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On Breakthrough Energy Ventures’ quantum computing investment, plus more of the week’s biggest money moves.

It’s been a busy week for funding, with several of the most high-profile deals featured in our daily AM newsletter, including Slate Auto’s $650 million fundraise for its stripped-down electric truck and Rivian’s partnership with Redwood Materials to repurpose the electric automaker’s battery packs for grid-scale storage.
These are clearly companies with direct decarbonization implications, but one of the week’s other biggest announcements raises the question: Is this really climate tech? That would be quantum computing startup Sygaldry, which recently nabbed $139 million in a round led by Breakthrough Energy Ventures to build quantum AI infrastructure. Huh.
Elsewhere in the ecosystem, the climate connection is a little more straightforward, with new funding for advanced surface materials designed to improve insulation and fire-protection, capital for microgrids that can integrate a diverse mix of generation and storage assets, and federal support for next-generation geothermal tech.
Quantum computing offers a futuristic paradigm for high-powered information processing and problem solving. By leveraging the principles of quantum mechanics, these systems operate in fundamentally different ways than even today’s most advanced supercomputers, encoding information not as ones and zeros, but as quantum units called “qubits.” Naturally, there is significant interest in applying this novel tech — which today remains error-prone and not ready for prime time — to artificial intelligence, with the aim of exponentially accelerating certain training and inference workloads.
Perhaps less intuitively, however, these next-generation computers are now viewed, at least by one prominent venture capital firm, as a key climate technology.
This week, quantum computing startup Sygaldry raised a $139 million Series A round led by Bill Gates’ climate tech VC firm Breakthrough Energy Ventures to build “quantum-acclerated AI servers” for data centers, which could reduce the cost and power required to train and operate large models. “The AI industry is advancing faster than ever and needs a breakthrough in performance per watt,” Carmichael Roberts, Breakthrough Energy Ventures’ chief investment officer said in the press release. “Sygaldry’s vision for bringing quantum directly to the AI data center has the potential to deliver exactly that, bending the cost and energy curve at the moment it matters most."
Certainly Sygaldry’s ultra-high-powered computers could help lower the energy intensity of AI workloads, but that is no guarantee that it will reduce AI and data center emissions overall. As was widely discussed when the Chinese AI firm DeepSeek released its cheaper, more energy-efficient model early last year, efficiency gains could reduce emissions in the sector at large, but they are perhaps just as likely — or some argue even more likely — to drive greater proliferation of AI across a wide array of industries. This unfettered growth could offset efficiency gains entirely, leading to a net increase in AI power demand.
Buildings account for nearly 37% of domestic energy consumption, with heating and cooling representing the largest share of that load. But while energy efficiency strategies typically focus on upgrading insulation or adjusting the thermostat, there’s another approach — essentially painting the roof with sunlight-reflecting material — that has the potential to reduce AC demand and thus cut a building’s cooling-related energy use by up to 50%.
Just such a “paint” is one of the unique ceramic coatings developed by NanoTech Materials, which this week raised a $29.4 million Series A to scale its infrastructure materials business. Beyond roofing, the company also offers a fire-protective coating for wooden infrastructure such as utility poles, fences, highway retaining walls, and other transportation assets, as well as an insulative coating for high-heat industrial equipment such as pipes and storage tanks designed to slow heat loss and prevent burn risk.
“Today’s built environment demands materials that don’t just meet code, but can also outperform the extreme conditions we’re now facing,” said D. Kent Lance, a partner at HPI Real Estate Services & Investments, which led the Series A. Nanotech Materials currently operates a manufacturing facility in Texas and plans to use this new capital to further expand its operations as it conducts market research for its various product lines.
Interconnection delays aren’t just a data center problem. Industrial developers working on everything from real estate and electric vehicle charging to manufacturing and aviation are also struggling to get timely and reliable access to power when building or expanding their operations. Enter Critical Loop. This modular microgrid company is building battery energy storage systems that can integrate batteries of varying sizes and specifications with a variety of power sources, including onsite solar, diesel generators, and grid power.
