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Stablecoins' dominance due to limitations of US banking  — Jerald David

Stablecoins rose to popularity as a result of limitations in the US financial system — particularly restricted banking hours and the lack of a non-USD trading pair, according to Jerald David, president of Arca Labs.

“So we start thinking about the reason why, we start talking about the nine-to-five banking hours,” David said during a panel at TokenizeThis 2025 event on April 16.

The panel discussion centered on yieldcoins or, essentially, the rising of cryptocurrencies that can generate yield through holding, staking or lending, like stablecoins.

“Well, nine-to-five banking hours don’t work, right? There are implementations right now of payment systems that are going to come to market very soon, that are a good combination of both yield-bearing instruments as well as stabletokens,” David said.

According to David, the need for stablecoins stems from the fact that the traditional US banking infrastructure doesn’t support round-the-clock transactions. “And this industry, as we all know, is a 24-hour industry.”

KYC for stablecoins

Know Your Customer procedures were a significant topic at the panel. One representative from Figure Markets said that everyone who owns a yield-bearing stablecoin would have to be KYC-ed for tax reasons.

But David pointed out that stablecoins have several use cases beyond yield generation, including payments. “Using this stable token to buy a cup of coffee is not something that really should require AML or KYC for somebody.”

Nick Carmi, head of exchange at Figure Markets, suggested that part of the solution could be a trust-based KYC system that allows users to carry their credentials across platforms. KYC is a process used by financial institutions to verify a user’s identity. It’s meant to prevent fraud, money laundering, and other illegal activities by ensuring users are who they claim to be.

Currently, users must complete separate KYC checks for each financial institution or service they use, creating friction and frustration — especially for those navigating multiple platforms or exploring different crypto ecosystems.

Magazine: Bitcoin payments are being undermined by centralized stablecoins

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Panama's capital to accept crypto for taxes, municipal fees

Panama’s capital city will accept cryptocurrency payments for taxes and municipal fees, including bus tickets and permits, Panama City mayor Mayer Mizrachi announced on April 15, joining a growing list of jurisdictions globally that have voted to accept such payments.

Panama City will begin accepting Bitcoin (BTC), Ether (ETH), Circle’s USDC (USDC), and Tether’s USDt (USDT) stablecoin for payment once the crypto-to-fiat payment rails are established, Mizrachi posted on the X platform.

Mizrachi said previous administrations attempted to push through similar legislation but failed to overcome stipulations requiring the local government to accept funds denominated in US dollars.

In a translated statement, the Panama City mayor said that the local government partnered with a bank that will immediately convert any digital assets received into US dollars, allowing the municipality to accept crypto without introducing new legislation.

Panama City joins a growing list of global jurisdictions on the municipal and state level accepting cryptocurrency payments for taxes, exploring Bitcoin strategic reserves to protect public treasuries from inflation and passing pro-crypto policies to attract investment.

Taxes, Panama, Bitcoin Adoption
Source: Mayer Mizrachi

Related: New York bill proposes legalizing Bitcoin, crypto for state payments

Municipalities and states embrace digital assets

Several municipalities and territories around the globe already accept crypto for tax payments or are exploring various implementations of blockchain technology for government spending.

The US state of Colorado started accepting crypto payments for taxes in September 2022. Much like Panama City said it will do, Colorado immediately converts the crypto to fiat.

In December 2023, the city of Lugano, Switzerland, announced taxes and city fees could be paid in Bitcoin, which was one of the developments that earned it the reputation of being a globally recognized Bitcoin city.

The city council of Vancouver, Canada, passed a motion to become “Bitcoin-friendly city” in December 2024. As part of that motion, the Vancouver local government will explore integrating BTC into the financial system, including tax payments.

North Carolina lawmaker Neal Jackson introduced legislation titled “The North Carolina Digital Asset Freedom Act” on April 10. If passed, the bill will recognize cryptocurrencies as an official form of payment that can be used to pay taxes.

