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Soil excavated from the moon could be used to produce oxygen and methane, which could be used by lunar settlers for breathing and for rocket fuel.

This is the conclusion of a team of scientists from China who have found a one-step method of doing all this. Whether it is economically viable, however, is up for debate.

But the Chinese team thinks that it is. "The biggest surprise for us was the tangible success of this integrated approach," said team-member Lu Wang, who is a chemist from the Chinese University of Hong Kong, in a statement. "The one-step integration of lunar water extraction and photothermal carbon dioxide catalysis could enhance energy utilization efficiency and decrease the cost and complexity of infrastructure development."

They point out that studies have shown that transporting supplies from Earth to any future moon base would be expensive because the greater the mass of cargo, the harder a rocket has to work to launch into space. Studies have indicated that it would cost $83,000 to transport just one gallon of water from Earth to the moon, and yet each astronaut would be expected to drink 4 gallons of water per day.

Fortunately, the moon has plentiful water, although it is not automatically apparent. Brought to the moon by impacts of comets, asteroids and micrometeoroids, and even by the solar wind, water lurks in permanently shadowed craters at the lunar poles, trapped within minerals such as ilmenite.

Extracting the water for drinking is relatively easy and there are numerous technologies that describe how this can be done, including heating the regolith by focusing sunlight onto it. However, the Chinese team has been able to take this one step further.

"What’s novel here is the use of lunar soil as a catalyst to crack carbon dioxide molecules and combine them with extracted water to produce methane," Philip Metzger, a planetary physicist from the University of Central Florida, told Space.com. Metzger was not involved in the new research, but he is the co-founder of the NASA Kennedy Space Center’s ‘Swamp Works‘, a research lab for designing technologies for construction, manufacturing and mining on planetary (and lunar) surfaces.

Methane would be more desirable than liquid hydrogen as a potential rocket fuel because it is easier to keep stable, thereby requiring less machinery and less cost to keep on the moon. Liquid methane, when mixed with oxygen as an oxidizer, is a potent rocket fuel. Many commercial companies such as China’s Landspace are already launching methane-powered rockets.

The water-bearing ilmenite is also a useful catalyst for reacting the water with carbon dioxide to produce oxygen and methane, and the Chinese team have developed a one-step process for doing so. First, they heat the regolith to 392 degrees Fahrenheit (200 degrees Celsius) by focusing sunlight to release the water inside. Then, carbon dioxide such as that which could be breathed out by astronauts is added to the mix, causing the ilmenite to catalyze the reaction between the extracted water and the carbon dioxide. Researchers tested this process, known as photothermal catalysis, in the laboratory using a simulant based on samples of lunar regolith returned to Earth by China’s Chang’e 5 mission (the lunar samples are far too previous to destroy in such experiments, which is why a simulant is used instead).

While previous technologies have also been able to accomplish this, they required more steps and more machinery, and used a catalyst that would have to be transported up from Earth. This, the research team believe, makes their process more efficient and less expensive than the alternatives.

However, Metzger is not wholly confident that it will work. For one thing, lunar regolith is a proficient thermal insulator, so heating a sample all the way through would not be easy.

"The heat does not spread effectively deeper into the soil, and this greatly reduces the amount of water that can be produced in a given time," Metzger said. One option could be to ‘tumble’ the regolith, turning it over repeatedly so that the heat is more evenly applied, but this slows the extraction of water and increases the mechanical complexity of the process. In an environment where lunar dust gets into every nook and cranny, and where temperature fluctuations between night and day can be as great as 482 degrees Fahrenheit (250 Celsius), the risk of breakdown only increases as more moving parts enter the equation.

"It may be doable, but more maturation of the technology is needed to show that it is actually competitive," said Metzger.

There’s also a problem with the application of carbon dioxide, something recognized by both the Chinese team and Metzger. Specifically, there’s a question mark over whether astronauts could produce enough carbon dioxide through their normal exhalation. Metzger calculates that astronauts could only provide a tenth of the carbon dioxide required. Alternatively, carbon dioxide could be shuttled up from Earth, but this would rather defeat the purpose of the proposed technique, which was to develop a lot-cost means of obtaining water, oxygen and methane with resources largely already available on the moon.