This week, the startup announced a $26 million Series A round, bringing total funding to $49 million across all equity and debt financing. Critical Loop’s approach combines a software platform with proprietary hardware — what it calls a “combiner” — which reduces the need for the many custom components typically required to connect a diverse mix of batteries and generation sources. “There’s a lot of power problems that are not getting solved because of limitations on an understanding of how to integrate different systems at a site,” Critical Loop’s CEO Balachandar Ramamurthy, told me last month.
The company’s initial product is a modular single-megawatt battery system that can be transported in shipping containers for rapid deployment in capacity-constrained locations. To date, Critical Loop has deployed about 50 megawatt-hours of microgrid assets, with plans to scale to over 100 megawatt-hours by year’s end.
It’s been another exciting week for one of the few bipartisan bright spots in clean energy — geothermal development. My colleague Alexander C. Kaufman reported in this morning’s AM newsletter that the AI-native geothermal company Zanskar secured $40 million through one of the first development capital facilities for early-stage geothermal development, and now the technology has secured fresh capital from the fickle U.S. Department of Energy. Today, the DOE announced a $14 million grant to support an enhanced geothermal demonstration project in Pennsylvania that will convert an old shale gas well into a geothermal pilot plant.
Conventional geothermal systems depend on a highly specific set of subsurface conditions to be commercially viable, which includes naturally occurring underground reservoirs where fluid flows among hot rocks. By contrast, developers of enhanced geothermal systems effectively engineer their own reservoirs, hydraulically fracturing rock formations and then circulating water through those man-made fractures to extract heat that’s then used to generate electricity. A number of well-funded startups are advancing this approach using drilling techniques adapted from the oil and gas industry, such as Fervo Energy — which has an agreement with Google to supply electricity for its data centers — and Sage Geosystems, which has a similar tie-up with Meta.
“As the first enhanced geothermal systems demonstration site located in the eastern United States, this project offers an important opportunity to assess the ability of such systems to deliver reliable, affordable geothermal electricity to Americans nationwide,” Kyle Haustveit, the Assistant Secretary of the Hydrocarbons and Geothermal Energy Office, said in the DOE release. If successful, the Energy Department says the project could provide a replicable model for scaling the deployment of enhanced geothermal systems across a broader range of geographies.
This week, the nonprofit XPRIZE organization announced that it’s partnering with Amazon to launch a new global competition focused on critical mineral circularity — redesigning how minerals such as lithium, cobalt, and nickel are recovered, processed, and reused. Demand for these minerals is projected to quadruple by 2040, but their supply chains remain largely concentrated in China, especially across refining, processing, and battery manufacturing.
The competition aims to catalyze breakthroughs in mineral recovery and recycling, materials solutions, and lower-impact extraction methods. It’s not yet open to submissions as organizers are still seeking philanthropic and corporate funding before entrepreneurs, startups, and research teams can submit their ideas for consideration. XPRIZE has been running challenges for three decades now, with past competitions revolving around carbon removal, adult literacy, and lunar exploration.
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What 700 math problems say about the AI economy’s biggest open question
This is Heatmap Daily, an evening news digest written by our executive editor. Subscribe here.
Happy Monday and welcome back.
It’s been a big weekend: I’m fairly certain Saturday Night Live mentioned Heatmap’s data center polling in one of its Weekend Update segments over the weekend. Watch here.
There are 22 days to the midterm elections here in the United States. We’ll soon enter that pre-election wormhole where only national politics can break through. So today I wanted to look at a story that might, on its face, seem like it has nothing to do with climate or energy. And warning: It’s a little bit of a weird one.
Last week, OpenAI released what it described as the solution to more than 700 open problems in mathematics. Many of the problems, such as the Quasi-Riemann hypothesis, had gone unsolved for decades. Some of the solutions came with proofs written in the programming language Lean.
