospheres. Everything on a subsea vessel must be engineered for forces that have no analog on land or in space, and which vary continuously with depth. Space is extreme, but the vacuum is a single, well-understood engineering problem. In the ocean, every meter deeper you go changes the engineering envelope.
We have thus far described fair weather conditions, but the ocean is a stormy place. Storms routinely destroy purpose-built infrastructure: Hurricanes Katrina and Rita alone destroyed 113 offshore platforms and ruptured 457 pipelines.
In each one of these cases, unless you are right there with your vessel, you’re unlikely to even know when things go wrong, because the ocean is a communications desert. GPS doesn’t work underwater at all. Radio and optical signals penetrate about 20 meters before the water absorbs them. Acoustic signals can travel further, kilometers in some cases, but at painfully low bandwidth, about a million times slower than surface 5G. To get around these constraints, you can tether a vehicle to a surface ship with a cable, but that limits your range and requires an expensive crewed vessel overhead, at which point, you’re still stuck in the expedition model.
The ocean is a domain that degrades everything you put in it, crushes anything you send deep, destroys what you bolt to the surface, and isolates whatever survives.
This is before we even address the immense scale of the ocean. So even if you solve every engineering problem, you still face the question of how to cover a domain that dwarfs anything we’ve ever tried to operate in while fighting corrosion, biofouling, pressure, storms, and the comms desert. None of these is impossible to overcome, but every one of them is a tax. A tax currently paid in steel thickness, redundant systems, $20,000/day ship time, mobilisation windows, insurance premiums, and in the engineers you have to send offshore to fix what can’t be fixed from shore.
And on top of that, the industry that grew up around this domain never got what aerospace and automotive got: scale, software, modern supply chains. Maritime is still largely a cottage business of bespoke parts and hand-built systems. So you pay the tax twice: once to the physics, and again to the pre-modern industry that evolved to serve the physics.
We call it the Ocean Tax: the compounding cost the sea, and the industry that grew around it, extracts from anyone who tries to do anything in it. Every existing ocean company is, at heart, a machine for paying the Ocean Tax.
So the natural question is, how do we get around it?
The good news about the ocean being such a challenging environment is that every problem that the ocean throws at you doubles as a design requirement. If we solve for the challenges, we know what kind of system to build.
The ocean is vast. Instead of a few expensive, exquisite vessels, you need a lot of cheap ones.
This is the same trend that we’ve seen in space, going from a few billion-dollar communications satellites to thousands of small, cheap ones. The latter means that the network can cover more area more reliably than single satellites can, and inevitable damage to a single satellite doesn’t knock it out. It is resilient. We are seeing the same trend in defense, with the move towards high-volume, attritable drones instead of a few exquisite platforms.
Like space, it is hard to comprehend just how much room there is to cover in the ocean. The 361 million square surface kilometer number hides just how big it is, because it also goes deep. Industrialization requires coverage of the X, Y, and Z axes. The ocean is more than two miles deep, on average, and its deepest trenches are so deep that Mount Everest could be dropped into the Challenger Deep with 2km of clearance above it. Its total volume is something like 1.3 billion cubic kilometers, which is so large that I’m not even sure what to tell you, other than to say that the number of vehicles we put in it each year stands absolutely no chance.
Today, the entire global autonomous underwater vehicle (AUV) market produces roughly 1,000 vehicles per year, and the incumbents’ AUVs cost on average $500k to $5 million each. For scale, a thousand units across the entire ocean is equivalent to just 27 vehicles across the entire United States. Imagine trying to patrol the entirety of the United States with just 27 vehicles. And that is just the surface comparison! These vehicles are precious, and are treated as such, which is no way to build an economy.
We think the answer to making ocean infrastructure possible is manufacturing at radically lower costs. At Ulysses, we build AUVs for as little as $50,000 per unit, a 10x to 100x reduction over the most commonly sold incumbent models. At that price, we and our customers can think in terms of fleets rather than individual vehicles, and fleets, we believe, are the unit of infrastructure the ocean demands.
The ocean demands you operate at the surface and subsea as a single integrated system.
How do you design a vessel meant to operate on the surface and in the deep ocean, when the two are almost entirely separate domains, with radically different physics? Well, you don’t.
You design a system that handles both, consisting of separate vehicles optimized for each. The surface is where GPS and Starlink work, and doesn’t face the same pressure challenges as lower down, so that’s where communications, fuel, power, and logistics live. But most of the work is below the surface, where the undersea cables, seafloor, and marine ecosystems lie. You need vehicles that can go where the work is, and you need surface platforms that can deploy, recover, recharge, and connect them to the rest of the world.
A fully autonomous system is a much cheaper system, because the cheapest AUV in the world is still expensive if it’s hand launched and recovered, and requires a crewed ship to operate it. There’s a joke in the maritime industry that “unmanned” systems are only unmanned in the sense that the people aren’t on or in them, but right beside them while they operate. As long as humans have to babysit autonomous vehicles, they’re not really autonomous, and it will be impossible to achieve scale.
We’ve designed the system at Ulysses with those requirements in mind. Our underwater vehicle Mako goes deep and does the work. Our autonomous surface craft and mothership, Leviathan, equipped with our autonomous launch, recovery, and recharge platform, Kraken, remains on the surface and serves as the fleet’s connective tissue: deploying Makos, recovering them, recharging their batteries, and relaying their data to onshore operators via satellite. Leviathan is a working asset in its own right, a node in a domain awareness network that can carry its own sensors and serve its own missions. Together, linked by Kraken, they form a single integrated system that can persist at sea without retreating to port.
The underwater environment demands autonomy.
Because of the underwater communications desert we described earlier, you cannot supervise an underwater vehicle in real time the way you would a drone in the air. The bandwidth simply isn’t there, and the latency would make remote control dangerous and unreliable.
AUVs need to think for themselves. Because we’re talking about large fleets of small, inexpensive vehicles, there is no room in either the cost structure or the vehicle itself for a human pilot. Each AUV needs to navigate without GPS, make decisions based on what they see, avoid obstacles, adapt to changing conditions, and execute complex missions with only periodic check-ins.
This is as much a compute problem as it is a software one. At Ulysses, we pack over 100 times more onboard compute than anyone else in our underwater form factor, data-center-class GPUs running inside an AUV. Since we can’t talk to our vehicles, they need to be smart enough not to need us.
Industrializing the ocean demands both observation and action.
Most ocean technology stops at sensors, which are valuable in their own right. However, sensors are not by themselves industrial infrastructure. To industrialize a domain, you have to be able to act on what you observe.
Consider a vehicle that can only observe. It would swim around, notice that a pipeline was in need of repairs, ascend to the surface, and send a message back to a team of humans, who would then schedule and weather permitting, get on an expensive vessel, travel out to the site of the damage, and send a human or ROV (remote operated vehicle) below to make the necessary repairs. That process costs an unnecessary amount of time and money. Conversely, a platform that can both observe and act would be able to both inspect and repair the pipeline, quickly and cheaply. More persistent monitoring would also mean that each individual repair is likely to be simpler.
Here, modern robotics is key. The fleet of machines we send into the ocean must be able to manipulate, intervene, and repair, which means that they need arms, tools, and the dexterity to do meaningful work at depth. If they can, you’ve turned a sensor network into an industrial presence. This is the hardest part of the stack to get right, but given our heritage in sea grass planting, it’s the part that we started with.
The ocean demands a fully integrated system.
You may have noticed, reading this section, that each requirement builds on the others. If you want low costs, for example, vehicles need to be autonomous and they need to be able to act. As soon as you introduce humans back into the equation, coverage and persistence drop while costs rise. If you want vehicles that are truly autonomous, persistent, and can act at depth, you need surface vehicles and subsea vehicles that work together to do what each can do best.
We think this is how you industrialize the ocean, and we believe that the solution has to look more like a network of Starlinks than a railroad: a distributed network of coordinated assets, surface and subsea, each playing a different role. Together, they collectively give you persistent coverage of the hardest domain on earth and the ability to do something about what you find.
This is not a novel insight. Mariners have understood it in theory for at least a few decades. But there have been two challenges: it wasn’t possible to build, because the underlying technologies weren’t ready, and it wasn’t easy to fund, because the urgent demand for such capabilities didn’t exist.
Within the past five years, both of these aspects have changed.
There is perhaps no more important question that a technology startup can answer than “why now?” I argued earlier that every frontier becomes industrialized when supply-side technology and demand-side urgency converge. For the ocean, that convergence is happening right now.
In Cable Caballero, Packy coined “Curve Convergence“: if multiple component technologies improve on exponential curves as industry architectures remain frozen around outdated assumptions, it’s possible to create the opportunity for disruption with a better product.
The ocean is experiencing its Curve Convergence right now. Four exogenous technology curves all crossed critical thresholds in the same window, roughly 2020 to 2025. Each crossing has removed a specific barrier that previously made persistent ocean work impossible, and together they enable a total rewrite of how mankind can work at sea.
Before Starlink, communicating at sea meant paying over $5,000 a month for slow, unreliable satellite connections with multi-second latency. That meant any “autonomous” ocean vehicle was really just pre-programmed and running a script with no ability to adapt in real time.
Starlink Maritime changed this completely: it offers roughly $250 a month for 100+ Mbps with sub-70-millisecond latency, or a 100x improvement in price-performance in about three years.
Starlink gives you high-bandwidth, high-fidelity visibility into what your fleet is doing, at a cost that scales. Before, you might have gotten a trickle of compressed data over a satellite phone. Now, if one of your vehicles surfaces or relays data through a surface platform, you’ll get full sensor feeds, video, vehicle health, and mission statuses. The full picture will be streamed in real time to an operator who might be sitting in Dublin or San Francisco. The cost also helps: $250 a month instead of $5,000 or more has meant that connectivity can be placed on every surface asset in a fleet, making it possible to coordinate hundreds of vehicles across an ocean basin. Underwater, the vehicles can think for themselves, and when they’re back above ground, you can see everything they saw.
Energy is one of the most critical binding constraints of ocean work. Vehicles need to stay on or under the water for days, weeks, or indefinitely, and that requires generating, storing, and efficiently using energy in ways that simply weren’t possible a decade ago. Improvements have come on those three fronts simultaneously.
On generation, solar costs have fallen 75% in a decade, and that drop has reached the water. Solar- and wind-powered surface vehicles have already stayed at sea indefinitely on harvested energy alone. Below the surface and beyond solar, wave energy is reaching viability, achieving capacity factors around 90% (compared to 30–40% for offshore wind and 25% for solar) because waves run round the clock.
