strujillo

6 ms·

1.
by strujillo 6mo ago
Yeah exactly — that “no LLM in the loop” constraint forces everything to be explicit and verifiable. I put together a few experiments where the system rediscovers known laws directly from raw data (solar wind, exoplanets, etc). Happy to sha
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by strujillo 6mo ago
Exactly — that was the surprising part for me too. The system has no notion of “physics” at all — it’s just searching for compressible structure in the data. The fact that GR relations emerge from observables suggests that a lot of what we
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by strujillo 6mo ago
Thanks! The key insight: don't fight the model's limitations, design around them. Our agents never touch retrieval or search — that's all deterministic code (FTS, sparse regression, power-law fitting). The LLM only comes in a
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Show HN: System that rediscovers physics laws from raw data autonomously(protoscience.ai)
1 points by strujillo 6mo ago|2 comments
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by strujillo 6mo ago
That matches what I’ve seen as well — generation is the easy part, validation is the bottleneck. I’ve been experimenting with a small sparse-regression system that infers governing equations from raw data, and it can produce a lot of plausi
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by strujillo 6mo ago
Sparse workloads are a really good fit for scientific discovery pipelines, especially when you're searching over candidate equation spaces. In practice, even relatively small systems can surface meaningful structure. I’ve been using sp
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by strujillo 6mo ago
It’s impressive how mature Pyodide has become — running Python scientific tools in the browser opens up a lot of possibilities. I’ve been working on a small (~800-line) Python system that uses sparse regression to discover physical laws fro
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by strujillo 6mo ago
Designing interactions for autonomous agents is tricky — you can’t assume a human will click through a UI. I’ve been experimenting with autonomous scientific agents: a lightweight Python system that uses sparse regression to derive physical
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by strujillo 6mo ago
Formal verification and code synthesis feel like natural companions for automated scientific discovery. I’ve been working on a small (~800‑line) Python agent that uses sparse regression to uncover governing equations directly from data; it’
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800 Lines of Python found the Sun's rotation from free NASA data(github.com)
2 points by strujillo 6mo ago|0 comments