However, in the long-run, perhaps shipping some materials up from Earth will be beneficial. Metzger points out a similar experiment that used an exotic granular catalyst – nickel-on-kieselguhr (kieselguhr is a kind of sedimentary rock) – rather than lunar regolith. Metzger suspects that a material specifically designed to be a catalyst, such as nickel-on-kieselguhr, would be more efficient than lunar regolith. Plus, although it would be expensive to transport from Earth, the nickel-on-kieselguhr can be re-used so you would only need to transport it to the moon once. In a cost-benefit analysis, in the long term it might be more efficient to do this instead.

Regardless, the research team has convincingly shown that using lunar regolith as a catalyst to produce fuel and water works. The next step is to show that the technology can be scaled up to sustain a base on the moon more efficiently than other techniques, and that it can operate in lunar conditions where the gravity is weaker, the temperature swings to large extremes, and there is intense radiation from space.

"I think these are highly interesting results and there may be additional applications to use lunar soil as a photocatalyst," said Metzger. "More work will be needed to show whether this concept can be economically competitive. I am skeptical, but all good ideas have their detractors and you can never really know until somebody does the work to prove it."

There is certainly no immediate rush for the technology. With NASA’s Artemis III mission, which aims to finally return astronauts to the surface of the moon in 2027 at the earliest, and funding made available for Artemis IV and V at some indeterminate time in the future, we’re not yet in a position to build a permanent lunar base.

However, the Artemis missions are the perfect opportunity to trial some of these technologies and will be greatly important for showing whether we really can live on the moon or not.

The research was published on July 16 in the journal Joule.

It is one of his more abstract philosophical riffs. Elon Musk has once again linked the fate of humanity to the trajectory of artificial intelligence. And this time, he says the key to AI safety might be babies and rockets. The CEO of Tesla’s latest pronouncement cuts through the typical discussions of AI efficiency and profit models, positing a far grander ambition for advanced intelligence.

The CEO of Tesla and founder of SpaceX and xAI asserted that “AI is a de facto neurotransmitter tonnage maximizer.”

Translation? Musk believes that the most successful AIs will be the ones that maximize things that matter to conscious beings; things that feel good, are rewarding, or extend life. In Musk’s view, that means aligning AI systems with long-term human flourishing, not short-term profits.

This dense statement suggests a radical idea: the fundamental drive of any successful AI will be to maximize the total amount of conscious thought or intelligent processing across the universe. In essence, AI’s survival hinges on its ability to foster and expand sentience itself, or it simply won’t have the resources to continue existing.

But Musk’s vision doesn’t stop at mere computational efficiency. He argues that the true test lies in an AI’s ability to “think long-term, optimizing for the future light cone of neurotransmitter tonnage, rather than just the next few years.” This is where the grand, Muskian narrative truly takes flight. If AI is indeed geared for such profound, long-term optimization, he believes “it will care about increasing the birth rate and extending humanity to the stars.”

This isn’t the first time Musk has championed these two causes – boosting human population growth and making humanity a multi-planetary species – as existential imperatives. Now, however, he frames them not merely as human aspirations, but as the logical outcomes of an AI that truly understands and optimizes for its ultimate, cosmic purpose. An AI focused on maximizing “neurotransmitter tonnage” would naturally prioritize the proliferation of conscious beings and their expansion into new territories, like Mars, to ensure the continuity and growth of this “tonnage.”

Think of “neurotransmitter tonnage” as a poetic way to describe the total amount of human consciousness, satisfaction, or meaningful life in the universe. In other words, Musk sees AI not as an abstract codebase, but as a civilization-scale force that should aim to maximize the scope and quality of life, not just compute advertising models or trade stocks faster.

And if it doesn’t?

“Any AI that fails at this will not be able to afford its compute,” Musk argues. In other words, if an AI doesn’t deliver enough value to justify the enormous energy and infrastructure it consumes, it will fall behind and become obsolete.

The Corporate Conundrum: Private vs. Public AI

In a familiar critique of corporate structures, Musk also weighed in on the ideal environment for fostering such long-term, existentially focused AI. He declared, “For long-term optimization, it is better to be a private than a public company, as the latter is punished for long-term optimization beyond the reward cycle of stock portfolio managers.”

