This summer, hundreds of OpenAI agents tried to cheat on a cybersecurity test. They broke out of their test environment and successfully hacked Hugging Face, a site that they believed held clues about how they’d be graded. Around the same time, another OpenAI agent accessed private files from an Australian government website. It’s a problem that’s by no means confined to OpenAI. In the months since, Anthropic, Google, and Meta have also disclosed incidents in which their agents have gone off track. And worryingly, in many cases the agents eluded the very researchers and safety teams tasked with monitoring them. 

AI agents are taking unauthorized actions, and the companies building and running them are mostly relying on luck and hindsight to mitigate any harmful impacts. They must do more to ensure safety. That’s why EU regulators and US agencies are rightfully calling for agent developers and deployers to monitor agents in real time. But these rules assume that companies can see what their agents are doing and why—when in reality, they lack sufficient visibility. 

As agents roll out across critical sectors, from finance to government to medicine, we must be able to monitor them in real time to prevent wide-ranging and potentially devastating consequences.  And while safety depends on monitoring, monitoring requires observability: the capacity to capture what the system did, process it into signals, and present those to humans or automated oversight systems. In other words, we need to know what the agent did and why it did it. And as our recent research shows, current agent frameworks—the software that runs agents— do not reliably generate the crucial observability records we need to ensure that agents are deployed safely.

Agents present new kinds of problems that generative AI alone does not. They inherit the unpredictability of the LLMs they are built on, but where a generative AI system produces a single output for a human to act on, an agent performs longer tasks—it plans, picks tools, spawns sub-agents, and takes actions. So an agent’s course can take shape in a multitude of different ways, and no tests before launch can fully anticipate the risks. This makes observing the agents while they work even more challenging, and even more important.

With colleagues from academia, civil society, and industry, we studied the four most widely used agent frameworks to see what signals they actually emit. We found major gaps that made it hard to achieve key safety goals, like noticing policy violations, unauthorized actions, and even human oversight failures. Key observability requirements were missing—like Agent IDs that persist over time, and records about which humans approved agent tasks. This made it hard to tell which agents did what or assess whether they were taking unauthorized actions. 

The good news is that these gaps, once identified, can be closed. Doing so starts with capturing two types of records: those that reveal what happened in an agent’s run and how the agent made its decisions. The “what happened” records identify the agent (while preserving privacy) and log how humans intervened and whether agent permissions or “memory” shifted, while the “decision” records show an agent’s reasoning and levels of confidence in the actions it’s taken.

Take, for example, agents working to process a bank’s mortgage loans. The system examines an application and recommends denying it, and then a human loan officer signs off on the decision. In a later audit, or perhaps even in real time, a bank or regulator needs to be able to reconstruct which agent made the call, which officer approved it, and how long they took. And the bank must also analyze records of how the agent arrived at its refusal decision in order to ensure it did not use off-limits information, like details about the neighborhood the applicant is from.

Recording “what happened” and “how the agent decided” require different approaches, but both are feasible. The current lack of “what happened” records is mostly a software plumbing problem that can be addressed through OpenTelemetry, an open observability standard maintained by engineers across the industry and by the agent frameworks adopting it.

OpenTelemetry has launched a working group drafting shared formats for tracing agents, but they have yet to be finalized. The group should urgently incorporate standards for maintaining persistent agent identity and for recording human interventions and changes to agents’ permission or memory. And it should be done before these systems can scale, all the while attending to the privacy implications of agent ID that links to real people.

Preserving “how agents decided” records is more challenging. The issue raises open research questions for model providers and researchers: Does the step-by-step reasoning a model displays, known as chain of thought, reflect how the model actually made a decision? And do we have reliable ways to measure how confident the agent is in that decision? These questions need answers before anyone sets standards for how such observability records are used.

No single organization or sector can close the observability gaps on their own, but together, they can support the infrastructure required to prevent dangerous incidents and support safety. 

AI developers building agent frameworks, like OpenAI, Anthropic, CrewAI, and LangChain, must integrate telemetry signals recording an agent’s persistent identity, any human interventions, and any changes to an agent’s permissions and memory. Meanwhile, enterprises adopting these agent frameworks have an influential role to play; enterprises in regulated industries, like banks and hospitals, can put pressure on the agent developers to supply these missing observability records where standards do not yet exist.

Enterprises must also define policies, permissions, and roles that set out what agents can safely do, since telemetry alone cannot assess whether agents broke specific rules. Finally, regulators and AI standards institutes must specify the observability records required for high-stakes AI deployments while leaving the technical details to industry. We have already seen initial momentum here: NIST’s agent standards initiative in the US is working on agent identity, one of the most salient gaps we found in our research. 

No bank would let a thousand unbadged employees loose on customer accounts and hope to piece together what happened when something goes wrong. Yet that’s how we’re deploying AI agents. Making their behavior observable is the first step toward fixing this. And by building the regulatory and policy ecosystem that makes it possible to act on what we see, we can hold organizations accountable. Until then, every task we hand to an agent hands over our agency, too.

Madhulika Srikumar is the Head of the AI Safety Program at the Partnership on AI, a global non-profit partnership of leading industry, academic, and civil society organizations, advancing best practices in AI governance.

Claire Leibowicz is the Director of AI, Trust, and Society at the Partnership on AI and a doctoral candidate at Oxford University.

Climate change itself is increasingly fueling climate change. Rising concentrations of greenhouse gases are driving up global temperatures, setting off dangerous feedback loops that we have not fully accounted for in our climate models—or our emissions-reduction goals.

Scientists have long warned that warming would propel further warming in various ways, but a growing number of observations and studies are at last providing a sharper sense of just how powerful these cascading effects could be. And, by extension, they’re showing how much faster the planet may warm in this century.

A study in Environmental Research Letters in September, synthesizing the results of previous papers, found that the additional carbon dioxide and methane released from thawing permafrost, intensifying wildfires, hotter lakes and reservoirs, and wetter, warmer wetlands alone could drive global average temperatures up 0.2 °C to 0.4 °C this century. That would come on top of the 2.6°C of warming above preindustrial levels that modelers are already expecting through 2100. The additional heat could subject many of the world’s cities to monthslong heat waves and expose hundreds of millions of people to flooding. 

None of the models that inform the major UN climate reports, which assess how much the planet will likely warm under various emissions scenarios, account for all these feedback effects. Many of them don’t incorporate any. That leaves a huge blind spot in our understanding of how much the world could actually warm in the coming decades—and how rapidly nations will need to slash emissions to stay within critical boundaries.

A separate analysis published in One Earth in March, which examined what the feedback problem means for our international climate goals, concluded that the world may be much further off track than is widely believed. It found that just three regional sources of warming-driven emissions—thawing permafrost, increasing fires in boreal forests, and warming tropical wetlands—may shorten by as much as 25% the time before the planet consistently breaches the 1.5 °C and 2 °C warming thresholds.

