Every Daily Hot Comment | "Six Little Dragons" Group Core Technology Gets Listing "Ticket," "Who Can Most Effectively Implement" Becomes the AI Investment Logic

AI · How will a shift in AI investment logic toward execution and delivery reshape the market?

Daily Economic News Commentator Zhao Linan

On March 29, the Hong Kong Exchanges and Clearing disclosed the post-hearing materials for the Spatial Intelligence unicorn group after its update. This means that one of “Hangzhou’s Six Little Dragons” has officially obtained the “entry ticket” to list and has entered the sprint stage for a Hong Kong IPO (initial public offering).

At a turning point in the global AI (artificial intelligence) industry, as it shifts from a “computing power race” to “value realization,” the fact that Qunhe Technology is first to cross the line is not only a major event for Hangzhou’s tech circle, but also a symbolic signal of China’s AI industry moving from “idealized narratives” to “value creation.” It is reported that among the “Six Little Dragons,” in addition to Qunhe Technology, the IPO application for the STAR Market on the Shanghai Stock Exchange initiated by Unitree Technology has been accepted, Yunshenchu Technology has entered the filing stage for IPO instructor/supervision records, and Qiangnao Technology has submitted its IPO application to the Hong Kong Exchanges and Clearing in a confidential manner. By knocking on the door of the capital market, the “Six Little Dragons” are also embarking on a new journey of corporate evolution and industrial development.

In the author’s view, there are at least three takeaways.

First, the certainty of commercial value is more important than the imagination behind storytelling.

There was a time when, as long as a company’s track was forward-looking enough, its story was told grand enough, and the space for imagining the future was broad enough, capital was still willing to generously fund it even if it posted massive losses year after year. However, today’s AI startup founders are facing a kind of collective anxiety: computing costs remain high, while the path to monetization for the C-end remains unclear. In the parameter “collisions” where “big efforts lead to miracles,” many companies have fallen into a swamp of having only “imagination” but no “cash flow.”

Qunhe Technology is able to stand out at this point largely because its financial statements contain tangible “certainty.” According to the hearing materials, in recent years Qunhe Technology’s gross margin has stayed at over 80%. More importantly, in 2025 the company has achieved a turnaround to positive adjusted net profit. This shows that its business model has already been proven, bringing a qualitative shift from “burning cash” to “generating cash.”

Second, hard-core strength built through deep vertical cultivation is easier to break through than an all-round layout.

Qunhe Technology provides an example: focus on the vertical field of “spatial intelligence,” make it deep and thorough, and form a moat. If today’s mainstream large language models are AI’s “language hub,” then spatial intelligence is the robot’s “visual and commonsense brain.” Traditional AI learns the world by “watching videos,” but what it learns are only flat two-dimensional pixels, lacking real perception of physical laws. Qunhe Technology, on the other hand, has access to tens of millions of real floorplan drawings and 3D structured models. These data include not only length, width, and height, but also materials, light-and-shadow reflection rates, and even topological relationships between objects—e.g., a table must be on the ground and cannot hang suspended in midair.

Backed by years of accumulation of 3D digital assets, Qunhe Technology has launched its spatial intelligence platform SpatialVerse. This is a “creation engine” capable of automatically generating massive numbers of physically correct synthetic 3D datasets. When general-purpose computing power is something everyone can buy, such extremely vertical, scarce, high-quality structured data become barriers that general large-model vendors find difficult to cross easily.

Finally, the ability to land applications in real scenarios matters to the market more than technical specifications.

For the industry, if trillion-parameter capability cannot solve an actual problem on the production line, then its value is equal to zero. Qunhe Technology’s first-mover advantage lies precisely in its strong ability to implement in real-world scenarios. It has not stayed at the stage of tech “self-indulgence” in a lab; instead, it has integrated high-end AI algorithms into the real industrial ground. In the design of traditional home furnishings, public interior projects, and retail chain stores, Qunhe Technology uses AI-based automatic layout and real-time cloud rendering to increase designers’ efficiency by several times.

Even more explosive is Qunhe Technology’s deployment in embodied intelligence. Today, for robots to truly enter millions of households, the biggest bottleneck is the lack of enough training scenarios that are both plentiful and sufficiently safe. Robots cannot directly practice walking and carrying tea in real homes because the cost of trial and error is too high. Qunhe Technology has ingeniously captured this huge industrial need. Its built 3D virtual space provides these AI robots with a perfect “sim-to-real” simulation practice environment. In the digital twin world constructed by Qunhe Technology, robots perform tens of millions of rounds of collision, grasping, and obstacle-avoidance training, and then transfer the learned capabilities to real-world physical bodies.

When a technology becomes the “infrastructure” and “water-seller” for a future trillion-level robot industry, its market value no longer needs to be proven by pale benchmark scores—the industry’s real willingness to pay is the best litmus test.

Only eagles that grow wings can keep flying. Qunhe Technology’s “IPO inspiration playbook” is very simple yet profoundly weighty: give up hollow stories and return to the essence of business; refuse fussy internal involution and deeply cultivate core barriers; don’t worship dull parameters—go all in on real-world implementation.

Daily Economic News