In a pine forest on Michigan's Upper Peninsula, the only active nickel mine in the US is nearing the end of its life. At a time when carmakers want the metal for electric-vehicle batteries, nickel concentration at Eagle Mine is falling and could soon drop too low to warrant digging. Demand for nickel, copper, and rare earth elements is rapidly increasing amid the explosive growth of metal-intensive data centers, electric cars, and renewable energy projects. But producing these metals is becoming harder and more expensive because miners have already exploited the best resources. Here's how biotechnology could help . What we've been getting wrong about AI's truth crisis What would it take to convince you that the era of truth decay we were long warned about--where AI content dupes us, shapes our beliefs even when we catch the lie, and erodes societal trust in the process--is now here?

Abstract--We develop an energy management system (EMS) for artificial intelligence (AI) data centers with colocate d renewable generation. Under a cost-minimizing framework, th e EMS of renewable-colocated data center (RCDC) co-optimize s AI workload scheduling, on-site renewable utilization, an d electricity market participation. Within both wholesale and re tail market participation models, the economic benefit of the RCD C operation is maximized. Empirical evaluations using real-world traces of electricity prices, data center power consumptio n, and renewable generation demonstrate significant electric ity cost reduction from renewable and AI data center colocations. Index T erms --AI data center power system, energy management system, flexible demand, large load colocation, worklo ad scheduling.

Fox News chief national security correspondent Jennifer Griffin reports on what the United States and Israel are doing to stay ahead of adversaries in A.I. on'Special Report.' Today, something big and unprecedented is happening in Pittsburgh. The inaugural Pennsylvania Energy and Innovation summit at Carnegie Mellon University is the clearest and most dramatic manifestation yet of President Donald Trump's promises to make America energy dominant, lead in advanced technology, and create jobs and opportunity for working families in Pennsylvania and across America. In 2017, Mr. Trump said he was "elected to represent the citizens of Pittsburgh, not Paris." Today in the Steel City, I am proud to welcome the President and more than 60 CEOs of the world's most important companies and largest investors to my hometown to announce over 50 billion in new investments in energy, artificial intelligence (AI), and workforce development all targeted at making sure Pennsylvania powers the AI revolution.

Secretary of State Marco Rubio attends a signing ceremony for a peace agreement between Rwanda and the Democratic Republic of the Congo at the State Department on June 27, 2025, in Washington. DIGITAL DECEPTION: The State Department is investigating an impostor who reportedly pretended to be Secretary of State Marco Rubio with the help of AI. TECH SHIFT: Artificial Intelligence and automation are often used interchangeably. While the technologies are similar, the concepts are different. Automation is often used to reduce human labor for routine or predictable tasks, while A.I. simulates human intelligence that can eventually act independently.

Hussain Sajwani, owner of DAMAC Properties, said his company will invest 20 billion to build data centers across the U.S. in a press conference hosted by President-elect Trump at Mar-a-Lago on Jan. 7, 2025. Artificial intelligence is expanding quickly, and so is the energy required to run it. Modern AI data centers use much more electricity than traditional cloud servers. In many cases, the existing power grid cannot keep up. One innovative solution is gaining traction: repurposed EV batteries for AI data centers.

Artificial intelligence (AI) is fueling exponential electricity demand growth, threatening grid reliability, raising prices for communities paying for new energy infrastructure, and stunting AI innovation as data centers wait for interconnection to constrained grids. This paper presents the first field demonstration, in collaboration with major corporate partners, of a software-only approach--Emerald Conductor--that transforms AI data centers into flexible grid resources that can efficiently and immediately harness existing power systems without massive infrastructure buildout. Conducted at a 256-GPU cluster running representative AI workloads within a commercial, hyperscale cloud data center in Phoenix, Arizona, the trial achieved a 25% reduction in cluster power usage for three hours during peak grid events while maintaining AI quality of service (QoS) guarantees. By orchestrating AI workloads based on real-time grid signals without hardware modifications or energy storage, this platform reimagines data centers as grid-interactive assets that enhance grid reliability, advance affordability, and accelerate AI's development.

The event marked the launch of the company's new business line, Redwood Energy, which will initially repurpose (rather than recycle) batteries with years of remaining life to create renewable-powered microgrids. Such small-scale energy systems can operate on or off the larger electricity grid, providing electricity for businesses or communities. Redwood Materials says many of the batteries it takes in for processing retain more than half their capacity. "We can extract a lot more value from that material by using it as an energy storage project before recycling it," JB Straubel, Redwood's founder and chief executive, said at the event. This first microgrid, housed at the company's facility in the Tahoe Reno Industrial Center, is powered by solar panels and capable of generating 64 megawatt-hours of electricity, making it one of the nation's largest such systems.

The explosive growth of artificial intelligence has created gigawatt-scale data centers that fundamentally challenge power system operation, exhibiting power fluctuations exceeding 500 MW within seconds and millisecond-scale variations of 50-75% of thermal design power. This paper presents a comprehensive theoretical framework that reconceptualizes Virtual Power Plants (VPPs) to accommodate these extreme dynamics through a four-layer hierarchical control architecture operating across timescales from 100 microseconds to 24 hours. We develop control mechanisms and stability criteria specifically tailored to converter-dominated systems with pulsing megawatt-scale loads. We prove that traditional VPP architectures, designed for aggregating distributed resources with response times of seconds to minutes, cannot maintain stability when confronted with AI data center dynamics exhibiting slew rates exceeding 1,000 MW/s at gigawatt scale. Our framework introduces: (1) a sub-millisecond control layer that interfaces with data center power electronics to actively dampen power oscillations; (2) new stability criteria incorporating protection system dynamics, demonstrating that critical clearing times reduce from 150 ms to 83 ms for gigawatt-scale pulsing loads; and (3) quantified flexibility characterization showing that workload deferability enables 30% peak reduction while maintaining AI service availability above 99.95%. This work establishes the mathematical foundations necessary for the stable integration of AI infrastructure that will constitute 50-70% of data center electricity consumption by 2030.

On June 12, Alexandr Wang stepped down as Scale's CEO to chase his most ambitious moonshot yet: building smarter-than-human AI as head of Meta's new "superintelligence" division. As part of his move, Meta will invest 14.3 billion for a minority stake in Scale AI, but the real prize isn't his company--it's Wang himself. Wang, 28, is expected to bring a sense of urgency to Meta's AI efforts, which this year have been plagued by delays and underwhelming performance. Once the undisputed leader of open-weight AI, the U.S. tech giant has been overtaken by Chinese rivals like DeepSeek on popular benchmarks. Although Wang, who dropped out of MIT at 19, lacks the academic chops of some of his peers, he offers both insight into the types of data Meta's rivals use to improve their AI systems, and unrivaled ambition.

A 10-year moratorium on state-level AI regulation included in President Donald Trump's "Big Beautiful Bill" has brushed up against a mounting battle over the growth of data centers. On Thursday, Representative Thomas Massie, a Kentucky Republican, posted on X that the megabill's 10-year block on states regulating artificial intelligence could "make it easier for corporations to get zoning variances, so massive AI data centers could be built in close proximity to residential areas." Massie, who did not vote for the bill, followed up his initial tweet with a screenshot of a story on a proposed data center in Oldham County, Kentucky, which downsized and changed locations following local pushback. "This isn't a conspiracy theory; this was a recent issue in my Congressional district," he wrote of concerns over the placement of data centers. "It was resolved at the local level because local officials had leverage. The big beautiful bill undermines the ability of local communities to decide where the AI data centers will be built."