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.
Keep Reading
Redefining sensor performance with advanced physical AI and signal processing.
Updated
January 8, 2026 6:32 PM
.jpg)
Robot with human features, equipped with a visual sensor. PHOTO: UNSPLASH
Atomathic, the company once known as Neural Propulsion Systems, is stepping into the spotlight with a bold claim: its new AI platforms can help machines “see the invisible”. With the commercial launch of AIDAR™ and AISIR™, the company says it is opening a new chapter for physical AI, AI sensing and advanced sensor technology across automotive, aviation, defense, robotics and semiconductor manufacturing.
The idea behind these platforms is simple yet ambitious. Machines gather enormous amounts of signal data, yet they still struggle to understand the faint, fast or hidden details that matter most when making decisions. Atomathic says its software closes that gap. By applying AI signal processing directly to raw physical signals, the company aims to help sensors pick up subtle patterns that traditional systems miss, enabling faster reactions and more confident autonomous system performance.
"To realize the promise of physical AI, machines must achieve greater autonomy, precision and real-time decision-making—and Atomathic is defining that future," said Dr. Behrooz Rezvani, Founder and CEO of Atomathic. "We make the invisible visible. Our technology fuses the rigor of mathematics with the power of AI to transform how sensors and machines interact with the world—unlocking capabilities once thought to be theoretical. What can be imagined mathematically can now be realized physically."
This technical shift is powered by Atomathic’s deeper mathematical framework. The core of its approach is a method called hyperdefinition technology, which uses the Atomic Norm and fast computational techniques to map sparse physical signals. In simple terms, it pulls clarity out of chaos. This enables ultra-high-resolution signal visualization in real time—something the company claims has never been achieved at this scale in real-time sensing.
AIDAR and AISIR are already being trialled and integrated across multiple sectors and they’re designed to work with a broad range of hardware. That hardware-agnostic design is poised to matter even more as industries shift toward richer, more detailed sensing. Analysts expect the automotive sensor market to surge in the coming years, with radar imaging, next-gen ADAS systems and high-precision machine perception playing increasingly central roles.
Atomathic’s technology comes from a tight-knit team with deep roots in mathematics, machine intelligence and AI research, drawing talent from institutions such as Caltech, UCLA, Stanford and the Technical University of Munich. After seven years of development, the company is ready to show its progress publicly, starting with demonstrations at CES 2026 in Las Vegas.
Suppose the future of autonomy depends on machines perceiving the world with far greater fidelity. In that case, Atomathic is betting that the next leap forward won’t come from more hardware, but from rethinking the math behind the signal—and redefining what physical AI can do.