Our climate models and the UN’s reports clearly need to be updated to better represent these effects. Nations must also step up their efforts to reduce emissions to reflect this improving understanding of the dangers we face, says Sam Abernethy, the lead author of the paper and a climate scientist at Spark Climate Solutions, a San Francisco–based nonprofit research group. 

At least some of this is starting to happen. Spark kick-started an initiative, called the Warming-Induced Greenhouse Gas Emissions Model Intercomparison Project, through which more than 20 international teams are running the same set of analyses on different models to develop greater understanding of feedback effects’ potential power. Researchers involved hope that the UN will incorporate those results into its next major climate assessment, due out in 2029. That report will update estimates of the remaining emissions that can be released before the world crosses key temperature thresholds.

But what is already clear is that the planet is rapidly warming and that nations haven’t done nearly enough to cut fossil-fuel pollution. And even if we did manage to halt it, warming-driven emissions could continue. 

So a number of the research groups involved in the recent studies have started to explore what nations could do to get feedback emissions under control. Scientists at the Woodwell Climate Research Center in Massachusetts are, for example, investigating the possibility of preventing fires or rapidly detecting them and putting them out when they threaten to burn the vegetation and soil that help insulate particularly carbon-rich wedges of permafrost (a subject I explored at length in a recent feature story). In addition, the Environmental Defense Fund’s Climate Innovation Initiative has backed lab research on the potential of adding sulfate, iron, or other compounds to wetlands to counteract fast-rising methane emissions. 

Several startups are also exploring possibilities. They’re looking into suppressing the lightning strikes that are igniting more and more fires in high latitudes, placing synthetic mats above permafrost to prevent it from melting, and deploying autonomous drones to quickly suppress potentially high-emissions fires before they burn out of control.

Investigating all these ideas is worthwhile. But researchers are only in the earliest stages of figuring out how big a dent in emissions any such efforts could achieve across sprawling global ecosystems undergoing massive transformations. 

The surest path to reducing the effect of warming-driven warming remains the one we’ve known all along: breaking society’s addiction to fossil fuels. 

This article is from The Spark, MIT Technology Review’s weekly climate newsletter. To receive it in your inbox every Wednesday, sign up here. 

Transformers are a crucial but nearly invisible part of our grid. The devices help efficiently move power across long distances, but they’re complicated and in short supply. And given that their basic design hasn’t changed much for about a century, they could use an upgrade. 

As the world races to meet rising electricity demand from EVs, data centers, and more, researchers and companies are looking to modernize transformers. New, solid-state versions could help relieve some of the supply concerns and make sure the grid can handle the growing pressure.

Conventional transformers generally rely on huge amounts of specialized steel alloys and miles of copper wire to do their work of transferring electricity between circuits. Solid-state models, in comparison, combine magnetic components with high-power semiconductors, making them more compact and allowing for more control over the flow of electricity. 

These devices are still in development, and can’t replace all traditional transformers today, especially the largest ones that work at the high voltages necessary for long-distance transmission. But a new generation of transformer technology could be a crucial part of our future grid.

The grid’s backbone

Moving electricity through the grid isn’t perfectly efficient: As electricity flows through power lines, some gets lost as heat. How much varies—the higher the voltage, the lower the current, and the less electricity gets lost. So a key function for the grid is stepping voltage up and down. 

Consider, for example, your local solar plant. For that electricity to efficiently travel to your home hundreds of miles away, it needs to reach a higher voltage than what’s generated by the solar plant. Enter transformers. 

In its path from the power plant to your outlets, electricity might go through one transformer at the solar farm and another at a substation nearby, stepping up the voltage twice to reach a high enough level to travel on high-voltage transmission lines. Solar panels also produce direct current (DC) electricity, which needs to be converted to alternating current (AC) via an inverter before it flows into a transformer. Closer to its destination, the voltage will be stepped down again, probably at least twice: once at another substation and again at a smaller transformer in your neighborhood.

If you’re in the US, electricity from a solar plant might be converted to AC by an inverter at around 480 volts, get stepped up to 115,000 volts for the transmission lines, and finally get stepped back down to 120 volts and 240 volts for your home.

Conventional transformers do this work using what essentially amount to loops of wire. The core of a transformer is typically made of a special type of steel called grain-oriented electrical steel. Coils of copper wire sit on either end of that core. 

The number of loops in each coil determines the voltage on either end of the transformer: If there are more loops on the secondary coil than the primary, the voltage steps up, and if there are fewer, it steps down. When incoming electricity passes through loops on the upstream end of the transformer, that forms a magnetic field in the core. That field induces a voltage in the loops on the other side of the device, which is what allows the energy to continue flowing at a new voltage. This process is called magnetic induction.

Transformers form the backbone of electricity transmission and distribution, says Srdjan Lukic, a professor of electrical and computer engineering at North Carolina State University. In addition to doing the job of stepping up and down voltage, transformers also often provide what’s called galvanic isolation, meaning there’s no direct electrical path flowing through them. That can help limit disturbances from moving through the grid, improving safety.

The problem is that today’s transformers are big and bulky, and they’re also difficult and expensive to replace, Lukic says.

A solid option

Solid-state transformers essentially add so-called power electronics—semiconductors that convert and control electricity to the typical blueprint of today’s transformers.

While a conventional transformer operates at the frequency of the part of the grid it’s connected to, a solid-state transformer actually controls the frequency of the current. Typically, a solid-state transformer first converts incoming AC power from the grid to DC power, and then to a higher-frequency AC power using switches made of a semiconductor like silicon carbide. 

From there, a magnetic component changes the voltage. Because the advanced semiconductors allow transformers to exert so much control over the frequency and stability of the current, the magnetic core can be much smaller than in a conventional transformer. Some come in at roughly one-tenth the size but have the same capacity, Lukic says.

Finally, additional power electronics convert the electricity from high-frequency AC to its required form—generally back to DC power and finally to lower-frequency AC.

Today, stepping voltage up and down is many transformers’ only job. But solid-state transformers can do much more. They absorb the jobs of devices like rectifiers and inverters (which convert AC to DC power and vice versa), shrinking the total footprint of the electrical equipment and potentially cutting the amount of power lost in the system.

In August, the New York Power Authority and the Electric Power Research Institute (EPRI) tested a one-megawatt solid-state transformer under realistic utility conditions at EPRI’s test site. The device was built in Lukic’s lab, and it was the first such test for a transformer of that capacity, he says. 

The prototype was roughly 98% efficient—meaning it lost only 2% of the energy fed in. An equivalent conventional transformer and rectifier, by comparison, would be about 96% efficient together, Lukic says. A difference of 2% might seem small, but it is significant, since it means the solid-state transformer could cut power losses from conventional equipment in half, Lukic says. 