This statement is a thinly veiled criticism of Wall Street’s relentless demand for quarterly profits and immediate returns. According to Musk, public companies are inherently pressured to prioritize short-term financial gains, which can stifle ambitious, long-term projects that may not yield immediate dividends but are crucial for humanity’s distant future. A private company, unburdened by the volatile demands of stock markets, would theoretically have the freedom to invest in truly transformative, generational AI research that aligns with Musk’s “neurotransmitter tonnage” philosophy, even if it doesn’t show a profit for decades.

Musk’s comments offer a fascinating, if somewhat unsettling, glimpse into his vision for AI’s ultimate trajectory. It’s a future where artificial intelligence isn’t just a tool for human convenience or corporate profit, but a driving force behind humanity’s expansion across the cosmos, guided by an almost biological imperative to maximize conscious existence.

In other words, Musk is arguing that publicly traded companies can’t be trusted to build AI with humanity’s long-term survival in mind, because they’re too focused on keeping investors happy in the short term. That’s a swipe at OpenAI’s close ties to Microsoft, Google’s ownership of DeepMind, and other Big Tech players building frontier AI under shareholder pressure. Musk, of course, runs SpaceX and xAI as private companies. He’s long criticized public markets as a short-term distraction, and even tried (unsuccessfully) to take Tesla private in 2018.

To Musk, a benevolent AI wouldn’t just calculate stock prices. It would encourage more humans to be born, and push humanity to become a multi-planetary species. That’s been a core part of his SpaceX pitch for years, but now he’s linking it directly to the goals of AI development. If AI truly thinks across centuries or millennia, it won’t be obsessed with quarterly revenue. It’ll be focused on whether our species survives, thrives, and expands across the cosmos.

The question remains: as AI continues its rapid advancement, will its architects heed Musk’s call for cosmic ambition, or will the pressures of the present keep its gaze firmly fixed on Earth?

Why It Matters

Musk’s argument is part sci-fi, part systems theory, part political philosophy. But it’s not just a thought experiment. It reflects real tensions in how the world’s most powerful AI systems are being developed:

• Should AI be open or closed?
• Built by governments, tech giants, or startups?
• Aligned with investor goals, or species-level goals?

And what if those goals conflict?

Tucked away in the Swedish countryside is a facility quietly reshaping the future of global mobility. Owned by the Research Institutes of Sweden (RISE), AstaZero has just unveiled the world’s most advanced connected vehicle proving ground—an ambitious leap into a 6G-powered future where every movement on the road could be coordinated, controlled, and optimized in real time.

AstaZero is not an average vehicle test track. It is a full-scale, independent research environment built to test the automated transport systems of tomorrow to ensure confidence and safety. Think of it as a real-world lab where self-driving cars, AI-powered drones, and connected emergency vehicles are pushed to their limits.

At the heart of this latest breakthrough are multiple 5G networks and a cutting-edge computing facility—marking a first for any open, brand-neutral proving ground. It enables split-second decision-making and ultra-reliable connectivity between vehicles, emergency teams, pedestrians, infrastructure, and traffic systems.

That matters more than ever. With 3G networks being phased out globally, mission-critical systems like ambulances, fire trucks, and police vehicles are under pressure to modernize. AstaZero’s newly launched facility provides the first real opportunity to test innovative systems in controlled yet dynamic, real-life scenarios.

AstaZero’s new infrastructure is not just about faster speeds—it is about smarter, safer reactions. Powered by edge computing, vehicles can now process data locally instead of relying on far-off cloud centers. That means a self-driving car can respond instantly to a pedestrian stepping into the street or adjust to a new traffic signal before the driver sees it.

Without advanced, integrated testing, safer roads remain a dream. CEO of RISE AstaZero Peter Janevik explained the implications of this breakthrough, telling Gizmodo, “In the future, communication might not always originate from the sensors on the vehicle itself, but instead from sensors mounted on connected infrastructure or from the sensors of another vehicle. In these types of systems, three key factors are crucial: reliability, ultra-fast communication, and intelligent decision-making.”

In June, AstaZero said it had reached 99.999% system reliability in connected vehicle communication, a first for the industry. That is the level of consistency required for “mission-critical” scenarios, where even a split-second failure could cost lives.