On storage, battery energy density has doubled in a decade, from 150 Wh/kg in 2015 to over 300 Wh/kg today, while pack costs have collapsed from $1,191 per kWh in 2010 to $115 per kWh in 2024. As Not Boring readers will understand intimately, increased battery density is important for everything from drones to AVs, but nowhere is it more important than it is underwater: every increment of energy density directly extends mission duration. Five years ago, a subsea vehicle on the best available batteries could run four-hour sprints before it needed to be recovered and recharged. Today, double the energy density, dramatically cheaper packs (which means you can afford to carry more total capacity), and more efficient motors and drive systems combine to make multi-day deployments possible.
All of these improvements compound. Each one matters, but it’s the combination, more energy per kilogram, cheaper per kilowatt-hour, less energy consumed per kilometer, that transforms the operating model from sprint-and-retrieve to deploy-and-sustain.
The vast majority of underwater work today is still performed by remotely operated vehicles (ROVs), tethered to a surface vessel by an umbilical cable and piloted in real time by a human operator watching a screen. The ROV goes where the pilot tells it, sees what the pilot looks at, and does what the pilot commands. It’s capable and proven, but it means every subsea operation requires a crewed ship overhead, which is why day rates for subsea work start at six figures.
Truly Autonomous Underwater Vehicles exist, but their capabilities have been narrow. They can run pre-programmed survey routes and collect data (sonar mapping, pipeline inspection, environmental monitoring), but that’s essentially read-only work. When it comes to acting on what they find, making a decision, adjusting course, manipulating something physical, the vehicle surfaces and a human takes over. The ocean has been a domain where machines can look but not think, and certainly not act.
That’s changing fast as the AI-driven terrestrial compute bonanza reaches the water. Onboard processing power has increased by orders of magnitude in the past five years, and the cost of edge inference is plummeting. Vehicles can now run real-time object detection, navigate around unexpected obstacles, and make mission-critical decisions without surfacing for instructions. The trend is moving from read-only to read-write: not just gathering data but interpreting it and acting on it autonomously. A thousand vehicles can’t each have their own human pilot. They need to think for themselves, and for the first time, they can.
An underwater vehicle is, at its core, a collection of motors, thrusters, actuators, sensors, seals, and structural components held together inside a pressure housing. Until recently, every one of those parts was bespoke, sourced from specialist defense suppliers who charged accordingly. This is one of the reasons that incumbent AUVs built by legacy defense contractors with artisanal production methods cost so much.
What has changed recently is that adjacent industries built new supply chains for us. The commercial drone industry commoditized motors, ESCs, and flight controllers. The EV industry drove down the cost of power electronics, drive systems, and battery management. Consumer electronics made high-performance sensors and embedded systems cheap and abundant. Packy has written about this phenomenon as the modern electric tech stack: the convergence of commodity components that lets you build sophisticated electromechanical systems at a fraction of what they used to cost.
A new generation of ocean vehicles, built on these supply chains, can be produced for hundreds of times less than incumbent vehicles.
That cost collapse makes the fleet model possible. We couldn’t possibly cover 361 million square kilometers of ocean with million-dollar vehicles, but we can with fifty-thousand-dollar ones. Thanks to these curves, we can make cheap vehicles useful enough that we need a lot of them, and by building more of them, we will make them even cheaper and more useful.
All four of these curves had to converge for ocean industrialization to become possible, and finally, they have. It’s the convergence of what I call the Ocean Stack that makes the phase transition possible.1
These curves are a thing of beauty, and we are fortunate to be alive at a time when so many of them are converging at once. I view it as our role to combine the Ocean Stack into useful products that are better, faster, cheaper, and entirely different in capability than previous generations of hardware.
No matter how good the technology, in order to reach the scale that both affordability and industrialization require, the supply needs to be met by demand, which it currently is, from all angles. What makes right now different from every previous decade is that the demand drivers are independent of each other. Any one of them would justify building ocean infrastructure, but all of them are accelerating simultaneously.
Ninety-nine percent of intercontinental internet traffic travels through submarine fiber-optic cables. Over a million kilometers of cable sit vulnerable on the ocean floor with essentially zero persistent surveillance. Now, there is simultaneously more demand for new cables and greater threats to them, natural and deliberate.
First, AI is driving an explosion of new builds: Meta announced Project Waterworth in 2025, a 50,000-kilometer cable spanning five continents --- the longest in history.
Amazon, Microsoft, and Google are all commissioning major new transoceanic routes. Investment in subsea cables is expected to nearly double between 2022 and 2027, with tech giants now controlling roughly half the market.
Second, those cables break 100 to 200 times per year due to accidental damage --- trawlers, anchors, earthquakes, and sharks --- and each break requires expensive, slow, ship-based repairs with no persistent monitoring in between.
Third, and most urgently: deliberate sabotage is escalating. In November 2024, two Baltic Sea cables were severed simultaneously --- the Lithuania-Sweden interconnect and the 1,200-kilometer C-Lion1 linking Finland to Germany. A month later, on Christmas Day, a Russian shadow-fleet tanker dragged its anchor through the Estlink 2 power cable and four telecom cables, cutting Estonia’s cross-border electricity capacity by two-thirds. NATO launched Operation Baltic Sentry in January 2025, sending frigates, patrol aircraft, and naval drones because no other assets were available to detect or deter these attacks.
Just two weeks ago, the UK accused Russia of running covert submarine operations over its cables and pipelines. Addressing Vladimir Putin, UK Defence Secretary John Healey said, “We see you. We see your activity over our cables and our pipelines, and you should know that any attempt to damage them will not be tolerated and will have serious consequences.”
In short, more cables are being built, more value is flowing through them, and more bad actors are learning what sharks have known since humans started laying subsea cables: that, Healey’s warning aside, they’re basically unwatched and undefended.
Today, subsea cable monitoring and repair is a ~$3B market expected to double by the early 2030s. That, however, underestimates the size of the opportunity, because the market is constrained by vessel supply, not demand. There are something like 60 specialized repair vessels in operation worldwide, and proactive monitoring is still in its infancy, as are novel approaches to using the cables themselves as sensors in a method called Distributed Acoustic Sensing (or DAS). Lower the cost of supply, and we will expand the market.
The Clarion-Clipperton Zone in the Pacific alone contains more cobalt than all known land reserves, along with polymetallic nodules rich in nickel, manganese, and copper.
Providentially, these are the exact minerals that EV batteries, wind turbines, and AI hardware are consuming at accelerating rates. Regulation, along with cost and technology, has kept these from being mined, but the regulatory dam seems to be cracking. After years of stalled negotiations at the International Seabed Authority, The Metals Company forced the issue in 2025 by filing the first-ever application for a commercial deep-sea mining license, bypassing the ISA entirely via a US regulatory pathway established in 1980. Whether you think deep-sea mining is the answer or not, the pressure to access these resources is intensifying, and you cannot extract, survey, or even responsibly monitor extraction without ocean infrastructure that does not yet exist.
It is not worth trying to pin down real numbers here, because the field is so nascent and the numbers so large. The Metals Company estimates the NPV of its first two projects to be $24 billion. The U.S. Geological Survey study on polymetallic nodules projects that if deep-ocean mining follows the evolution of offshore petroleum production, about 35–45% of the demand for critical metals will come from deep-ocean mines by 2065. And there is an estimated $233 trillion worth of value in polymetallic nodules worldwide, although, as with asteroid mining, these reserves will be difficult to access and, if accessed at scale, should dramatically decrease prices. For our purposes, it is safe to say that there is a lot of value down there.
When we started discussing writing this piece, maritime defense was already an important topic. We’ve all seen the chart comparing China’s shipbuilding capacity to the United States’. The ability to manufacture ships, traditional or autonomous, big or small, will be a deciding factor in any conflict between China and the U.S. Ideally, this ability will also be instrumental in deterring conflict in the first place.
Over the past couple of weeks, however, the question of maritime defense has become urgent. I’m writing this in April 2026, as the IRGC and United States are locked in a conflict over whether to reopen the recently closed Strait of Hormuz, the passage through which a fifth of the world’s oil supply normally flows. When Iran first closed the Strait, tanker traffic dropped 70%. On the surface, ships passing through the Strait have been struck by missiles, and below the surface, Iran has planted mines. In a dark confirmation of everything we have been arguing in this piece, Iran was unable to comply with President Trump’s demands to allow more ships to pass through the Strait, because it is unable to find the mines it just recently put there.
In the Red Sea, Houthi attacks forced global shipping to reroute around Africa, adding 11,000 nautical miles and 10 to 15 days per voyage, at a cost of roughly $1 million per ship. Container rates on the Shanghai-to-Europe route quadrupled. A trillion dollars worth of goods were disrupted in the first six months of the Houthi effort alone.
Meanwhile, China is building submarine-sized autonomous underwater drones with ranges exceeding 18,000 kilometers, developing cable-cutting tools that operate at a depth of 4,000 meters, and constructing an “Underwater Great Wall” of seabed sensors across the Indo-Pacific.
The post-war international order was fundamentally underwritten by the United States’ ability to make the ocean safe for trade. That either has broken or is breaking, depending on who you ask.
The United States is aware of it and is putting resources behind maritime superiority in the modern paradigm. The FY2026 Pentagon budget allocates $13.4 billion for autonomous systems. This is the first time autonomy has been its own budget line. The Navy alone gets $5.3 billion, a 70% year-over-year increase.
This is another truth about frontier industrialization. Every frontier in history was industrialized when powerful competition demanded it.
America pushed West to fulfill our Manifest Destiny. We raced Russia to the Moon to achieve superiority in the Cold War. The drive to industrialize the ocean is now fueled by China, Iran, and a world waking up to the fact that America is no longer capable of guaranteeing the maritime safety that has underpinned global trade since World War II.
Beyond the specific demand drivers, though, there is something more fundamental driving the Oceanic Renaissance.
If you look at the sweep of human history, there is an inexorable, consistent drive to pursue the frontier. We make the most of everything. We find everything. Technology, capitalism, human ingenuity, creativity, and sheer stubbornness combine to produce extraordinary outcomes from the resources available to us. Every frontier that could be industrialized eventually was.
The ocean is the last frontier. The technology is finally ready at the same time as demand is coming from every direction at once. This is going to happen. The only question is who builds it and how fast.
One thing is certain: the incumbents cannot lead this transition.
Other than the water, the ocean industry looks like any other that’s dominated by sclerotic incumbents too content with the world that was. You’ll even recognize many of the names.