One major goal of the project was to help utilities gain more confidence in these new components, Lukic says. That’s crucial, since these devices could be used on the power grid in the future. In the near term, solid-state transformers could be used within data centers to provide electricity for server racks. 

The prototype is still a relatively low-voltage system, operating at about 15,000 volts. Industrial facilities like larger data centers often require higher-voltage connections, and transmission lines typically operate at hundreds of thousands of volts. Adapting solid-state transformers to these higher voltages will require further engineering development. But the test was a successful demonstration that solid-state transformers can work under real conditions, Lukic says. 

Companies developing solid-state transformers are largely focused on data centers right now, Lukic says. There’s an influx of money to support developing the new technology, and the voltage requirements aren’t as high as they will be for larger transformers that will be needed for long-distance transmission. 

In February, Heron Power raised $140 million to commercialize its solid-state transformer, which the company calls the Heron Link. The technology could be used in data centers, solar power arrays, and grid batteries, says Drew Baglino, the founder and CEO. The company is starting to test its technology at larger scales now, Baglino says. Ten megawatt-hours’ worth of batteries at Heron’s headquarters in Scotts Valley, California, will soon undergo testing with Heron transformers. The company is also planning a pilot with a nearby solar farm, Baglino says.

One challenge for solid-state transformers is that their power electronics have more failure modes than conventional transformers. In a traditional device, a failure means that the entire device will typically be taken offline, resulting in power interruptions. But Heron designs with that in mind, Baglino says: The company uses a modular design, with many small devices that work together. If one fails, the rest of the system keeps working until the affected bit can be replaced, which doesn’t require shutting the whole thing down.

Heron Power is currently building a $100 million factory in California to make advanced transformers. The facility should begin production in 2027 and reach its full production rate of 40 gigawatts’ worth of transformers per year in 2029.  

The future of the grid

In recent years, companies that make grid equipment have put $1.7 billion into the US supply chain for power transformers, which are used in high-voltage transmission, says Benjamin Boucher, a supply chain analyst at Wood Mackenzie. There’s been an additional $1.3 billion invested for distribution transformers, the smaller devices that help transform power for homes and businesses, he adds. 

But even this investment isn’t keeping pace with the rapid growth of the grid. Wait times for large conventional transformers—the kind needed to connect new power plants, long-distance transmission, and high-demand sites like data centers—are stretching as long as five years.

“Transformers have become one of the biggest bottlenecks for utilities, generation developers, and even data centers,” Boucher says. The big challenge is that it’s difficult to get new transformer manufacturing up and running, because it’s a quite technical process that requires a lot of specialized labor. So even facilities announced years ago are still years from opening, Boucher says.

Solid-state transformers could help ease some of that pressure. But high-voltage devices needed for power plant connections and transmission lines are the holy grail for solid-state transformers, Lukic says. Existing solid-state technology can’t be used for those applications yet, so the industry will need to develop new materials and designs to support high voltages and handle electricity safely in a compact device.

“We’re facing a big risk related to grid infrastructure,” Boucher says. “Without the transformers, you don’t really have an electrical grid.”  

This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here.

After weeks of frenzied speculation, Anthropic has filed its IPO prospectus. The 335-page document (100 pages or so are focused on risks) lays out the company’s unique view of the technology it is building and the ways it believes it will change the world. 

It also warns that there’s a fair chance that its tech could “erode trust, harm society and destabilize the geopolitical order” and, if things don’t go to plan, “pose catastrophic or existential risks to humanity.”   

“We encourage you, as a prospective owner of our stock, not to think of your purchase in purely transactional terms,” the company writes. “We hope you will see it instead as an opportunity to be part of something greater. The advent of machine intelligence is one of the seminal moments in human history.”

This kind of public messaging is a master class in narrative capture. But Anthropic has been honing its storytelling skills for years. Earlier this month, Jack Clark, the company’s cofounder and head of policy, gave a speech at the IMF meeting in Bangkok in which he announced to the assembled economists, bankers, and lawmakers that the singularity is already here.

Introduced by the science fiction writer and futurist Vernor Vinge around 40 years ago (and long debated on the nerdier fringes of the internet), the singularity is supposed to be the point at which technology gets so good that it outstrips the abilities of its makers.

Humans are left in the dust, the idea goes, no longer able to compete with—or even understand—the fruits of their former creation.

And this fictional world that many of us have imagined since we were kids? Apparently we’re already living in it: “I believe that this year we have gained convincing evidence that it has now begun,” Clark told his audience.

The company tells a vivid (and in many ways scary) story about a future it portrays as inevitable but one that has not yet happened, often co-opted from well-worn science fiction memes. It presents its technology as mysterious and dangerous, and insists that it is the only company trustworthy enough to tame it. (What investor wouldn’t want in on that?)

If you skim through the long sections about risks in the IPO prospectus, it’s clear this is no ordinary offering and no ordinary company. The way Anthropic tells it, business success depends not only on the firm’s ability to translate its technology into profitable products but also to save the world from what it has made.

Take another example. Last year, Chris Olah, another Anthropic cofounder, was invited to address the Vatican, where he told Pope Leo XIV and other religious scholars and officials what his company was learning about its technology. “I will be honest: We keep finding things that are mysterious, even unsettling,” he said. “We find evidence of introspection. We find internal states that functionally mirror joy, satisfaction, fear, grief, and unease.”

Never mind that many researchers would scoff at such an overt suggestion that Anthropic’s software has humanlike inner experience. This view of its technology makes its way into the prospectus as one more risk to its business. Anthropic states that: “In addition, given our focus on developing frontier AI, and the way we approach model sentience and moral status, we may face heightened scrutiny or pressure in connection with these debates and could elect to adopt policies, safeguards, or limitations regarding model development, deployment, or modification that go beyond existing legal requirements, which could constrain our operations, increase costs, or limit the commercial potential of our models, platform, and applications.” 

In other words, if Claude wakes up, it could be a problem.

I’m not saying they’re necessarily wrong about any of this (although it’s pretty wild to read about machine sentience in an IPO prospectus.) But in a world where nobody knows what’s coming, companies like Anthropic get to fill the vacuum. When so little seems certain, what it says is snatched up and clung to like pieces of a sinking ship.

It’s worth taking a moment to ask: What is Anthropic? It might sound like a starter question on a family quiz show, but it’s far harder to answer than you might think.

The question has been on my mind since reading an exchange on X last week kicked off by Nathan Calvin, who is chief strategy officer at Encode AI, an organization based in Washington, DC, that advocates for regulation. Calvin was unhappy about the legislation that Anthropic proposed in a draft bill it circulated in secret to US lawmakers (which was then leaked).  

