Your kid is getting a ‘Trump account.' Should you put your money in it?
The new savings vehicles, akin to Individual Retirement Accounts, are designated for children who are U.S. citizens born from 2025 through 2028. In addition to the one-time government contribution, parents and others can chip in as much as $5,000 a year to the accounts, which beneficiaries can access at 18, with some constraints.
Hashtags
Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles
Wall Street Journal
20 minutes ago
- Wall Street Journal
Elon Musk Says He's Forming ‘America Party'
Tesla CEO Elon Musk said Saturday he created a new political party called the America Party after reigniting a feud with President Trump. 'By a factor of 2 to 1, you want a new political party and you shall have it!,' Musk wrote in a post on X, the social-media platform he owns. 'Today, the America Party is formed to give you back your freedom.'
Yahoo
26 minutes ago
- Yahoo
Elon Musk confirms xAI is buying an overseas power plant and shipping the whole thing to the U.S. to power its new data center — 1 million AI GPUs and up to 2 Gigawatts of power under one roof, equivalent to powering 1.9 million homes
When you buy through links on our articles, Future and its syndication partners may earn a commission. Elon Musk's next xAI data centers are expected to house millions of AI chips and consume so much power that Elon Musk has reportedly bought a power plant overseas and intends to ship it to the U.S., according to Dylan Patel from SemiAnalysis, who outlined xAI's recent progress in a podcast. Interestingly, Musk confirmed the statement in a subsequent tweet. Elon Musk's current xAI Colossus AI supercomputer is already one of the world's most powerful and power-hungry machines on the planet, housing some 200,000 Nvidia Hopper GPUs and consuming around an astounding 300 MW of power, and xAI has faced significant headwinds in supplying it with enough power. The challenges only become more intense as the company moves forward — Musk faces a monumental challenge with powering his next AI data center, one that is predicted to house one million AI GPUs, thus potentially consuming the same amount of power as 1.9 million households. Here's how the data center could consume that much power, and how Musk plans to deliver it. Elon Musk's xAI has assembled vast computing resources and a team of talented researchers to advance the company's Grok AI models, Patel said. However, even bigger challenges lay ahead. It is no secret that Elon Musk has already run into trouble powering his existing xAI data center. Currently, the company's main data center, Colossus, which houses 200,000 Nvidia Hopper GPUs, is located near Memphis, Tennessee. To power this machine, xAI installed 35 gas turbines that can produce 420 MW of power, as well as deploying Tesla Megapack systems to smooth out power draw. However, things are going to get much more serious going forward. Beyond the Colossus buildout, xAI is rapidly acquiring and developing new facilities. The company has purchased a factory in Memphis that is being converted into additional data center space, big enough to power around 125,000 eight-way GPU servers, along with all supporting hardware, including networking, storage, and cooling. A million Nvidia Blackwell GPUs will consume between 1,000 MW (1 GW) and 1,400 MW (1.4 GW), depending on the accelerator models (B200, GB200, B300, GB300) used and their configuration. However, the GPUs are not the only load on the power system; you must also account for the power consumption of CPUs, DDR5 memory, storage, networking gear, cooling, air conditioning, power supply inefficiency, and other factors such as lighting. In large AI clusters, a useful approximation is that overhead adds another 30% to 50% on top of the AI GPU power draw, a figure typically expressed as PUE (power usage effectiveness). That said, depending on which Blackwell accelerators xAI plans to use, a million-GPU data center will consume between 1,400 MW and 1,960 MW (given a PUE of 1.4). What can possibly power a data center with a million high-performance GPUs for AI training and inference is a big question, as this undertaking is comparable to powering the potential equivalent of 1.9 million homes. A large-scale solar power plant alone is not viable for a 24/7 compute load of this magnitude, as one would need several gigawatts of panels, plus massive battery storage, which is prohibitively expensive and land-intensive. The most practical and commonly used option is building multiple natural gas combined-cycle gas turbine (CCGT) plants, each capable of producing 0.5 MW – 1,500 MW. This approach is relatively fast to deploy (several years), scalable in phases, and easier to integrate with existing electrical grids. Perhaps, this is what xAI plans to import to the U.S. Alternatives like nuclear reactors could technically meet the load with fewer units (each can produce around 1,000 MW) with no direct carbon emissions, but nuclear plants take much longer to design, permit, and build (up to 10 years). It is unlikely that Musk has managed to buy a nuclear power plant overseas, with plans to ship it to the U.S. In practice, any organization attempting a 1.4 – 1.96 Gigawatt deployment — like xAI — will effectively become a major industrial energy buyer. For now, xAI's Colossus produces power onsite and purchases power from the grid; therefore, it is likely that the company's next data center will follow suit and combine a dedicated onsite plant with grid interconnections. Apparently, because acquiring a power plant in the U.S. can take too long, xAI is reportedly buying a plant overseas and shipping it in, something that highlights how AI development now hinges not only on compute hardware and software but also on securing massive energy supplies quickly. Without a doubt, a data center housing a million AI accelerators with a dedicated power plant appears to be an extreme measure. However, Patel points out that most leading AI companies are ultimately converging on similar strategies: concentrating enormous compute clusters, hiring top-tier researchers, and training ever-larger AI models. To that end, if xAI plans to stay ahead of the competition, it needs to build even more advanced and power-hungry data centers. Follow Tom's Hardware on Google News to get our up-to-date news, analysis, and reviews in your feeds. Make sure to click the Follow button. Error in retrieving data Sign in to access your portfolio Error in retrieving data Error in retrieving data Error in retrieving data Error in retrieving data
