Compute and the grid must be planned together, Anthropic's CEO dines alone at the White House, and big US companies start putting cheap open models on procurement lists.
A column from Weijin Research reposted by Huxiu on September 27, by author Zhou Jiangong. The piece is about compute-power coordination — that is, putting compute (the machine resources needed to run AI, mainly consuming power and chips) together with the grid and communications networks on a single plan. Domestically it's been written into the preparatory work for the "15th Five-Year Plan," on the grounds that data center power consumption growth has already outpaced grid expansion. The article's judgment is that this has to be done as a systems engineering effort, and electricity pricing needs to be recalculated economically. The US has surplus power but slow grid approvals; China has cheap electricity but heavy pressure to absorb green power. Each side has its own weak spot, and neither can offer an answer that relies only on its own strengths. The part relevant to you is electricity prices. Where data centers cluster, residential and small-business rates often move first. To find out whether a large data center is being built in your city, check the local NDRC project disclosures and the grid's power supply commitments — these two documents usually come out earlier than the news.
TechCrunch reported on September 27 that Anthropic CEO Dario Amodei had dinner with Trump at the White House that evening. The news was first disclosed by Axios, and TechCrunch subsequently confirmed it with people familiar with the matter. This was the first one-on-one meeting between the two. The two differ on AI safety. Amodei published a plan on September 12 to slow the pace of development, arguing for more caution; Trump had previously said public opposition to AI was fabricated by Democrats, and proposed renaming the technology "superintelligence." Earlier this year, the Pentagon listed Anthropic as a supply chain risk because the company put restrictions on its own technology, and the company is fighting this in court. The meeting's landing point is policy and procurement. Anthropic mainly makes money from enterprise customers, and US federal agencies are among the big buyers of such companies; whether the White House is looser or tighter on safety, the terms of government procurement and compliance certification will shift accordingly. Readers who use tools like Claude to handle work content can watch for changes in its access to the government and enterprise market going forward.
A Financial Times report on September 27 says US enterprise customers are slotting open-weight models (code and parameters you can download and deploy yourself) into production environments, replacing part of the top-tier services billed by the token. The report sums it up in one line: enterprises buying AI are starting to tier by cost-performance, no longer always picking the most expensive. The push comes from cost. These models have low per-call prices and can be moved into your own data center, so data never leaves the internal network. The report also mentions a specific hassle: under the same label of "the cheap tier," capabilities vary widely, so selection can only be done by running your own business problems through them — public leaderboards easily mislead. If you manage an AI budget at your company, here's how to act on this: break down your call volume by task. Leave work like drafting proposals and making complex judgments to strong models; switch fixed work like proofreading, summarization, classification, and customer service scripts to self-deployed open models. Start with a comparison test on one business line — far more stable than a wholesale replacement.
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