Maritime defense primes include old faithfuls like Lockheed Martin, RTX, L3Harris, Leidos, and Thales. They sell everything from combat systems to sonar suites to legacy AUVs, often in a cost-plus model. Shipbuilders, like HII, General Dynamics Electric Boat, BAE Systems Maritime, Kongsberg, and the big three Korean yards, turn out hulls on multi-year contracts, which are cost-plus as well. Then there are companies that you’ve probably never heard of, the subsea service primes like Fugro, DOF, Oceaneering, Subsea 7, and ASN, which run thousands of campaign-based vessels for oil majors and telcos.
Between the ocean’s incumbents, hundreds of thousands of people generate tens of billions of dollars a year, every cent of it organized around the assumption that the ocean is expensive and will stay that way. You can forgive them for operating as if nothing will change, because that’s how their customers buy.
This is textbook Innovator’s Dilemma.
Christensen’s point is that incumbents fail by doing everything right for their best customers. Here, ocean incumbents’ best customers (navies, oil majors, telcos, shipping companies) are conservative, risk-averse, and demanding. They want proven, crewed, campaign-based services with mil-spec redundancy and rigorous SLAs. Autonomy-first, priced-for-scale platforms don’t meet those requirements yet. So the incumbents, rationally, keep investing in the fleets they already own in order to protect their margins and serve their best customers better.
By the time the new cohort is good enough to matter, the incumbents will have a decade of sunk cost in crewed vessels, a specialist workforce that has never shipped an autonomy stack, a mil-spec supplier network that cannot pivot, and an entire organization whose every incentive points at the existing business. The incumbents never lose because they’re stupid, or even because they don’t listen to the market. In fact, they listen to the current market too closely.
Once again, space is the case study. For fifty years, launch was owned by a small cohort of cost-plus primes – Lockheed, Boeing, and Northrop Grumman – whose economics depended on expendable rockets, government contracts, and scarcity. Then a new generation showed up, looked at the same physics, and decided that if you vertically integrated the supply chain, built for reusability, and priced for scale instead of scarcity, everything changed. That cohort, led by SpaceX and including Rocket Lab, Astranis, Planet Labs, Relativity, Varda, K2, and far too many to list, has a name now: New Space. As the cost of a kilogram to orbit fell by more than an order of magnitude, entire industries, including Earth observation, satellite-IoT, constellation broadband, and even space drugs, space-laser energy, and orbital data centers became possible and potentially profitable.
The same thing is happening in the ocean right now.
A new generation of companies is rebuilding the ocean from first principles. They operate less like modern versions of the rusty old ocean incumbents, and more like New Space companies that happen to work in salt water instead of vacuum.
While each of these companies is different, they tend to share some common characteristics:
Vertically integrated instead of subcontracted.
Autonomy-native instead of crewed-first with autonomy bolted on.
Software-defined instead of hardware-frozen.
Built on commercial supply chains (drone motors, EV battery packs, Jetson-class compute) instead of custom mil-spec.
Priced for scale instead of for scarcity.
We call this cohort the New Ocean.
As with any market map, there are a number of ways that we could slice and dice our fellow ocean startups, but the simplest is to group them into three buckets: infrastructure, platforms and vehicles, and vertical applications.
At the foundation are the Infrastructure companies that enable the Ocean Stack. These are the companies that are bending the curves on which the rest of us ride.
Starlink put a high-bandwidth, low-latency pipe to every square meter of ocean for the price of a weekly Uber habit. Panthalassa will generate persistent electricity at sea from wave energy, a marine renewable that runs through the night at much higher capacity factors than solar or wind.
Karpowership already operates forty floating power stations delivering 7.5 gigawatts across multiple continents, proving that energy supply at sea can be mobile and matched to demand.
Armada is deploying full compute clusters at sea, bringing the data center to the data with nearly free cooling from the ocean itself. Kraken Robotics builds the synthetic-aperture sonar that turns a cheap AUV into a survey-grade mapping platform. Each new capability that one of the Infrastructure players provides is a capability that the rest of the Ocean Stack can snap in and use.
In the middle of the stack are the Platforms, or Vehicles. These companies, including Ulysses, take advantage of the infrastructure layer and enable vertical applications. Collectively, these are the railroads of the ocean’s industrialization.
Above water, Saildrone has sailed more than two million autonomous nautical miles across the world’s oceans on solar and wind power alone. They are proof that persistent surface presence without humans or fossil fuel is an operational reality.
Saronic is rebuilding American shipbuilding around autonomous surface vessels for defense, attacking the same capacity gap that keeps the US Navy dependent on decades-old hulls. Blue Water Autonomy is designing 190-foot Liberty Class uncrewed naval ships from a blank sheet. The ships would be larger than any USV afloat today, built for the open ocean rather than the coastline.
Regent is electrifying coastal transport with all-electric seagliders that skim above the water faster than a ferry and don’t need an airport. Poseidon Aerospace is flying autonomous cargo aircraft to move freight across ocean basins at a fraction of the cost of a container ship and a fraction of the time of a plane.
Navier is building electric hydrofoiling boats that use 75% less energy than traditional hulls. Arc is rethinking how boats are built entirely: electric-first, hull-up, designed for modern manufacturing instead of inherited from the combustion era. In addition to its electric sport boat (which is incredibly fun, fast, and quiet), Arc is now moving into commercial tugboats on the same electric platform.
Beneath the surface, Anduril’s Dive division is producing the Dive-LD large-displacement AUV and leading Australia’s Ghost Shark program, bringing a defense-tech mindset to underwater warfare.
Across the sensor layer, Andrenam is weaving low-cost AI-powered sonar buoys into persistent maritime domain awareness meshes to string together a distributed listening grid from surface to seabed. Sofar Ocean is doing something similar for ocean observation, operating the largest privately-owned network of ocean sensors on Earth and turning real-time wave, weather, and current data into a platform the rest of the stack can build on.
With modern Infrastructure and Platforms, new Vertical Applications become economical.
The Metals Company and Impossible Metals are making the case that the ocean floor holds the cleanest path to the critical minerals the energy transition demands. TMC is filing the first-ever commercial deep-sea mining license, while Impossible builds robots that selectively pick nodules off the seabed rather than vacuuming it.
Shinkei Systems is using robotics and computer vision to automate the ancient Japanese ike jime harvesting method. They put their machines right on fishing boats to instantly, humanely, and precisely kill fish, eliminating the stress response that degrades most of the world’s wild-caught seafood and tripling its shelf life.
A market map of the New Ocean today looks platform-heavy, because that’s what new frontiers looks like at this stage. The platforms always show up early. But even among the platforms today, we think something is still missing. Each company on this map is solving a critical slice, but to truly industrialize the ocean — to turn it from a domain of campaigns and expeditions into one of systematic, repeatable, economically productive work at scale — you need all of those pieces operating as one integrated system: persistent surface and subsea vehicles, edge autonomy, real-time communications, and the ability to act. You need the whole stack in one.
That’s our thesis at Ulysses, and that is what we are building.
We’ve always believed that the ocean was Earth’s most mismanaged resource, and if it had better tools, it would be transformative for society. We looked at how SpaceX had approached space — the bet on vertical integration, the bet on pricing for scale instead of scarcity, the refusal to accept that the physics of the domain justified the legacy cost base — and decided the ocean needed someone willing to take the same approach. Our bet is that if the whole stack is built together, as one autonomous system, you can dramatically collapse the cost of working in the ocean.
My co-founders and I think about the opportunity through a single governing metric: the cost of ocean work, which we define as the cost of active operation over one square kilometer of ocean for one month ($/km²-month).
We believe the ocean is a constrained economy, severely limited by the tools available to work in it. Every constrained economy has a governing metric, the one number that, if you move it, everything else follows. For space, it was $/kg to orbit. For the ocean, it is the cost of ocean work.
That cost is unreasonably enormous today: covering a meaningful area of ocean with incumbent methods (crewed vessels, campaign-based operations, six-figure day rates) costs millions of dollars per month. If we can collapse it, we’ll make it economically viable to monitor cables, survey mineral deposits, manage fisheries, patrol shipping lanes, and do a hundred things nobody has thought of yet, at a scale that was previously impossible.
The ocean economy today is $2.6 trillion, built almost entirely on transit, extraction, and coastal adjacency. Imagine what it becomes when you can actually afford to work in the ocean, persistently, at scale. We are very early on the cost curve.
We collapse the cost of ocean work in two ways: on OpEx and on CapEx.
On OpEx, we integrate surface and subsea vehicles into a single autonomous system, removing the crewed surface vessel that drives the majority of incumbent operating costs. Our surface platform, Leviathan, deploys, recovers, and recharges our subsea vehicles via our autonomous launch, recovery, and recharge platform, Kraken, without returning to port and without requiring a crew of 80 to 150 people on board.
On CapEx, we design and manufacture the vehicles ourselves. Our underwater vehicle, Mako, is a modular AUV that starts at $50,000 per unit, compared to $500k to $5 million for incumbent AUVs. It carries more onboard compute than any small or medium AUV on the market, and we build for read-write, not read-only: these vehicles are designed for robotics from the start, not just data capture. The modular design means we and our customers can reconfigure the same vehicle for entirely different missions in minutes.
We’re deeply vertically integrated because we have to be. The existing supply chains and component manufacturers for ocean hardware are slow, expensive, and not built for scale. So we design and build many of our sensors in-house, we do our own manufacturing, we do our own PCB assembly, we develop all our own software from the autonomy stack down to the middleware, and we’re progressively bringing more complex components (navigation systems, advanced sensors, motors) under our own roof. And we believe the best way to capture the value of collapsing the cost of ocean work is to sell the work itself: we operate these vehicles for customers as a service, selling outcomes rather than hardware.
Build the fleet, deploy the fleet, sell the coverage.
The demand thus far has validated our thesis. Just this month, a major commercial customer requested a network of 10,000 vehicles operated as a service. Another requested at least 1,000. We have never seen numbers like this before, and they keep getting bigger. I fully expect this year to be the year demand outstrips our ability to supply, and our challenges shift from market creation to manufacturing and scaling.
Scale, after all, is what it will take to truly industrialize the ocean.
We’ve drawn many parallels between the ocean, the American West, and space in this essay. We expect that there will continue to be many similarities between those stories and the one that plays out at sea. Permanent infrastructure will replace episodic missions, and it will enable new types of businesses to operate at high volume and affordable prices. Governance will replace lawlessness, because those businesses will have assets they need to protect.
Space and the ocean share the same incumbent problem. Their incumbents are incentivized to keep things the way they are, which shows up as a high cost-physics gap, or what Elon Musk calls the “Idiot Index.” Prices are too high for all but the most profitable or profit-agnostic use cases. The same strategy to beat the incumbents applies to both, as well: vertically integrate and collapse the supply chain, and sell what used to be expensive hardware as an affordable service.
But the ocean is unique. Where space inspires sci-fi, the ocean inspires poetry. And the ocean has structural advantages that space doesn’t.
