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The author claims astrophysics has become an information science and that if…

2026-08-08 · 03:27 UTC ·@deanwball ·2 min read

Brief

Astrophysics has become an information science in practice, and the author argues that modest donations of compute from prosumer Codex and Claude Code users could enable automation of much data-driven astrophysics now done by humans. Public funding would shift to capex (telescopes) and elite human teams, producing open research as a global commons as experiments trend toward automation.

Why it matters

The author claims astrophysics has become an information science and that if every prosumer-tier subscriber to Codex and Claude Code donated a tiny share of their monthly compute, we could soon automate more astrophysics work than human astrophysicists currently perform in the “astrophysics as data science” regime.

Key details

  • They argue government and philanthropic funding would refocus solely on capex (e.g., building telescopes) and on financing rare, high-talent human teams, while computationally produced research — if made fully open — could serve as a global commons for downstream work.
  • The post asserts that harvesting spare compute has the same structural logic as taxation but with far lower transaction costs, and that increasing automation of experiments could make much science near-autonomous and extremely cheap, though total automation is unlikely.
Source evidence

there are some sciences, for example astrophysics, that have really become information sciences in practice, alongside very high capex shared tools (ie telescopes).

it is probably the case that if every current prosumer-tier subscriber to codex and claude code donated a tiny share of their monthly compute, we will soon be able to automate more astrophysics than is currently done by human astrophysicists—the ones who operate in the “astrophysics as data science” regime at least. each coding agent user can plausibly, almost without noticing, fund a large share of the labor in the areas of science most susceptible to computation.

the role of government and philanthropic funding becomes purely focused on the capex: in this case, the construction of ever more exquisite instruments to collect data for the machines. perhaps also it could focus on funding the true heavy-tailed genius human individuals/teams whose ideas, talent density, etc are so extraordinary that we have some reason to think they can ask and answer questions beyond what the data-mining machines can do. of course in the sciences that remain less susceptible to pure computational approaches, the funding structure would look more diverse, because there’d be wet labs, experiments etc.

but the point is that, in principle, if all users of coding agents gave up an ultimately negligible share of their tokens, it may become possible to explore ~all questions in science that can be explored using a computer alone. if the resultant research and data was then made public, wholly open, it could be used as a global commons and foundation for much more research, including in wet labs, which I suspect will remain more decentralized and human-centric for the foreseeable future.

notice the structural similarities between this and the current way in which tax dollars are harvested by governments for science. it’s the same idea, just with dramatically lower transaction costs throughout the whole chain of production.

also imagine what could happen as increasing fractions of real-world scientific experiments are automated. over time, more and more of science becomes this thing that happens close to autonomously, and almost for free.

we may never realize total automation, asymptotes being what they are. but the direction feels clear to me, even if the extent of the trend and the precise timeline over which it will unfold do not.