A $12 Billion Window Into AI's Race for Power
The artificial intelligence arms race has prompted a contest for America's power plants. NRG Energy Inc.'s acquisition of a gas-fired fleet comes a few months after Constellation Energy Corp.'s even bigger deal for Calpine Corp. US power generation deals announced through mid-May add up to $51 billion, more than in any entire year this century save one.
NRG's offers a $12 billion proof point that Big Tech's datacenter boom, among other things, demands vast quantities of power. It also underscores a related point: History shows the US will struggle to build the plants required to generate that power.
Hashtags
Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles
Washington Post
an hour ago
- Washington Post
American Vanguard: Q1 Earnings Snapshot
NEWPORT BEACH, Calif. — NEWPORT BEACH, Calif. — American Vanguard Corp. (AVD) on Friday reported a first-quarter loss of $8.5 million, after reporting a profit in the same period a year earlier. On a per-share basis, the Newport Beach, California-based company said it had a loss of 30 cents. Losses, adjusted for non-recurring costs, came to 24 cents per share.
Forbes
an hour ago
- Forbes
SAP Insights Newsletter: Forget LLMs. SLMs Might Be What You Need.
Artificial intelligence, data mining, modern computer technologies. SLM, Small Language model, Generative AI Small vs. large: Not every company needs a large language model. Small language models (SLMs) are great tools for specific use cases. They're also quicker, cheaper, and easier to add to your tech portfolio. We discuss why some companies are choosing SLMs and how to figure out if an SLM is right for your organization. Flex vs. fixed: B2B is trending toward B2C pricing strategies, specifically flex pricing. Many businesses are finding that flex pricing has many advantages over fixed pricing. With global events, trade, tariffs, and the like, being able to adjust pricing is how companies protect their revenue. Productivity vs. GenAI: World Productivity Day is meant to inspire us to reach new levels of GTD (getting things done). Yet, where does GenAI fit in? The productivity promises of GenAI tools are, shall we say, maybe a little unrealistic (at least right now). We explain the challenges and where GenAI tools can make the most impact right now. Research that hasn't reached your inbox: We discover the importance of colleague support; how labor vs. luck is viewed by employees; and a promising new approach to mental health.
Forbes
an hour ago
- Forbes
How AI Can Decode The Hidden Stories In Immigration Applications
Raghu Para is a tech exec with over 15 years of progressive experience in software, artificial intelligence and machine learning. getty Picture this: You've spent years gathering documents, filling out forms and waiting for your immigration decision. Meanwhile, the officer reviewing your case is buried under a mountain of paperwork, armed with the patience of a kindergarten teacher and the attention span of a detective running on espresso. This is the modern immigration system—a finely tuned cocktail of bureaucracy, backlogs and burnout. Governments want meticulous vetting. Applicants wait so long they could've binged Living Undocumented on Netflix. And the kicker? Much of the work is mind-numbingly repetitive. Officers aren't just reviewing facts—they're decoding intent. Is this a legit work visa? A bona fide asylum claim? They play legal detective, scan for red flags and occasionally channel TSA energy—unpacking a grandma's suitcase only to find a single, compliant three-ounce shampoo bottle. Could AI help? Sure. But the question is—can it understand human intent without making a mess? Let's address the customs officer in the room: AI in immigration is controversial. On the bright side, processing times are expedited, costs can be reduced and the risk of human error deciding anyone's fate can be mitigated. But let's not hand it a rubber stamp just yet. AI bias is real. It can reject perfectly good applications like it's giving out Halloween candy—and worse, hallucinate fake laws like the "Deportation Reform Act of 2065." That's not a typo—it's fiction. So what's the answer? Let tech sit at the desk—but humans still hold the stamp. As an AI researcher who's navigated the anxiety-inducing immigration process myself, I can tell you the challenge isn't building smart algorithms—it's building guardrails that stop them from going off-script. When designed carefully, AI can be the ultimate sidekick—bringing technical muscle and just enough empathy to keep things human. Today's systems aren't the clunky chatbots that used to ask, "Did you mean refugee or retirement visa?" before crash-landing on a 404 page from the Bush administration. Modern systems combine machine precision with human oversight, making a huge difference. Here's how: One of the biggest delays in immigration comes from verifying intent. AI now uses natural language processing to read between the lines, flag inconsistencies and detect fraud. Take a framework like Agent-Driven Semantic Analysis & Intent Detection (ADS-ID)—a multi-agent model I helped design: • The "document detective" deciphers even the messiest handwriting (think doctor's prescription, but worse). • The "legal scholar" cross-references case law better than your cousin with a law degree and zero follow-through. • The "consistency checker" spots contradictions like "You were working in Canada while attending school in Mexico?" Okay, time traveler. Other approaches use deep learning trained on millions of past cases or hybrid models combining logic rules and machine learning. But the solutions always keep humans in the loop to interpret AI's findings. And yes, there are challenges. • The Black Box Problem: If an AI makes a decision, it needs a "Kindergarten Explanation Layer"—something even a five-year-old (or a policy analyst) can understand. • Biased Training Data: Immigration decisions are rooted in decades of judgment calls—many flawed. We need AI that can recognize, adapt to and correct for that. • Constant Policy Change: Immigration rules can change faster than the promises of a politician. AI needs regular policy memos just to keep up. Some fraud is obvious, but some fraud is sneaky. AI can help by analyzing digital footprints for inconsistencies and flagging suspicious patterns in application histories. The U.K.'s Whitehall system, for instance, used AI to detect sham marriages, though critics noted it sometimes flagged real couples, too. Embassies are starting to use AI to estimate wait times based on application type, country of origin and historical data. It's not flawless, but it beats refreshing your status page 37 times a day. Officers often deal with documents in rare dialects, bad translations or messy handwriting. Systems should evolve to support the human dynamic, ensuring officers operate like collaborators who use AI as a sounding board—not make them "overrulers" who distrust any algorithmic suggestion or rubber-stampers who approve whatever AI says. AI in immigration isn't perfect. It can hallucinate laws, mishandle sensitive data that deserves Fort Knox-level security or reject a case with a digital shrug: "Too complicated, goodbye." That's why we need transparency, human oversight—and maybe a big red "Don't Panic" button. But if we build with care, the future is promising. We'll see AI that analyzes video (Photoshop weddings won't cut it), uses quantum computing (finally faster than a clerk on dial-up) and sends real-time updates that don't leave you in "Pending" purgatory. Immigration is—and always will be—a human business. But with AI as a savvy, respectful assistant, officers can focus on what really matters: serving people, not pushing paper. Ultimately, the goal is to ensure it's faster, fairer and insightful so families can reunite while processes flow. Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?