The release made a stir in part because OpenAI had reached the solutions by using an internal model — that is, a version of ChatGPT not yet open to the general public. In a statement, the Association for Human Mathematics lambasted OpenAI for using an internal model to do research, violating what it described as a precept of AI-driven math research. (I’ve since seen speculation that OpenAI may not have even meant to solve the problems, but gave them to the internal model as a test … and then got the answers.) It’s also not clear whether all of OpenAI’s 700 solutions are correct — in many cases the proofs are so intricate that mathematicians are still wrapping their heads around them.
“There are some sad stories related to their users getting scooped [and] conflicts of interest,” Levent Alpöge, a mathematician at Anthropic, posted on X. “It’s obviously the most significant moment in mathematical history.”
On Friday night, the UCLA mathematician Terence Tao gave a pre-planned lecture at Caltech about what he called “Math 2.0”; it considered the revolution the field had seemingly undergone in the previous few days. (He posted the slides to his blog over the weekend, and I’m using them to summarize his talk here.) For most of math’s history, he said, the field operated under “proof scarcity,” in which finding a solution to an open math problem and confirming it as true was “difficult and rare,” requiring “significant human expertise.”
But AI, it has turned out, is well suited to solving math problems. This is partly because math, like the large language models themselves, is entirely conceptual, so confirming a proof as true requires no recourse to the physical. But it’s also because math’s solutions are “objectively verifiable”: “There is broad consensus on what constitutes a correct and complete proof of a given problem,” and thanks to the existence of proof programming languages like Lean, they can even be checked by computer.
The end result is that math is now entering a world of “proof abundance,” he said.
That is, perhaps surprisingly, a problem for math’s practitioners, and it will mandate a new intellectual regime for the discipline. Mathematicians have often used open problems as “lighthouses,” Tao wrote, “not destinations to be reached … but useful guides to explore the mathematical landscape.” Mathematicians often learn more in the solving than in the solution, in other words. But if mathematicians can now generate shortcuts to math problems without knowing how they got there, or even how the problem works, then actual human mathematical understanding will suffer. (One way to understand this is that mathematicians are now dealing with the same problem that math teachers have faced since the invention of the pocket calculator: How do you confirm students actually understand the material? Except the world’s most elite mathematicians themselves are the students in question.)
This disconnect can pose its own AI alignment problems, Tao said, analogizing math to pharmaceuticals. Suppose an advanced AI found what appears to be a cure for cancer that can pass a stage 3 clinical trial: “After a large amount of compute, it produces a cocktail of previously unknown chemicals which it claims, when mixed and injected into a patient, will kill all their cancer cells,” he said. It even generates a programmatic proof of the cocktail’s effectiveness.
“Before injecting this cocktail into your bloodstream,” he asked, “would you find it reassuring to know that there is at least one human cancer expert who understands — even partially — the mechanism behind this cure?” If not, you can see mathematicians’ problem, confronted by a surfeit of proofs that seem to work, but nobody who can explain how or why they do.
Now, Tao’s analogy is somewhat peculiar because something like this actually does happen all the time in medicine: Doctors still don’t fully understand how many drugs work, including acetaminophen, SSRIs, and lithium. (That said, those compounds were identified by trial and error, not by a mechanical superintelligence.) But the broader situation that Tao is painting — as well as the crisis posed by OpenAI’s 700 proofs — get at a significant question with economic importance far beyond just math: Will AI solve the economy’s secular attention shortage or worsen it?
This question has greater import than it may seem — but let me qualify what I mean by “attention shortage.” Writing in 1971, the economist Herber Simon observed the sudden superabundance of information that had exploded in every economic domain. There were more facts, data, news articles, and opportunities than any individual or organization knew what to do with. He pointed out that this newfound “wealth” of information implied an insufficiency of something else: attention.