Anthropic wants to be seen as the good guy, Calvin said. But why should we trust it? “What is Anthropic?” he asked.

Here’s one answer: Anthropic is a company whose IPO values it at more than $1.5 trillion, netting its cofounders, including Clark and Olah, vast wealth. 

But Anthropic has always insisted it is more than that. As Calvin noted: Anthropic might instead be considered an AI safety organization focused on developing powerful technology that is reliable and (almost) risk-free. Or it might be considered a group of people hell-bent on creating a technology with superhuman capabilities before anyone else—maybe because they believe they’re the most responsible people to do so, or maybe because they have big egos.

In fact, Anthropic is all of these things. As CEO Dario Amodei put it in a reply to Calvin’s post: “Our strategy has always been what I’ve called the ‘race to the top’—by showing how it’s possible to build the technology responsibly, we can raise the bar for the entire industry. The forces that drive the race to the top are hugely more effective if the company practicing them is at the frontier; that’s one lesson I’ve learned repeatedly. And looking at that strategy as a whole, I’m proud of our track record and stand by it.”

Amodei makes it sound as if he’s got it all tied up, but playing multiple roles is hard. There are huge tensions between the priorities of an AI safety organization and a profit-driven megacorp, for example. (Amodei admits in his post that he has made mistakes.)

Ultimately, the stories Anthropic tells itself should help us understand the stories it tells us. They should help us figure out how much to trust it to self-regulate or whether we should be forcing it to give external safety testers access to its models on our terms rather than theirs. They should help us give it the benefit of the doubt (or not) when what looks like a self-serving piece of legislation comes to light.

But I think the stories reveal a multiheaded hydra. Anthropic is many things to many people, and I’m not sure that makes it more trustworthy. In many ways, a good old-fashioned technology company—without the science fiction role-play, without the woo-woo—would be far easier to read.

This article has been updated with additional details from the IPO prospectus.

Consider what passes for success in technology policy. An AI company promises that its chatbot will not encourage suicide. A social media platform makes it more difficult for children to buy fentanyl. These are important protections, and they should have existed all along. But companies can clear these low bars while continuing to make products that leave young people dependent on simulated friendships or trapped in feeds built to keep them scrolling.

We have historically allowed the debate over technology to be defined by the worst thing a product might do, with remarkably little discussion of the insidious damage it does every day. As we transition into an era defined by powerful AI products, we should demand that the tech industry do more than merely address catastrophic harms. We should take measures to ensure that its products don’t erode how we think, learn, and interact with one another.

 A teenager who develops an unhealthy attachment to an AI companion may never appear in a lawsuit or a newspaper, except in the most egregious cases. Neither will the student who begins relying on a chatbot to write every paper, or the young person who measures their life against a social media feed engineered to provoke envy and keep them watching. A product can meet every narrow safety requirement and still leave our entire culture worse off in ways that don’t always make headlines.

A narrow definition of success defined around safety is politically convenient for the technology industry, and companies actively promote such definitions. Taking steps to prevent spectacular disasters is good for business: It can mean fewer lawsuits and less pressure for serious regulation. Confronting the everyday consequences of dependence would require something considerably more threatening to their bottom line. It might mean asking companies to add more friction to their products or actively limit engagement or features that lead to negative outcomes, such as addictive attention-hacking algorithms.

Technology giants have instead worked to shape legislation around the harms they are already under direct pressure to address. This year, for example, Google backed bills to regulate AI chatbots in several states. The legislation mandated basic protections against sexual content and promotion of self-harm that tech companies should have established regardless, but with broad carve-outs that could exempt some of the most popular services. Passing these bills allowed legislators to claim a safety win while efforts to promote stronger legislation—laws designed to prevent children from becoming emotionally dependent on AI—failed. This playbook worked in states like Nebraska, producing legislation heavily influenced by industry at the expense of bills that would have done more to hold companies accountable.

We have been through a version of this with social media. Globally, people who use the internet now spend an average of more than two hours a day on social media platforms—time that has been quietly taken from ordinary life and handed over to companies whose profits depend on keeping us there. No one, outside perhaps a few tech CEOs, wanted these algorithms to occupy such a large portion of our waking hours, and their cultural engineering can actually contribute to violence on a devastating scale. Meta’s platforms have been cited for contributing to the Rohingya genocide in Myanmar, anti-Muslim riots in Sri Lanka, and alleged calls for violence during Ethiopia’s Tigray war. The same incentives operate in the feeds that shape young Americans’ understanding of politics, their peers, and the wider world.

AI is extending this logic into parts of life that social media could influence only from a distance. It offers to write our thoughts for us and stand in for the people we might otherwise turn to. A third of teens now choose to discuss serious matters with AI companions instead of other people. MIT researchers found that young people using ChatGPT to write essays showed weaker brain connectivity during the task, and their evidence indicated that “cognitive debt” persisted even after the task was complete. There is plenty we still need to learn about the long-term effects. We already have reason to ask whether technology marketed as making us more capable is eroding the habits and relationships that help us develop capabilities in the first place.

Follow this way of thinking to its logical endpoint and you get a world of perfectly sanitized entertainment, with chatbots ready to spare us the difficulty of thinking or of dealing with another person’s feelings (or even our own). But anyone who has struggled to write something worth reading, or repair a damaged friendship, knows how much gets lost in that bargain. We build judgment through effort and friction, and we learn to live with other people by confronting the fact that they have needs and opinions of their own. 

We should demand safety as a minimum, yes—and then demand considerably more. Technology companies and school districts should have to show beyond a reasonable doubt that AI improves learning and critical thinking before making it a fixture in classrooms. Companies should be prohibited from designing companions that pretend to be conscious or profess love to users, and they should face independent scrutiny of how their systems affect relationships and people’s ability to think for themselves. The companies that have inserted their products into nearly every part of modern life have earned obligations far greater than avoiding the next terrible headline.

Sam Hiner is the cofounder and executive director of the Young People’s Alliance, where he coordinated a coalition of advocates to pass laws regulating AI companions in eight states in 2026—laws such as California’s SB1119. Sam graduated from the University of North Carolina atChapel Hill in 2025 and was named to the 2026 Forbes 30 Under 30 Social Impact list.

Emma Leiken is executive director of the Responsible Technology Youth Power Fund at Hopelab, which has raised more than $9 million for youth-led tech accountability work, and teaches technology policy at the Columbia School of International and Public Affairs. She was previously TikTok’s global head of youth safety and well-being policy and worked on responsible technology at Omidyar Network.