The ocean economy is already seventeen times larger than the space economy was at its inflection point. The ocean contains physical resources (minerals, energy, protein) that we have not yet been able to access (or find) in space. And the regulatory environment is the most permissive of any frontier: international waters begin 12 nautical miles from shore, with no FAA equivalent beyond that. The ocean is where modern cowboys roam.
The exciting part about operating among the cowboys is that it’s hard to predict exactly how things are going to play out. But I have a few thoughts and predictions.
Permanent autonomous infrastructure will replace episodic campaigns. Fleets of autonomous vehicles will operate continuously across ocean regions, persisting there as Starlink satellites do in orbit. Docking and charging stations will create underwater and surface logistics networks. Energy nodes will harvest wave and solar power. Compute clusters will float at sea. The ocean’s infrastructure will be networked instead of physically connected, but it will be no less permanent.
Resource management will move from blind to precise. Fishing will evolve from blind harvesting to precision management, replete with real-time stock assessment, targeted harvesting, and sustainable yields at scale. Mineral extraction on the seafloor will become viable with proper monitoring. We will harvest from the ocean itself at an industrial scale while stewarding its resources. The resources have been there since long before we were, but it’s only now that humans are cracking the economics of managing and accessing them with technology, as we once did with agriculture to great success in the Green Revolution.
Governance will follow infrastructure and economy. Sunlight is the best disinfectant, they say, and they haven’t even seen what sunlight does to a surface covered with salt water. The era of lawlessness will end through better visibility. The Bad Guys can’t fish illegally if the good guys can track every vessel, can’t cut cables if the routes are patrolled, and can’t dump waste if the water chemistry is monitored. The Wild West tamed down when the railroad brought people and their economic interests. More generally, lawlessness ends when persistent infrastructure brings visibility and an economy produces something people are incentivized to protect.
Infrastructure will beget infrastructure. Autonomous vehicles will create demand for energy nodes, which will enable longer missions. Longer missions will generate more data, which will create demand for communications networks. Each layer will make the next layer viable and necessary at greater scale.
Commercial activity will overtake military spend. Defense is always the early customer for frontier infrastructure. Before the Gold Rush transformed it into a commercial hub, San Francisco began as a Catholic mission and a military fort, the Presidio; today the Bay Area generates $1.4 trillion in GDP and would rank as the world’s sixteenth-largest economy if it were a country. Just as military forts preceded commercial towns in the West, military satellites dotted the skies before telecommunications satellites. The military cares more about capabilities than cost and can therefore bootstrap markets before the economics pencil out. But as always, the commercial market will dwarf defense in time via cable monitoring, offshore energy, fisheries, shipping, and a number of unknown but inevitable use cases that always emerge when costs come down.
New industries will emerge that nobody can predict today. I’m cheating a bit here, because this happens every time. The most valuable businesses that emerge from frontier industrialization are often the ones that people figure out once they have time to get their hands dirty with new capabilities. It’s not a coincidence that a disproportionate number of the richest people who have ever lived (Vanderbilt, Carnegie, Rockefeller, Musk) built the access infrastructure at exactly the right moment and then created new markets around the new capabilities they brought into the world.
That said, we can imagine some specific opportunities, including but not limited to: managed fisheries at scale; critical mineral extraction with proper environmental monitoring; persistent maritime domain awareness sold as a subscription; autonomous shipping and smarter logistics; ocean energy at industrial scale; offshore compute powered by ocean energy and cooled by seawater; an undersea acoustic and optical communications network (the subsea equivalent of Starlink), connecting every vehicle and sensor in the water; a persistent ocean observation layer (the subsea equivalent of Planet Labs) continuously mapping the ocean in three dimensions; systematic scientific exploration of the 99.9% of the deep seafloor that nobody has ever studied.
There are an estimated three million shipwrecks on the ocean floor, most of them never found, collectively carrying billions of dollars in treasure and untold secrets about the human story. And we may finally realize our parents’ and grandparents’ dreams of permanent ocean habitats (seasteading, seriously: I think it could actually work in the next decade with the right supporting logistics, communications, and energy infrastructure). A new Atlantis is at hand.
The scale of what opens up when you collapse the cost of persistent ocean presence is difficult to overstate. The ocean economy today is built on transit, extraction, and coastal adjacency, and it’s already worth trillions. Imagine what happens when you add persistent infrastructure, domain-wide monitoring, in-water energy, autonomous logistics, undersea communications, and a continuous observation layer covering 70% of the planet. The new economy will dwarf the old one. We just can’t see most of it yet, and that’s exactly what you’d expect at this stage.
We return to the question at the heart of my mission. What does industrialization mean for the health of the ocean itself?
There is a widespread assumption that economic activity in the ocean and ecological health are in tension and that industrialization means exploitation. I believe the opposite is closer to the truth.
Counterintuitively, with all of this economic activity, we will get conservation that actually works, practically for free.
The technologies that industrialize the ocean are the same technologies that make real conservation possible for the first time.
Consider the state of ocean conservation today. Marine protected areas cover roughly 8% of the ocean on paper. In practice, many of them are “paper parks,” with no enforcement and no monitoring. We protect the ocean by drawing lines on maps and hoping people respect them. I know this because I have worked in marine protected areas on both coasts of Australia and the US. I can tell you that it doesn’t work for the same reason that protecting the Amazon didn’t work until Brazil launched real-time deforestation alerts in 2004, after which Amazon deforestation fell 70%. Visibility is what made the difference. You can’t conserve what you can’t see.
Persistent ocean infrastructure gives you that visibility, as well as the ability to intervene. We won’t know what’s possible until we experiment with the right equipment and measurement.
Consider the story of Russ George.
In 2012, George, a Californian entrepreneur, tried one of the boldest and most controversial experiments in the history of ocean science. He decided to implement the work theorized by the controversial oceanographer John Martin, the father of an idea called “ocean iron fertilization”. A few decades earlier, Martin stood up at a scientific conference and declared: “Give me half a tanker of iron, and I’ll give you an Ice Age.”
Martin’s hypothesis was that iron fertilizes ocean plankton, which multiplies and absorbs enormous quantities of CO₂. This then feeds the base of the marine food chain, which, if done at scale, might be able to alter the planet’s climate and restore fish stocks. He died before he could test it properly.
In 2012, Russ George picked up his work and convinced a First Nations village on Haida Gwaii, a remote archipelago off the coast of British Columbia, to invest $2.5 million in the experiment. He loaded 100 tonnes of iron sulfate onto a fishing boat and dumped it into the Pacific about 200 miles offshore.
And by George, he did it. NASA satellites confirmed a plankton bloom covering 35,000 square kilometers — an area so large that it was visible from space. The following year, the pink salmon run returned at 226 million fish, the largest run in Canadian history.
The scientific establishment lost its mind. Researchers disputed the causal link. Environment Canada executed search warrants on his office. The Canadian government investigated George for violating international dumping conventions. The UN imposed a moratorium on ocean fertilization.
None of his opponents argued that the idea was wrong, nor even that it didn’t work. The problem was that nobody could verify what had actually happened. There was no persistent monitoring to measure the bloom’s full effects, no way to track downstream consequences across time and space, and no ability to adjust the intervention as conditions evolved.
George had a hypothesis and a budget, but he was intervening blind. One rogue entrepreneur with a fishing boat had produced what looked like one of the most successful ecological interventions in history, and nobody could prove it, so nobody has reproduced it.
Now imagine that same experiment in a fully instrumented ocean. Autonomous vehicles monitoring the bloom in real time across its full extent. Sensors tracking nutrient levels, oxygen, pH, and biodiversity indicators continuously. The ability to see unintended consequences developing and respond before they cascade. Real-time data flowing to scientists and regulators who can assess the intervention as it unfolds, not years later from fragmentary satellite data. Iron fertilization is just one example. Targeted reef restoration, invasive species removal, pollution response, managed rewilding: these are the kinds of active stewardship that become possible when you can actually see what’s happening in the ocean and respond to it. The problem was never the idea of active ocean management. The problem was attempting it without the infrastructure to close the feedback loop.
The same sense-intervene-measure-adjust feedback loop that George’s experiment lacked is exactly what persistent infrastructure provides.
The dual-use nature of ocean infrastructure could make all of this work. The same vehicles monitoring subsea cables will collect environmental data. The same platforms enabling offshore energy will measure ocean chemistry. The same communications networks connecting autonomous fleets will transmit scientific data. It is inefficient to build one system for commerce and another for conservation when you can run both on the same system.
Economic growth and biodiversity health can and should be genuinely symbiotic. The fishing industry benefits from healthy stocks, which require monitoring. The offshore energy industry benefits from accurate ocean data. The insurance industry benefits from better climate models. Every commercial use case generates data that improves our understanding of the ocean, and better understanding leads to better stewardship. We still need to respect the ocean as a living system, and there will be hard decisions about where and how to operate, but we need to have the ability to decide. The virtuous cycle only works if the infrastructure is in the water.
I am not naive about this. There are real risks. Poorly managed extraction can damage fragile ecosystems. Increased activity in previously untouched areas brings the possibility of contamination. Geopolitical competition over ocean resources could intensify rather than stabilize. The fact that international waters have no FAA equivalent is an opportunity, but it is also a governance gap that will need to be filled as activity scales. Getting this right requires exactly the kind of persistent monitoring and real-time visibility that ocean infrastructure provides. The best argument for building the infrastructure is that without it, the ocean’s resources will continue to be exploited blindly and unsustainably by those who can already afford to be there.
When you fix the cost of doing persistent work in the ocean, you fix everything downstream of it. Conservation, commerce, defense, science, and discovery are all bottlenecked by the same constraint. If we remove it, we can unblock all of them.
Berry Cannon died at 610 feet, breathing helium in the dark, because somebody forgot to fill a scrubber. That was 1969. That was the best we could do back then.
We can do much better today. The technology exists to build persistent, autonomous infrastructure across the ocean without sending human beings into the abyss. But the point of this essay is not that we can finally do it safely. The point is convincing you that we have to do it at all.
We have the means now to conquer the Great Blue Frontier and do what our grandparents dreamed of. Frontiers matter. Conquering them matters. Not just economically, though the economic case is extraordinary, but for what they do to us and more broadly, the soul of civilization. Their pursuit lights a fire in the heart of men that leads to civilisational greatness.
Every great era of advancement has corresponded to an active frontier. The Renaissance had the Age of Exploration. The twentieth century had aviation, then space. When there is somewhere new to go, the best minds build toward it. When there isn’t, that energy turns inward. It optimizes. It litigates. It fights over what already exists. I think we’ve all felt that. The creeping sense that the great adventures are behind us. That the best we can do is make what we have a little more efficient.