Magazine: Crypto City: The ultimate guide to Miami

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Elon Musk’s AI company, xAI, is slowly bringing its Grok chatbot to parity with top rivals like ChatGPT and Google’s Gemini. Wednesday night, xAI announced a “memory” feature for Grok that enables the bot to remember details from past conversations. Now, if you ask Grok for recommendations, it’ll give more personalized responses — assuming you’ve […]
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Zoom says its platform is back online after suffering an outage for much of Wednesday afternoon. “Service has now been restored after the earlier outage, and we sincerely appreciate your patience and understanding,” Zoom said in a post on X at around 2 p.m. Pacific. The trouble began around 11:40 a.m., according to The Verge, […]
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Chapter, a Medicare advisory startup co-founded by former Republican presidential hopeful Vivek Ramaswamy, has closed a $75 million funding round at a valuation of $1.5 billion led by private equity and venture firm Stripes. The startup helps seniors choose Medicare health plans analyzing doctors, hospitals, and prescription drug coverage. Unlike many other Medicare insurance brokers, […]
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The Trump administration is considering new restrictions on the Chinese AI lab DeepSeek that would limit it from buying Nvidia’s AI chips, and potentially bar Americans from accessing its AI services, The New York Times reported on Wednesday. The restrictions are part of the Trump administration’s effort to compete with China on AI. Months after […]
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The only office within the US State Department that monitors foreign disinformation is to be eliminated, according to US Secretary of State Marco Rubio, confirming reporting by MIT Technology Review.

The Counter Foreign Information Manipulation and Interference (R/FIMI) Hub is a small office in the State Department’s Office of Public Diplomacy that tracks and counters foreign disinformation campaigns. 

In shutting R/FIMI, the department’s controversial acting undersecretary, Darren Beattie, is delivering a major win to conservative critics who have alleged that it censors conservative voices. Created at the end of 2024, it was reorganized from the Global Engagement Center (GEC), a larger office with a similar mission that had long been criticized by conservatives who claimed that, despite its international mission, it was censoring American conservatives. In 2023, Elon Musk called the center the “worst offender in US government censorship [and] media manipulation” and a “threat to our democracy.” 

The culling of the office leaves the State Department without a way to actively counter the increasingly sophisticated disinformation campaigns from foreign governments like those of Russia, Iran, and China.

Shortly after publication, employees at R/FIMI received an email, inviting them to an 11:15AM meeting with Beattie, where employees were told that the office and their jobs have been eliminated. 

Have more information on this story or a tip for something else that we should report? Using a non-work device, reach the reporter on Signal at eileenguo.15 or tips@technologyreview.com.

Then, Secretary of State Marco Rubio confirmed our reporting in a blog post in The Federalist, which had sued GEC last year alleging that it had infringed on its freedom of speech. “It is my pleasure to announce the State Department is taking a crucial step toward keeping the president’s promise to liberate American speech by abolishing forever the body formerly known as the Global Engagement Center (GEC),” he wrote. And he told Mike Benz, a former first-term Trump official who also reportedly has alt right views, during a YouTube interview, “We ended government-sponsored censorship in the United States through the State Department.”  

Censorship claims

For years, conservative voices both in and out of government have accused Big Tech of censoring conservative views—and they often charged GEC with enabling such censorship. 

GEC had its roots as the Center for Strategic Counterterrorism Communications (CSCC), created by an Obama-era executive order, but shifted its mission to fight propaganda and disinformation from foreign governments and terrorist organizations in 2016, becoming the Global Engagement Center. It was always explicitly focused on the international information space, but some of the organizations that it funded also did work in the United States. It shut down last December after a measure to reauthorize its $61 million budget was blocked by Republicans in Congress, who accused it of helping Big Tech censor American conservative voices. 

R/FIMI had a similar goal to fight foreign disinformation, but it was smaller: the newly created office had a $51.9 million budget, and a small staff that, by mid-April, was down to just 40 employees, from 125 at GEC. In a Wednesday morning meeting, those employees were told that they would  be put on administrative leave and terminated within 30 days. 

