一 | 就在刚刚，苹果正式更新了 Mac mini 产品线，售价 6999 元起，首发搭载全新一代 2nm 制程的 M6 芯片，同时提供 M5 Pro 版本可选，8 月 25 日开启订购，9 月 22 日正式发售。
Illustration: Liu Xiangya/GT Recent media reports have questioned whether a natural gas plant built to power an Amazon data center project in Texas could become the largest climate polluter in the US. The controversy, whatever the eventual outcome, offers a reality check for America's artificial intelligence (AI) drive. It exposes a growing contradiction: The US is racing to expand its AI capabilities, yet its protectionist trade policies are making it harder and more costly to access some of the clean-energy technologies needed to sustain that expansion. This raises a broader question: Can an energy-intensive AI race afford the costs of renewable energy protectionism? The US is entering a new era of rising electricity demand. Data centers, the backbone of the AI economy, are emerging as one of the fastest-growing sources of power consumption. Much of that demand is still being met by fossil fuels: The International Energy Agency reports that natural gas supplies more than 40 percent of the electricity used by data centers in the US, making it their largest source of power. So, it's not surprising that the expansion of data centers has raised concerns over their environmental impact and the pressure they could place on local power systems and electricity bills. A Gallup survey conducted in March found that seven in 10 Americans opposed the construction of AI data centers in their local area, including 48 percent who strongly opposed such projects. The findings point to a broader challenge for the US: The race to develop AI is increasingly becoming a race to meet growing energy needs. Addressing this challenge will require more than advances in computing technology; it will also depend on an energy system capable of delivering large amounts of reliable, affordable and cleaner power. That, in turn, will require faster development and broader deployment of clean-energy technologies, from solar power to energy storage. Yet in the clean-energy sector, the US has increasingly relied on protectionist trade measures that limit access to cost-competitive products from global markets. The country has placed greater emphasis on expanding domestic manufacturing capacity, but rebuilding entire clean-energy supply chains at home is a costly and time-consuming process. Even if expanded domestic production is achieved, it is likely to come at a higher cost, making the deployment of renewable technologies more expensive and potentially slower. The solar industry offers a clear illustration of this policy direction. The US has continued to expand trade barriers in the sector. Reuters reported that the US government announced on Thursday a series of price floors and a 15 percent tariff on products made from polysilicon, a raw material used in solar panels. The challenge lies in the limited scale of the US polysilicon industry. Reuters reported that the country has two polysilicon factories. Against this backdrop, relying on domestic polysilicon production while restricting access to imports runs counter to the goal of expanding solar power in the US. The country risks creating barriers that ultimately constrain its own access to the global supply chains needed for growth. The pressing issue for the US is the speed at which new power demand is emerging. The expansion of data centers is creating electricity needs that cannot wait for domestic clean-energy capacity to develop gradually. Global supply chains can provide the scale and speed required in the near term. By narrowing access to these sources, the US risks turning clean-energy policy into a drag on the infrastructure needed for its AI race. The US has placed AI high on its economic and technological agenda. The outcome of this race will matter greatly, as financial markets are also watching whether America can turn its AI efforts into commercial success. This leaves the US with a difficult choice: Can it afford the cost of clean-energy protectionism while racing to build AI infrastructure? The answer may be no. Trade barriers that limit access to competitive renewable technologies could ultimately become a constraint on the AI expansion that Washington is seeking to accelerate. The author is a reporter with the Global Times. [email protected]
。 ·首次在主流级 M 系列配备 12 核 CPU（2 颗 Super Core + 4 颗性能核心 + 6 颗能效核心），相比 M4 增加 2 颗核心，多线程性能最高提升 40%；·图形部分升至 12 核 GPU，并首次在 Mac mini 的 GPU 中加入神经网络加速器（Neural Accelerator），本地 LLM 等 AI 计算性能相比 M4 最高提升 4 倍，图形性能最高达到 M4 的 2 倍；·GPU 升级动态缓存、光线追踪和增强型着色器核心，新增 FP8 支持；·神经网络引擎升级为两组 16 核设计，峰值 AI 计算性能最高翻倍；·统一内存带宽达到 170GB/s，最大支持 32GB 统一内存。 除了带来2nm芯片首秀的Mac mini外，Mac Studio的更新则是专业用户等待已久的实力兑现。M5 Max：18核CPU，性能较前代提升30%；40核GPU，图形性能提升50%；每颗GPU核心集成神经加速器，AI任务处理速度提升4倍。CAD建模、游戏开发、长上下文AI推理，这些场景的体感提升是肉眼可见的。M5 Ultra则采用新一代Ultra Fusion技术，这次进化到四芯片架构，最高支持512GB统一内存，内存带宽达1.2TB/s。互联带宽超4TB/s，连接密度较上代提升6倍以上。36核CPU（12超大核+24性能核），80核GPU，首次在Ultra芯片中引入神经加速器，AI算力提升4.3倍。Mac Studio M5 Max 起售19999元，M5 Ultra 46999元。
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