Redefining sensor performance with advanced physical AI and signal processing.
Updated
January 8, 2026 6:32 PM
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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.
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Sensing technology is facilitating the transition of drone delivery services from trial phases to regular daily operations.
Updated
January 8, 2026 6:27 PM
A quadcopter drone with package attached. PHOTO: FREEPIK
A new partnership between Hesai Technology, a LiDAR solutions company and Keeta Drone, an urban delivery platform under Meituan, offers a glimpse into how drone delivery is moving from experimentation to real-world scale.
Under the collaboration, Hesai will supply solid-state LiDAR sensors for Keeta’s next-generation delivery drones. The goal is to make everyday drone deliveries more reliable as they move from trials to routine operations. Keeta Drone operates in a challenging space—low-altitude urban airspace. Its drones deliver food, medicine and emergency supplies across cities such as Beijing, Shanghai, Hong Kong and Dubai. With more than 740,000 deliveries completed across 65 routes, the company has discontinued testing the concept. It is scaling it. For that scale to work, drones must be able to navigate crowded environments filled with buildings, trees, power lines and unpredictable conditions. This is where Hesai’s technology comes in.
Hesai’s solid-state LiDAR is integrated into Keeta's latest long-range delivery drones. LiDAR stands for Light Detection and Ranging. In simple terms, it is a sensing technology that helps machines understand their surroundings by sending out laser pulses and measuring how they bounce back. Unlike GPS, LiDAR does not rely solely on satellites to determine position. Instead, it gives drones a direct sense of their surroundings, helping them spot small but critical obstacles like wires or tree branches.
In a recent demonstration, Keeta Drone completed a nighttime flight using LiDAR-based navigation alone without relying on cameras or satellite positioning. This shows how the technology can support stable operations even when visibility is poor or GPS signals are limited.
The LiDAR system used in these drones is Hesai’s second-generation solid-state model known as FTX. Compared with earlier versions, the sensor offers higher resolution while being smaller and lighter—important considerations for airborne systems where weight and space are limited. The updated design also reduces integration complexity, making it easier to incorporate into commercial drone platforms. Large-scale production of the sensor is expected to begin in 2026.
From Hesai’s perspective, delivery drones are one of several forms robots are expected to take in the coming decades. Industry forecasts suggest robots will increasingly appear in many roles from industrial systems to service applications, with drones becoming a familiar part of urban infrastructure rather than a novelty.
For Keeta Drone, this improves safety and reliability. And for the broader industry, it signals that drone logistics is entering a more mature phase—one defined less by experimentation and more by dependable execution. Taken together, the partnership highlights a practical evolution in drone delivery.
As cities grow more complex, the question is no longer whether drones can fly but whether they can do so reliably, safely and at scale. At its core, this partnership is not about drones or sensors as products. It is about what it takes to make a complex system work quietly in real cities. As drone delivery moves out of pilot zones and into everyday use, reliability matters more than novelty.