⚙️ The real challenge in AI for engineering isn’t model size, it’s relevance.
- Adagos
- 30 oct.
- 1 min de lecture
A model that integrates the underlying physics will generalize well, even with limited data. A purely correlative model, on the other hand, needs large datasets to compensate for what it doesn’t understand.
That’s why we design neural networks that are parsimonious by construction: they adapt to the structure of the problem rather than just fitting the data.
🔎 The result: lighter, more interpretable, and more robust predictive models, the very philosophy behind NeurEco, our physics-informed AI software for engineering.
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