Civilization is a lot like sharks in this regard. Many species of shark (e.g., Great Whites, Makos, Whale sharks) die when they stop swimming. They need the forward motion to oxygenate their gills. Stop, and they suffocate. Humans are the same. Without forward motion, we stagnate, and stagnation is a kind of death.
The ocean is the answer to this stagnation. It has been there the whole time, covering 70% of the planet, largely unknown, barely touched, immensely rich. We mapped its surface and called it quits. We drilled through it and called it industry. We fished from it and called it the economy. But we never truly entered it, and we certainly never built the infrastructure to stay, steward, and leverage its full potential
The last great frontier on Earth isn’t behind us. It’s below us.
I grew up jumping off the pier at Garrettstown, pulling crabs out of rock pools, heading out in the boat with my dad to catch mackerel. I loved the ocean before I understood it, before I could have told you anything about technology curves or governing metrics or the cost of persistent presence. I just knew there was something down there worth knowing. I still believe that. And now we can finally go find out.
Come build it with us. There is no greater adventure than settling a frontier.
Will O’Brien is the co-founder and President of Ulysses Maritime Technologies, the ocean company, building the fleets of autonomous underwater and surface vehicles to solve the most critical tasks in the ocean.
Thanks to Will for sharing his knowledge, to Badal for my favorite cover art yet, and to all of the oceanic explorers buried beneath the waves.
That’s all for today. We’ll be back in your inbox tomorrow with another Weekly Dose.
Thanks for reading,
Packy
Note: curves may be slightly different from The Electric Slide because these are measuring specific components ocean companies might use and because, in the case of batteries, starting in 2010 vs. further back means the ability to use one canonical data source on pack costs. All the curves are pointing in the same direction, though.
2026-04-17 20:48:26
Hi friends 👋,
Happy Friday and welcome back to our 189th Weekly Dose of Optimism.
There are a couple of big themes this week: energy, and non-invasive, non-molecular control of the human body and brain. If we’d published this week’s Dose back in, say, 1995, I worry that a few readers would drop dead from shock. It’s hard to recognize you’re in a sci-fi novel when you’re living through it, but if you zoom out a little bit, it sure looks like we are.
I’d highly recommend the Extra Doses this week, for Friedberg contextualizing everything happening and why it’s good, and for one of the craziest stories we’ve covered in Science Breakthroughs on gene control in mice using electromagnetic fields. Plus, Science Breakthroughs now have one-sentence plain English summaries thanks to a request from Chris B.
Let’s get to it.
Funnily enough, I’m writing this as I sip my morning Creatine + Electrolytes. It’s something of a morning ritual in our house. The kids wake up and come downstairs, Maya asks if we can make creatine, we open two packets, she pours them in, Maya and Dev each take a small sip, and then I down the rest. Dan is making me do a Hyrox with him, so C+E is a lifesaver.
I’m apparently not alone. Since Dan and Sienna launched Creatine + Electrolytes two weeks ago, the product is already run-rating $15 million. And no wonder.
Each packet contains 5g creatine monohydrate, 800mg electrolytes, and 1000mg taurine. I take two in the morning, and one or two later in the day when I work out or if I’m tired. These little packets, mixed into a glass of water, support hydration, improve recovery, increase energy, and boost cognition.
They have all of the well-studied benefits of creatine, plus the hydration, muscle function, recovery, nerve signaling, heart rhythm, and pH balance benefits of electrolytes. Before they put it all in a little packet, I was dumping salt in my creatine water. This is better, and it tastes so good that my kids demand sips.
So if you want a great-tasting extra kick for your muscles and your brain, and you want to support long-time Dose writer and my brother Dan, get 30% off C+E here:
Beneath our feet sits essentially infinite, always-on, carbon-free power. Estimates are that there 63 terawatts, or roughly eight times all the electricity humanity currently generates, would become accessible by tapping just 1% of the world’s superhot rock resources. It’s just really far down there. The hottest, densest heat sits two to twelve miles down, past the point where conventional drill bits work.
This week, MIT spinout Quaise Energy announced Project Obsidian: the world’s first commercial superhot geothermal power plant, being built in Central Oregon near the Newberry Volcano. Phase I will be 50 MW, Phase II will scale to 250 MW, and Phase III will be more than a gigawatt. Quaise is targeting commercial operations in 2030.
The reason this can exist now is a new way to drill. Quaise uses a gyrotron, originally developed for fusion research at MIT’s Plasma Science and Fusion Center, to produce millimeter-wave energy that ablates rock by vaporizing it with no mechanical contact. Last year, they drilled through 100+ meters of granite in Central Texas in the first field demonstration of the technology. This year, they’re targeting a kilometer, then eventually, 10-12 miles. At full depth, a single superhot well would produce 5-10x more power than a conventional geothermal well.
Both the superhot rock and the drill that can reach it are what make this different from Fervo, a company we’ve covered previously in the Dose, and the other EGS players working closer to the surface. Conventional EGS taps warm rock. Quaise is going for the really hot 300–500°C rocks, which provide enough pressure to produce supercritical water, which makes gigawatt-per-well plausible.
We have been waiting for this. When Julia and I talked to Eli Dourado about geothermal on Age of Miracles, he said the reason we couldn’t just count on geothermal for all of our electricity needs was heat. “Geothermal doesn’t get super hot,” Eli said.
If Quaise pulls this off, that may no longer be true. Drill baby drill.
and Garth Sheldon-Coulson on
A year or so ago, I had coffee with Lowercarbon Capital’s Ryan Orbuch, and I asked him what the coolest companies in his portfolio were. The first one he brought up was Panthalassa, which I remember him describing as building massive structures in novel geometries to pull energy from the ocean’s motion (turns out both the size of the boat and the motion of the ocean matter).
Panthalassa, based out of Portland of all places, has been working on an 80-meter-tall, 20-meter-wide, lollipop-shaped self-driving floating power plant that lives on the open ocean miles and miles offshore and generates electricity from waves, which it will first use, of course, to power GPUs. The lollipops will have just one moving part. Waves force water through internal channels, the channels pressurize the water, the pressurized water spins a turbine, and the turbine spins a generator.
CEO Garth Sheldon-Coulson told Ashlee Vance that they chose offshore waves because it’s one of three potential tens-of-terawatt-scale energy sources (the other two are solar and nuclear (fission and fusion), and there’s a potential fourth in the next story). When he and co-founder Brian Moffat dug in, they realized it also had advantages over other renewable sources: capacity factor up to 90%, against 30-40% for offshore wind and 25% for solar and a target cost around $1,500 per kilowatt. It can also self-propel to wherever the wave resource is best at a given time at 1-1.5 knots. It all sounds insane, but results from sea trials of their Ocean-2 prototype in Puget Sound matched simulation almost exactly.
If this works, we’re going to need to figure out a lot more things to do with all our power.
One of which may be to desalinate the very water in which Panthalassa swims.
Look, I love putting Creatine + Electrolytes in my water more than the next guy, but there are plenty of times when you want to get the salt (and other stuff) out of your water to make it safe to drink. For those times, there is now Vital Lyfe’s Access.
Jon Criss (13 years at SpaceX, Lead Integration and Test Engineer on Dragon, Product Manager on Starlink) and Andrew Harner (9 years at SpaceX, Stanford aero) co-founded Vital Lyfe to build what they call a personal water-making system. This week, pre-orders went live for Access: a 25-pound box that turns seawater into drinking water. Put a hose in the ocean, press start, and collect six gallons of clean water per hour. Freshwater sources get you 12-13 gallons.
Access is $749, with an $8 deposit to reserve, and deliveries begin later this year.
Desalination has always worked. Israel runs its whole country on it. The problem is that it has required municipal-scale infrastructure like billion-dollar plants, dedicated power, and pipelines, which means that the 2+ billion people who lack reliable access to clean water can't get it, because it depends on the kind of infrastructure their governments haven't built and probably won't.
Vital Lyfe's bet is the same bet that made Starlink work: if centralized infrastructure can't reach everyone, decentralize the infrastructure. Make the unit small enough that an individual, an NGO, a fishing village, a disaster response team can just… have one. In March, they field-tested Access in Tierra Bomba, Colombia, with local NGO Amigos Del Mar. They opened a 37,000-square-foot manufacturing facility in Torrance the same month. Criss told press the production line is designed to manufacture more desalination units in a single month than currently exist worldwide.
Drink up.
Humans have been wearing hats for at least ~30,000 years. We’ve been thinking even longer than that. What if, Sabi asks, we could just think while wearing a hat that reads our brain, and use that to interact with machines?
Yesterday, Sabi, backed by Khosla, Accel, Initialized, and OpenAI VP of Science Kevin Weil, came out of stealth with a BCI that decodes the words you think into text on a screen, but instead of needing brain surgery, the BCI comes in a hat.
The device uses 70,000 to 100,000 EEG sensors, versus a dozen to a few hundred for most consumer EEGs, all in a baseball cap or beanie. The bet is that a ton of sensors can compensate for the skull’s signal dampening, the problem that most BCI companies compensate for by going under the skull. “If you're going to have a billion people use BCI for access to their computers every day,” Vinod Khosla said in a WIRED interview, “it can't be invasive.”
Sabi is also building a Brain Foundation Model to decode the brain’s signals and turn it into speech. They’re targeting 30 words per minute, but the plan is to improve the speed as the hats learn about their wearers’ brains.
Sabi expects to begin shipping at the end of the year, so now is the time to start meditating and controlling your thoughts before your hat starts telling everyone around you what you really think about them.
Speaking of non-invasive brain devices… we’ve written about Prophetic, a company that plans to use Transcranial Ultrasound to induce lucid dreams, a few times here in the Dose, for the simple reason that it’s one of the coolest companies imaginable. It is also an expression of a belief I have that as the machines get more capable, we will see a wave of technologies built to unlock the superpowers latent in our human bodies and minds.
Good news for the humans: Prophetic has successfully demonstrated the ability to increase lucidity in dreams. “By sending safe ultrasonic energy through the forehead and into the prefrontal cortex,” the company tweeted, “we are able to activate the Central Executive Network aka Frontoparietal Network.” Test subjects reported greater dream recall, dream vividness and continuousness, clearer dream thinking, and the ability to make deliberate choices that changed what happened inside of the dreams.
Lucid dreams are wild, with benefits (studied to varying degrees) around nightmare reduction (including PTSD-related ones), motor skill practice (you can practice throwing darts in a lucid dream and get better at actually throwing darts), emotional processing and fear exposure, and creative problem solving. Nikola Tesla wrote about his deliberate conscious dream-journeys in his excellent and short autobiography My Inventions, writing “Every night, when alone, I would start on my journeys – see new places, cities, and countries; live there, meet people and make friendships.” Christopher Nolan created Inception on concepts from the lucid dreaming literature, and said in interviews that he drew on his own dream experiences for the film.
