El Salvador Made Bitcoin an Official Currency. Now It’s Backtracking for IMF Loan.
Organization is showing flexibility by allowing the bitcoin program to proceed in a limited way
Organization is showing flexibility by allowing the bitcoin program to proceed in a limited way
The government of El Salvador’s President Nayib Bukele agreed to scale back his ambitious plan to adopt bitcoin as a national currency in exchange for a much-needed $1.4 billion loan by the International Monetary Fund.
The IMF said in a statement Wednesday that in exchange for the financial-aid program to support the Bukele administration economic overhaul agenda, the government agreed to implement measures to mitigate bitcoin-related risks.
The deal signals an important shift by the IMF, showing greater flexibility over government use and regulation of bitcoin in anticipation of friendlier crypto policies by the incoming administration of President-elect Donald Trump , said Alejandro Werner , a former director of the IMF’s Western Hemisphere Department.
Bukele’s surprise decision to make bitcoin legal tender was cheered by crypto enthusiasts but stalled financial support from the IMF in the midst of concern that the volatile crypto asset could rock the finances of the impoverished and indebted Central American nation.
“In a situation where the international financial community didn’t want to set a precedent on the adoption of bitcoin as legal tender, it became an obstacle to close an agreement with the IMF,” said Werner, who also served as adviser to El Salvador’s government and currently heads the Georgetown Americas Institute in Washington, D.C.
The use of bitcoin as a national currency in this country of around 6.5 million didn’t take off, surveys show. After the government spent more than $200 million in 2021 rolling out bitcoin ATMs and an e-wallet with $30 of free bitcoin for anyone who signed up, most users took the virtual currency to buy goods or exchange it for dollars.
The government began purchasing bitcoin when it was trading at about $30,000, booking losses at first and then posting significant gains as its volatile price surpassed $100,000 recently.
Among the concessions made by the Bukele administration, acceptance of bitcoin by the country’s businesses will no longer be mandatory, while the public sector’s participation in bitcoin-related activities will be restricted, the IMF said.
“The potential risks of the bitcoin project will be diminished significantly” in line with fund policies, the IMF said.
Under the agreement, El Salvador’s government agreed to reduce bitcoin purchases, and it will no longer accept tax payments with the crypto asset. The government’s participation in Chivo, the crypto e-wallet launched in 2021, will be gradually unwound, the IMF said.
“Transparency, regulation, and supervision of digital assets will be enhanced to safeguard financial stability, consumer and investor protection, and financial integrity,” it added.
Bukele highlighted on X the IMF’s remarks about the steady expansion of the country’s economy since the pandemic, bolstered by “robust remittances and a remarkable pickup in tourism,” in the midst of improvements in public security.
A divide has opened in the tech job market between those with artificial-intelligence skills and everyone else.
A 30-metre masterpiece unveiled in Monaco brings Lamborghini’s supercar drama to the high seas, powered by 7,600 horsepower and unmistakable Italian design.
A divide has opened in the tech job market between those with artificial-intelligence skills and everyone else.
There has rarely, if ever, been so much tech talent available in the job market. Yet many tech companies say good help is hard to find.
What gives?
U.S. colleges more than doubled the number of computer-science degrees awarded from 2013 to 2022, according to federal data. Then came round after round of layoffs at Google, Meta, Amazon, and others.
The Bureau of Labor Statistics predicts businesses will employ 6% fewer computer programmers in 2034 than they did last year.
All of this should, in theory, mean there is an ample supply of eager, capable engineers ready for hire.
But in their feverish pursuit of artificial-intelligence supremacy, employers say there aren’t enough people with the most in-demand skills. The few perceived as AI savants can command multimillion-dollar pay packages. On a second tier of AI savvy, workers can rake in close to $1 million a year .
Landing a job is tough for most everyone else.
