China is winning AI race

Investors start taking Chinese AI seriously

MetaX opened in Shanghai and jumped 700% on day one.

Global investors are adding exposure to Chinese AI companies as new chipmakers and software firms rush to list in mainland China and Hong Kong, encouraged by Beijing’s push for tech self-reliance. Reuters reports this is happening alongside growing unease about stretched valuations in U.S.-listed AI stocks, especially on the Nasdaq.

This is less about believing China suddenly leads AI and more about investors wanting another place to stand when the U.S. trade looks crowded. When firms like UBS Global Wealth Management call China tech “most attractive,” they are reacting to policy clarity, fast commercialization, and companies like Alibaba tying models, chips, and cloud into real products.

Expect more capital flowing into Chinese chip and robotics names as long as listings keep coming and policy support stays visible. It also signals that diversification now feels like risk control, not caution.

At some point, do these bets become conviction, or just a hedge made at 9 a.m. while trading screens glow white?

The AI boom is built on borrowed belief

ChatGPT has 800 million weekly users, and the money still isn’t slowing.

Rafael Behr argues the US economy is being propped up by an AI investment surge that looks a lot like past bubbles, from railroads to dotcoms. OpenAI is valued near $500bn, big tech firms are committing roughly $1.5tn to AI infrastructure, and without that spending, US growth would look thin.

What stands out is how much of this bet rests on future promises rather than current capability. Large language models still hallucinate, recycle junk data, and lack real understanding, yet they are already embedded in work, education, and even children’s products.

Behr’s sharpest point is that neither the US nor China wants global rules while racing for advantage, which leaves regulation to executives and states with every incentive to move fast and clean up later. If the correction comes, it could force a long-delayed conversation about limits, oversight, and who actually controls these systems.

When the screens go quiet after the next sell-off, will anyone still be willing to slow this down and ask what AI is really for?

AI helps output, not always thinking

MIT put electrodes on people’s heads to watch them think with AI.

Researchers used EEG scans on 54 students while they wrote essays, some with ChatGPT and some without it. The AI-assisted group showed less activity in brain networks linked to cognitive processing and struggled to quote their own work afterward.

The issue here is not laziness, it’s substitution. When AI summarizes questions, generates ideas, and polishes language, the brain often skips the hard middle where learning actually happens.

Similar results show up elsewhere. A Carnegie Mellon and Microsoft survey of 319 white-collar workers found higher trust in AI tools meant less critical thinking, while six in 10 UK schoolchildren told Oxford University Press AI had hurt their school skills. Better outputs, weaker understanding, quieter classrooms.

If AI keeps getting easier to use late at night on a glowing screen, the real question is whether we design it to replace thinking, or to force us back into it.

Prohuman team

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