Aside from the practical benefits, lucid dreaming just seems magical, like VR that the brain you always have with you can generate. In lucid dreams, people can fly, interact with dream characters, and generate worlds that defy the laws of physics. The world needs more magic.
Ultrasound is making a lot of noise this week. Salk Institute neuroscientist Sreekanth “Shrek” Chalasani received up to $41.3 million from ARPA-H to turn the technology he invented, sonogenetics, into a clinical therapy.
Where Prophetic is using ultrasound to stimulate brain regions we already know respond to acoustic energy, sonogenetics flips the approach: you engineer specific cells to express an ultrasound-sensitive protein, then use a focused ultrasound pulse to turn just those cells on or off. It’s like optogenetics (using light to control neurons), except ultrasound goes through skin and bone without needing fiber-optic implants. It’s also more precise than a drug, because only the tagged cells respond.
Chalasani found the first ultrasound-sensitive protein in C. elegans in 2015, coined the term "sonogenetics," and spent the past decade building the field on seed funding from the Jacobs family at Salk. The ARPA-H award pulls together a team built for this kind of translation: Nobel laureate Ardem Patapoutian at Scripps engineering the next generation of ultrasound-sensitive proteins, Aravind Asokan at Duke working on delivery vectors (Go Duke), Xuanhe Zhao at MIT on wearable ultrasound hardware, plus collaborators at UC San Diego, St. Boniface/Manitoba, and the California Medical Innovations Institute. Salk spinout SonoNeu (co-founded with Venkat Reddy at General Inception) will manage the path to FDA.
Their first target is peripheral neuropathies, including diabetic neuropathy. Longer-term, they want to build a platform for on-demand, location-specific control of cell activity in both the peripheral and central nervous system.
One of the things I find most exciting about biology today is how many of the big frontier ideas are about programming living systems with something other than small molecules: Michael Levin on bioelectrics, Prophetic on ultrasound at the circuit level, Chalasani on ultrasound at the cell level. Welcome to the Body’s Electric Age.
2026-04-10 20:32:59
Hi friends 👋,
Happy Friday and welcome to our 188th Weekly Dose of Optimism!
I keep saying this, and then it gets cold again, but I think this is the one: it’s a beautiful morning here in New York City, spring is springing, and our fellow humans keep pumping out optimism-worthy work.
This week, for example, we have new funding for AI-assisted Alzheimer’s research and, in Science Breakthroughs, a peptide that degrades the amyloid-β linked with the disease. That, and much much more, in this week’s Dose.
Let’s get to it.
There is a lot of noise out there about how AI is impacting companies. Of course, big AI lab CEOs are predicting massive job disruption and productivity increases. But to find out what’s really going on, ask the people who control where the dollars flow: the CFOs.
SVB surveyed 200+ startup finance leaders for its new State of the VC-Backed CFO report, and a few things jumped out:
AI adoption is now the #1 issue for startups, and 63% of CFOs rank it top-two
Companies are doubling AI spend this year (to ~$50K median)
Over half of CFOs surveyed are already seeing real ROI on AI spend
The biggest impact to staffing isn’t layoffs, it’s hiring fewer junior hires
In short, startups are getting leaner, faster, and more experimental. If you want to understand where company-building is going next from the people who control the spend, grab your free copy today.
My grandmother had Alzheimer’s. One of my biggest fears in life is that me and the people I love will get it; it’s one of the reasons I started writing, to help me remember. Unfortunately, since my grandmother had it, we’ve made no progress on defeating Alzheimer’s. Measured by age-standardized mortality rate, while we’ve made strides against cardiovascular disease, cancer, and infectious diseases, Alzeheimer’s has only gotten worse. It is a complex disease with hundreds of environmental and genetic risk factors interacting across cell types over decades, and as such, treating it has been a sad game of whack-a-mole.
Maybe AI can help. This week, the OpenAI Foundation, the nonprofit parent of OpenAI, now sitting on a $25 billion life sciences and resilience commitment, announced it’s putting $100M+ into six research institutions to throw modern AI at the problem. Jacob Trefethen, who ran half a billion dollars of science grantmaking at Coefficient Giving before joining OpenAI, is leading the effort. The grants span AI-assisted drug design, biomarker discovery, mapping disease pathways, and personalizing treatment.
The most interesting grantee is Arc Institute, whose progress we’ve covered many times in the dose, which announced a parallel partnership focused on what co-founder Patrick Hsu calls an “AI lab-in-the-loop” approach. The idea is to systematically perturb human brain organoids guided by patient data, measure what happens, feed the results back into AI models, and iteratively build a causal map of the disease, the actual chain of cause and effect from genetics to protein misfolding to synaptic collapse. Arc executive director Silvana Konermann describes the goal as finding “perturbations that can click and drag a cell from a diseased state back into a healthy one.” The other grantees include David Baker’s Institute for Protein Design and EvE Bio.
NIH funds Alzheimer’s, and has for decades, and we are where we are. What Arc and the OpenAI Foundation are doing is what private capital and motivated foundations can do that institutional science usually can’t: pick a hard problem, fund a full-stack experimental-and-AI engine, and run the loop fast enough that we might actually get somewhere by the time it matters to my family.
I would very much like to forget about Alzheimer’s once and for all.
Substrate x Google DeepMind
One big lab I have been consistently impressed with is Google DeepMind, and those wacky geniuses are at it again. This week, the American semiconductor foundry startup Substrate, whose launched we kicked off with in Dose #168, shared that GDM’s AlphaEvolve rewrote a chunk of its lithography software and made it nearly seven times faster while cutting compute costs by 97%.
Substrate is the James Proud-founded startup that came out of stealth last October with $100M and a crazily ambitious mission: build a U.S. foundry that uses X-ray lithography to compete with ASML's EUV machines by patterning features tens of atoms wide, on American soil, at lower cost than the Dutch monopoly. AlphaEvolve is DeepMind’s evolutionary coding agent, the latest entry in the Alpha lineage that runs from AlphaGo to AlphaGoZero to AlphaZero to MuZero to AlphaFold to AlphaChip.
This week, Substrate pointed AlphaEvolve at its computational lithography stack, the software that simulates how trillions of photons interact with photoresist to print a chip layer. In just a few weeks, AlphaEvolve explored thousands of algorithmic variations and landed on lossless compression tricks and lower-precision representations that cut memory by 74%, sped up runtime 6.8x, and dropped the Google Cloud TPU bill by 97%. Now, Substrate’s tool can print metal-one layers (the hardest, most defect-prone layer in a chip) at a 24nm pitch in a single exposure, with bidirectional 2D patterns and sharp 90-degree corners. That’s 2nm-node territory, the bleeding edge. Without the speedup, the same patterns would have required multi-patterning: two or three exposures, which means more defects, more cost, and more time.
This is fun because: a) we are rooting for American ASML and b) it’s a combination of the stuff we’ve talked about in the last couple of co-written essays: World Models talked about the evolution of the Alpha line of models, which learn causality instead of rules, and Electromagnetism Secretly Runs the World talked about using AI to design better chips. It’s also an example of America’s best hope in the electric competition with China: using new technologies to find new, better, and cheaper ways to build the things we don’t build today. I suspect we’ll be hearing more from Substrate - it would be insane to compete with ASML at their own game, so they’re creating a new one.
Speaking of EM modeling… A couple of weeks ago, in Electromagnetism Secretly Runs the World, Arena Physica CEO Pratap Ranade and I mentioned the new models and blog posts they would be releasing soon. Soon has come. Its new model, Heaviside, is its first EM foundation model, and you can play with it in the RF Studio.
I have spent a lot of time thinking about robotics recently, and I’ve got to admit, I did not think of a lamp that folds your laundry. This is the future that Beauty and the Beast and The Brave Little Toaster promised.
Lume is a pair of six-foot bedside floor lamps with hidden six-axis robotic arms, cameras, and on-device AI processors. Toss your clean laundry on the bed, the lamps quietly extend their arms and fold it in under two hours for a full load. You don’t have to tell it to do anything, it just watches the bed and figures out when to get to work. (There’s a Lume sitting in the factory somewhere just praying Bryan Johnson orders it.)
The graveyard of laundry-folding robots is packed. Foldimate made you feed clothes in one at a time and quickly… folded. Laundroid was a $16,000 closet-sized monster that bankrupted its parent company in 2019. Laundry is so hard that every robotics company makes demos of their bots figuring out how to do it in a controlled environment, and people go wild, because folding laundry is decidedly a thing we want the robots to do for us.
The why now? is the perception stack. Vision-language models (VLMs) are now good enough that a small startup can train a thing to look at a balled-up t-shirt on a comforter, figure out what it is, grab it, and fold it.
It’s also a constrained problem. It doesn’t promise to do everything; it gets paid to do one thing well, and learn. Maybe it, like Standard Bots, will be able to take small steps across the spectrum. And you gotta buy a lamp anyway.
I want to wait to see the reviews before I drop $2,499 on two lamps, but if you want to be an early adopter, be our guest.
Jared Isaacman for NASA
Last week, we covered the launch of the Artemis II mission, which planned to take North Americans back to the Moon for the first time in more than half a century, and farther from the home planet than we’ve ever traveled (that we know of). As the crew rounded the Moon on Monday, NASA Administrator Jared Isaacman tweeted:
On the far side of the Moon, 252,756 miles away, Reid, Victor, Christina, and Jeremy have now traveled farther from Earth than any humans in history and now begin their journey home. Before they left, they said they hoped this mission would be forgotten, but it will be remembered as the moment people started to believe that America can once again do the near-impossible and change the world.
It’s rare for us to do back-to-back coverage of the same story, but unprecedented accomplishments call for unprecedented measures. Instead of writing about it, I’d just ask you to watch Astronaut Victor Glover’s Easter message back home:
Primer is one of the not boring capital portfolio companies I’m most proud to be involved with. I’ve written about them here and talked to the CEO Ryan Delk on moving from software into running schools here. They take kids seriously, and exist to give more kids access to excellent education.
This week, they released a video narrated by one of its students and featuring others that highlights both its approach to education, and an optimistic vision for how we can all meet the future: “The next 200 years will look nothing like the last. We will face problems we can’t yet imagine, and possibilities we can barely dream of. We won’t just need answers. We’ll need resilience, flexibility, courage, mastery.”
Amen.
2026-04-03 20:35:07
Hey friends 👋,
Happy Friday and Happy Easter Weekend!
