Launch HN: Discovered Materials (YC P26) – AI agents to discover new materials

What changed

Lastly, we describe the harness, tools and graders used in this benchmark to measure model performance. All models are tasked with finding materials where $kappa, $epsilon, $youngs and $shear. The pinned values are chosen to define the appropriate desired window, and the objective below is what the model is given.

Why it matters

A concrete addition to Practical AI: Tools, Models & Frameworks: it changes what's available to builders today rather than being general commentary.

How it compares

Related prior coverage to compare against:

• Show HN: Echo – Fable-level results at 1/3 the cost using open-weight models
• A $500 RL fine-tune of a 9B open model beat frontier models on catalog review
• Nvidia, Microsoft, Meta warn against overregulating open-weight models

• Show HN: Echo – Fable-level results at 1/3 the cost using open-weight models similarity 0.11
• A $500 RL fine-tune of a 9B open model beat frontier models on catalog review similarity 0.09
• Nvidia, Microsoft, Meta warn against overregulating open-weight models similarity 0.09