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- 1Physics-informed machine learning improves wearable sweat biosensor calibration▼Physics-informed machine learning for robust calibration and physiological validation of wearable electrochemical sweat biosensors for metabolite monitoring
Researchers publishing in Nature describe a physics-informed machine learning approach for calibrating wearable electrochemical sweat biosensors used to monitor metabolites. The method combines physical models of sensor behaviour with data-driven learning to achieve robust calibration and physiological validation, aiming to make wearable biochemical monitoring more reliable in real-world conditions.
- 2Heavy water isotopes improve weather forecast accuracy▼Heavy water isotopes make weather predictions more accurate
Researchers report that tracking isotopes of heavy water can make weather predictions more accurate. By measuring variations in hydrogen and oxygen isotopes in atmospheric water, scientists can better trace moisture sources and movement, refining the models used in forecasting. The finding, reported by Physics World, suggests isotope data could become a valuable addition to meteorological observation and prediction systems.
- 3World's most accurate atomic clock passes a crucial test▼World’s most accurate atomic clock passes a crucial test
The world's most accurate atomic clock has passed a crucial test, confirming the precision and reliability of the timekeeping technology. Atomic clocks underpin GPS, telecommunications and fundamental physics research, so any advance in accuracy is closely watched by scientists. The result is being reported as a milestone in precision measurement, though details of the test and the team behind it are not specified.
- 4Nvidia settles trademark lawsuit over Modulus AI software●Nvidia settles trademark lawsuit over 'Modulus' AI software
Nvidia has reached a settlement in a trademark lawsuit concerning its 'Modulus' AI software, according to a Reuters report. The dispute centred on Nvidia's use of the Modulus name for its framework for building physics-based machine learning models. Terms of the settlement were not disclosed in the report, and the company has not issued a detailed public statement on the outcome.
- 5Black Forest Labs releases Flux 3 Action robotics model●Flux 3 Action: A 7B open-weight world action model for robots
Black Forest Labs has released Flux 3 Action, a 7-billion-parameter open-weight world action model aimed at robotics, available via Hugging Face. The model is designed to let robots perceive and act in physical environments. Early discussion among developers is focused on the unusual choice of an image-model company entering robotics and on how a relatively compact 7B model performs on real robot tasks.
- 6Roboharm study tests whether robots refuse unsafe instructions●Roboharm: Do frontier robot policies refuse unsafe instructions?
A project called Roboharm is asking whether frontier robot policies actually refuse unsafe instructions. The work examines how AI systems controlling robots respond to harmful commands, a safety question increasingly urgent as AI models are deployed in physical robotics. Discussion is focused on how well current safeguards carry over from language models to embodied systems.