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China wants to solve the hardest problem in robotics — making hands

Human hands – nimble, nerve-filled appendages that are the most flexible part of the human skeleton – are exceptionally complex. Many tasks that most people can do largely without thinking, from tying a pair of shoelaces to buttoning up a shirt, in fact require a complex set of neurological instructions and precise choreography. In thousands of years of human history, no machine has been able to truly replicate human’s greatest tool.

But now, as artificial intelligence (AI) races forwards, some companies think they are close to surpassing this final but most difficult hurdle in robotics. Most of them are in China.

A new suite of Chinese start-ups are leveraging China’s advantages in manufacturing and enthusiasm for what the government calls “embodied AI” to build the fully dextrous robotic hands that are needed to transform humanoid robots from dancing gimmicks into useful products.

Spray-on coating traps particles more tightly and nearly doubles air filter lifespan

Breathing clean air is essential for human health, making air filters indispensable in homes, hospitals, workplaces and industrial settings. However, despite decades of advances in filter materials and design, a major challenge remains. Capturing airborne particles is only half the battle; keeping them securely trapped is equally important.

Conventional air filters rely on weak adhesive forces, allowing some captured particles to detach and re-enter the air. This reduces filtration efficiency, shortens filter lifespan and highlights the need for smarter, more durable air filtration technologies.

China’s Moonshot pauses Kimi subscriptions amid hot demand, IPO push

SHANGHAI/HONG KONG, July 20 (Reuters) — Chinese startup Moonshot AI has temporarily paused new subscriptions after demand for its newly launched Kimi K3 model strained capacity, a bottleneck that comes as the company seeks fresh funding and prepares for a potential Hong Kong listing.

Moonshot ‌is in the process of unwinding its current offshore structure ahead of a Hong Kong initial public offering, two sources with knowledge of the matter said.

New driving AI ranks possible routes for safer, clearer decisions

A research team led by Jun Won Choi, a professor in the Department of Electrical and Computer Engineering at Seoul National University College of Engineering, has developed SafeDrive, an end-to-end (E2E) autonomous driving AI model aligned with recent global trends in autonomous driving technology. The work was selected as a highlight paper at the Conference on Computer Vision and Pattern Recognition (CVPR) 2026.

Highlight papers at CVPR represent approximately 3% of all submissions and about 10% of accepted papers, recognizing a small group of highly impactful studies. The achievement by Choi’s team is regarded as a significant milestone demonstrating that Korean researchers can independently develop world-class autonomous driving AI technologies.

Recent advances in autonomous driving have increasingly shifted toward Physical AI-based approaches to improve safety and handle edge cases. In particular, end-to-end learning methods—where large-scale driving data is collected, refined and used to emulate human driving decisions—have emerged as a core technology for building autonomous driving foundation models.

Repeating distance patterns let optical systems tackle large optimization problems

From planning transportation networks to organizing massive datasets, many of society’s most important challenges boil down to an optimization problem: finding the best solution among an enormous number of possibilities. As these problems increase in size and scope, however, the computational resources required to solve them can increase dramatically.

Now, researchers from Japan have identified a new way to tackle a broad class of optimization problems while keeping computational demands manageable.

Cellular and signalling mechanisms that regulate the bloodbrain barrier Reviews Molecular Cell Biology

This Review summarizes the latest advances in blood–brain barrier (BBB) research, highlighting how emerging findings on the modulation of BBB function and heterogeneity by cellular interactions and signalling pathways might shape BBB-targeted therapeutics.

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