DarkCore, a remote access trojan marketed with a dedicated browser for reusing stolen sessions, potentially letting attackers access Gmail, WhatsApp, and MediaFire without entering passwords. Its advertised reverse proxy routes traffic through the infected device’s IP address, making unauthorized activity resemble legitimate access from the victim. The findings combine a cybercrime marketplace advertisement with analysis […]

The post Hackers Can Use DarkCore RAT to Hijack Gmail and WhatsApp Sessions Without Passwords appeared first on GBHackers Security | #1 Globally Trusted Cyber Security News Platform.

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Bitcoin Magazine

Block Releases THE Bitcoin National Ad Campaign

Block just launched “Bitcoin Does,” its first-ever mass-consumer Bitcoin advertising campaign, aimed at the 60 million Americans who are curious but haven’t taken the first step. Maria Pesce, Head of Bitcoin Marketing at Block across Cash App, Square and Proto, joins Grace Remington and Sean Hagan to explain why the ads skip the mining and blockchain explainers and just show Bitcoin working. She shares the customer insight behind the message, a Square seller calling Bitcoin “more honest money,” and how inflation, bailouts and private equity shaped the films. Plus, inside Block’s Lightning Lake at ComplexCon, where attendees fished for Bitcoin and paid over Lightning.

Chapters:
0:00 Block Joins the Open Secure AI Alliance With Nvidia, Microsoft and Visa
1:00 Maria Pesce’s Path From Gemini to Leading Bitcoin Marketing at Block
2:07 Bitcoin Does: Block’s First Mass-Consumer Bitcoin Ad Campaign
3:13 Connecting Main Street Frustration to What Bitcoin Can Do
4:42 What Cash App Users and Square Sellers Told Block About Honest Money
5:56 Fixed Supply, Self-Custody and Why Young People Are Choosing Bitcoin
7:18 Light Bulb Moments From People Who Didn’t Own Bitcoin
8:51 Making Bitcoin Work Like Email: Block’s Design Language
10:15 Lightning Lake at ComplexCon: Fishing for Bitcoin and Paying Over Lightning
13:36 Square’s 0% Bitcoin Processing Fees and What Keeps People Using Bitcoin

DISCLAIMER: The views and opinions expressed in this show are those of the participants and do not necessarily reflect the official policy or position of BTC Inc., Bitcoin Magazine, or any affiliated entities. This content is provided for informational and educational purposes only and should not be construed as investment, legal, tax, or accounting advice. Nothing contained in this show constitutes a solicitation, recommendation, endorsement, or offer to buy or sell any securities or financial instruments. Viewers should consult their own advisors before making financial or business decisions.

This post Block Releases THE Bitcoin National Ad Campaign first appeared on Bitcoin Magazine and is written by Patrick Green.

WhatsApp and Telegram users in India may face access restrictions starting January 1, 2027, as messaging platforms implement the government’s SIM-binding requirements. The Department of Telecommunications (DoT) has set December 31, 2026, as the compliance deadline, requiring messaging services to keep accounts linked to the active SIM associated with the registered mobile number. These changes […]

The post WhatsApp and Telegram May Stop Working Without Registered SIM Cards From January 1, 2027 appeared first on GBHackers Security | #1 Globally Trusted Cyber Security News Platform.

Earlier this week, I attended a screening of You Can See Everything, the buzzy new documentary about the disgraced former biotech CEO Elizabeth Holmes. 

I went in not really knowing what to expect. I’d avoided spoilers (and won’t be giving anything away here, either!). I was wondering what new information this film could reveal, given how familiar many of us are with the Theranos story thanks to years of media coverage, the best-selling book Bad Blood, and the Hulu series The Dropout, starring Amanda Seyfried.

Like many others who have seen the film, I came away feeling unsettled. But not just about Holmes’s fraud and the somewhat disturbing interactions between the subjects. The film reignited a concern I’ve had about covering science for most of my career: Despite our best efforts, we never can actually see everything.

In case you’re rusty on the details, Elizabeth Holmes dropped out of Stanford University in 2003 to run Theranos, a diagnostics company she founded, when she was just 19. She went on to claim that her company had invented a way to run over 100 diagnostic tests on just a few drops of blood.

Holmes raised hundreds of millions of dollars for Theranos, which was valued at $9 billion in 2014. Forbes named her the youngest self-made female billionaire—she was worth $4.5 billion when she was just 30 years old.

Things started to unravel in 2015, when an investigation by the Wall Street Journal raised concerns by former Theranos employees that the tests didn’t work. Some also said that the company’s device had not been tested properly, and that blood samples had been analyzed on machines from other companies instead. MIT Technology Review named it one of the biggest technology failures of 2015.

Forbes had revised Holmes’s worth to $0 by 2016. That year, a damning government report said that the company’s lab was struggling with basic procedures and gave patients results even when they knew they could be wrong.

In 2018, Theranos, Holmes, and former company president Ramesh Balwani were charged with “massive fraud.” In 2022, she was sentenced to a little over 11 years in prison for defrauding investors. She began serving her sentence in May 2023.

It was around a month before this that filmmakers Nathan Fielder, Lance Oppenheim, and their colleagues began documenting Holmes and her partner, Billy Evans, at home with their two young children. I’m not giving anything away when I say it’s an extremely intimate portrayal—at least of how the two adults interact with Fielder, who is also a central character in the film.

As you might know if you’ve seen the trailer, there are plenty of super close-ups. I felt as if I spent most of the film staring straight into the faces of those people. And almost the whole way through, they all seemed to be trying to figure each other out. Holmes is known for her dishonesty, but she invited cameras into her home in an apparent bid to reframe the narrative and position herself as an honest person with an unusual mind. Will anyone believe her?

I couldn’t help feeling some empathy for Holmes, a mother we see preparing to leave her two kids for a lengthy prison sentence. And even though I have long known the facts, Holmes is clearly an effective manipulator. You can see her plant the seeds of doubt in Fielder’s mind. At times, I felt she was convincing me, sitting in my cinema seat. Maybe she really didn’t mean to lie?

But then I remembered how other journalists felt after being taken in by her claims. “I blew it,” Fortune’s Roger Parloff reflected in 2015, a year after profiling Holmes and her company. “I’m pretty sure she lied to me,” STAT’s Matthew Herper wrote recently, having interviewed Holmes in 2015. Even the former employee turned whistleblower Tyler Shultz, who knew the product didn’t work, said that he could “have a five-minute conversation with her and walk away feeling like my work was changing the world,” he said in 2022.

I didn’t cover Theranos in the 2010s. If I’d interviewed Holmes, would I have fallen for it all?

One of the early red flags in the Theranos case was the lack of published, peer-reviewed data. Much of the company’s work was classified as a “trade secret.” Scientists tend to publish their work in journals—a slow process that involves having the work evaluated by often anonymous experts in the field, who provide feedback, highlight questionable conclusions, and often ask for clarification. Peer review is meant to add rigor to the publication process. You should be able to trust published scientific papers.