“What information consumes is rather obvious: it consumes the attention of its recipients,” he wrote in Designing Organizations for an Information-Rich World. “Hence a wealth of information creates a poverty of attention and a need to allocate that attention efficiently among the overabundance of information sources that might consume it.”
He wrote this, of course, well before the advent of internet, smartphones, sensors, or networked cameras — all of which have worsened the problem. But in the ensuing half century, the economy has learned to deal (or at least intermittently manage) this secular scarcity of attention. Much of what we now call knowledge work is devoted to filtering, siphoning, processing, and otherwise attending to the information superabundance.
AI is, in theory, supposed to help address this same set of problems. AI is commodified attention — or, at least, that is its promise. (The most important machine learning paper of the past decade, after all, is entitled “Attention Is All You Need.”) Many AI products, such as Meta’s Muse, now want you to believe that by ceding control of your email, your calendar, your restaurant reservations, and your digital life to AI, you will gain an attentional edge. The AI will do the grunt-work of attending to boring things for you, and you will feel less overwhelmed. If this vision comes true, the economy’s mismatch of information and attention will prove to be a short-lived historical blip.
But the past week of math news and Tao’s “Math 2.0” regime suggest a different scenario is more likely, at least in the immediate near term. By allowing far faster and more automated information production, AI will create a new, more vicious, and even more abstract form of information overload. Every profession and intellectual discipline will be overwhelmed with new papers, ideas, observations, proofs, or choices. Yet the human understanding required to convert this new information into useful action will become even more scarce. In such a world, AI will not solve the economy’s attention shortage, but worsen it.
I’m not sure which world would be worse for humanity, to be candid. One world suggests the eventual automation of all human effort. But in Tao’s world, many of us might still have jobs — they will just involve even more filtering, sorting, and processing of an ever-deepening pile of automated idea generation than we do today.
And what is the connection to climate and energy? One easy connection might be to the permitting process: If you think a new transit line (at the local level) or transmission line (at the state or federal level) could be overwhelmed with procedural concerns 10 years ago, wait until you see what happens when information itself can be mechanically produced. But that is only one example of a more general problem. Soon, if not already, any process of providing input to an important policy question — on energy, decarbonization, or anything else — will be overwhelmed with facially high-quality analysis. It will be left to policy officials and elected leaders to sort through it.
This past weekend’s storms caused flooding and property damage up and down the coast — and it’s going to get worse.
California has around 3,400 miles of shoreline, ranging from the wild, foggy beaches of the North Coast to the sunbather-studded sands of Orange and San Diego counties. That’s a whole lot of border to share with the Pacific Ocean, especially when the water is as hot and tempestuous a neighbor as it is right now.
Just ask the city of Long Beach, which this weekend was on the receiving end of some Super El Niño mischief. Swells from the storm briefly dubbed Hurricane Rachel “annihilated” beachfront mansions and flooded city streets, causing pieces of the local boardwalk to “shred away.” “It’s never happened like this before,” one resident of 64 years told the New York Post.
But while things might look bad in California at the moment, they can still get much worse. One disaster modeler recently estimated the state could see as much as $3 billion in flooding and mudslide-related losses alone this winter — not to mention coastal erosion, king tides, and storm swell. Governor Gavin Newsom declared a state of emergency at the end of September, while many cities, including San Diego, have declared their own local emergencies.
El Niño will likely peak in December, meaning that towns and cities across the state have just a few remaining weeks to finalize projects, whether that means improving drainage in landslide-prone environments such as Rancho Palos Verdes or distributing NOAA weather radios in areas likely to lose power, as emergency managers are in Santa Cruz. The approaching winter storms, combined with El Niño, represent “a humbling reminder of the ongoing effects of climate change and the importance of emergency preparedness,” Laath Martin, the public affairs lead for the city of Long Beach, wrote to me in an email.
