Overview Energy plans to collect sunlight in orbit and send it to Earth, giving Meta early access to a new source of round-the-clock power
Updated
April 29, 2026 3:20 PM
A corona mass ejection erupts from our sun. PHOTO: UNSPLASH
Overview Energy, a startup focused on space-based power systems, has announced a new agreement with Meta to develop a new source of electricity for data centers. The partnership centres on space solar energy, with an orbital demonstration planned for 2028 and commercial power delivery targeted for 2030.
The deal gives Meta early access to as much as 1 gigawatt of future capacity from Overview’s system. That matters because large technology companies are searching for reliable power sources as demand rises from AI computing and data center expansion.
Overview’s idea is straightforward, though the engineering is ambitious. The company plans to place satellites in orbit that collect sunlight continuously in space. That energy would then be sent to existing solar sites on Earth, where it would be converted into electricity.
Unlike ground-based solar farms, which only generate power when the sun is shining locally, a space-based system is designed to extend power generation beyond daylight hours. In theory, this could help solar facilities produce electricity around the clock without using extra land.
"Space solar technology represents a transformative step forward by leveraging existing terrestrial infrastructure to deliver new, uninterrupted energy from orbit. We're excited to partner with Overview Energy to pioneer innovative energy solutions to advance our AI ambitions and infrastructure", said Nat Sahlstrom, VP of Energy and Sustainability, Meta. "This collaboration demonstrates our commitment to innovation – leveraging cutting-edge technology to strengthen America's energy leadership".
For Meta, the agreement is less about a near-term energy fix and more about securing future options. Major data center operators are increasingly competing for electricity as AI systems require more computing power and more cooling capacity. Traditional energy projects can take years to build, making alternative supply models more attractive.
Overview says its system is designed to work with solar projects that already exist. Instead of building entirely new power plants, the company aims to increase output from current sites by adding energy received from orbit.
"Space is becoming part of America's energy infrastructure", said Marc Berte, CEO of Overview Energy. "Our approach to space solar energy enables hyperscalers and technology providers to secure clean power with reliable siting, and speed to power.” "Together with Meta, we're looking beyond traditional constraints on where and when power can be delivered to meet the growing demand for electricity".
The larger significance of the partnership is what it signals about the energy market. As AI infrastructure expands, companies are beginning to look beyond conventional grids, gas plants and land-based renewables. Technologies once considered experimental are now being explored as part of long-term infrastructure planning.
There is still a long road ahead. Space solar power has been discussed for decades, but commercial deployment remains unproven. Launch costs, regulation and system reliability will all matter.
Even so, the Meta-Overview agreement shows how rising demand for constant power is reshaping where the technology sector looks for its next energy source.
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HKU professor apologizes after PhD student’s AI-assisted paper cites fabricated sources.
Updated
January 8, 2026 6:33 PM
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The University of Hong Kong in Pok Fu Lam, Hong Kong Island. PHOTO: ADOBE STOCK
It’s no surprise that artificial intelligence, while remarkably capable, can also go astray—spinning convincing but entirely fabricated narratives. From politics to academia, AI’s “hallucinations” have repeatedly shown how powerful technology can go off-script when left unchecked.
Take Grok-2, for instance. In July 2024, the chatbot misled users about ballot deadlines in several U.S. states, just days after President Joe Biden dropped his re-election bid against former President Donald Trump. A year earlier, a U.S. lawyer found himself in court for relying on ChatGPT to draft a legal brief—only to discover that the AI tool had invented entire cases, citations and judicial opinions. And now, the academic world has its own cautionary tale.
Recently, a journal paper from the Department of Social Work and Social Administration at the University of Hong Kong was found to contain fabricated citations—sources apparently created by AI. The paper, titled “Forty Years of Fertility Transition in Hong Kong,” analyzed the decline in Hong Kong’s fertility rate over the past four decades. Authored by doctoral student Yiming Bai, along with Yip Siu-fai, Vice Dean of the Faculty of Social Sciences and other university officials, the study identified falling marriage rates as a key driver behind the city’s shrinking birth rate. The authors recommended structural reforms to make Hong Kong’s social and work environment more family-friendly.
But the credibility of the paper came into question when inconsistencies surfaced among its references. Out of 61 cited works, some included DOI (Digital Object Identifier) links that led to dead ends, displaying “DOI Not Found.” Others claimed to originate from academic journals, yet searches yielded no such publications.
Speaking to HK01, Yip acknowledged that his student had used AI tools to organize the citations but failed to verify the accuracy of the generated references. “As the corresponding author, I bear responsibility”, Yip said, apologizing for the damage caused to the University of Hong Kong and the journal’s reputation. He clarified that the paper itself had undergone two rounds of verification and that its content was not fabricated—only the citations had been mishandled.
Yip has since contacted the journal’s editor, who accepted his explanation and agreed to re-upload a corrected version in the coming days. A formal notice addressing the issue will also be released. Yip said he would personally review each citation “piece by piece” to ensure no errors remain.
As for the student involved, Yip described her as a diligent and high-performing researcher who made an honest mistake in her first attempt at using AI for academic assistance. Rather than penalize her, Yip chose a more constructive approach, urging her to take a course on how to use AI tools responsibly in academic research.
Ultimately, in an age where generative AI can produce everything from essays to legal arguments, there are two lessons to take away from this episode. First, AI is a powerful assistant, but only that. The final judgment must always rest with us. No matter how seamless the output seems, cross-checking and verifying information remain essential. Second, as AI becomes integral to academic and professional life, institutions must equip students and employees with the skills to use it responsibly. Training and mentorship are no longer optional; they’re the foundation for using AI to enhance, not undermine, human work.
Because in this age of intelligent machines, staying relevant isn’t about replacing human judgment with AI, it’s about learning how to work alongside it.