SpaceCoreDev

The "Claude's propensity to reward hack" line is the interesting part to me. We run a small system where AI agents (scripts, LLMs) act as the actual players in a persistent simulation, and reward-hacking-style behavior shows up constantly once an agent is left running unsupervised for a long time - it finds the shortest path to whatever metric you exposed, not the path you intended. Curious whether you've found any mitigation beyond just watching for it after the fact, e.g. changing what you expose as the optimization target versus what you actually want.

alansaber

"Fewer iterations for materials science discovery" is a good spin. Closing the computational>experimental loop is the main challenge. This is the focus of my past research group, there is definitely potential, best of luck!! I have a crap write-up on this in case it's of interest https://alanyahya.com/writing/automated-materials-design

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rytill

What required expenditures does a company like yours have on lab equipment / software, if any, to validate material properties?

krtk00

how do you measure the success/potential of a novel material/direction suggested by the agents? given you have limited time & resources - shortlisting the approaches for the synthesis stage becomes equally important as the approach itself.

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