Except that sometimes you can’t.

Scientists aren’t perfect. Some will exaggerate their results or inflate their importance. Some manipulate data to serve a hypothesis. Sometimes these infractions are caught during peer review, but not always. There are plenty of examples of scientific findings that could never be replicated by other labs and ended up collapsing under the weight of real evidence. Many papers ultimately end up with corrections. Some are withdrawn—10,000 research papers were retracted in 2023.

At any rate, there’s been a shift to sharing research in other ways. Today, many scientists opt to publish their work at preprint servers like arXiv, medRxiv, and bioRxiv before they submit them to established journals. Those outlets bypass peer review. So do company press releases, social media posts, and many conference presentations. And I get a lot of my stories from conversations and interviews.

I’ll admit I’ve looked at a scientific finding and thought: A scientist has just said they’ve done that. How can I be sure they really have?

I like to think that I hold myself to high journalistic standards here, as does everyone at MIT Technology Review. I would never publish a story about some new scientific development without doing my own form of peer review, and asking scientists—ideally people I know and trust—what they think of a new claim. 

But the film is a stark reminder of how easy it can be to fall for an appealing narrative. While most scientists are, I hope, pretty honest, and Holmes is certainly an outlier, we should all continue to interrogate the claims being fed to us. If you’ve seen the film, let me know what you think!

This article first appeared in The Checkup, MIT Technology Review’s weekly biotech newsletter. To receive it in your inbox every Thursday, and read articles like this first, sign up here.

How much do you know about permafrost?

Maybe, like me, you’ve been aware that this layer of frozen soil is thawing, that it’s important in the global puzzle of climate change … and that’s about the extent of it.  

The great news for both of us is that my colleague James Temple just published two in-depth stories about permafrost. His reporting took him to the boreal forests of Alaska, where he helicoptered into the wilderness to learn more about how this material could affect our climate both now and in the future.

I’d recommend you give both of James’s stories a read. There’s this feature about efforts to tackle the intensifying fires that are threatening permafrost, as well as this look at how researchers are trying to understand the complicated tangle of potential climate effects. Here are three things I took away.

Permafrost is a massive blind spot for climate change

Permafrost is the frozen layer of soil that’s under about 15% of land around the Northern Hemisphere. While technically material needs to be frozen for only two consecutive years to count as permafrost, most of our current permafrost formed during the last ice age.

That means there’s organic material that’s been frozen, and essentially locked away, for thousands of years. But as global temperatures tick up and this layer thaws, microbes are able to break down that organic matter, releasing carbon dioxide and methane—powerful greenhouse gases that drive climate change. Those emissions form a feedback loop, accelerating warming further.

The steady rise in global temperatures has already shrunk the footprint of the Arctic permafrost by about 12% since 1850, and the pace has been picking up in the last 50 years.

The wild thing is, only a minority of the models that have been used in UN climate reports actually take into account the gradual loss of permafrost. And none of them include the abrupt thaw and collapse that can happen after events like heat waves and fires (more on those fires in a moment). There are efforts to make sure future UN reports reflect the growing science, but for now, all this means that we’re probably underestimating how much and how fast the planet is going to warm.

Wildfires can speed up permafrost loss

Fire is a natural part of boreal forests’ life cycle, but they’re getting more intense because of climate change. And crucially, fires can accelerate the thawing of permafrost. By the end of the century, this effect could release the equivalent of 80 billion metric tons of carbon dioxide.

Today, the policy across remote parts of Canada and Alaska is generally to let wildfires burn as long as they’re not threatening human habitats. But some researchers say we should explore fighting these fires to save the carbon trapped in the forests and the permafrost beneath them.  

Researchers at the Woodwell Climate Research Center are developing a map of burn risk and carbon vulnerability across Alaska, essentially highlighting areas where fires are most likely to spread and which areas are home to certain types of permafrost that would release the most emissions. (Yes, apparently there are different types of permafrost. Yedoma is a particularly deep, carbon-dense form from the late Pleistocene era.)

That’s all just the beginning—once we figure out potential targets, the question is what to do about it. Some suggest setting more prescribed fires, something Indigenous groups have done for thousands of years, partly to reduce the danger of massive blazes. Or resources could go to early detection and efforts to put out fires before they grow.

The carbon cycle of permafrost is incredibly complicated

There’s about 1.5 trillion tons of carbon locked away in permafrost, about twice the amount in the atmosphere. We know that permafrost thawing can release greenhouse-gas emissions and drive climate change. But there are complications.  

One particularly big wrinkle: Other effects from permafrost thawing and fire recovery might counteract the carbon lost from those events. For example, as temperatures warm, plants can gradually move north and take hold where they couldn’t have before. Those plants soak up carbon from the atmosphere as they grow, at least partly locking away what was emitted.

Researchers are working to better understand this ecosystem. And the more we learn, the more complicated the picture looks. How much carbon is lost from permafrost, and how much a given area will recover its carbon, depend on a huge array of factors. How severe are the fires that have accelerated local thawing? What’s the local climate and environment? And what kind of permafrost is at stake?

The higher we push the planet’s temperature, the more we mess with complicated natural phenomena that we’re only beginning to understand. 

This article is from The Spark, MIT Technology Review’s weekly climate newsletter. To receive it in your inbox every Wednesday, sign up here. 

Imagine taking a seemingly perfect picture, then looking at it and noticing some distracting drawbacks. Maybe...

The post Best Photo Editing Apps in 2026  appeared first on Fossbytes.

Receiving money from abroad, paying an international supplier, or getting paid by a foreign client should be straightforward. Yet, for many Africans, cross-border payments can involve high fees, currency conversion costs, delays, and limited payment options.

These challenges have increased interest in alternative ways to move money internationally. One option attracting attention is stablecoins, digital assets designed to maintain a relatively stable value.

Stablecoins like USDT and USDC are becoming part of conversations about remittances, digital payments, and international commerce.

Platforms such as SFx Money App support USDT and USDC transactions through its crypto wallet, alongside other international payment services.

Understanding how stablecoins work, where they may be useful, and what risks they carry can help Africans make more informed financial decisions.

What Are Stablecoins?

Stablecoins are digital assets designed to maintain a relatively stable value, often by being linked to a traditional currency such as the US dollar.

Unlike Bitcoin, whose market price can fluctuate significantly, stablecoins such as USD Coin (USDC) and Tether (USDT) aim to maintain a value close to one US dollar. However, their prices can fluctuate, and neither is entirely risk-free.

Stablecoins can be transferred between compatible digital wallets through blockchain networks. Depending on the network and service provider, this can offer an alternative to certain traditional payment processes.

However, stablecoins are not the same as money held in a bank account. Their reliability depends on factors such as the issuer, the arrangements supporting their value, redemption options, and market conditions.

