Open-source AI workbench Translucent designs battery experiments and beats Bayesian optimization in sims
YashasGunderia · x · 2026-11-05
Developer Yashas Gunderia unveiled Translucent, an open-source AI workbench for experimental engineering. Give it lab records and a goal; it digests data, tests physical models, proposes experiments, runs simulations, and replans as results come in — starting with batteries.
- In one investigation, a system built on Meta's Muse Wonder found two cells couldn't be explained by one thermal model, then autonomously designed new simulated tests and arrived at an evidence-backed charging design
- In a simulation benchmark, with the same budget of eight experiments, it found charging protocols 5–12 minutes faster than constrained Bayesian optimization (simulated only, not yet validated on physical cells)
The goal: AI that participates in engineering the physical world, heading next toward energy systems and materials.
More from Research
- ICML Weight-Space Symmetries keynote slides survey weight-space learning — orvieto_antonio · 2026-11-05
- Three distinct reasons researchers study looped transformers, explained — Kangwook_Lee · 2026-11-05
- PhD researcher launches 'paper nostalgia' series with Real NVP coupling-layer explainer — LucaAmb · 2026-11-05
- New theory says curricula help with unlearning simple rules, not learning — summerfieldlab · 2026-11-05
- uni-robot-agent gets Qwen working in sim and on real robots, launching OpenRUA — teortaxesTex · 2026-11-05
- Fabricated references in 500K-paper sample surge from 6.3 to 23.0 per 10,000 since 2023 — skdh · 2026-11-05