We’re going back to the Moon. OpenAI bought TBPN for a lot of money. Somos is going to blanket the globe in fast internet. And a whole lot more good news where that came from.
Let’s get to it.
Your company has invested in AI tools, which is a great first step. But your AI is only as good as the knowledge behind it. And for most companies, that knowledge is scattered, outdated, and nobody’s job to fix. So your AI gives confidently and sneakily wrong answers to all of your employees.
Guru is the governed knowledge layer that fixes this at the foundation. Companies like Spotify and Brex use Guru to structure their company knowledge, keep it accurate automatically, and make it available to every AI tool and every person, all from one trusted source.
With Guru, when an expert corrects something once, it’s right everywhere you work, in every AI tool, workflow, and answer.
No more garbage in, garbage out. Just cited, verified, always-current knowledge your AI can actually rely on.
NASA
For the first time in 53 years, 5 months, and 20 days, human beings are on their way to the Moon.
Last night at 6:35 p.m. EDT, NASA’s Space Launch System (SLS), standing 322 feet tall, weighing 5.7 million pounds, and generating 8.8 million pounds of thrust (17% more than the Saturn V), lifted off from Pad 39B at Kennedy Space Center carrying four astronauts aboard the Orion spacecraft (which the crew named Integrity). Commander Reid Wiseman, Pilot Victor Glover, and Mission Specialists Christina Koch and Jeremy Hansen are now on an approximately 10-day trip around the Moon and back. No one has done this since Apollo 17 splashed down in December 1972.
Integrity will spend about a day in a high Earth orbit stretching 46,000 miles out, the crew will manually fly the capsule to test its handling, and then a six-minute translunar injection burn will send them on a free-return trajectory using the Moon’s gravity to slingshot them around the far side and back home. On Monday, April 6, the four of them will become the first humans to lay eyes on parts of the lunar far side, reaching a record distance of 252,000 miles from Earth. They’ll splash down in the Pacific on April 10.
Is getting to the Moon more expensive than it should be? Hell yeah, roughly $4.2 billion per SLS flight by the Inspector General’s math. Did it take way longer than planned? Also hell yeah. But four people are about to travel further from our home planet than any human has traveled before, in the first of a series of missions designed to get us back to the Moon to stay.
I can’t really sum up how I feel any better than this kid did:
Katie Deighton for WSJ
Speaking of going to the f*cking moon… OpenAI, which just closed a $122 billion round at an $852 billion post-money valuation, has spent some of its treasure to acquire tech media’s crown jewel, TBPN. The FT reported that the deal is in the “low hundreds of millions of dollars.”
Huge congrats to Jordi, John, Dylan, Ben, and the whole TBPN crew.
This is an incredibly smart acquisition for OpenAI. I’ve been saying that the frontier AI labs have completely botched their narrative, and this is about as good of a way to get to work fixing it as I could imagine.
A lot of the commentary so far has been about OpenAI acquiring the media property, which will certainly be helpful, but the big get is Jordi & John. They’re simultaneously highly generative creative geniuses and normal guys. I expect that we’ll see their impact on the way the company communicates to non-San Franciscans pretty quickly, and I hope they’ll have a hand in shaping where AI goes more broadly.
In the meantime, it’s just great to see the good guys get a W.
Completely unrelatedly, I’ve told you guys how awesome I think Google DeepMind is, right? Been saying it for years. What a great lab. Could obviously use a little help telling their story, but wow. What a family of models. AlphaFold! Gemini! AlphaProof! AlphaGo! AlphaZero! Nano Banana! Genie! SIMA! DolphinGemma! I could go on and on.
Yesterday, the good folks at GDM just released a family of AI models that can see images, watch video, understand speech, reason through competition-level math, and write code, all open source. You can download them for free, modify them, and ship them in a commercial product under the Apache 2.0 license.
GDM released Gemma 4 in four sizes: a 31B dense model, a 26B mixture-of-experts model, and two edge models (E2B and E4B) designed to run on phones and laptops. None of them is quite up to par with the best frontier models, including GDM’s Gemini, but since they can run locally on your hardware, it means you get the tokens they produce basically for free.
Yesterday, in Bad Analogies, I wrote that OpenAI and Anthropic were burning a ton of money to compete in an incredibly competitive field, and that Google DeepMind was Zeus in this battle of the gods. Gemma is another lightning bolt. The more things people can do with free tokens, the less they’ll spend on tokens, even if the most advanced capabilities will always come at a price. Of course, closed model customers are paying for more than tokens: reliability, ease-of-use, etc… but it’s fun to see the competition drive down prices for consumers.
Jokes aside, I continue to be very impressed by GDM. The lab came up more than any other in my research for both World Models and Many Small Steps for Robots; they’ve done more to push the frontier in more directions than any lab in the world. With Gemma 4, Demis the Menace strikes again.
Kyushu University via Science Daily
Three weeks back, we led off the Dose with a story on Swift Solar buying a gigawatt-scale solar factory to produce 30-40% efficiency silicon-perovskite tandem solar cells.
This week, researchers at Kyushu University in Japan announced cells with a seemingly impossible 130% efficiency.
There’s a number in solar energy called the Shockley-Queisser limit. It says that a single-junction silicon solar cell can convert, at most, about 33% of the sunlight hitting it into electricity. Silicon-perovskite tandems can up that to 45%. In either case, the rest, especially the high-energy photons, gets wasted as heat. Shockley-Queisser been the ceiling since 1961.
Until now! A team led by Associate Professor Yoichi Sasaki at Kyushu University in Japan, collaborating with Katja Heinze’s group at Johannes Gutenberg University Mainz in Germany, just published a paper in the Journal of the American Chemical Society showing that they paired tetracene-based molecules with a molybdenum-based metal complex (a “spin-flip” emitter) and achieved a quantum yield of roughly 130%. That means for every photon absorbed, the system produced 1.3 energy carriers. More out than in, which seems like it shouldn’t happen.
The trick is a process called singlet fission. When a high-energy photon hits the tetracene, instead of creating one excited electron and dumping the rest as heat, the molecule splits that energy into two lower-energy “triplet” excitons, a little bit like nuclear fission (don’t yell at me real physicists). The problem has always been that a competing process called Förster resonance energy transfer tends to steal the energy back before fission can finish.
Sasaki’s team solved this with the molybdenum complex, which selectively accepts only the multiplied triplet excitons by flipping the spin of its electrons during near-infrared emission. If molybdenum sounds familiar, it’s because it’s the hard-to-pronounce mineral Earth AI found in its first discovery, and because it’s come up a couple of times in recent American Alchemy episodes.
There is an asterisk, for now: the process was demonstrated in solution, not in a working solar panel. It’s a proof of concept. The team’s next step is integrating the tetracene and molybdenum materials together in a solid-state system.
But the result proved that the 100% quantum yield barrier isn’t a physical law, which means the engineers can get to work sorting out the details. If singlet fission can be made to work in commercial cells, we’re going to start putting a lot more photons to good use.
Alex Konrad for Upstarts Media
In November, I released my longest company Deep Dive ever: Cable Caballero, the story of Forrest Heath III and the vertically integrated internet company he and his band of pirates are building down in Medellín, Colombia.
Explaining how he built what is now the best-performing internet in the region, and maybe the world, with its own fiber network, switches, routers, and ISP, Forrest said:
It’s been this never-ending game of doing something janky, getting credibility, doing crazier stuff, getting more resources, getting smarter people so that we can fix the things that were messed up in the janky past iteration, then gaining credibility to get more resources to get cooler people to do crazier stuff. It’s like this self-sustaining fission process.
Now, Somos has a lot more resources to hire more smart people and do even crazier stuff! This week, the company announced that they raised a $40 million Series B co-led by Bracket Capital and Ribbit Capital. Following on to not boring capital’s original investment was a no-brainer.
Somos is growing fast in Colombia, and it announced that it’s getting ready to expand into Mexico. On TBPN, Forrest even hinted at Somos Caracas…
I think this company is going to build a ton of better, faster, cheaper infrastructure in the coming decades, and they have both the fuel and the backers to do it. If you’ve been looking for a sign to put your stuff in a bag and move to Colombia, this is it.
Vamos Somos!
2026-04-02 22:01:40
Welcome to the 514 newly Not Boring people who have joined us since our last essay! Join 261,204 smart, curious folks by subscribing here:
Hi friends 👋,
Happy Thursday! I wasn’t planning on sending an essay this week. I wanted to give you a little time to breathe after World Models and Electromagnetism.
But then I saw someone make a bad point on the internet, and it was a particular bad point that has always bugged me, so I whipped up a short and sweet rebuttal. In short: not every company that burns a lot of money is the next Amazon. (a bit of a strawman, I admit, except this analogy keeps popping up!)
Let’s get to it.
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I saw an interaction on twitter the other day that I’m not going to share here because these specific people don’t deserve to be singled out because almost everyone is guilty of something similar.
Basically, one person said, “It’s amazing that OpenAI was able to raise $122 billion when they don’t have a single business that works,” and the other person replied, “Yeah they do they have a bunch of different business lines doing billions of dollars in revenue,” and the OP responded, “Yes but none of them is profitable, they’re losing a lot of money,” and the replier replied, “You could have said the same thing about Amazon!”
Amazon’s success has done a great deal of harm to a great number of companies.
Obviously, it’s done more good. AWS is a miracle. But go with me.
Jeff Bezos is a generational entrepreneur who came from a hedge fund and made a very calculated decision to lose money in the short term if it meant making more of it in the long term. In his 1997 Letter to Shareholders, his first as a public company CEO, he makes the trade-off he’s willing to make clear: “When forced to choose between optimizing the appearance of our GAAP accounting and maximizing the present value of future cash flows, we’ll take the cash flows.”
He spends his entire 2004 Letter to Shareholders walking investors through the logic.
Earnings don’t directly translate into cash flows, and shares are worth only the present value of their future cash flows. Working capital and capital expenditures matter too, and a company can actually destroy shareholder value by growing earnings if the capital investments required exceed the present value of the cash flow derived from them.
Bezos had his hands firmly on the wheel, and a negative working capital engine at his back. There are a million little details that made Bezos’ plan work, all of which, and the connections between them, were taken into consideration. Get to scale category-by-category, starting with the ones best suited to the internet, build an unmatched distribution and logistics network, drive down prices and delivery times, get more scale, grow the distribution network, drive down prices, make the “divinely discontent” customers discontent with anything slower or more expensive than what they’d come to expect with Amazon, get them hooked on Prime, paying a subscription and ordering more, keep pressing the advantage, grow FCF per share. All the while, thanks to negative working capital, growth generated cash, cash funded more infrastructure, infrastructure enabled lower prices and faster delivery, which drove more growth.
