alt Hacker News> As a result, producers need a way to rapidly explore and validate new formulations without spending months in the lab.
How do you bypass the normal process of pouring test articles and testing them months and years after cure? This is fundamentally a research activity that needs to conduct verifiable science. Not something you can guess at with an LLM.
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Somebody needs to coin a new term for the scattershot zero-thought AI griping that is pervasive in online comments these days. Meatslop?
Obviously it's going to be more productive for a manufacturer to do a years-long curing test on 100 likely candidates instead of 100 random mixes. They obviously already screen candidates through traditional methods, but if this AI technique improves accuracy, all the better.
What part of move fast and break things did you not understand?
It doesn't use an LLM
What could possibly go wrong?
https://dailygalaxy.com/2026/03/rubber-used-in-undersea-tunn...
All the chemical companies do it. They pair it with testing, but still.
They have a new scapegoat to blame if things turn out badly.
Hi, I developed the model. We are not bypassing the regular testing process, and are not using LLMs, but Gaussian processes with vetted test data. The predictions are used as recommendations for onsite testing, to accelerate finding mixtures with optimal strength-speed-sustainability trade-offs.