With the change in administrations, R/FIMI had never really gotten off the ground. Beattie, a controversial pick for undersecretary—he was fired as a speechwriter during the first Trump administration for attending a white nationalism conference, has suggested that the FBI organized the January 6 attack on Congress, and has said that it’s not worth defending Taiwan from China—had instructed the few remaining staff to be “pencils down,” one State Department official told me, meaning to pause in their work. 

The administration’s executive order on “countering censorship and restoring freedom of speech” reads like a summary of conservative accusations against GEC:

“Under the guise of combatting “misinformation,” “disinformation,” and “malinformation,” the Federal Government infringed on the constitutionally protected speech rights of American citizens across the United States in a manner that advanced the Government’s preferred narrative about significant matters of public debate.  Government censorship of speech is intolerable in a free society.”

In 2023, The Daily Wire, founded by conservative media personality Ben Shapiro, joined The Federalist in suing GEC for allegedly infringing on the company’s first amendment rights by funding two non-profit organizations, the London-based Global Disinformation Index and New York-based NewsGuard, that had labeled The Daily Wire as “unreliable,” “risky,” and/or (per GDI), susceptible to foreign disinformation. Those projects were not funded by GEC. The lawsuit alleged that this amounted to censorship by “starving them of advertising revenue and reducing the circulation of their reporting and speech,” the lawsuit continued. 

In 2022, the Republican attorneys general of Missouri and Louisiana named GEC among the federal agencies that, they alleged, were pressuring social networks to censor conservative views. Though the case eventually made its way to the Supreme Court, which found no First Amendment violations, a lower court had already removed GEC’s name from the list of defendants, ruling there was “no evidence” that GEC’s communications with the social media platforms had gone beyond “educating the platforms on ‘tools and techniques used by foreign actors.’”

The stakes

The GEC—and now R/FIMI—was targeted as part of a wider campaign to shut down groups accused of being “weaponized” against conservatives. 

Conservative critics railing against what they have alternatively called a disinformation- or censorship- industrial complex have also taken aim at the Department of Homeland Security’s Cybersecurity and Infrastructure Security Agency (CISA) and the Stanford Internet Observatory, a prominent research group that conducted widely cited research on the flows of disinformation during elections. 

CISA’s former director, Chris Krebs, was personally targeted in an April 9 White House memo, while in response to the criticism and millions of dollars in legal fees, Stanford University shuttered the Stanford Internet Observatory ahead of the 2024 presidential elections.  

But this targeting comes at a time when foreign disinformation campaigns—especially by Russia, China, and Iran—have become increasingly sophisticated. 

According to one estimate, Russia spends $1.5 billion per year on foreign influence campaigns. In 2022, the Islamic Republic of Iran Broadcasting, that country’s primary foreign propaganda arm, had a $1.26 billion budget. And a 2015 estimate suggests that China spent up to $10 billion per year on media targeting non-Chinese foreigners—a figure that has almost certainly grown.

In September 2024, the Justice Department indicted two employees of RT, a Russian state-owned propaganda agency, in a $10 million scheme to create propaganda aimed at influencing US audiences through a media company that has since been identified as the conservative Tenet Media. 

The GEC was one effort to counter such campaigns. Some of its recent projects have included developing AI models to detect memes and deepfakes and exposing Russian propaganda efforts to influence Latin American public opinion against the war in Ukraine. 

By law, the Office of Public Diplomacy has to provide Congress with 15-day advance notice of any intent to reassign any funding allocated by Congress over $1 million. Congress then has time to respond, ask questions, and challenge the decisions—though to judge from its record with other unilateral executive-branch decisions to gut government agencies, it is unlikely to do so. 

We have reached out to the State Department for comment. 

This story was updated at 11:55am to note that R/FIMI employees have confirmed that the office closed.
This story was updated at 12:37am to include confirmation about R/FIMI’s shutdown from Marco Rubio.
This story was updated at 6:10pm to add an identifier for Mike Benz.

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Anyone who crammed for exams in college knows that an impressive ability to regurgitate information is not synonymous with critical thinking.