Frustrated job seekers contend businesses could expand the AI talent pipeline with a little imagination. The argument is companies should accept that relatively few people have AI-specific experience because the technology is so new. They ought to focus on identifying candidates with transferable skills and let those people learn on the job.
Often, though, companies seem to hold out for dream candidates with deep backgrounds in machine learning. Many AI-related roles go unfilled for weeks or months—or get taken off job boards only to be reposted soon after.
It is difficult to define what makes an AI all-star, but I’m sorry to report that it’s probably not whatever you’re doing.
Maybe you’re learning how to work more efficiently with the aid of ChatGPT and its robotic brethren. Perhaps you’re taking one of those innumerable AI certificate courses.
You might as well be playing pickup basketball at your local YMCA in hopes of being signed by the Los Angeles Lakers. The AI minds that companies truly covet are almost as rare as professional athletes.
“We’re talking about hundreds of people in the world, at the most,” says Cristóbal Valenzuela, chief executive of Runway, which makes AI image and video tools.
He describes it like this: Picture an AI model as a machine with 1,000 dials. The goal is to train the machine to detect patterns and predict outcomes. To do this, you have to feed it reams of data and know which dials to adjust—and by how much.
The universe of people with the right touch is confined to those with uncanny intuition, genius-level smarts or the foresight (possibly luck) to go into AI many years ago, before it was all the rage.
As a venture-backed startup with about 120 employees, Runway doesn’t necessarily vie with Silicon Valley giants for the AI job market’s version of LeBron James. But when I spoke with Valenzuela recently, his company was advertising base salaries of up to $440,000 for an engineering manager and $490,000 for a director of machine learning.
A job listing like one of these might attract 2,000 applicants in a week, Valenzuela says, and there is a decent chance he won’t pick any of them. A lot of people who claim to be AI literate merely produce “workslop”—generic, low-quality material. He spends a lot of time reading academic journals and browsing GitHub portfolios, and recruiting people whose work impresses him.
In addition to an uncommon skill set, companies trying to win in the hypercompetitive AI arena are scouting for commitment bordering on fanaticism .
Daniel Park is seeking three new members for his nine-person startup. He says he will wait a year or longer if that’s what it takes to fill roles with advertised base salaries of up to $500,000.
He’s looking for “prodigies” willing to work seven days a week. Much of the team lives together in a six-bedroom house in San Francisco.
If this sounds like a lonely existence, Park’s team members may be able to solve their own problem. His company, Pickle, aims to develop personalised AI companions akin to Tony Stark’s Jarvis in “Iron Man.”
James Strawn wasn’t an AI early adopter, and the father of two teenagers doesn’t want to sacrifice his personal life for a job. He is beginning to wonder whether there is still a place for people like him in the tech sector.
He was laid off over the summer after 25 years at Adobe , where he was a senior software quality-assurance engineer. Strawn, 55, started as a contractor and recalls his hiring as a leap of faith by the company.
He had been an artist and graphic designer. The managers who interviewed him figured he could use that background to help make Illustrator and other Adobe software more user-friendly.
Looking for work now, he doesn’t see the same willingness by companies to take a chance on someone whose résumé isn’t a perfect match to the job description. He’s had one interview since his layoff.
“I always thought my years of experience at a high-profile company would at least be enough to get me interviews where I could explain how I could contribute,” says Strawn, who is taking foundational AI courses. “It’s just not like that.”
The trouble for people starting out in AI—whether recent grads or job switchers like Strawn—is that companies see them as a dime a dozen.
“There’s this AI arms race, and the fact of the matter is entry-level people aren’t going to help you win it,” says Matt Massucci, CEO of the tech recruiting firm Hirewell. “There’s this concept of the 10x engineer—the one engineer who can do the work of 10. That’s what companies are really leaning into and paying for.”
He adds that companies can automate some low-level engineering tasks, which frees up more money to throw at high-end talent.
It’s a dynamic that creates a few handsomely paid haves and a lot more have-nots.
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