We all know the Amazon story to some extent, right? I don’t need to go into more detail than that for now. We could tell a similar story about Facebook: they had no revenue! they didn’t even have a business model!
You could, and many have, use this to justify all manner of sins in your business, in a business in which you’ve invested, or, in the case of the AI labs, in a business that a bunch of weirdos on the internet seem to feel is their duty to defend.
I am perhaps a bit sensitive to this after spending six years pre-not boring in the same industry as WeWork. WeWork lost a lot of money, and so people compared WeWork to Amazon, and maybe there’s an argument to be made that of course you need to spend a lot of money in real estate because you need to do construction and furnish spaces and buy a lot of beer and tequila upfront but then you have this whole network of long-term leases that will generate cashflow for years to come. Bezos wasn’t afraid of spending money today for cashflow tomorrow, why should Neumann be? But we often put in offers on the same spaces as WeWork, and we had these super finely tuned underwriting models, and looking at our underwriting models versus the prices they paid to outbid us on certain spaces it was clear that no matter how optimistic your monthly revenue projections, there was just no way they were going to make money on each space. That was before you took into account the custom builds they were fronting for customers who signed two-year deals (builds that would potentially need to be redone for the next one) or the 100% commissions they were paying brokers for an entire year’s worth of revenue on any customer they brought in. Adam Neumann went on Rick Rubin recently, and it was incredible and made me like him more and even made me bullish on Flow, but even Adam Neumann admitted that he let the economics get away from him in the halcyon days of 2018 and 2019.
If you had justified a WeWork investment to yourself by analogizing to Amazon and repeating “It takes money to make money,” you would have lost it all in the 2023 bankruptcy. Maybe the cleaned up company makes a lot more sense today than the bloated one did then, I haven’t looked at it so I don’t know, but if it does, it’s certainly not because it’s like Amazon.
Of course, analogies can be a useful starting point. “This thing that I might have otherwise dismissed out of hand is probably worth a closer look, because things that have looked this obviously wrong in the past have turned out to look pretty good” is a good way to think.
Uber, too, lost a shitload of money. Uber lost way more money than WeWork. WeWork lost like $2-3 billion in its worst year. Uber burned $9.1 billion in 2022. Uber’s losses made WeWork’s look like rookie numbers.
And yet… Uber is still a publicly traded company, with a market cap hovering around $150 billion.
If you’d looked at Uber and said, “Hey, Amazon lost money too, let me take a closer look,” and then realized that Uber was burning money in actually kind of the same way that Amazon was, to get its product as close to customers as possible in order to improve the customer experience, particularly if you’d looked during the depths of 2022 when it was burning so much cash, you could have made a smart investment.
Then again, using Uber as an analogy – literally, as in Uber-for-X – has kept the startup graveyard operators in business. The one successful company that could be called an Uber-for-X is DoorDash, and it worked explicitly because the team looked at Uber, said “there’s something interesting here,” and then tuned it to fit the situation at hand. Instead of competing in dense urban markets, they took the model to underserved suburbs, where competition was lower, CACs were lower, average order values were higher, retention was higher (fewer alternatives), pickups and dropoffs were easier (stores and homes have driveways and parking lots), and then, per Dan Hockenmaier, they executed relentlessly: “They made deliveries just a little faster and more reliable every week. They scrutinized the quality of every one of their restaurants and dashers. They optimized cost out of the system and gave it back to customers in the form of Dashpass (which launched in 2018 at the start of this chart).”
So are frontier AI labs good or bad businesses? I don’t know. Smarter minds than mine are doing a lot of non-analogical work trying to answer this question. The economy depends on it.
I do know that they’re not definitely bad businesses because they’re losing money.
They are certainly generating a lot of revenue very quickly, and growing at rates that are unprecedented at their scale. Anthropic grew from a $9 billion run rate at the end of 2025 to a $19 billion run rate in February (and rumors are it went much higher in March). In announcing its $122 billion fundraise, OpenAI said, “Within a year of launching ChatGPT, we reached $1B in revenue. By the end of 2024 we were generating $1B per quarter. We are now generating $2B in revenue per month. At this stage, we are growing revenue four times faster than the companies who defined the Internet and mobile eras, including Alphabet and Meta.”
To dismiss those numbers because of a little cash burn would be just as dumb as saying that cash burn is the same as Amazon’s.
On the other hand, it’s worth looking more closely at the burn to understand what you get for it.
Amazon was a high fixed-cost business with variable revenue. The more customers it served, the cheaper each marginal customer got. Each time you ask Claude to build you an app that tells you when to do your laundry, it costs Anthropic money. Each time you ask(ed) Sora to make you a video of Sam Altman twerking, it cost OpenAI money (and scarce compute that could be used for other things), which is why they shut it down. That said, margins at both Anthropic and OpenAI are improving, and with every point in margin, that variable cost problem gets less painful.
One thing to consider is that API tokens are likely a much better business because Anthropic charges based on tokens consumed. Funnily, when I asked Claude about this, it linked me to a public artifact of research someone else had done with Claude, which said that average users of Pro and Max make Anthropic money, Heavy users of Pro and Max lose Anthropic money, and the API business (which is 70-75% of revenue) produces “50–65% gross margins on Sonnet workloads and 35–50% on Opus workloads.” Caveat emptor. This is a monster business, but I wonder how much it benefits from another bad analogy: linesofcodemaxxxxxing.
In the olden days, lines of code (LOC) were expensive to produce. Only a select few even knew how. There were more problems to solve than people or LOCs to solve them, so companies would create a backlog and their engineers would crank through them by producing more LOCs. The lines of code themselves were not the valuable thing; they were valuable insofar as they were used to solve problems the company needed to solve. You could look at a successful software company, see that they’d written a lot of code, and lazily analogize: LOCs are correlated with success, lines of code are themselves a goal. Goodhart’s Law strikes again.
“You gotta be tokenmaxxxxxing,” they’ll tell you. I do wonder if this part of the business slows down once the psychosis breaks and we have maxxxxed all that we can maxxxx. At some point, when you’ve gone too deep, the ghost of Jeff Bezos appears and asks you what any of these tokens you’re maxxxxing has done for your customers.
Anyway, another thing about Amazon’s business is that while they had a ton of direct competitors - Barnes & Noble, eBay, Walmart, a graveyard of dot com competitors - they had no real competition in their strategy. If Bezos was right that getting to scale category-by-category, starting with the ones best suited to the internet, building an unmatched distribution and logistics network, driving down prices and delivery times, getting more scale, growing the distribution network, driving down prices, making the “divinely discontent” customers discontent with anything slower or more expensive than what they’d come to expect with Amazon, getting them hooked on Prime, paying a subscription and ordering more, continuing to press the advantage, and growing FCF per share proved to be the winning strategy, Amazon would emerge on the other side of all that spend as the only company with all of that in place, and with the pricing power and control over the levers of profitability that come with domination.
Uber had direct competition, but it was weaker, and Uber was making a very explicit bet that scale and network effects were all that would matter. They were right, too, and emerged on the other side of all that spend as the only company with the right network in place, and with the pricing power and control over the levers of profitability that come with domination.
Could you say the same for any of the AI labs?
We don’t have to spend a lot of time answering this. There is a lot of direct competition. The strategies seem to be very similar from the outside. Sure, different companies play with targeting different end users, and maybe OpenAI will turn ads into a big business while Anthropic owns the enterprise (although it looks like OpenAI is pushing all of its resources towards competing directly for coding and enterprise), but the core strategy is spend a lot on CapEx now to build increasingly strong models and maybe God is on the other side of all of that spend.
Ask any of the polytheistic religions whether competition among the gods is any less intense. And if we’re playing gods, Google is probably Zeus. Meta is Hermes - god of commerce, god of thieves, trickster god making everyone else’s shit more expensive. Should we do DeepSeek? Sun Wukong, the Monkey God who stole and devoured the peaches of immortality until the Jade Emperor begged Buddha to intervene, and Buddha trapped him under a mountain.
Our competition is multidenominational, and everyone is fighting with basically the same weapons. Every major lab, it seems, prays at the same altar, the Altar of Scaling Laws.
But! You say. But! Recursive self-improvement! Fast takeoff! Those tokens aren’t just producing code — they’re creating a proprietary data flywheel! There will be One True God.
Maybe!
Another reason I am allergic to some of this analogizing and extrapolating is because I have done it myself. I, too, have sinned. I have analogized crypto protocols to companies that didn’t fit just right. I have written I, Exponential and Compounding Crazy. As much as you think you love a good exponential, I can assure you I love them more. So when I ever dare question whether AI might hit a ceiling before it makes us irrelevant meatbags, and am met with the inevitable, “You don’t get exponentials! This is exactly like X! Have you even seen the Tim Urban chart?!” just know that I know these tricks. I have learned their painful lessons.
Not all exponentials are created equal. Does God think forever or does he know all in an instant?
I have been pushing back against Leopold’s assertion that believing ASI will come soon after 2027 “doesn’t require believing in sci-fi; it just requires believing in straight lines on a graph” since he first tweeted it. (to be fair, he’s made billions more dollars than me in the interim.)
Just this week, METR’s Joel Becker wrote a post attempting to provide an intuition for the “Straight lines on graphs” argument. The point is that even if it doesn’t make sense, the line will continue to go up. We’ll figure out ways. But my point is that even if the models can think longer, it doesn’t mean that we will birth God. I think we’re going to end up with really excellent software, which is great, instead of an all-knowing and all-loving AI.
AND, more relevant to the Amazon discussion, if each lab’s model can think longer and get smarter at roughly the same rate, without any clear runaway winner, then the situation is not analogous to Amazon, or even Uber, who ate short-term pain for long-term strategic solitude.
I don’t mean to pick on the AI labs, I don’t even think they themselves are the ones perpetrating this malanalogous thinking, it’s just that they’re the only thing anyone is talking about so they are the richest source of bad analogies. And I really don’t know how it’s going to play out. There is a chance we wake up in a decade and OpenAI and Anthropic are the most valuable companies in the world. There is also a chance that they are the AOLs of this whole thing. There’s a chance that the biggest business in a decade is the one that bought all the cheap tokens after the crash, the way Rockefeller bought all the excess rail capacity worth buying.
AOL and Rockefeller are analogies, too, huh? Avoiding them is hard, because they truly are useful starting points. They’re so easy to reach for, in fact, that on their own, they are at best consensus and at worst dangerous.
It’s the work you do from those starting points that will decide whether you end up the next Hummer Winblad or the next J.P. Morgan. (damnit)
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Thanks for reading,
Packy
