AutoFlight’s five-tonne Matrix bets on heavy payloads and regional range to prove the case for electric flight
Updated
February 10, 2026 12:56 PM

A multiroter flying through a blue sky. PHOTO: UNSPLASH
The nascent industry of electric vertical takeoff and landing (eVTOL) aircraft has long been defined by a specific set of limitations: small payloads, short distances and a primary focus on urban air taxis. AutoFlight, a Chinese aviation startup, recently moved to shift that narrative by unveiling "Matrix," a five-tonne aircraft that represents a significant leap in scale for electric aviation.
In a demonstration at the company’s flight test center, the Matrix completed a full transition flight—the technically demanding process of switching from vertical lift-off to forward wing-born flight and back to a vertical landing. While small-scale drones and four-seat prototypes have become increasingly common, this marks the first time an electric aircraft of this mass has successfully executed the maneuver.
The sheer scale of the Matrix places it in a different category than the "flying cars" currently being tested for hops over city traffic. With a maximum takeoff weight of 5,700 kilograms (roughly 12,500 pounds), the aircraft has the footprint of a traditional regional turboprop, boasting a 20-meter wingspan. Its size allows for configurations that the industry has previously struggled to accommodate, including a ten-seat business class cabin or a cargo hold capable of carrying 1,500 kilograms of freight.
This increased capacity is more than just a feat of engineering; it is a direct attempt to solve the financial hurdles that have plagued the sector, specifically addressing the skepticism industry analysts have often expressed regarding the economic viability of smaller eVTOLs. These critics frequently cite the high cost of operation relative to the low passenger count as a barrier to entry.
AutoFlight’s founder and CEO, Tian Yu, suggested the Matrix is a direct response to those concerns. “Matrix is not just a rising star in the aviation industry, but also an ambitious disruptor,” Yu stated. “It will eliminate the industry perception that eVTOL = short-haul, low payload and reshape the rules of eVTOL routes. Through economies of scale, it significantly reduces transportation costs per seat-kilometer and per ton-kilometer, thus revolutionizing costs and driving profitability.”
To achieve this, the aircraft utilizes a "lift and cruise" configuration. In simple terms, this means the plane uses one set of dedicated rotors to lift it off the ground like a helicopter, but once it reaches a certain speed, it uses a separate propeller to fly forward like a traditional airplane, allowing the wings to provide the lift. This design is paired with a distinctive "triplane" layout—three layers of wings—and a six-arm structure to keep the massive frame stable.
These features allow the Matrix to serve a variety of roles. For the "low-altitude economy" being promoted by Chinese regulators, the startup is offering a pure electric model with a 250-kilometer range for regional hops, alongside a hybrid-electric version capable of traveling 1,500 kilometers. The latter version, equipped with a forward-opening door to fit standard air freight containers, targets a logistics sector still heavily reliant on carbon-intensive trucking.
However, the road to commercial flight remains a steep one. Despite the successful flight demonstration, AutoFlight faces the same formidable headwinds as its competitors, such as a complex global regulatory landscape and the rigorous demands of airworthiness certification. While the Matrix validates the company's high-power propulsion, moving from a test-center demonstration to a commercial fleet will require years of safety data.
Nevertheless, the debut of the Matrix signals a maturation of the startup’s ambitions. Having previously developed smaller models for autonomous logistics and urban mobility, AutoFlight is now betting that the future of electric flight isn't just in avoiding gridlock, but in hauling the weight of regional commerce. Whether the infrastructure and regulators are ready to accommodate a five-tonne electric disruptor remains the industry's unanswered question.
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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.