Author Archives: Ben Lorica

I have written separately about the shaky economics behind the data center boom and the growing pressure on the frontier labs. This post connects the two. Microsoft reported $24.1 billion of revenue from its OpenAI relationship, an amount equivalent to almost one-quarter of Azure’s scale, although the figure includes revenue-sharing payments as well as cloudContinue reading “If the Labs Wobble, the Clouds Feel It First”

Table of Contents What AMD Actually Sells Now The Software Story, Which Is the Whole Story The Open-Standards Bet Who’s Buying, and How the Money Actually Moves Where This Could Still Come Apart What It Means If You’re Buying AI Compute What AMD Actually Sells Now AMD’s most important change is not that it hasContinue reading “Inside AMD’s AI Bet”

Last week I argued that open models will absorb most of the money and compute the world spends on AI. A week later, open weights are even more central to the conversation. Recent releases have made the gap between capable and affordable harder to ignore, and a broad coalition of technology companies is now publiclyContinue reading “Specialized AI Is Getting Easier to Build”

The most useful thing I’ve learned watching this latest round of open model releases is that “open” has stopped predicting anything. It used to be a reliable shorthand for cheap and second-tier. Now the top-ranked open coding model in the world costs roughly thirteen times more per million tokens than the cheapest credible open modelContinue reading “Multiple Dials, Not One: Reading an Open Model Release”

I keep coming back to the same uncomfortable math on AI data centers: the money going in is piling up faster than any economic proof that it should. Usage of AI systems has reportedly been climbing seven to twenty times a year, while the revenue that usage produces has grown maybe three or four times,Continue reading “AI Can Win While Data Centers Lose”

Three frontier level models landed within weeks of each other this fall, GLM 5.2 from Zhipu, Kimi K3 from Moonshot, and Gemini 3.6 Flash from Google, and I wanted to capture early developer reaction so I can monitor how feelings about these models change over time. The individual verdicts differ, but together they hint atContinue reading “Three New Models, One Signal About Where AI Spending Goes Next”

Here is my bet: open models (open weights and open source alike) will end up absorbing most of the money and compute the world spends on AI. The proprietary frontier models get the headlines and the IPO valuations, but developers and AI teams see something different up close. Open models are improving fast, the gapContinue reading “Open Models Will Absorb Most of the AI Spend”

Since June 2026, Chinese officials have been in closed door talks about restricting foreign access to the country’s most advanced AI models, both open and closed. The Ministry of Commerce is leading the discussions, China’s state planning agency is also in the mix, and the companies involved include Alibaba, ByteDance, and Zhipu. Nothing has beenContinue reading “What We Actually Know About China’s AI Export Controls”