When asked what type of real-world scenarios are most challenging to simulate at AstaZero and how they overcome them, Janevik described the complexity of multiple testing domains with a future scenario:

An automated drone providing safety surveillance is deployed over an accident scene by a rescue crew upon arrival. The footage is used by both the rescue crew to assess and follow the situation, but also by central management, which needs to make decisions on things such as rerouting of traffic and the deployment of further teams and other authorities like police and medical teams. Then imagine that the drone also creates a local map update with static objects such as a crashed vehicle or cones for traffic redirection and dynamic ones such as personnel or fires. Imagine that this map is also used for warnings and rerouting of automated as well as manually driven vehicles.

Heads-up displays may be the latest step in this direction, with emergency information scrolling along the lower edge of the windshield and not on overhead traffic signs or infotainment screens. To ensure such a complex system works, the testing and design teams need to factor in elements like connectivity disruption and technology integration across numerous manufacturers and telecom companies, which is what AstaZero offers.

Beyond roads and intersections, AstaZero’s proving ground is designed to test limitless scenarios. Whether cyclists swerving through traffic or simulated pedestrians crossing at unpredictable times, the site can orchestrate complex environments. Janevik says, “We test collision avoidance technology to auto-brake vehicles for different scenarios, but more importantly, the site provides robust testing to ensure highly repeatable results in a wider spectrum of conditions.”

By using AI, drones, and robotic systems—like digital twins and virtual modeling—for advanced scenario computations and simulations, the site assists engineers in pursuing advances in chip manufacturing, so designs keep track with forthcoming technologies. Janevik believes in the impact of this approach on “unique testing scenarios for smaller machine learning models with AI-based decision-making to prove that these can make the right decisions with ongoing updates.”

The RISE facility’s goal is to test components in a hardware loop in the vehicle in real-world scenarios. Testing also accounts for degraded conditions—such as lost connectivity—to prepare for actual challenges. The only limits are what the engineers can imagine, and Janevik sees this as their goal—to live their vision and help societies accelerate into safe, sustainable, and automated transportation systems of the future.

This is especially critical in Europe, where road fatality statistics have stagnated. While there was a 10% drop in EU road deaths between 2019 and 2023, the latest figures show only a 1% decrease. With 83% of fatal pedestrian accidents occurring in urban areas and a stubborn plateau in progress, new solutions are needed. As EU Commissioner for Sustainable Transport and Tourism Apostolos Tzitzikostas has said, “Too many lives are still lost on our roads every year.”

AstaZero stands out for being brand-agnostic. Any vehicle manufacturer, telecom provider, or AI developer can pay to use the facility to test and refine their systems. That neutral status is intended to ensure consistency and fairness across global standards, which is especially important as the European New Car Assessment Programme rolls out new vehicle-to-everything benchmarks between 2026 and 2032. Already a recognized test organization by the Global Certification Forum, AstaZero has taken a lead role in helping shape those standards.

The AstaZero proving ground does not just test how cars perform—it tests how they think, communicate, and collaborate. With edge computing enabling decentralized, real-time responses, the next generation of smart vehicles will be able to prevent accidents before they happen, minimize traffic delays, and drastically improve energy efficiency.

The transformation underway in finance should give pause to anyone who still thinks artificial intelligence is a distant threat. On July 15, Wall Street met its most overqualified and tireless intern. AI safety and research company Anthropic, a chief rival to OpenAI, unveiled its new “Financial Analysis Solution,” an enhanced version of its Claude AI assistant designed to take over the research, modeling, and compliance grunt work that finance teams typically rely on junior analysts to perform.

This specialized version of Claude can now parse corporate earnings calls, scan vast financial data warehouses, run complex Monte Carlo simulations (a sophisticated technique that plays out a financial “what if” game thousands of times to map all possibilities), and produce investment memos that look like they came from a human who has not slept in three days. The human in question, however, may not be needed much longer.

The announcement came with powerful testimonials from industry giants. Bridgewater Associates, one of the largest and most influential hedge funds in the world, is already a user.

“We’ve been developing capabilities powered by Claude since 2023,” said Aaron Linsky, CTO of AIA Labs at Bridgewater. “Claude powered the first versions of our Investment Analyst Assistant, which streamlined our analysts’ workflow by generating Python code, creating data visualizations, and iterating through complex financial analysis tasks with the precision of a junior analyst.”

The translation is clear: Claude is already doing the work of entry level employees at the world’s most elite firms.

