“The industry is thinking about how to make machines understand people’s minds, while we are exploring how to make the brain understand machines,” said Dr. Liu Bing, founder of Mindtrix, at the 2026 Yabuli Forum, explaining their work.

Currently, the global competition in brain-computer interfaces focuses on “reading” brain signals to achieve cool applications such as thought control. Mindtrix, however, focuses on feedback-based motor control based on “brain-computer dual learning” and visual reconstruction based on closed-loop large-scale stimulation. Dr. Liu Bing defines this as “reverse engineering”—they are tackling “writing” brain-computer interfaces, aiming to input precise electrical signal maps into the visual cortex of the brain to restore sight to those who are completely blind.

These two directions outline two completely different philosophies of innovation. The former iterates and optimizes along a relatively clear path, while the latter attempts to establish a completely new basic communication protocol at the boundary between biology and machines. This is widely recognized in the industry as one of the ultimate challenges of “brain-computer interfaces,” its difficulty likened to the “Mount Everest” of the field.

Liu Bing stated that this "reverse" choice is essentially a redefinition of the "time dimension" of innovation. MingShi Brain-Computer actively embraces the highest uncertainty and the longest R&D cycle. The reward is not an immediate product, but the right to define a "root technology" first. We are providing a set of understandable and traceable "development consensus" for hard-core innovations that cannot be "agilely iterated."

He announced a clear timeline: complete the first fully blind subject experiment in 2026, initiate registration clinical trials in 2028, and aim for product launch around 2030.

Liu Bing frankly stated, "In the field of hard technology, what's more difficult than technological breakthroughs is managing the expectations of all parties and setting a clear benchmark for 'patience.'" This timeline, in effect, erects beacons for all participants, including investors, partners, and even regulatory agencies, amidst the fog of scientific exploration. It transforms prolonged uncertainty into a series of verifiable and debatable

phased goals, thereby attempting to build a long-term trust relationship based on rational consensus. This is perhaps the essential skill that all long-cycle hard-tech companies must cultivate.

Regarding the investment and financing environment in the brain-computer interface field, Liu Bing also pointed out several shortcomings in the current ecosystem: a lack of sufficiently long-term dedicated funds, insufficient tax incentives for investments in cutting-edge technologies, and overly singular and short-term exit channels. Liu Bing's views coincide with the earlier appeals of some hard-tech investors—only when investing in the most cutting-edge and fundamental technologies becomes a "profitable and sustainable" endeavor will social capital systematically flow into these tracks that determine the future of the nation.

"The biggest risk may not be temporary technological failure, but rather the loss of resolve of the entire system in the face of the 'sunk costs' of long-termism," Liu Bing pointed out, highlighting the deepest challenge of hard-tech innovation. Climbing the "Mount Everest of brain-computer interfaces" requires not only the courage of one or two explorers, but also a complete logistical support system to support a long-term expedition.

Mindtrix is an implantable brain-computer interface (BCI) technology company founded by PhDs who returned from top overseas BCI laboratories. It focuses on solutions such as visual reconstruction. With a vision to become a globally leading implantable BCI technology company for disruptive medicine, the company provides revolutionary solutions for the treatment of neurological diseases and the development of human potential.

Currently, the company focuses on cutting-edge fields such as visual reconstruction and motor control. Based on "brain-computer dual learning" for feedback-based motor control and visual reconstruction based on closed-loop large-scale stimulation, the company has made breakthroughs in several key technologies for implantable BCIs.

The founding team comes from top international research institutes and universities such as the University of California, Berkeley, Duke University, the Sokel Institute for Biological Studies, the University of California, Irvine, Johns Hopkins University, the University of Chicago, and the Institute of Automation, Chinese Academy of Sciences. They have extensive research experience and achievements in brain-computer dual learning decoding algorithms, visual reconstruction, flexible neural electrodes, and neuromodulation, making their overall technological strength globally leading.

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