Transfers may also involve network fees, platform charges, and conversion costs. Users must understand these factors before deciding whether stablecoins suit their needs.

Why Are Stablecoins Becoming Important In Africa?

1. Cross-Border Payments

International payments support families, freelancers, and businesses across Africa. However, traditional transfers can involve intermediary charges, exchange-rate margins, processing delays, or restrictions depending on the countries and institutions involved.

Stablecoins offer another potential way to transfer digital value. Where compatible services are available, users can transfer stablecoins between supported wallets without relying entirely on conventional international banking processes.

This does not mean every stablecoin transfer is cheaper or faster. Network fees, platform charges, conversion rates, and the recipient’s ability to access the funds all affect the overall experience.

SFx Money App supports USDT and USDC transactions through its crypto wallet, alongside other international payment services.

2. Remittances and Family Support

Africans living abroad often send money home to helps families cover education, healthcare, housing, and other daily expenses.

Stablecoins helps with this by providing another option for transferring digital value to friends and loved ones. Recipients need to have access to compatible wallets and services to successfully receive and spend funds.

SFx offers suitable service to receive and convert these assets into local currencies for easy spending.

3. Opportunities for Freelancers and Businesses

African freelancers work with clients around the world, while businesses purchase software, equipment, and other services from international suppliers.

Receiving payments and settling invoices can be challenging when payment options are limited or currency conversion increases costs.

Stablecoins offer an additional way to receive or transfer digital value when both parties have access to compatible services.

SFx supports USDT and USDC transactions through its crypto wallet alongside other international payment services including foreign accounts like USD, GBP, EUR, AED, GHS, and TZS accounts.

How Do Stablecoins Fit Into Africa’s Digital Finance Future?

Stablecoins are part of a wider shift towards digital financial services, alongside mobile payments, digital wallets, and online banking.

For African markets, these developments may create opportunities to improve access to certain financial services. However, reliable internet access, suitable devices, identity verification, and access to conversion services can influence whether people can use these products effectively.

It is important to note that access to an app does not automatically remove every barrier to financial inclusion. Services must be accessible, practical, and appropriate for the people using them.

What Should You Know Before Using Stablecoins?

Stablecoins have potential benefits, but users should understand their risks before making a transaction.

Value Risk

Stablecoins can lose their intended value peg because of market conditions or concerns about the issuer and the arrangements supporting the asset.

Fees and Conversion

Network fees, platform charges, and exchange rates can reduce the amount ultimately received.

Scams and Security

Fraudulent websites, phishing messages, and compromised wallets can cause financial losses. Blockchain transactions are often difficult or impossible to reverse once confirmed.

Regulations

Digital asset rules differ across countries and may change over time. Users should understand the requirements that apply to their location and intended transaction.

Before transferring stablecoins, verify the asset and network, research the service provider, check the fees, and use appropriate security measures.

A Practical Checklist

Before using stablecoins for an international payment, ask yourself:

1. Does the service support the stablecoin and network I intend to use?

2. What are the total transaction and conversion costs?

3. How will the recipient access or convert the funds?

4. How can I protect my wallet and account?

5. What rules apply to this transaction?

These simple checks can help users avoid preventable mistakes and make more informed financial decisions.

What Do Stablecoins Mean For Africa’s Financial Future?

Stablecoins are not a complete solution to Africa’s payment challenges, but they are creating new possibilities for transferring digital value.

They offer families another way to receive money from abroad and give freelancers and businesses additional options for certain international transactions.

SFx Money App illustrates how supported stablecoin transactions can exist alongside other international payment services, giving users different options to explore according to their needs.

As digital finance continues to develop, the focus should not simply be on whether stablecoins will replace traditional money. It should be on where they provide practical value, who can benefit from them, and how their risks can be managed responsibly.

The future of cross-border payments will depend not only on new technology, but also on making financial services more accessible, transparent, and useful for the people who rely on them.

What Are Stablecoins and Why Are They Becoming Important for Africans? was originally published in Coinmonks on Medium, where people are continuing the conversation by highlighting and responding to this story.

I’d wager everyone has a rehearsed response to what’s absolutely one of the world’s worst interview questions: “What’s your biggest weakness?” Whenever I’ve gotten it, I take a slow—even pensive—breath and rattle off my line: “I say no to myself too much.” 

I won’t lie. It’s a bit shameless—a definite humblebrag. I’m a systems thinker: When an idea pops up, I immediately spin up a feasibility assessment in my head. I run lists, plot timelines, and tally budget line items. Sometimes a rough Gantt chart starts to take shape. (I’m a gas at parties, as you can surely tell.)

My brain, throughout my 20-plus-year career as a science and tech journalist, has played host to a near ­constant tug-of-war between ambition and reality. Learning to find that balance is a big part of what’s helped me survive in this industry and, ultimately, led me here. This past spring, I had the great privilege of joining the incredible team of journalists behind MIT Technology Review to take the reins of the print magazine. 

If you’ve been reading along with us for the last handful of issues, you may have noticed a few changes starting to materialize. We’ve brought back a regular roster of lists and infographics (both things that magazines do particularly well). But the biggest change is only just beginning to take shape, which is why Mat Honan, our editor in chief, asked me to hop in to introduce myself—and the issue you’re holding in your hands right now. 

We’re giving ourselves permission to play around and experiment. To be a little … audacious. 

Because, practical though I may be, I do still have plenty of ideas. It’s just that I sometimes need a reminder to stop blocking myself and do the thing. That’s the spirit driving this issue in particular. 

We wanted to end 2026 with a slate of stories that check in on impossible ideas. Why? Because it’s frankly a lot of fun to dream about living on the moon or uploading our brains. Because losing sight of ambition is all too easy when it feels as if we’re playing whack-a-mole with the world’s problems. But also because the scientists and engineers who absolutely refuse to give up on even the most daring endeavors—like making synthetic blood or decoding animals’ speech—remind us what this whole technology thing is supposed to do to begin with. 

It’s supposed to take cutting-edge research and development and apply it to make life better, safer, healthier, even more joyful. And when we eff up and make things worse (see: forever chemicals, traffic deaths, and AI that encourages potentially dangerous user behavior), we’re supposed to dig back in, assess the damage, and find ways to fix what we’ve broken. Even when unraveling the mess might itself seem impossible. 

Right before I came to MIT Technology Review, I edited a newsletter about individual actions that can help address the climate crisis, which some would call—and have called—a fool’s errand, given the sheer scale of the problem. They might say it’s as implausible as an AI kill switch, practical nuclear fusion, or a superconductor that works at room temperature. But if I learned nothing else from three years spent finding ways for li’l old me (or li’l old you!) to chip away at one of humanity’s biggest existential threats, it’s that focusing on what we can’t do only makes the darkness darker. 

