🧠 From Newton to Einstein to Neural Nets: Rethinking Gravity Through the Eyes of Software Engineering

#ai #softwareengineering #coding #alirezaminagarmd

By: Alireza Minagar, MD, MBA, MS (Bioinformatics) Software Engineer

When Isaac Newton described gravity, he gave us a world of absolutes—mass, force, and deterministic pull. His laws were elegant, mechanical, and intuitive.

Then came Einstein. He shattered that certainty with curved spacetime, non-linearity, and relativity. Suddenly, gravity wasn’t a force—it was geometry.

As a software engineer working in AI, I see something eerily similar in how we write code and build intelligence today.

Newtonian Coding: Rules, Logic, Determinism
Classical programming is Newtonian.

Inputs → deterministic rules → outputs.

We debug with reason, control flow like gravity, and expect predictable behavior.

Einsteinian Coding: Deep Learning, Probabilistic Logic
AI models, especially large neural nets, are Einsteinian.

Instead of if-else statements, we curve the “space” of data using layers and weights.

Inputs are distorted through latent space; outputs are probabilistic, not exact.

🧬 Just as Einstein replaced force with curvature, AI replaces logic with learned structure.

🔄 The Parallel is Profound
| Physics | Software Engineering |
| --------------------- | --------------------------- |
| Newtonian mechanics | Rule-based systems |
| Einstein's relativity | Deep learning architectures |
| Gravity as force | Logic as deterministic code |
| Curved spacetime | Latent space in neural nets |

👨‍🚀 Why This Matters
We are transitioning—from rule-based programming to model-driven intelligence, just as physics transitioned from Newton to Einstein.

To build next-gen software, we must think less like Newton and more like Einstein:

Accept uncertainty.
Embrace curvature.
Architect for adaptability.

Maybe the future of software isn’t a set of rules—it’s a warped field shaped by data, where intelligence simply “falls” into place.
Would Newton understand GPT-4? Would Einstein?

Let me know what you think.