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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.
Inflammation may drive Dravet syndrome, offering a potential new treatment target
An overactive immune response in the brain may play a role in Dravet syndrome, a rare and severe genetic epilepsy that typically begins in infancy, according to Weill Cornell Medicine researchers. Children with the condition experience frequent seizures that are often difficult to control with medication and may also face developmental, cognitive and behavioral challenges. Until now, most research has focused on how a mutation in the SCN1A gene disrupts electrical signaling in the brain.
“Rather than being a disorder only involving abnormal electrical signaling, the disease may also involve a self-sustaining immune response triggered by DNA released from stressed neurons,” said study senior author Dr. Li Gan, the Burton P. and Judith B. Resnick Distinguished Professor in Neurodegenerative Diseases and director of the Helen and Robert Appel Alzheimer’s Disease Research Institute at Weill Cornell. “As a result, inflammation may help drive and sustain the disease. This finding links seizures to the brain’s immune system in a way that had not been fully appreciated before.”
The new preclinical study, published July 29 in Nature Neuroscience, identified an inflammatory pathway called cGAS-STING-interferon (IFN-I) signaling as a major contributor to disease progression. Blocking this molecular pathway could lead to new therapeutic strategies for epilepsy disorders.