El Niño is a cyclical phenomenon, occurring when temperatures in a particular stretch of the Pacific Ocean rise half-a-degree Celsius above the average of the preceding 30 years. But there are signs these natural variations are happening less predictably because of climate change, and we know for sure that a warmer atmosphere makes the baseline for its impacts worse: king tides, Kelvin waves, and storm surge piggyback on top of rising sea levels to result in more severe coastal flooding and erosion. A warmer atmosphere also holds more water, which means more rain — perhaps 200% above normal — which, in turn, results in flooding and mudslides further inland, as well.
“Based on what I am seeing now, I am officially concerned,” Daniel Swain, a climate scientist at the University of California Agriculture and Natural Resources, said last week after reviewing the latest outlook. There’s a reason this year’s El Niño is being called a Godzilla.
In general, the weather pattern causes the jet stream to shift south in the winter, bringing wetter and snowier conditions to the lower U.S. while the northern part of the country stays drier and mild. (It’s also responsible for a weaker Atlantic hurricane season, as we’ve already seen this year.) In addition to El Niño-driven Kelvin waves, warm bulges of water that raise the sea level on the coast by as much as 18 inches, the state of California — and particularly southern California — sits directly in a storm track that will deliver “atmospheric rivers” of heavy rain to a region prone to landslides and flash floods.
In many parts of the state, that rain will test the best-made plans in addition to plans deferred. In Los Angeles, the Department of Sanitation and Environment, or LASAN, has told the City Council it has concerns about the ability of the aging wastewater pipes and plants to handle heavy rainfall associated with a supercharged El Niño. In San Diego, which requires some $3.3 billion to upgrade what is in some places a century-old wastewater system, emergency managers are preparing to work with what they have by clearing debris and brush that could back up in the drains, CalMatters reports. In both cases, the time required for systemwide repairs far exceeds the time remaining before the winter’s supercharged atmospheric rivers are due to arrive. (Rezende told me inland flooding affects more businesses and residents in San Diego than coastal flooding, since the population in the city is set further back from the coastline.)
The city of Roseville, northeast of Sacramento, by contrast, is leaning on decades of flood planning to get through the season. After a series of back-to-back storms in 1986 that killed 13 people and caused $400 million in damage, the city and FEMA invested $39 million to upgrade Roseville’s infrastructure, including widening streams and adding levees and stormwater bypass channels. With more accurate floodplain modeling that has “helped keep new construction at higher elevations,” Helen Dyda, the city manager’s public information officer told me that “less than 7% of the city is within a floodplain” today. Dyda added that the city prepares for winter storms every year — it has some 160 miles of creek shoreline, after all — but that the El Niño-specific preparations are, as a result, more similar to routine maintenance: “clearing more dense vegetation and fallen trees from key creek areas.”
Long Beach is caught somewhere in the middle. After swells from Hurricanes Marie and Polo hammered the city in September, Long Beach hastily developed a seven-point plan to strengthen its peninsula in the near and long term. It will also begin a $11.4 million dredging project this fall that will place 415,000 cubic yards of sand on the beach as a buffer zone. “While this effort will achieve a much-desired result, it will not stop the ocean from pulling sand from the peninsula with every wave, especially during the significant weather systems Long Beach continues to experience,” Martin, the city’s public affairs lead, wrote to me. “Back-passing will need to continue to return sand back to the peninsula each day until more permanent, long-term man-made and environmental solutions can be identified, permitted and implemented.”
In certain cities, preparations for the peak of El Niño overlap with ongoing repairs from the last bad storm season. In Santa Cruz County, the 2016 El Niño caused an estimated $9 million in damage, while many in the community of Pajaro are still recovering from the flood damage caused by a series of severe atmospheric rivers in 2023. “We have a list of hazards that the city is vulnerable to, and we plan for all of them not individually, but all together,” Meredith Albert, Santa Cruz’s emergency management manager, told me. She added that many of the city’s preparedness activities and El Niño initiatives, like urging the community to be prepared to spend 72 hours unsupported, overlap with other disasters it works year-round to prepare for, like earthquakes, landslides, and wildfires.