The large language models (LLMs) first publicly released in 2022 were impressive but limited—like talented students who excel at multiple-choice exams but stumble when asked to defend their logic. Today’s advanced reasoning models are more akin to seasoned graduate students who can navigate ambiguity and backtrack when necessary, carefully working through problems with a methodical approach.

As AI systems that learn by mimicking the mechanisms of the human brain continue to advance, we’re witnessing an evolution in models from rote regurgitation to genuine reasoning. This capability marks a new chapter in the evolution of AI—and what enterprises can gain from it. But in order to tap into this enormous potential, organizations will need to ensure they have the right infrastructure and computational resources to support the advancing technology.

The reasoning revolution

“Reasoning models are qualitatively different than earlier LLMs,” says Prabhat Ram, partner AI/HPC architect at Microsoft, noting that these models can explore different hypotheses, assess if answers are consistently correct, and adjust their approach accordingly. “They essentially create an internal representation of a decision tree based on the training data they’ve been exposed to, and explore which solution might be the best.”

This adaptive approach to problem-solving isn’t without trade-offs. Earlier LLMs delivered outputs in milliseconds based on statistical pattern-matching and probabilistic analysis. This was—and still is—efficient for many applications, but it doesn’t allow the AI sufficient time to thoroughly evaluate multiple solution paths.

In newer models, extended computation time during inference—seconds, minutes, or even longer—allows the AI to employ more sophisticated internal reinforcement learning. This opens the door for multi-step problem-solving and more nuanced decision-making.

To illustrate future use cases for reasoning-capable AI, Ram offers the example of a NASA rover sent to explore the surface of Mars. “Decisions need to be made at every moment around which path to take, what to explore, and there has to be a risk-reward trade-off. The AI has to be able to assess, ‘Am I about to jump off a cliff? Or, if I study this rock and I have a limited amount of time and budget, is this really the one that’s scientifically more worthwhile?’” Making these assessments successfully could result in groundbreaking scientific discoveries at previously unthinkable speed and scale.

Reasoning capabilities are also a milestone in the proliferation of agentic AI systems: autonomous applications that perform tasks on behalf of users, such as scheduling appointments or booking travel itineraries. “Whether you’re asking AI to make a reservation, provide a literature summary, fold a towel, or pick up a piece of rock, it needs to first be able to understand the environment—what we call perception—comprehend the instructions and then move into a planning and decision-making phase,” Ram explains.

Enterprise applications of reasoning-capable AI systems

The enterprise applications for reasoning-capable AI are far-reaching. In health care, reasoning AI systems could analyze patient data, medical literature, and treatment protocols to support diagnostic or treatment decisions. In scientific research, reasoning models could formulate hypotheses, design experimental protocols, and interpret complex results—potentially accelerating discoveries across fields from materials science to pharmaceuticals. In financial analysis, reasoning AI could help evaluate investment opportunities or market expansion strategies, as well as develop risk profiles or economic forecasts.

Armed with these insights, their own experience, and emotional intelligence, human doctors, researchers, and financial analysts could make more informed decisions, faster. But before setting these systems loose in the wild, safeguards and governance frameworks will need to be ironclad, particularly in high-stakes contexts like health care or autonomous vehicles.

“For a self-driving car, there are real-time decisions that need to be made vis-a-vis whether it turns the steering wheel to the left or the right, whether it hits the gas pedal or the brake—you absolutely do not want to hit a pedestrian or get into an accident,” says Ram. “Being able to reason through situations and make an ‘optimal’ decision is something that reasoning models will have to do going forward.”

The infrastructure underpinning AI reasoning

To operate optimally, reasoning models require significantly more computational resources for inference. This creates distinct scaling challenges. Specifically, because the inference durations of reasoning models can vary widely—from just a few seconds to many minutes—load balancing across these diverse tasks can be challenging.

Overcoming these hurdles requires tight collaboration between infrastructure providers and hardware manufacturers, says Ram, speaking of Microsoft’s collaboration with NVIDIA, which brings its accelerated computing platform to Microsoft products, including Azure AI.