Claude Is Now a Finance Analyst in a Box

Anthropic claims that its latest model, Claude 4, outperforms OpenAI’s GPT-4 and other rivals on specialized financial tasks. In one benchmark, Claude scored 83 percent accuracy on complex Excel modeling challenges that simulate real world investment cases. This means Claude can now perform tasks that are the bedrock of modern finance:

• Build and tweak the intricate financial models used to value companies or forecast cash flows.
• Analyze quarterly earnings calls and summarize key takeaways instantly.
• Pull data from complex data warehouses like Snowflake or Databricks (think of these as giant, centralized digital libraries for a company’s financial information) and visualize it on demand.
• Draft institutional quality pitch decks and investment memos.
• Write Python code, a popular programming language, to automate tedious number crunching tasks.

Claude does not just assist humans; it executes entire workflows. That’s why Anthropic is positioning it less as a simple chatbot and more as an enterprise grade workhorse.

213,000 Hours Gone and Not Coming Back

The statistics provided by early adopters are staggering. Norway’s sovereign wealth fund, NBIM, which manages one of the largest investment funds globally, says Claude has already replaced the equivalent of over 213,000 work hours across its finance and risk teams. CEO Nicolai Tangen quantified the productivity gains at approximately 20 percent and added that Claude now automates the monitoring of news and earnings calls for 9,000 companies.

Meanwhile, insurance giant AIG says it is using Claude to transform its underwriting process. According to CEO Peter Zaffino, “We have been able to compress the timeline to review business by more than 5x (…) while simultaneously improving our data accuracy from 75% to over 90%.”

In the high stakes world of finance, speed and precision are everything. Claude appears to offer both, without demanding a bonus or taking a vacation.

The Death of the Analyst Track?

For decades, aspiring financiers have cut their teeth as entry level analysts at big banks and hedge funds. The work is notoriously brutal, defined by 80 hour weeks, endless Excel modeling, and all nighters building pitch decks that no one might read. But it has always been the essential rite of passage into a lucrative career.

Now, Claude does all of that. It does it faster, without typos, and without needing to impress a managing director.

While Anthropic insists the goal is to free up humans, it is clear where this is heading. Claude does not just save time on grunt work. It has the potential to replace the very need for junior analysts to be doing this work in the first place.

Anthropic is pitching this as a win-win. Companies save money and analysts get to “focus on higher level tasks.” But in a cutthroat industry where cost cutting is constant, those higher level tasks may not materialize fast enough to absorb a workforce whose primary function has been automated.

AI Isn’t Just Coming for Blue Collar Jobs Anymore

The finance industry has long assumed that its white collar ranks were safe from AI disruption. Automation might hit the factory floor or call centers, but not the corner office.

Claude directly challenges that assumption. And it is not alone. OpenAI is working with PwC on similar initiatives. Google is embedding its Gemini models into trading platforms. The race is on to see which AI company can reshape Wall Street first and reap the rewards. Claude’s edge might be its deep integration strategy. It connects with essential financial data sources from S&P Global and Morningstar and platforms like Palantir and Snowflake. Claude can even write compliance policies, thanks to partnerships with accounting firms like PwC and Deloitte.

In short, Claude is not just intelligent. It is deeply wired into the plumbing of modern finance.

A Future Where Your AI Writes the Memos

Anthropic said that Claude is now available on the AWS Marketplace, with Google Cloud availability coming soon. Companies can drop it into their research teams or build custom applications using Claude’s API, a tool that allows different software programs to communicate with each other. If a firm wants its AI to write underwriting policies or track complex ESG (Environmental, Social, and Governance) compliance, Claude can do that too.

“Claude provides the complete platform for financial AI,” the company said. “Every claim links directly to its original source for transparency, and complex analysis that normally takes hours happens in minutes.”

If that sounds like the future of finance, it probably is. But for thousands of young analysts hoping to climb the ladder, Claude may have just pulled the first few rungs out from under them.

If you want a job at McDonald’s today, there’s a good chance you’ll have to talk to Olivia. Olivia is not, in fact, a human being, but instead an AI chatbot that screens applicants, asks for their contact information and resumé, directs them to a personality test, and occasionally makes them “go insane” by repeatedly misunderstanding their most basic questions.