一个由人工智能初创公司、云服务提供商、研究人员和投资者组成的联盟正在发起一项“国家计算网格”计划，旨在汇集人工智能计算资源，以应对导致人工智能基础设施巨额支出的供应短缺问题。
A coalition of AI startups, cloud providers, researchers and investors is launching a National Compute Grid, an effort to pool AI computing to help address a supply crunch driving enormous spending on AI infrastructure.
重要性：构建人工智能基础设施已成为一项数万亿美元的赌注，这在很大程度上是因为获取稀缺计算资源的成本高昂。然而，许多数据中心处于低负载运行状态，这意味着极其宝贵的芯片处于闲置状态，而一些初创公司和研究人员却难以获得使用权。
Why it matters: Building AI infrastructure has become a multi-trillion-dollar bet largely because of the high cost of accessing scarce computing resources. Yet many data centers run at low capacity, meaning extremely valuable chips sit idle while some startups and researchers struggle to get access.
计算网格的创建者希望让闲置的计算能力更容易被利用，如果这一目标得以实现，可能会显著改变人工智能热潮的发展方向。
The creators of the compute grid want to make it easier for idle computing capacity to be used, a goal that could significantly alter the direction of the AI boom if it were to take off.
各方观点：该项目的负责人安杰尼·米达（Anjney Midha）告诉Axios，该项目是一种为商业研究和公共部门使用共享计算资源的方式。他表示，在美国高效扩展人工智能、保持前沿地位并与中国保持竞争力的最佳方式，是围绕一个开放标准进行协调。
What they're saying: Anjney Midha, a leader of the effort, told Axios the project is a way to share computing for both commercial research and public-sector use. "The best way to scale AI in America efficiently, and stay at the frontier and stay competitive with China, is to be" coordinated around an open standard, he said.
“事实证明，我们拥有的计算能力实际上比人们预期的要多得多。它只需要被互联和协调起来，”曾任风险投资人、现经营人工智能控股公司Amp（一家公益公司）的米达说道。
"Turns out, we actually do have a lot more compute than people expect. It just all needs to be interconnected. And coordinated," said Midha, a former venture investor who now runs AI holding-company Amp, a public benefit corporation.
专注于人形机器人具身智能的初创公司1X的人工智能负责人萨姆·辛哈（Sam Sinha）表示，像他这样的人工智能公司经常难以获得计算资源。像OpenAI和Anthropic这样的大型企业可以支付高得多的费用，而...
Sam Sinha, Head of AI at 1X, a startup focused on embodied AI for humanoid robots, said AI companies like his often struggle to get access to computing resources. Larger players like OpenAI and Anthropic can pay far more, and