AI & Machine Learning
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More on Bing, particularly the Sydney personality undergirding it: interacting with Sydney has made me completely rethink what conversational AI is important for.
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The first obvious casualty of large language models is homework: the real training for everyone, though, and the best way to leverage AI, will be in verifying and editing information.
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The SpaceX IPO and Data Centers in Space
There isn’t a financial model that justifies the SpaceX IPO, but data centers in space are plausible, and that might be enough.
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Nvidia Earnings, The AI Stack, Nvidia’s New Reporting
Nvidia is changing its reporting to delineate between hyperscaler sales — where Nvidia is fighting commoditization — and everyone else, where Nvidia runs the whole stack.
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Google I/O, World Models, I/O Spaghetti
Google I/O put AI everywhere, for better and for worse. Meanwhile, is DeepMind aligned with Google’s business objectives?
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The Deployment Company, Back to the 70s, Apple and Intel
OpenAI is forming a new company to deploy AI, and the other labs aren’t far behind, reinforcing the thesis that AI’s impact will require top-down implementation. Then, Apple has economic reasons to work with Intel.
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SpaceX and Anthropic, xAI’s Two Companies, Elon Musk and SpaceXAI’s Future
The Anthropic xAI deal is shocking but not surprising: Musk should double down on serving other companies.
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The Inference Shift
Agentic inference is going to be different than the inference we use today, and it will change compute infrastructure because speed won’t matter when humans aren’t involved.





