So next time you run a fast, production-level calculation, thank the awkward, unoptimized, 1990s-era ab initio code that proved the physics first.
Here’s a draft for an interesting post about ab initio versions — tailored for a computational chemistry, materials science, or ML/physics audience. Why “Ab Initio” Versions Still Matter in an AI-Driven World ab initio versions
And if you’re building something new — start with the ab initio version. Even if it only runs on 10 atoms. So next time you run a fast, production-level
The first implementation of a theory — no experimental fitting, no empirical parameters, just fundamental constants and equations. Even if it only runs on 10 atoms
Real insight emerges when you know exactly what you’re approximating. Would you like this adapted for LinkedIn, Twitter, or a blog format?
We talk a lot about machine learning potentials, DFT surrogates, and foundation models for materials. But here’s a quiet truth: every new, truly predictive method still starts with an ab initio version.