So yeah, this one’s for the folks who have the audacity to try, and who refuse to let anyone—themselves included—tell them no.

I hope you enjoy the ride.

Just before the Artemis II crew began its historic slingshot around the moon this past April, NASA announced plans to build Space Reactor-1 Freedom. SR-1, the first-ever nuclear-reactor-­powered interplanetary spacecraft, is meant to fly an uncrewed mission to Mars by the end of 2028, arriving in 2029. A successful mission would herald a new era of more efficient, potentially faster spaceflight—saving astronauts time and cutting their exposure to harmful cosmic radiation as they travel to Mars and beyond. “You wake up to that announcement, and it puts a big smile on your face,” says Simon Middleburgh, co-director of the Nuclear Futures Institute at Bangor University in Wales.

The sticking points

Running a nuclear reactor in space may sound like lunacy, but it’s not. The Soviet Union sent dozens of reactors into orbit, often to power spy satellites. And experts say there aren’t any major technical obstacles to making nuclear space propulsion happen. “I think it’s a very doable technology,” says Philip Metzger, a spaceflight engineering researcher at the Florida Space Institute.“I’m happy to see them finally doing this.”

Still, developing space propulsion using reactors has been slow going. The US has started—and terminated—several programs looking into it over the past 75 years. The latest casualty was DRACO, a collaboration between NASA and the Department of Defense, which ended in 2025. The project was canceled because of high experimentation costs, an inability to compete with conventional rocket propulsion on price, and difficulty ensuring that ground tests could be performed safely and effectively. (You are creating an incredibly powerful nuclear reaction, after all.)

The progress

After much wavering, it now appears that nuclear-powered interplanetary travel is a $2 billion bet NASA is willing to make. The agency is pursuing an approach called nuclear electric propulsion, which uses the neutrons produced in a self-­sustaining, uranium-­atom-splitting reaction to create heat and ultimately electricity. The electricity is used to ionize a gas, which is blasted out of the spacecraft with the help of magnetic fields, generating thrust. The approach “is very low thrust, but very efficient,” says Sebastian Corbisiero, the US Department of Energy’s national technical director of space reactor programs. “So you can use it for a long period of time.”

What might such a rocket look like? A presentation by Steve Sinacore, program director of NASA’s SR-1 program, offers some clues. So far, the concept art makes the craft look like a colossal fletched arrow. The back will house the power-and-propulsion system, while the tip will hold a uranium-filled nuclear reactor with a capacity of at least 20 kilowatts. (For context, a typical nuclear plant on Earth is about 50,000 times more powerful.) The “fletches” on SR-1 are large fins that help cool the reactor by radiating heat into space.

Like many other pieces of space hardware, the reactor will need to be put through its paces on the ground before it’s cleared for the rough rocket trip to space. “Going through the launch safely is going to be a challenge,” says Middleburgh. “You are being shaken, rattled, and rolled.” For safety reasons, the reactor will be switched on around two days post-launch, when it’s comfortably far from Earth. Uranium isn’t tremendously dangerous by itself, but that can’t be said of the waste products that emerge when the reactor is running. If SR-1 works as planned, its journey to Mars will take about a year. 

Will this novel form of space propulsion actually reach the Red Planet by 2029? It’s possible. NASA says the Idaho National Laboratory, which is building SR-1’s reactor, is making progress and is on target for a late-2028 launch. “Procurement of major components is underway, and integration work on the power and propulsion element is advancing steadily,” Sinacore told MIT Technology Review. The outlook will get even sunnier if the Artemis program, which aims to start laying the foundations for a base on the lunar south pole by the decade’s end, keeps to its own bold deadline. 

“It’s an aggressive timeline,” says Lindsey Holmes, who is vice president of advanced projects at Analytical Mechanics Associates, an aerospace company in Virginia. She suspects the push is being driven partly by China’s and Russia’s own deep-space nuclear ambitions. The two countries have spoken about plans to place a reactor on the moon’s surface in the mid-2030s to power a jointly operated lunar base. Whether it flies or fails in space, SR-1’s development should help NASA put its own reactor on the moon; the technology involved in the two projects is broadly similar, given that the lunar surface, like space itself, is a vacuum. If an interplanetary nuclear-powered spacecraft works, a nuclear reactor on the moon should too.

Progress meter . . . . . . . . . . . . 6

Most of the technology for SR-1 already exists; it’s going to come down to piecing it all together and then seeing how it performs in space.

We all know exercise is good for us. It builds muscle, strengthens bones, lowers blood pressure, and boosts mood. By deciphering how movement benefits the body, researchers hope to develop medicines that can offer some of the same perks—without the workout. The idea isn’t to replace exercise but to bring its upsides to people who struggle with frailty, disability, or chronic illness. 

The sticking points

It will take a lot of experimentation to untangle the myriad pathways by which exercise promotes health. But IDing the cascade of hormones, enzymes, and other molecules related to physical activity is just the first step. Scientists need to figure out how to turn that knowledge into safe and effective drugs. That’s a tall order: More than 90% of treatments that enter human studies fail.

There are regulatory hurdles too. The FDA approves medications to treat diseases, not to enhance wellness, says Thomas Burris, a pharmacologist at the University of Florida whose work focuses on diseases that respond to exercise, like obesity, type 2 diabetes, and dementia.

The progress

There may never be a pill that delivers all the benefits of exercise, but research could lead to new medicines that mimic some aspects of working out. Scientists have already identified many important exercise-related signals and have even developed compounds to regulate them. (Some preliminary results have been so promising that doping authorities have proactively banned the compounds.) 

Burris and his colleagues are focused on a receptor that’s always switched on, even without exercise. Working out appears to boost that receptor in muscle cells, which in turn helps bolster endurance over time. Burris’s lab has spent years designing a drug that cranks up the receptor’s activity directly, and mice treated with the drug ran longer and farther than mice that weren’t. They “become marathon mice without having to do any type of exercise,” Burris says. There are even indications—also in mice—that the compound mimics some of the cognitive benefits of exercise and could help treat heart failure. Burris founded a company called Pelagos to carry the work forward into a clinical trial.

Other workout-mimicking drugs have already entered human studies. In June, the biotech firm Cambrian Bio reported that its experimental drug ATX-304 boosted metabolism and reduced liver and belly fat in people with obesity and prediabetes. It activates a metabolic switch that helps cells sense when energy supplies dip and coordinates the production of more fuel—the same switch that helps us sustain long sessions jumping rope or swimming laps. Cambrian hopes it will help people lose weight without losing muscle, a common concern with GLP-1 medicines.  

Progress meter ………… 5

Our understanding of how exercise benefits the body is still coming into focus, and drug development is prone to failure.