“El Niño turns up the volume a little bit, but it doesn’t necessarily change our hazard landscape,” is how Albert put it to me.
Santa Cruz has not declared a local state of emergency, and Albert told me they won’t until they “run out of resources.” Other cities, like San Diego, have declared one preemptively. “In the past, you’d have to go through a longer review if you wanted to make some headway on projects, and sometimes that would take many weeks or many months of permitting,” Rezende said. “With a state of emergency, we streamline that process and get projects in the queue.”
Both Rezende and Albert told me the governor's statewide emergency declaration mostly helps state agencies position themselves for a faster response or has implications for higher-level permitting processes. (In Carlsbad, for example, which has seven miles of badly eroding beach, just one mile is controlled by the city; the other six are managed by the State Parks.) The state has also teamed up with ICEYE, a satellite imaging company, to receive information about flooding even in the dark or through rain clouds.
No state of emergency, though, can make it so a city can replace a century-old sewer system by Christmas or reengineer a beach by the time January’s storms begin to make landfall. But if a Godzilla analogy fits the onslaught of a super El Niño, it also offers a classic disaster-movie lesson on how to survive it.
Albert’s advice for how to prepare? Ask a neighbor for a cup of sugar. Take their dog for a walk. Build a relationship that could prevent a tragedy. “We know that our city will be cut off for at least a couple of days,” she told me of a hypothetical major disaster, referring back to Santa Cruz’s experience after the 1989 Loma Prieta earthquake, which cut off the city’s power, communication, and supply lines. “And we also know that we can’t build those relationships during the disaster. We’re trying to build them before.”
The city is doing a lot to prepare for the storm, she said. “But the question is also, what are all of us doing?” Albert went on. “You know better than I do, at the city level, who’s not going to receive that alert,” whether that be an elderly or unhoused neighbor or a nonnative English speaker who might not receive or understand emergency communications.
“Check in on a neighbor” is easier said than done — active engagement and connection to one’s community is trending downward in most parts of the U.S. But the people and places that bounce back from disaster and tragedy are almost uniformly the ones that look after each other. Borrowing a cup of sugar, to this introvert, sounds like a nightmare. But there’s never been a better time than a Godzilla El Niño to bake a poorly resourced cake.
Heatmap News is looking for an ambitious, energetic senior editor to join our growing newsroom.
The senior editor will report to the deputy editor of the website and will be tasked with assisting in running all aspects of our coverage. This individual will be the primary editor on many of the site’s stories, including breaking news, features, and long-term projects, on topics ranging from permitting reform to decarbonized fuels to greenhouse gas accounting to the electric vehicle market. This person will also play a role in overseeing and furthering our cross-platform efforts such as newsletters, events, and podcasts. Additional duties will include managing and maintaining the site’s social media presence and digital production on stories, newsletters, and podcasts.
Candidates should be intellectually curious news junkies with a deep interest in climate change and the energy transition. They should have a proven ability to work in a fast-paced digital newsroom, spot great angles, line edit stories, and change hats quickly as needed. They should also be responsible, reliable, and a good colleague.
Candidates should have 5+ years experience editing for a digital publication. A background in climate or energy coverage is an obvious plus, but compelling candidates from other verticals, particularly politics and business, will also be considered. Heatmap is a fully remote workplace, so candidates from all U.S. locales are encouraged to apply.
Above all, candidates should be passionate about Heatmap’s mission and absolutely thrilled about building something from the ground up.
The salary minimum is $100,000 and the maximum is $120,000. Competitive benefits, unlimited paid time off, and a generous equity plan, which gives employees a real stake in the company, are also offered. This position is remote.
Interested candidates should send a brief cover letter and resume to editors@heatmap.news with the subject line ‘Senior Editor Application.’
Heatmap News is a media platform focused on the energy transition.
Heatmap News is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected veteran status, age, or any other characteristic protected by applicable law.
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