Yahoo
an hour ago
- Yahoo
'Into a void': Young US college graduates face employment crisis
Over two years, Rebecca Atkins filed more than 250 job applications, and felt like every one was going into a gaping chasm -- one opened by the highest unemployment rate for recent college graduates in the United States in more than a decade. "It was extremely dispiriting," said the 25-year-old, who graduated in 2022 with a degree in law and justice from a university in the US capital Washington. "I was convinced that I was a terrible person, and terrible at working." At 5.8 percent, unemployment for young, recent graduates from US universities is higher than it has been since November 2013, excluding 15 months in the Covid pandemic, according to official data. Moreover, it has also remained stubbornly higher than overall unemployment -- an extremely unusual situation, analysts say. And while overall US unemployment has stabilized between around 3.5 and 4 percent post-pandemic, unemployment for recent college graduates is only trending higher. The labor market for new grads has weakened consistently since 2022, with new hiring down 16 percent in 2025, year-over-year, according to payroll firm Gusto. Analysts say the trend is likely a result of cyclical post-pandemic hiring slowdowns -- particularly in new-grad-heavy sectors like technology, finance, and business information -- and overall economic uncertainty in the tumultuous early days of the Trump administration. That is scant consolation to the droves of young people -- often saddled with huge amounts of student debt -- on the hunt for their first full-time job. "All of the jobs that I wanted, I didn't have the requirements for -- often entry-level jobs would require you to have four or five years of experience," said Atkins, who bounced between part-time roles and working in restaurants for years. - 'Extremely high uncertainty' - "It is definitely an outlier," said Matthew Martin, senior US economist at Oxford Economics. "You'd expect that the white collar positions would not be as exposed to cyclical downturns (as other jobs)." Job openings for professional and business services have declined by more than 40 percent since 2021, according to research authored by Martin, with tech sector jobs disproportionately impacted. "Part of that is a slower pace of hiring as they right-size after they hired at very high rates in 2022, but at the same time the sheer volume of decline also points to the impact of AI," he told AFP, signaling the potential of artificial intelligence technology to eliminate some entry-level roles. Gregory Daco, chief economist at EY-Parthenon, said slowing tech sector hiring as companies focus on holding on to their talent "disproportionately" affects recent graduates. The hiring slowdown is also a result of US President Donald Trump's far-reaching policy swings since taking office in January, said Daco. "The experience of extremely high uncertainty when it comes to the administration's trade, tax or other policies has caused many firms to potentially slow down or freeze their hiring." He cautioned, however, against jumping to the conclusion that AI had already begun to eliminate entry-level roles, pointing to a so-far limited uptake of the technology by most sectors. "The reality is that a lot of firms are still in the early stages of adoption of these new technologies, and I think it would be a bit premature to assume that we've reached a level of use... that would have a visible macro impact." - 'Constantly working' - The United States is perhaps the most expensive country in the world for a university education, with an average cost of $27,673 per year for an undergraduate degree, according to official data. In 2020, 36.3 percent of US undergraduates took on federal student loans to help meet those spiraling costs, the data shows, with the Education Data Initiative putting average student loan debt for graduating students at $29,550. Even without student loan debt, however, the weakening job market can leave some recent graduates feeling like they are stretched thin. Katie Bremer, 25, graduated from American University with a dual-degree in Environmental Science and Public Health in 2021. It took her more than a year to find a full-time job -- one not in her field -- and even then, she had to supplement her income by babysitting. "I felt like I was constantly working," she told AFP. "It seems overwhelming, looking at the costs, to try and make your salary stretch all the way to cover all the milestones you're supposed to reach in young adulthood." There is little hope on the immediate horizon, with analysts warning that it will likely take some time for the labor market to resolve itself, with part of that adjustment likely seeing students picking different majors. "It's likely to get worse before it gets better," said Martin. Looking at her peers, many of whom are saddled with huge debt and struggled to find work, Bremer says she worries for their collective long-term future. "There have been times where I've thought 'how is my generation going to make this work?'" aha/sla Error in retrieving data Sign in to access your portfolio Error in retrieving data Error in retrieving data Error in retrieving data Error in retrieving data
