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Robots learning without us? New study cuts humans from early testing

Humans no longer have exclusive control over training social robots to interact effectively, thanks to a new study from the University of Surrey and the University of Hamburg.

The study, which will be presented at this year’s IEEE International Conference on Robotics and Automation (ICRA), introduces a new simulation method that lets researchers test their social robots without needing human participants, making research faster and scalable.

Using a humanoid robot, the research team developed a dynamic scanpath prediction model to help the robot predict where a person would look in a social setting.

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This common prescription drug could reduce deaths by sepsis, study finds

Critically ill patients with sepsis who are given statins may be more likely to survive, new research suggests.

Researchers set out to explore whether the cholesterol-busting drugs may bring additional benefits for patients.

The new study examined information on sepsis patients who received statins during a stint in intensive care and compared it with patients in a similar situation who did not receive statins.

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Exclusive: Start-up FutureHouse debuts powerful AI ‘reasoning model’ for science

As artificial intelligence (AI) tools shake up the scientific workflow, Sam Rodriques dreams of a more systemic transformation. His start-up company, FutureHouse in San Francisco, California, aims to build an ‘AI scientist’ that can command the entire research pipeline, from hypothesis generation to paper production.

Today, his team took a step in that direction, releasing what it calls the first true ‘reasoning model’ specifically designed for scientific tasks. The model, called ether0, is a large language model (LLM) that’s purpose-built for chemistry, which it learnt simply by taking a test of around 500,000 questions. Following instructions in plain English, ether0 can spit out formulae for drug-like molecules that satisfy a range of criteria.

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Electronic ink enables room-temperature printing of circuits capable of switching between rigid and soft modes

Variable-stiffness electronics are at the forefront of adaptive technology, offering the ability for a single device to transition between rigid and soft modes depending on its use case. Gallium, a metal known for its high rigidity contrast between solid and liquid states, is a promising candidate for such applications. However, its use has been hindered by challenges including high surface tension, low viscosity, and undesirable phase transitions during manufacturing.

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