“When we think about Azure, and when we think about deploying systems for AI training and inference, we really have to think about the entire system as a whole,” Ram explains. “What are you going to do differently in the data center? What are you going to do about multiple data centers? How are you going to connect them?” These considerations extend into reliability challenges at all scales: from memory errors at the silicon level, to transmission errors within and across servers, thermal anomalies, and even data center-level issues like power fluctuations—all of which require sophisticated monitoring and rapid response systems.

By creating a holistic system architecture designed to handle fluctuating AI demands, Microsoft and NVIDIA’s collaboration allows companies to harness the power of reasoning models without needing to manage the underlying complexity. In addition to performance benefits, these types of collaborations allow companies to keep pace with a tech landscape evolving at breakneck speed. “Velocity is a unique challenge in this space,” says Ram. “Every three months, there is a new foundation model. The hardware is also evolving very fast—in the last four years, we’ve deployed each generation of NVIDIA GPUs and now NVIDIA GB200NVL72. Leading the field really does require a very close collaboration between Microsoft and NVIDIA to share roadmaps, timelines, and designs on the hardware engineering side, qualifications and validation suites, issues that arise in production, and so on.”

Advancements in AI infrastructure designed specifically for reasoning and agentic models are critical for bringing reasoning-capable AI to a broader range of organizations. Without robust, accessible infrastructure, the benefits of reasoning models will remain relegated to companies with massive computing resources.

Looking ahead, the evolution of reasoning-capable AI systems and the infrastructure that supports them promises even greater gains. For Ram, the frontier extends beyond enterprise applications to scientific discovery and breakthroughs that propel humanity forward: “The day when these agentic systems can power scientific research and propose new hypotheses that can lead to a Nobel Prize, I think that’s the day when we can say that this evolution is complete.”

To learn more, please read Microsoft and NVIDIA accelerate AI development and performance, watch the NVIDIA GTC AI Conference sessions on demand, and explore the topic areas of Azure AI solutions and Azure AI infrastructure.

This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review’s editorial staff.

This content was researched, designed, and written entirely by human writers, editors, analysts, and illustrators. This includes the writing of surveys and collection of data for surveys. AI tools that may have been used were limited to secondary production processes that passed thorough human review.

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This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology.

AI is coming for music, too

While large language models that generate text have exploded in the last three years, a different type of AI, based on what are called diffusion models, is having an unprecedented impact on creative domains.

By transforming random noise into coherent patterns, diffusion models can generate new images, videos, or speech, guided by text prompts or other input data. The best ones can create outputs indistinguishable from the work of people, as well as bizarre, surreal results that feel distinctly nonhuman.

Now these models are marching into a creative field that is arguably more vulnerable to disruption than any other: music. Music models can now create songs capable of eliciting real emotional responses, presenting a stark example of how difficult it’s becoming to define authorship and originality in the age of AI. Read the full story.

—James O’Donnell

This story is from the next edition of our print magazine, which is all about how technology is changing creativity. Subscribe now to read it and get a copy of the magazine when it lands!

A small US city is experimenting with AI to find out what residents want

Bowling Green, Kentucky, is home to 75,000 residents who recently wrapped up an experiment in using AI for democracy: Can an online polling platform, powered by machine learning, capture what residents want to see happen in their city?

After a month of advertising, the Pol.is portal launched in February. Residents could go to the website and anonymously submit an idea (in less than 140 characters) for what a 25-year plan for their city should include. They could also vote on whether they agreed or disagreed with other ideas.

But some researchers question whether soliciting input in this manner is a reliable way to understand what a community wants. Read the full story.

—James O’Donnell

How Colossal Biosciences is attempting to own the “woolly mammoth”

What’s new: Colossal Biosciences not only wants to bring back the woolly mammoth—it wants to own it, too. MIT Technology Review has learned the Texas startup is seeking a patent that would give it exclusive legal rights to create and sell gene-edited elephants containing ancient mammoth DNA.

