AI Ultrasound Brain-Computer Interface Company 'BCI-Sonics' Completes Angel Round Series Financing of 100 Million Yuan
Huachao Shenkong has secured another 100 million yuan in its angel round—a name that sounds like it belongs in a sci-fi movie. Ultrasonic brain-computer interface? This tech combo may sound intimidating at first, but when you think about it, how much better can ultrasonic waves be at reading or intervening with brain signals compared to traditional electrode-based BCIs? Isn't it just slapping together two buzzwords—"ultrasound imaging" and "brain-computer interface"—to create a new concept for f
Analysis
Looking at that "Top 50 Tech Innovators" list, the average stock price increase this year has exceeded 30%, with companies like Rilix Technology and Dingtai High-Tech doubling in value. Media headlines are written in an inspiring tone, as if China's hardcore tech is about to crush the global competition overnight. But unpack it: what are the selection criteria? Segment leaders, increased capital expenditure, consecutive growth in R&D investment, institutional forecasts of profit growth above 15%—this is practically a tailor-made stock pool. Capital is betting big on A-share tech, and international investment banks are forming a consensus? Consensus is often a precursor to a bubble. These companies are spread across electronics, semiconductors, and PCB fields—indeed critical links in the supply chain—but are their soaring stock prices driven by genuine technological breakthroughs or by the "domestic substitution" narrative and capital clustering? Increased R&D spending doesn’t necessarily mean stellar output; consecutive rises in capital expenditure could also indicate low-level repetitive construction. The A-share tech sector loves to package "cyclical upticks" as "growth explosions," but when the tide recedes, how many companies will be found swimming naked?
In the AI boom, this contradiction is even starker. On one hand, companies like Huachao Shenkong are raising hundreds of millions, while on the other, hot topics include "After using AI, companies seem poorer." How many businesses treat AI as a miracle cure, only to find that the tools haven’t saved costs—instead, they’ve spent fortunes on servers and hired PhDs, ending up with nothing more than a chatbot? The difficulty in implementing AI lies not in the technology itself, but in unclear application scenarios and business models. Capital doesn’t care about these; it just invests in projects with flashy names in crowded tracks. OpenAI chip veterans jumping ship to Anthropic, industry talent shuffling around like mahjong tiles—technical expertise gets diluted. And domestic companies? Busy with fundraising, going public, cashing out—few are truly tackling the hard problems.
As for the 600% surge in the street-stall economy, with night market vendors returning and making it onto the hot list alongside AI high-tech—it’s a masterful piece of irony. On one side, Silicon Valley elites discuss superhuman intelligence; on the other, small vendors are shouting to make a living. Whose lives has AI actually improved? The R&D staff at those tech companies with doubled stock prices might be pulling all-nighters until they go bald, while stock traders are losing sleep over anxiety from chasing ups and downs. Capital pouring into the tech track sounds high-end, but take a closer look at those companies' businesses—how many are slapping "smart" labels on low-end manufacturing? Semiconductors and high-end manufacturing are national necessities, but when capital rushes in en masse, it’s easy to inflate valuation bubbles. Companies like Huachao Shenkong, working on brain-computer interfaces, are still eons away from commercialization, yet they’re already valued in the hundreds of millions—doesn’t that sound like drawing a cake to satisfy hunger?
We always love to talk about disruptive innovation, but in reality, many AI advances are nothing more than incremental improvements. If ultrasonic BCIs could truly and non-invasively read neural signals, it would indeed be a medical breakthrough—but at this stage, it’s more of an experimental concept. Those companies in the Top 50 Tech Innovators list have seen their stock prices soar, but how deep are their technological moats? Retail investors in A-shares follow the herd, buying tech stocks thinking they’re investing in the future, when in fact they might be buying a pile of PowerPoint slides and expectations. The game of capital is always like this: first hype the concept, then tell the story, and when the bubble inflates, cash out and leave behind a mess. Let’s hope the AI industry doesn’t become the next bike-sharing or blockchain craze—lots of noise, but in the end, all that’s left is overcapacity and loss-making companies.
Of course, we can’t completely dismiss everything. Funding can accelerate R&D, and capital injection can drive industrial upgrades. The question is: is our innovation ecosystem healthy enough? Are there teams truly making breakthroughs in foundational technology? Or is everyone playing a game of passing the hot potato? Huachao Shenkong’s fundraising might be a good omen, but only if it can bring the technology out of the lab and stop keeping it on paper. The surge in the Top 50 Tech Innovators list should also serve as a warning: what the market adores is often the most bubble-prone. In the AI era, we need cool heads even more—don’t let the noise of capital throw you off track. Technology should serve people, not become a financial derivative. For now, less gimmicks and more substance is what really matters.
Disclaimer: The above content is generated by AI and is for reference only.