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新加坡的医疗成本不断上涨，究竟是什么导致的？_我的网站

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     Lingjun Zhenwu M890 supernode instance  Photo: Courtesy of Alibaba CloudAlibaba Cloud on Tuesday officially launched its Lingjun Zhenwu M890 supernode instance in Ulanqab, North China's Inner Mongolia Autonomous Region, with the first batch of instances now available for sale in the region. 
The instance is designed to handle inference for mixture-of-experts models with up to 10 trillion parameters, the company said in a statement sent to the Global Times on Wednesday. 
This marks the first supernode-form computing architecture in China to successfully run large language models exceeding 2 trillion parameters, according to the company.
Industry expert Tian Feng told the Global Times that the commercial rollout of supernode infrastructure could significantly reduce training cycles, lower costs, and speed up iteration for AI developers requiring massive computational resources.
The company said the new instance has already been used to power commercial services for large language models such as KimiK3 and Qwen3.8Max.
The Lingjun Zhenwu M890 ­supernode instance supports FP8/FP4 low-precision computing. Through the ICNSwitch 1.0 chip, its scale-up interconnect scale has been expanded from 16 cards to 64 cards, with inter-card interconnect bandwidth boosted to 800 GB/s. Enterprises can provision 64-card, high-speed-interconnect computing units through the cloud without building their own data centers, according to the company.
In training scenarios such as autonomous driving and embodied intelligence, the instance delivers three times the training performance compared with the previous-generation Zhenwu 810E, the company said.
Ulanqab, where the supernode instance debuted, is one of Alibaba Cloud's five super data centers. The facility sources approximately 90 percent of its electricity from green energy, providing a low-carbon operating environment for high-density computing power.
Leveraging its climate, energy and network advantages, Ulanqab has transformed from "China's potato hometown" into the "token factory"  - a term increasingly used in the AI industry to describe infrastructure dedicated to producing the digital building blocks generated by large language models. 
By the end of 2025, the city had attracted 84 data center projects, including 81 intelligent computing centers, with total investment exceeding 500 ­billion yuan ($74.1 billion) and operational computing power reaching approximately 172,000 petaflops, ranking it firmly in the nation's top tier, according to domestic media reports.
On August 6, China's largest AI computing industrial park was completed and put into operation in Ulanqab. The project highlights a broader race in ­China to build massive AI data centers capable of supporting the next generation of AI models while addressing soaring electricity demand, according to Chinese experts.
In recent years, Inner Mongolia has been rapidly positioning itself as a global-scale AI computing center cluster. Major technology companies, including Huawei, Tencent, ByteDance and Alibaba; telecom operators China Mobile, China Telecom and China Unicom; as well as cyberspace infrastructure service provider VNET, have established computing facilities in the region.
As the AI industry gradually transitions from the training era to the inference era and large model parameters continue to expand, supernodes have become a central battleground for AI infrastructure.
Chinese vendors are accelerating deployments in this space. Huawei has commercially deployed more than 750 sets of its Ascend 384 supernodes across industries including internet, telecom operators, finance, education, healthcare, transportation and manufacturing. It is also the only domestic supernode to have trained state-of-the-art (SOTA) models.
Baidu AI Cloud has also launched its Tianchi 256-card supernode based on Kunlun chips, with support for major models including Wenxin, DeepSeek, GLM, and MiniMax.
Meanwhile, supercomputer manufacturer Sugon has unveiled China's first fully domestic 100,000-card AI ­supercluster Sugon 8000 (Dengfeng), integrating supercomputing and AI computing on a unified architecture. It has now been connected to the national supercomputing internet to provide computing services to government, research, and enterprise clients nationwide. 
Tian, former dean of SenseTime's Intelligence Industry Research Institute, told the Global Times that the flurry of domestic supernode launches reflects a broader inflection point as China's AI sector pivots from training capacity toward efficient, large-scale inference. 
The expert further said that the commercial viability of these systems - evidenced by Huawei's extensive deployed base, Baidu's rapid model adaptation and Sugon's integration into the national computing network - suggests domestic vendors are moving beyond proof-of-concept to genuine production-grade infrastructure, a prerequisite for sustaining the next wave of ­trillion-parameter model proliferation, Tian noted.
The move also underscores China's push for self-reliance in AI infrastructure as US chip export restrictions continue to tighten, Tian said, noting that, in the supernode domain, Chinese companies are shifting from imported graphics processing units toward homegrown interconnect chips and domestic compute clusters, a transition that could reshape value allocation across the AI industry chain.
。    新加坡的医疗成本不断上涨，引发了广泛的社会关注。而背后潜藏的主要问题——健康保险中的“按收费”模式，正逐渐成为国家金融灾难的潜在威胁。1. “按收费”计划的起源与问题2005年，新加坡健康保险领域的新秀Aviva引入了“按收费”计划，打破了健康保险市场的格局。该计划允许保险公司为医生和医院批准的任何治疗买单，导致医疗成本迅速上涨。这种模式让医生和医院可以选择最昂贵的治疗方案，而患者则因相信“最好的治疗”而积极参与。结果，医疗费用激增，公共医疗支出大幅攀升，最终负担转嫁给了消费者。数据显示，自2009年以来，政府在医疗保健方面的支出已增加了四倍，这种不可持续的增长趋势引发了社会的广泛担忧。来源：clema risk solutions2. 成本上升的背后：谁在为“按收费”买单随着“按收费”计划的普及，私立医院的医疗费用远远超过了公立医院，导致整体医疗成本的大幅上涨。研究表明，有“按收费”保险的患者，其医疗支出比没有此类保险的患者高出25%。这一问题引发了政府的关注。李显龙资政呼吁遏制过度治疗和过度开药，以控制医疗成本的攀升。然而，政治意愿的不足使得问题迟迟未得到根本解决。

二 | 在这一背景下，政府近年来尝试了一些零碎的措施，例如限制医生选择，但这些措施效果有限，未能真正解决成本上升的核心问题。来源：联合早报3. 变革迫在眉睫：如何解决“按收费”问题要解决医疗成本上升的问题，必须从根本上改革“按收费”保险计划。

三 | 我的建议是，取消在综合盾计划中使用MediSave资金的“按收费”覆盖范围，转而采用更具成本效益的计划。此外，保险计划的可移植性问题也需要得到解决。

四 | 新加坡精算协会的研究表明，提升保险的可移植性将有助于增强市场竞争，允许新加坡人选择更适合的保险产品。

五 | 总之，取消“按收费”计划和提升保险的可移植性，将是解决新加坡医疗成本问题的关键举措。

六 | 这是一场必须进行的改革，为了全社会的利益，迫切需要采取行动。来源：联合早报面对日益严峻的医疗成本问题，新加坡亟需对现有的健康保险体系进行全面改革。只有通过各方的共同努力，才能为全体居民提供可持续的、负担得起的医疗保障。参考资料：1. Commentary: To contain spiralling healthcare costs in Singapore, we must remove the original sin，channelnewsasia。

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Published on:12:50:47