But why? Ben Lamm, the CEO of Colossal, says that holding patents on the mammoth and other creatures would “give us control over how these technologies are implemented, particularly for managing initial releases where oversight is critical.” Patents, which usually last 20 years, could provide “a clear legal framework during the critical transition period when de-extinct species are first reintroduced,” he says. Read the full story.

—Antonio Regalado


If you’re interested in what else Collossal’s been up to, check out:

+ Game of clones: Colossal’s new wolves are cute, but are they dire? The company recently claimed it has revived an extinct species, but scientists are skeptical. Read the full story.

+ As a first step towards resurrecting woolly mammoths, Colossal created these adorable gene-edited ‘woolly mice.’

The must-reads

I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.

1 OpenAI might be  building its own social network
It’s a move that’s likely to enrage Elon Musk even further. (The Verge)
+ Musk and Sam Altman are still locked in a legal dispute. (CNBC)
+ There are plenty of reasons why OpenAI might want to build a social feed. (NY Mag $)

2 Buying directly from Chinese factories is not a good idea
Despite what TikTok tells you. (WP $)
+ The popularity of apps allowing shoppers to buy from factories is skyrocketing. (WSJ $)

3 Mark Zuckerberg tried to settle Meta’s antitrust case last month
Unfortunately for him, the head of the FTC was unmoved by the offer. (WSJ $)
+ The CEO considered spinning off Instagram in 2018, apparently. (Reuters)
+ The first two days of the trial have focused on 2010-2014. (Bloomberg $)

4 A whistleblower has shed light on how DOGE may have taken private data
Labor law experts are certain the information is completely unrelated to making the government more efficient. (NPR)
+ Federal workers are wading through the chaos. (The Atlantic $)
+ A lot of DOGE’s fraud claims are old news. (The Guardian)
+ DOGE’s tech takeover threatens the safety and stability of our critical data. (MIT Technology Review)

5 Nvidia is bracing itself to lose $5.5 billion
As a result of the Trump administration’s new chip sales restrictions. (FT $)
+ Its new H20 chip now requires a special license. (The Guardian)
+ The company’s shares plunged in response to the news. (CNN)

6 We’re getting closer to a cure for seasonal allergies
An injection usually administered to treat asthma could hold the key. (Vox)

7 Maybe LLMs don’t need language after all
Allowing them to process queries in mathematical spaces could improve their output. (Quanta Magazine)
+ Why does AI being good at math matter? (MIT Technology Review)

8 YouTube was given an exemption from Australia’s social media ban for under-16s
Even though it’s the most popular platform for children by far. (Bloomberg $)

9 Social media can still fight hate without censorship
Although X is probably too far gone, admittedly. (The Atlantic $)
+ How to fix the internet. (MIT Technology Review)

10 How to survive on Mars
Thanks to water-rich asteroids. (Wired $)
+ The quest to figure out farming on Mars. (MIT Technology Review)

Quote of the day

“How else can OpenAI acquire new training data at scale going forward?”

—Bill Gross, the founder of tech incubator Idealab, believes OpenAI has a very clear motive for wanting to build its own social network, Insider reports.

The big story

How refrigeration ruined fresh food

Three-quarters of everything in the average American diet passes through the cold chain—the network of warehouses, shipping containers, trucks, display cases, and domestic fridges that keep meat, milk, and more chilled on the journey from farm to fork.

As consumers, we put a lot of faith in terms like “fresh” and “natural,” but artificial refrigeration has created a blind spot. We’ve gotten so good at preserving (and storing) food, that we know more about how to lengthen an apple’s life span than a human’s, and most of us don’t give that extraordinary process much thought at all. But all that convenience has come at the expense of diversity and deliciousness. Read the full story.

—Allison Arieff

We can still have nice things

A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or skeet ’em at me.)

+ This list of the 30 best fiction books of the last 30 years does not disappoint.
+ Travel ghost stories? Truly chilling.
+ It’s time to caulk the wagon—the seminal Oregon Trail is celebrating its 50th anniversary.
+ These photos of fifties fashion are simply the best.

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