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Philipp D. Dubach

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阅读学习 Independent writing and research on AI and markets, covering the economics of models and compute, quantitative finance, and macro.

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The site stands out for combining practitioner-level strategy consulting experience with independent research, so posts tend to be argument-driven rather than news summaries. Its project section is unusually transparent, showing working tools and experiments such as LLM benchmark comparisons and tim

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Philipp D. Dubach is the personal site of a strategy consultant and independent researcher working at the intersection of artificial intelligence and financial markets. Rather than a news feed, it functions as a publishing hub for essays, research notes, and hands-on projects, with the author’s background and contact details kept easily accessible.

The writing section covers the economics of AI models and compute, quantitative finance, and macro topics, with recent pieces ranging from AI predictions for 2030 to enterprise knowledge management and inflation lessons from John Cochrane. The projects section complements the essays by documenting concrete builds, including a tool for comparing LLM benchmarks, financial market forecasting with Timestral, and a performance-focused Hugo site setup.

The site is aimed at analysts, investors, researchers, and technically minded readers who prefer structured arguments over commentary. Because content is organized by writing and projects rather than by topic tags, visitors should start with the latest writing index or browse the full archive to locate themes relevant to their work.

A subscribe option and a links page make it easy to follow new posts or reach the author directly. Overall, it works best as a slow-reading resource: pick one essay or project write-up, follow its references, and treat the archive as a body of research rather than a stream of updates.

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